THE FEDERAL DEMOCRATIC REPIRUC IF ETHIOPIA
MINISTRY OF WATER RESOURCES
Arjo-Dedessa Irrigation Project Feasibility Study Report
VOLUME-III
Water Resources
VOLUME - III (a)
Annexure - 7 Meteorological And Hydrological Studies
Annexure - 8 Hydrogeological Studies
May. 2007
Addis Ababa
WATER WORKS DESIGN a SUPERVISION ENTERPRISE
IK ASSOCIATION WITH
IHHRCOHTWIMTM COHSBITMTS *H0 TtCHH9CMTS IH5IIW ITS
I’0 Box 2561 Addis Ababa Ethiopia
Tel (251)1 614501/631890 Fax (1251)1 6l5171E-inail w w d s c alclccom net clARJO-DEDESSA IRRIGATION PROJECT
FEASIBILITY STUDY REPORT
CONTENTS OF THE REPORT
serial volume NO.
NO.
2 3
PARTICULARS EXECUTIVE SUMMARY
MAIN REPORT
Parti - Report
Part II - Maps & Drawings
ANNEXURES
4
VOLUME -1               SURVEY AND INVETIGATION (ANNEXURES - 1 to 3) volume -1 (a)             Topographic Survey, Geomorphological Studies &
Geological & Geotechnical Investigation Part l - Report
5              Volume -1 (b)
Part II - Appendices
6               VOLUME -II               NATURAL RESOURCES (ANNEXURES - 4 to 6) Forestry. Energy & Catchment Development Plan
VOLUME - III             WATER RESOURCES (ANNEXURES - 7 to 11)
Volume - III (a) Meteorological & Hydrological & Hydrogeological Studies Dam & Appurtenant Works
Part I - Report
8               Volume - III (b)
9
10              Volume-III (c)
11
12 Volume - III (d)
13
Part II - Drawings
irrigation & Drainage Part I - Report Part II - Drawings
Hydraulic Structures Part I - Report
Part II - Drawings
VOLUME IV
AGRICUTLRUE (ANNEXURES - 12 to 18)
14
Volume - IV (a)
Soil Survey & Land Evaluation
15
Volume - IV (b)
Agricultural Planning
16
Volume - IV (c)
Livestock, Fisheries, Agricultural Mechanization &
Agricultural Marketing
VOLUME - V
ENVIRONMENTAL AND SOCIO - ECONOMIC ASPECTS
(ANNEXURES-19 to 25)
17
Volume - v (a)
Environment. Health & Socio-economic Aspects
18
Volume-v (b)
Organization & Management, Physical infrastructure
Resettlement, Financial & Economic AnalysisAnnexure - 7
METEOROLOGICAL AND
HYDROLOGICAL STUDIESArjo Dedessa Irrigation Project Meteorological and Hydrological Aspects
May 2007
Table of Contents
table of contents...........
LIST OF TABLES
LIST OF ANNEXI RE......................
LIST OF FIGURES..........................
III
1. INTRODUCTION........................... ................-............................................. -.................... ------------- ----------------- —1
I
I               The Nile Basin.........................................................................................................................
1.2       abbay Basin ................................................................................................. ................................................. 1
I               3 The Dedessa Catchments....................... ......................................................................... -.................... 3
2.        REVIEW OF PREVIOUS STUDIES
2   I      LaHMAYER 1962 STUDY............................................................................................................................... 5
2.2       Land and Water Resources of the Blue Nile Basin Ethiopia................................................................. 5
23        Country wide Master Plan studies-EVDSa'WaPCOS (1988-90)............................................................. 8
2   4     STUDY BY BCEOM-IN ASSOCIATION WITH ISL AND BRG 1999
9
2 5       Study by ministry of Water resources for Lower Dedessa (2001>................................................... 15
2.6 Utility of Earlier Studies....................................................-............................................................................ 16
3.       DATA BASE.
3   1 Climatological Data....................................................................................................................................... I7
3.2. Rainfall..................................................... .................................................................................................._......17
3.3        River Discharge................................. ...................................................................................................... 17
3   4 SedmentData..................................................................................................................................................... 18
4.      ESTIMATION OF REFERENCE EVAPOTRANSPIRATION........................................................................ ....19
4. l Introduction......................................... _............................................................................................................. 19
4.2             Meteorological Data.........................................................................................................................  20
4.2.1 Meteorological Observation Stations........................................................................................................... 20
4              2.2 Air temperature.............................................................................................................................. 21
4              2.3 Air humidity1 ................................................................................................................................... 22
4.2.4 Wind speed......................................................................................................... ........................................ .23
4 2 5 Solar radiation.............................................................................................................................................. 23
4 3        Penman-Monteith Equation........................................................................................................................ 24
Arjo Didesa Project Area Arjo Dedessa Project Area............................................................................ JO
5.      RAINFALL ANALYSIS.................................................................................... ... .......................................................32
5.1         Introduction..............................................................................................................................................32
5.2         Rainfall Internal and External Consistency........................................................................................32
5 3        Estimation of Rainfall Reliability Level................................................................................................ 33
5.4        Estimation of Maximum Rainfall Frequencies....................................................................................... 34
6.      MONTHLY STREAMFLOW ANALYSIS____________ __________________ __________ ____________ 46
6.1        Hydrological Observation Stations........................................................................................................4b
6.2         Extension of records...................................................................................................................
6 3 Synthetic flows.............................................................................................................’ ’ ’'
47
7        ESTIMATION OF FLOODS FOR UNGAUGED CATCHMENTS...................... .............. ......................... „..5]
7 1 Rational Method..............................................................................................................................
7 2 SCS METHOD..................................................................................................... \
53
7.3         Transferring Gauged Data ..................................................................................................................... 54
7 4        Estimation of Weighted average.............................................................................................................. 54
7 5        Synder method of Constructing Synthetic Hydrograph
55
8         FLOOD FREQUENCY ANALYSIS........................................................................................ ....... ....................... 59
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8 1        INTRODUCTION
8 2        Estimation of Probability Weighted Moments ..
May 2007
59
60
8 3        Generalized Extreme v alue Distrjbl tion....................................................................................... 61
8 4        Log-Logistic Distribution ........................................................................................................................ ol
8 5        Regionally a veraged quantiles............................................................................................................. 62
8 6        Choice of Distribution ............................................................................................................................. 63
9. PROBABLE maximum flood
10
SEDIMENT ANALYSIS
10 1     Estimation of Sediment yield..................
10.2     Distribution of sediment in the reservoir ..................................................................................... 70
il. Water QUALITY........
12.
65
69
o9
73
12.1     Synthetic Hydrograph ....................... —....................................................................................................75
12 2     Flood Routing Through the Reservoir................................................................................................... 75
i 2.3     Routed Design F_ood at the Coffer Dam................................................................................................ 78
13.     RESERVOIR SIMULATION
14. DEDESSA SUB-BASIN MODELING..........
87
91
14 i Modelinc for arjo Dedessa dam for irrigation ........................................ ...... -............................................ 91
14 2 The sub basin modeling......................................................... -........................................................................ 92
/4.2 / Power Generation tn Dedessa Dam.......................................................................... -.......................... 93
/4.2.2         Optimal Power Generation ............................................................... ............ ................................... 94
J4.2.3        Reduction inflows at Dedessa Suo-oasin ........................................................................ ................. 96
14 2 4        Conclusions ...... ........ .......................... ................................................... .... 15.     RECOMMENDATIONS ON TRAINING NEEDS
REFERENCES
96
II
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LIST OF TABLES
Table i i Break up of Abbay Basin Area.......................................................................................... 4
Table 4 1 Table Details of meteorological Observation Stations located in and around the
PROJECT area            .................................................................................................... 26
Table 4 2 Types of Climatic Data available at the various Meteorological Observation
Stations ........................................................................................................................................... 26
Table 4.3: Summary of Meteorological Characteristics at Project area
Table 4 4 Summary of Estimated mean ETo of Arjo Dedessa Project area
27
28
Table 4.5.          Magnitude of ETo at given non-exeedance probability level............................................. 29
Table 5 1           Cross Correlation Matrix of annual Rainfal^ ..................................................................... 36
Table 5.2:          mean Monthly Rainfall ..............................................................................................................  36
Table 5 3           Parameter Estimates of weibulx Distribution ....................................................................... 36
Table 5 4           Monthly Rainfalls Corresponding to Different Reliability levels
37
Table 5.5           Parameter Estimates of Half-monthly Rainfall..................................................................  37
Table 5.6           Half-Monthly Rainfall Magnitudes at Different Reliability Levels
Table 5 7           Half-Monthly Rainfall Magnitudes in Percent of the Mean Corresponding to
38
Different Reliability levels......................................................................................................... 39
Table 5.8:           Maximum Annual 24-hr Rainfall ..............................................................................-.................. 40
Table 5.9:          maximum Rainfa^ Magnitudes and Frequencies...................................................................... 40
Table 5.10:        Maximum Rainfag. Magnitudes for Higher Durations........................................................... 41
Table 6.1           Availability of Streamflow Data in the Region.................................................................... .48
Table 6.2.          Mean Monthly Flow (in Mm3/seC).............................................................................................. 48
Table 6.3           Coefficient of Variation of Monthly Discharges................................................................. 48
Table 6 4           Summary of Regional monthly flow characteristics......................................................... .49
Table 6 5 Table Statistics of monthly flows at arjo Dedessa dam site
....
49
Table 6.6           Reliability level Vs Monthly Streamflows at Dam Site ...................................................... 49
Table 6.7           Characteristics of Random numbers Used for Flow Generation..................................... 50
Table 8 i            Estimated Flood Quantiles Based on GEV Distribution......................................................<>4
Table 8.2           Estimated Flood Quantiles Based on llG Distribution
64
Table 9 i            Table Cumulative volume of Probable Maximum F^ood.......................................................  67
Table 9.2:          Design Flood hydrograph Derived from Estimated PMF ................. Table 10 1 Relationships between water discharge and sediment load ....
........ .
68 70
Table 10.2:        Monthly Total Sediment load at the Reservoir Site ...........................................................71
Table 10 3         Accumulated Total Sediment load at the Reservoir Site.................................................. 71
Table 10 4         Distribution of Sediment in the arjo Dedessa Reservoir.....................................................72
Table 11 1         Water quality results for sites on the Dedessa river....................................................... 74
Table 12.1:        Catchment Characteristics....................................................................................................... 80
Table 12.2: Routed Design Flood at FRl Corresponding to 1352 m
Table 12.3. Routed Design Rood at frl Corresponding to 1555 m
go
si
Table 12 4         Routed Design Flood at FRL Corresponding to     1356m.................................................   82
Table 12.5;        Routed Design Rood at Coffer Dam of arjo Didessa Reservoir Table 13 1         irrigation Water Requirements for various Scenarios
83
88
Tablei3.2          Reservoir Characteristics at Dead Storage level.............................................................. 89
Table 13.3:        Storage Reservoir Characteristics and Reliability Levels............................................... 90
Table  14  1  Total  monthly  Release  (Irrigation  plus  Power)  options  for  various  frl  values
considered.................................................................................................................................. 97
Table 14.2:        Annual Energy generations at Dedessa dam for the various options
........ 97
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LIST OF ANNEXURE
annex A Results obtained from the Meteorological Analysis ........................................................ 103
Al:                Estimated Mean Temperature at Arjo Dedessa Project area (in°C).................................... .103
A2                Estimated Minimum Temperature at arjo Dedessa Project area (in°C)................................... i04
A3                Estimated Maximum Temperature at Arjo Dedessa Project Area (in°C) A4               Estimated Relative humidity at arjo Dedessa Project Area (in percent/ A5               Estimated Mean Daily Sunshine Duration at arjo Dedessa Project area.
I05
I06
107
A6                Estimated mean Daily ETo of arjo Dedessa Project area........................................................108
A7               Estimated Mean Monthly ETo of arjo Dedessa Project Area
A8 Estimated mean monthly Rainfall at Arjo Dedessa Project Area
i 09
ho
A9               Estimated Mean half-monthly Rainfal at the Project area (in mm/hr)..................................... ill
Annex B     Results obtained from the hydrological Analysis .....................................................................H3
B1               Estimated Monthly Flows at arjo Dedessa Dam Site................................................................ 113
B2                Regional monthly coefficient of variations (CV) ........................ ............................................. 114
B3:              Regional monthly coefficient of skewness................................................................................ 114
B4               16 Regional monthly coefficient of correlations (R)          .................................................... H 4
B5               Standardized probability weighted moments ............................................................................... 115
B6               Mean monthly Total (Suspended and Bed) Sediment load ..................................................... 11 o
B7               Eleveation-area-Capacity Relationships of arjo Dedessa Reservoir B8.              Sample Simulation Results of Arjo Dedessa Reservoir
i 17
118
Annex C     Standards............................................................................................................................................ 121
C1               Commonly used values of runoff coefficients......................................................................... 121
C2               Runoff coefficient for pervious surfaces by selected hydrologic soil
I2!
C3               SCS Curve numbers for Various Conditions1 ........................................................................... 122
C4               Reservoir Flood Standards............................................................................................................124
C5.              Ratios of the basic dimensionless hydrograph of the SCS............................... 125
C6               Guidelines for interpretations of Water Quality for irrigation ........................................ .126
Annex D: Meteorological Data............................................................................................................................127
D1.              Details of meteorological Observation Stations ........................................ ............................. 127
D2:              Types of Climatic Data available at the various meteorological ............... ........................... ) 27
D3:              Mean Monthly Rainfall at Bedele Station................................................................................... 128
D4               Mean Monthly Rainfall at jimma Station .......................................................................................129
D5.              Mean Monthly Rainfall at Dedessa Station................................................................................ 131
D6               Mean Temperature at Bedele Station ...................................................................................... ..... 132
D7               Relative Humidity at Bedele Station (in%).................................................................................  133
D8               Wind Speed at jimma Station............................................................................................................ 134
D9               Sunshine Duration at Bedele Station .........................................................................................  135
Annexe, hydrological Data .................................................................................................................................. 136
E1
list of Selected hydrological Observation Stations............................... ..................... 136
E2               Mean Monthly Streamflow at Dedessan near arjo Station E3              Mean Monthly Stream flow at Dedessan near Dembi Station
i 37
139
E4              Annual Maximum Floods................................................................................................................... 140
E5              Measured Sediment Concentration at Gumara Gauging Station.......................................... .141
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LIST OF FIGURES
Figure 4 1 mean monthly Temperature at Figure 4.2: Mean monthly Relative humidity at so
Figure 4.3:        mean Monthly Wind Speed at Figure 4 4 Mean Monthly            Sunshine hours at             30
Figure 4.5         mean Monthly ETo at arjo Dedessa Project Area Figure 5 1(a):   Trend Analysis of Annual Rainfall at jimma Station Figure 5.1(B). Trend Analysis of Annual Rainfal*. at BedellE Station Figure 5.1(C).     Trend Analysis of Annual Rainfall at Dedessa Station
...
31
42
42
43
Figure 5.2(a).    Single Mass Curve of jimma Rainfall......................................................................................43
Figure 5.2(B):     Single mass Curve of BedeluE Rainfall............................................................................... 44
Figure 5.2(c):     Single Mass Curve of Dedessa Rainfall
Figure 5.3;         mean Monthly Rainfall at arjo Dedessa Projetct Area
Figure 12 1        Elevation-Area-Capacity Curves of Arjo Dedessa Reservoir
Figure 12.2:       inflow and Outflow Flood hydrographs at arjc Dedessa Reservoir
Figure 12.3:       inflow and Outflow Flood hydrographs at arjo Dedessa Reservoir Figure 12 4        Average hydrograph of maximum flows at Arjc Dedessa Dam      Site
44
45
84
84
85
86
Figure 14 1        Power Duration Curves .................................................................................................... 98
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1.     INTRODUCTION
1.1    The Nile Basin
May 2007
Having a length of 6.825 km., the Nile River takes the rank of number one with respect to
length, in tne world It drains a total drainage area of 2.96 M.Krrf, with its annual total flow
of about 84 Bm  As one could appreciate, the discharge per Km
3
2  is small when compared
J
to other large rivers of the world. From the Lake Victoria, to the Mediterranean Sea, the river crosses very many different areas associated with different climate relief ano geology The main sources of the river are the equatorial lake plateau and the Ethiopian Highlands. The three major tributaries which emanate from the Ethiopian Highlands are. from south to the north, the Baro Akobo, the Blue Nile, familiarly known as AODay and the Tekeze -Atbara System.
1.2    Abbay Basin
The ADbay Basin is one of the most important basims, in Ethiopia It accounts for about 17.5% of Ethiopian land area, 25% of its population and 50% of its annual average surface water resources. In the Lake Tana, it has the country’s largest fresh water lake, covering an extent of 3000 kmz The Aobay nas an average annual run off of about 50 B m The rivers of Abbay contribute on an average 62% of Nile over flows in Aswan dam.
The climate of the Abbay Basin is dominated by two features, namely, it's near equatorial location and in altitude range between 590 m.amsl. to 4000 m. amsl. These influences result in rich variety of local climates, ranging from not/desert like along the Sudan border to the temperate type on the high plateau with depiction of cold in the high mountains The Basin can g enerally be d escribed a s t emperate a t h igher e levation a nd tropical a t lower elevations However due to the distinctive aspects of the mghiand climate, it is perhaps better to describe it using the local climatic zones, that have bean established witn elevation (and resultant temperature) as controlling factors.
The Qolla zone lies below 1800 meters and has annual temperature range from 20°C to 28°C The Woma Dega zone lies between 1800 meters and 2400 maters and has annual average temperature ranging from 16°C to 20°C The Dega zone, above 2400 meters has average annual temperature ranging from 1O°C to 16°C The major portion of the population inhabit in the more climatically pleasant ano nealthier upper two zones, whicn leaves the lower Qolla zone sparsely populated.
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There are mainly  3 rainy  seasons  The main one (kiremt) lasts  generally  from June to September, during which, the south west winas bring rains from the Atlantic Ocean. About 70% to even up to 90% of the rainfall occurs during this season. This season obviously is associated with minimum levels of sunshine, low variations in daily temperature and high relative humidity A dry season (Bega) lasts from October to January, during wnich clear skies are associated with maximum sunshine hours, high daily temperature vanation and low relative humidity F inally the minor rainy season (Belg) lasts from February to May, during which south east winds  bring the small rains  from the Indian Ocean. The temperature range is very high in this season The precise timing and duration of these seasons vary considerably depending upon location within Abbay Basin, and to some lesser extent, year to year as well
Generally  speaking, the low altitude depicts  the pattern of 11 5 to even 12.5 nours  of sunshine and temperature varying only for a small range from 3°C to 7°C through out the year
The mean annual rainfall over the entire basin could be reckoned at 1400 millimeters, where as the mean evapotranspiration is aDout 1 300 millimeter. Broadly, based on the rainfall pattern, 4 different areas  have been identified by  the earlier Master Plan study (Abbay River Basin Integrated Master Plan Project - BCEOM in association with BRGM. ad ISL consulting Engineers - 1998). These are
i)    Southern area covering East ano West Wellega, Jimma and lllubabor Zones with relatively hign rainfall (1400-2200 millimeters) and a iong wet season.
ii)   A central area covering most of Western Gojam ano Darts of neignooring zones as well, charactenzed by relatively high rainfall (1400 - 2200 millimeters). But there is a  more  pronounced  seasonal  pattern  associated  with  short  wet  and  longer  dry seasons
iii)  An area covering most of the eastern part of the basin including North ano South Wello, Eastern part of East Gojam and South Gondar and much of North and North West Snewa region, excluding small proportion of mountain areas. This area is characterized by relatively low rainfall (less than 1200 millimeter) distributed in both the rainy seasons, depicting bimodality.
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iv)         The West and North West area covenng North Gondar region. The rainfall is about 1200 millimeters, falling predominantly, in the mam rainy season associated with high average rates of evapotranspiration.
With respect to the hydrographic scenario, the Basin is dominated by Abbay River which rises in the center of the catchment and develops its course in a clock wise spinal. It collects tributaries all along its 992 km journey up to Sudan border. As said earlier, the Abbay Basin catchment area of 199,812 km2 is encompassing the break up as below:
As Gilgel AbDay the main river flows north from its source near Sekela into the wide and shallow Lane Tana The take also receives other tributaries from a catchment of 15,054 km2 including tributaries Megech, Ribb and Gumara. Shortly after leaving the lake, the river reaches the celebrated Tis Abbay falls, thereafter flowing in a deep and rugged gorge on its way to Sudan Border The break-up of Abay oasin catchment area is available in Table 1 1
1.3    The Dedessa Catchments
The Dedessa River is the largest tributary of the Abbay in terms of the volume of water contribution to the total flow of Abbay  at the Sudan border Draining nearly  an area of 34,000 square kilo meters, the Dedessa over o nginates in the Mt.Vennio and Mt.Wache ranges, flowing in an easteny direction for about 75 kilo meters, then turning rather sharply to the north until it reaches the AbDay River The major tributaries of the Dedessa river are the Wama, entering from the east, the Dabana from the west, and the Angar from the east.
Dedessa Catchment is situated in tne south-west part of Abbay Basin. The catchment area at a gauging station near Arjo town is 9,981 Km The climate of the Dedessa Catchment results  from its  location and elevation (1220 to 3012 meters; The catchment is characterized by mountainous, highly rugged and dissected topography with deep slopes The iowest part of the catchment is characterized by valley floor with flat to gentle slopes
Most of the rainfall in the Dedessa Catchment is concentrated in the June to SeptemDer period with virtual drought from November througn February Annual totals, average from less than 150 centimeters to more than 200 centimeters. The Dedessa catchment, besides reflecting a marked rainfall increase with higher elevation, also receives heavier annual quantities  than most or the catchments  in the Abbay  basin Examination of the rainfall records from this area shows that this is due to a longer (May through OctoDer) rainy season rather than heavier maximum monthly quantities
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The mean annual flow of Dedessa nver at Arjo station is about 3,800 million m naving its maximum flow in August and September (52 percent of the annual) and minimum flow in February and March (less than 1.5 percent of the annual).
Further  vivid  descnption  of  the  climatic  factors,  rainfall  and  hydrological  parameters  are made in the ensuing respective sections of this report
Table 1.1:       Break up of Abbay Basin Area
May 2007
3
System Tributary
Joining Catchment
From Area (Km )
2
Lake Tana
—                      15,054
North Gojam                    Right side
Beshilo
Weieka
Jemma
Left side
tf
M
South Gojam                    Rignt side
Muger Guder Fincha Deaessa Angar Wonoera Dabus Beles Dinder Rahad
Left side
M
*
M
M
Right side
Left side
Right side
—
—
Total
14,389
13,242
6,415
15,782
16,762 8,188
7,011
4,089
19,630
7,901
12,957
21.032
14,200
14,891
8.269
199,812
>1
il d
d
d
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2.
REVIEW OF PREVIOUS STUDIES
Because  of  the  importance  of  the  Abbay,  very  many  studies  had  been  carried  out  in  the  past,
concerning   the   basin.   Though,   there   was   not   any   specific   study   for   the   development   of
Dedessa  suo  basin  exclusively,  all  the  studies  under  taken,  pertaining  to  Abbay  or  the  country 
as  a  whole,  spoke  of  Dedessa  development.  Hence  thougn  such  a  review  has  to  be  more
exhaustive,  it  is  necessary  to  undertake  such  a  review  before  attempting  Dedessa  sub  basin
development  especially  the  aspects  connected  with  hydrology  in  this  sectoral  study.  Such  a
review is presented in the following sub paragraphs
2.1     Lahmayer 1962 Study
This  was  mainly  concerned  with  Gilgel  Abbay  Scneme  Although,  it  was  not  having  adequate
data  base,  the  study  provided  interesting  information  about  Gilgel  Abbay  and  its  tributaries,
which could be considered as a data base for review ano up dating in the light of the raw data
2.2     Land and Water Resources of the Blue Nile Basin Ethiopia
The   study   was   under   taxen   by   the   United   States   Department   of   the   Interior   Bureau   of
Reclamation   during   1958   -    1964    This   detailed   study   on   land   and   water   resources 
development  of  the  Abbay  Dasin  is  wortn  mentioning  important  study  Even  at  a  time,  when
there was a little or no data, very exhaustive analysis of the available data had been carried out
to  establish  nyoroiogicai  studies  In  fact,  the  pioneering  works  undertaken  during  that  time,  has 
made  ADbay  basin  in  Ethiopia,  to  be  proud  of  a  possessing  a  good  net  work  of  hydrometric 
stations   for   making   reliaDle   estimates.   The   hydrological   aspects   nave   been   covered   in
Appendix  III  of  the  report.  In  4  different  sections  of  this  Appendix,  the  various  facets  of
hydroiogical analysis nave been put forth as below:
•    Section I: A general cescnption on climate, availability of water, sedimentation rates
and possible irrigation requirements.
•    Section II’ A presentation of the status of historical stream flow and their
elaborations.
•    Section III. A presentation on flood flows and the analysis attempted
•    Section IV: A presentation on water use
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In the Section I. on giving an account of the synoptic  and climatic  situations, the 22 stations with long data have been analyzed for precipitation and temperature The basin isotherm and precipitation maps  have been prepared based on above analysis. The water availability aspects  have been also addressed in this  Section I The samples  analyzed at 5 stations indicated a low sodium hazard; most of them showed low to medium salinity  hazard, some samples  contained from none to a maximum of 0.2 ppm of Boron, which was  found to be tolerable by  most sensitive crops. The samples  showing highest salinity  were from Mugger and Dinder. With respect to sedimentation, ratings  were established at 4 stations  and based on extrapolation; the sediment rate was  computed at all the identified potential dam sites. The pattern of sediment distribution in reservoirs, expected after 50 years of useful life was adopted uniformly  in a water balance type of simulation, for establishing the success  of each of the identified projects. In tne section, 3 regions  have been identified for development with respective crop projections, cropping calendar and crop water requirement. The water requirements varied from 782 millimeters in Gilgel Abbay to 1375 millimeters in Dinder area
The section II has  addressed the stream flow development for locations  of the identified dam sites  by  possible best set ot analysis  available at tne time In the study  period 59 gauging stations  were established, including 14 stations  with automatic  stage records  By  the various analysis  including grapnicai rainfall runoff correlations, the flow series  were built up at all dam locations  and at salient locations  The annual mean flows  at Sudan border was  estimated at 50 Bm3.
For the Deoessa at Arjo, the correlated flows  were established for 8 years  (1911 to 1917 and 1932j. The mean annual flow estimate was  4332.82 Mm3 (catchment area 9486 Square kilo meters)
For the Dabana at Abasina, the mean annual flow was established at 1757.26 Mm3  (catcnment area 3080 Square Kilometers)
For  the  Angar  near  Nekemte,  the  flow  estimate  at  annual  mean  level  was  2523.33  Mm3 (Catcnment area 4350 square Kilometersj
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3
For the proposed Deaessa dam, with a catchment area of 3360 square kilo meters, the flow was estimated to be 1533 75 Mm Similarly, for the dam site at Dabana. with a catchment area of 2654 kilo meters, the annual flow at mean level was  estimated at 1515 63 Mm3 For the Angar, 2 dam sites had been identified one at a location with a catchment area of 1780 square kilo m eters (AG-2 D am) a nd a nother a 11 ocation with a c atchment a rea o f 4 523 s quare k iIo meters  (AG-6 Dam). The mean annual flows  estimated respectively  at these two locations were, 983 125 and 2251 26 Mm3
The section ill, addresses  the causative factors  of floods  in Abbay  The design rainfall for the basin was  estimated Daseo on 6 representative station s  data. These are presented below, which are forming a qata base, worth for review and up dating for adoption.
1 day design rainfall
=          87 Midi meters
2 day design rainfall
=
126  "
5 day design rainfall
=
185  “
10 day design rainfall
=
251  “
15 day desigr rainfall
=
321  “
3
The design flood was  estimated by  physical approach using unit hyorograpn, storm analysis and design flood nydrograpn convolution for 21 dam sites  F or the others, flood frequency analysis based statistical return period floods were estimated
For the Deoessa DD-2 reservoir, the PMF was computed as 5390 m3/sec with a base period of 99 hours. For the Dabana storage reservoir, the PMF estimate was at 4860 m /sec with a Dase penod of 91 hours. For the Angar-2 reservoir with a catchment area of 1780 square Kilometers the PMF  ano the duration of the nydrograph were 3970 m /sec  and 80 hours  respectively  For the Angar-6 reservoir, the above respective figures were 6180 m /sec and 111 hours.
For the Dedessa storage dam, the 5 10 25, 50,100, year floods  were estimated to be 1700, 1900. 2100, 2300 and 2400 m /sec  respectively  These formed a good data base for review in the present study
3
3
3
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The section IV, as indicated in the beginning deals with the water use studies. The 1960 water use status was reviewed along with such water uses in villages. Then, the run off estimates have been adopted considering the envisaged irngation and power developments in respective simulation study. Due to Dedessa dam USBR study, estimated a reduction of about 139 M mJ in Dedessa flows to the Abbay .
On the whole, this USBR study is a useful one for the basin as a whole, though with paucity of data, because of its systematic treatment of hydrological and simulation aspects.
2.3   Country wide Master Plan studies - EVDSA/WAPCOS (1988-90)
These studies  were carried out during 1988-90 for country  wide water and land resources development, covering all nver basins. These were primarily  desK studies  for identifying potential irrigation and hydropower sites based on country wide data collection and analysis, coupled with detailed map studies. The study was addressing the Abbay basin also, along with other basins. The USBR studies  were reviewed in detail for the Abbay  basin, and subsequently  this  study  came out with modifications  in the USBR sites  in some cases  and proposed many other sites as well. Though desk study, the data base available to this study, on nydrological and hydro meteorological aspects were fairly adequate because of the earlier pioneering works by USBR in establishing a good net work of such data observation stations.
In this study, the rainfall as well as run off data for the vicinity of the identified projects were collected ano analyzed even though elaborate consistency checks were not under taken. The
data gaps filling and extrapolation of data have been done using statistical regression analysis, using mostly oi-variate linear as well non linear correlations. In certain major dams, synthetic 
data generation by single site multi season stochastic models as well has been under taken
With respect to floods, the flood frequency analysis of the annual maximum flood series has been earned out for the observation stations, in the vicinity of all identified potential dam sites The EV1 distribution with the method of maximum likelihood fitting has  been followed in the above flood frequency  analysis. On deciding the appropriate design criteria for the inflow design flood for each identified dam site, the flood peaks of the nearest gauging station have been transferred to the dam site by empirical formula. For deriving the shape of the complete design inflow hydrograph at the dam site the procedure as indicated below has been followed.
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For the nearest gauging station, the observed maximum flood hydrograph were isolated For these a relationship between time and Q/QP ratio were established (t against Q/QP) where t represents  time Q represents  the discharge aft’ and QP is  the peak  discharge Using this pattern of relationship the cam site hydrograph has  been developed using the peak  as estimated by flood frequency analysis.
Simulation studies have been systematically carried out to judge the success of a scheme at cntena based reliability  levels. Climatic  data otner than rainfall have also been documented, though without detailed processing or elaborations. The sediment rates as quoted by various previous  studies  of different Dasins  have been adopted and used in simulation studies, considering life expectancy of projects as 50 years.
The data base on the geometry  of identified studies  could be considered to be only approximate, as  were based on purely  topographic  maps. The hydroiogicai and hydro meteorological data were also not put into rigorous  analysis, which is  called for design of identified projects. However, this study aiong with USBR study back up gave a very good data base/ inventory  of all possible exploitable cam sites  in Abbay  Dasin. This  EVDSA/WAPCOS study has cameo out such exercise in all the other river basins of the country as well
The dams  identified in the Dedessa sub basin by  this  study  is  the Arjo Dedessa irrigation project. This  proposal envisaged a dam, a chute spillway, an irrigation outlet with in take structure and a canal taking off on the nght side. The project envisaged irrigation over 139.00C nectares with 160% irrigation intensity The inflow in a 75% reliaDle year was estimated to oe 776.80 Mm3 The 10,000 year flood with a peak of 890 cubic meters per second was getting moderated to an out flow hydrograph of peak  of 642 cubic  meters  per second The dead
storage was fixed as 93 Mm , on the basis of annual rate of around 1.9 Mm
3
3
2.4    Study by BCEOM - in association with ISL and BRG 1999
The study entitled "Abbay River Basin integrated development Master Plan Project” has Deen carried out with the following water resources onented objectives.
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•     Preparation  of  the
nver  basin  development
m
aster  pla
n  that  will  guid
e  the  development
of  the  resources  of
the  basin  potentially  wit
h
respect
to  occurrence,
distribution,  quality 
and quantity of water resources for the coming 30 to 50 years
•       To   prepare   water   allocation   and   utilization   plans   under   alternative   development scenarios  and  to  generate  data,  information  and  knowledge  that  will  contribute  to  the future water allocation negotiations with downstream countries
The  hydrological  and  hydro  meteorological  studies  are  more  relevant  for  review  in  this  section These aspects have been covered in Section II, volume ill of the Master Plan Study report.
The Dasic  climatic  features  and the climatological data of the Abbay  river basin are discussed first. The rainfall data procured by the study was for 173 stations; the data length varied from 3 to 40 years, with associated monthly  gaps. The data for other climatic  factors  were availaDle for 108 stations. The field verification of these stations  and equipments  has  also been under taken The data is  said to nave been subjected to analysis  and some errors  connected with observations  or processing were laentified. The study  has  perhaps  not attemDted to improve the quality  of sucn data on the plea that it was  outside the consultant's  capacity  or responsibility  As  such, tne data base after screening and omitting such erroneous  data is stated to be good.
With  respect  to  Hydrology  in  the  part  2  of  the  aoove  volume  III,  the  following  aspects  nave been covered systematically.
•    Basic Hydrograpmc Features
•    The Hydrometric net work
•    Review of orevious studies
•    Data collection ana Analysis
•    Sectoral methodology
In the basic  hydrographic  aspects, a good work  of preparing a map of the basin has  been presented dividing the basin in to reasonably  homogeneous  areas, named Basin Units', representing each of the catchment of one tributary  or of several minor ones., with similar behaviors. With respect to the hydrometric  net work, it has been considered to be adequate as 
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per WMO norms, taking in to consideration 116 effective stations. The list of station, tneir locations, and drainage areas  controlled have been well documented in T  ables, appendices and maps The master plan has found that the spatial distribution of the stations is not even or equitable The parts  of Besnilo, Weleka and Jemma were not adequately  represented Based on visit to all accessible observation stations the master plan could identify.
•     In  many  cases  those  stations  which  have  been  abandoned  are  not  worth  reconstruction either  they  had  not  been  installed  at  optimal  locations  or  the  catchment  area  controlled by them was too small
•     The  numbers  of  automatic  water  level  recorders  still  operational  at  the  study  time  were low  though  most  of  the  stations  had  been  equipped  with  such  recorders  at  the  time  of tneir installations
•    In many gauges stations the cables of bank operated cable way were missing
•     On  tne  other  hand  most  staff  gauges  were  in  good  condition  and  water  level  data  was considered to De quite reasonable.
There  upon  recommendations  have  been  spelt  out  to  be  executed  as  and  when  budget, equipment and man power are made available.
In the first observation, it is  felt that what is  meant as  optimum could have been indicated As far as  hydroiogicai net works  are concerned, optimality  vanes  depending upon the purpose of the net work. It could De a general purpose net work or could be a specific purpose net work. It is  not clear that what is  the master plan ascribed optimality. Further, since because a gauging station controls  a small catcnment, it seems  they  have been ignored by  the master plan study.
Measurement of discnarges have a multipurpose oriented utilities like, ascertaining the
sensitive or non sensitive areas, flood rate estimation or for a specific purpose including
community based water harvesting schemes etc. Hence, the approach of ignoring stations 
with small catcnments does not seem to be Dased on analysis of vivid concepts.
Subsequently,   the   Master   Plan   has   made   a   very   brief   review   of   hydroiogicai   aspects   of previous studies. Again it is felt that a Master Plan of the magnitude could have reviewed in a
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more elaoorate manner. The review could have brought out each aspect of hydrological and hydro meteorological and simulation studies  attemptea by  the earlier studies  Only, such detailed review would hare formed the datum to appreciate the further studies  taken up by  the Master Plan.
Next, the data collection and analysis  part is  discussed in the report. The data sets  processed were mean daily  levels, discharge measurements  and suspended sediment concentration data. With respect to data processing, the major study  carried out seems  to oe review and reestablishing rating curves. The details  on very  many  hydrological analysis, which should have been carried out before final use of he data in basin simulation are not finding a place in the hydrology volume (not explicitly described).
With respect to rating curve analysis, detailed exploration of the discharge data of 121 stations have been made and equation of the form.
Q = a (H-H )°
o
have been fitted, wmch is common practice in Hydrology It is a good thing that Master Plan
has used both analytical ana graphical methods in parallel in establishing such rating curves 
For all the stations analyzed, a total of 253 equations have been arrived with good correlation coefficients of 0.90 and above in 90% of the pairs of data.
The  discnarges  have  been  estimated  using  these  equations.  Then  Master  Plan  study  states that  on  checking  homogeneity,  the  monthly  values  wee  extracted
it  would  have  been  better  to  appreciate  if  the  nomenclature  of  Homogeneity  with  justifications had been indicated in the report.
It  is  also  stated  further  in  the  Master  Plan  that  the  discharges  were  compared  witn  earlier studies ana the results did not nave major variations.
Again it is felt that better appreciation could have been made, if the concept of major variation had been spelt out.
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Subsequently, water Balance model of the basin has  been formulated taking only representative s tations so a s t o m ake t he m odel c omprehensive without o ver loading T he selection criteria used for identification and inclusion of hydrometric  stations  in the model seem to be appropriate. The input hydrological discharges  were established on daily  time resolution level for the period of 33 years  (1960-1992). The gap filling techniques  seem to have in built subjective inferences.
With respect to assessment of water availability, a map has  been prepareo on a scale of 1 1000. 000 to estimate the global water availability  to be applied to all potential water resources development sites in Abbay basin.
This map couid De of use just for a preliminary estimate of annual flows at pre-feasibility level
The water availability has Deen further estimated by aetailed water balance model. In this in
the first run, tne present scenario has been in built and for 18 net work stations, and water
availability has Deen estimated. The salient findings of this run are as Deiow which are in order.
•    The annual average volume flowing across the border from Abbay River is 50.30 Bm3
•      Adoui   83%  of  tne  average  annual  volume  at  border  is  flowing  in  4  months  (July  - October),  while  tne  4  montns  from  FeDruary  to  May  account  for  less  than  4%  of  the mean annual flow
•     The  average  annual  flow  at  the  out  let  from  Tana  represents  aDoui  7%  of  the  above annual flows at border.
Floods:   The   highest   flood   nydrographs   recorded   at   each   of   the   water   balance   net   work stations have Deen put to analyses to establish the relation Detween time and Q/Qm ratios.
Then flood frequency  analysis  of the annual maximum discharges  has  been carried out by Gumbei's  EV1 distribution to estimate the return period flood peaks  (It is  not clear wnetner the annual maximum oDservec  peaks  were converted in to instantaneous  peaks). Further another relationship connecting catchment size to flood peak  has  been derived for 2 groups  of catcnment sizes; one for catchment groups  having catchment area less  than 10,000 km2 and another one for catchment sizes  more than 10.000 km2. It has  been concluded that the formulae derived so can be used for pre-feasibility  level studies  only  Master Plan has 
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attempted to link slope of different catchments with flood discharge rates, which a*so did not exhibit any correlation It has been opined in the Master Plan that rainfall runoff correlations were not applicable
No data or study results on flood side will be of any use to the present project specific study The flood studies adopted by the Master Plan might be useful for preliminary estimates teve' only
Sediment  transportation:  For  96  stations,  sediment  rating  curves  have  been  analyzed  with available data, on the basis of following type of relationships
QL = a (H-Ha)° linking water level with flow
QS = aQLp linking sediment
discharge QS with liquid discharge QL with a and 0 as parameters
The total sedimentation transported is accounted as the sum of suspended sediment load and bed load For bed load estimation. 3 different options  are indicated, with a sort of recommendation on Meyer Peter equation However, at the end of sediment deliberations Master Plan study has felt that a global estimate of bed load transport for the whole Abbay basin or for any of the large sub basins has no meaning: Hence the study nas further stated that at Master Plan level, considering the amount of bed load transport definitely being small compared to suspended load and considering the size of the Abbay  basin it was  not necessary to proceed with data collection for evaluation of bed load estimation
The  above  statement  of  Master  Plan  is  not  able  to  be  appreciated  without  elucidation Subsequently, the Master Plan has prepared maps related to erosion
The other studies connected with water balance ano water resources modeling seem to be in order Software WATBAL has been used in the modeling for vanous scenanos of development after initial calibration for the present scenario
These have been done for
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• present situation
• Future situation encompassing
o  Scenario  N°  1
(identified projects 1)
g   Scenario  N°  2
(identified projects 2 including Tana Beles)
o  Scenario  N°  3 o Scenario N° 4
(identified projects in main stream) (Full development)
The  results  could  De  utilized  for  comparing  the  results  of  specific  sub  basin  oriented  modeling studies, like the one under taken in the present study
2.5 Study by Ministry of Water resources for Lower Dedessa (2001)
This  is  a reconnaissance level study  for the Lower Dedessa Medium hydro power project. This gives  a vivid analysis  of the data and the Hydrological features  of the Dedessa sub basin The aam site controlling a catchment area of 18,200 square Kilo meters, has  the following water resources potential according to this study
Mean annual flow
=7290 Mm3
Annual Flow in 75% exceedance year=6300 Mm3
Annual Flow in 80% exceedance year=6100 Mm3
Annual Flow in 90% exceedance year=5230 Mm3
Annual Flow in 95% exceedance year=4600 Mm3
The following are the frequency floods estimates
10 Year return period flood
20 Year return period flood 100 Year return period flood 1000 Year return period flood 10000 Year return period flood
=1977 cubic  meter per second =2210 cubic  meter per second =2735 cubic  meter per second =3480 cubic  meter per second =4224 cubic meter per second
A sediment rate of 500tons  per square kilo meter per year has  been adopted. This  gives annual sediment load of 9 1 million tons  per year. The 50 year sediment volume of 329 Mm3 had been accounted for reservoir sizing.
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n
The  study  had
analyzed
the  energy  generation  with  a  net
head  of
133  meters  and  with  tne
m
in
IN
IN
assumption  of
regulation
of  70%  of  the  mean  annual  flow  T
he  energ
y  that  could  be  generated
so, was estimated to be 1580 GWh per year, with an installed capacity of 299 MW, on adopting a plant factor of 0.6. This  is  very  relevant to Dedessa sub basin and the present study  The useful data were taken in to account.
2.6 Utility of Earlier Studies
All the earlier studies  reviewed have some useful data base All the useful information (data of all the above studies  have been reviewed and utilized as  per need and appropriateness). However, the present study  is  specific  sub basin (Dedessa) development study, and as  such, systematic  hydrological ano modeling studies  are warranted with modern tools  of analysis. This sectoral report narrates these specific studies.
ri
id
id
id
id
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3.
DATA BASE
For
the
study  towards  the  development
of
the  Dedessa
sub  basin,
the  data  on
climate,
river
flows and sedimentation become relevant with respect to Hydrological Modeling ano W ater
Resources Planning
3.1    Climatological Data
The climatological data like sunshine duration, relative humidity, wind speeds  temperature in the resolution levels  of monthly  means  of daily  means, monthly  mean of daily  maximum and monthly  mean of daily  minimum, become very  important parameters  with respect to the proposed command area development. These, in association with command area rainfall form the basic  inputs  for the estimation of the crop water requirement exercise. A vivid analysis follows on these important parameters in the section 4 of this report
3.2.   Rain fall
The rainfall requires  critical analysis  for the dam site and the upstream for appreciating and developing floods; either as  a full hydrograph or in the form of flood peak  rate, expecteo at different Exceedance probability  levels  (return penods). The rainfall data needs  to be analyzed in its various forms, like maximum of observed 1 day/2 day or 3 to 15 days values, or as a time senes  of observed annual maximum 1 day  rainfall or as  monthly  / fortnightly  totals  as  Der analysis  at different stages  The analysis  has  to under take tne gambit of short duration rainfall intensities  as  well, in connection with design of drainages  and return period rainfall peaks  for the design of flood control works, in tne downstream of the dam, in and in the vicinity  of the proposed command area.
3.3.   River Discharge
Likewise, the river flows  data time series, preferably  on monthly  or fortnightly  time resolution levels, forms  the fore runner for establishing water resources  availability  for performing simulation whether as  basic  historical time series  or indirectly  througn synthetically  generated time series  (mostly  generated by  a stochastic  generation scheme); where as, the same flow data nas  to be analyzed in a different form as  discharge (flow rates  instead of flow volumes) with respect to flood analysis
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3.4.
Sedment Data
The
s
ediment  data
is  obv
iously  req
uired
to
pian  the
si
ze
of
the
storages,  for
app
ortion
ing
the
activ
e
and  inactive
storag
e  spaces 
and
for
determin
in
g
the
revi
sed  geometry
of
the
stor
age
after
certain   design
life,
(revised
elevat
ion
-   area
-
c
apa
city 
relationship);
as 
this 
revi
sed
relation is  used in the simulation modeling The water quality  is  another aspect, which needs  to De a daressed i n H ydrological s tudy along with I ow f low a nalysis f or m andatory d ownstream releases, closely associated with the concerns of environmental and ecological aspects.
With sucn appreciation of the frame work  of nyarological studies  and modeling, the data base was  established, as  elaborately  discussed in the Interim report. However in the following sections and in the annexure enclosed with this report, the data base on climatology, hydrology including sedimentation, floods  are indicated All the data available in a regional sense, up to date (2004) were brougnt to analysis desk and appropriately included.
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4. ESTIMATION OF REFERENCE EVAPOTRANSPIRATION
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4.1
Intro
duction
The
climate
of  the  Aqo
Didessa  catchme
nt
results  from
its 
lo
cation
and  e
levation
(1
300  to
3012
mete
rs).
The
Iist  of
stations  for
observations  of
m
eteorological
dat
a
along
with
iength
of
records
and
availability  of data types  is  given in Table 4.1 All relevant types  of data have been recorded at Jimma (located very  close to the head of the Didessa catchment) stations  since 1953 Rainfall and temperature have been observed at Didessa and Bedele. Rainfall and temperature have been also recorded at Dembi and Agara stations.
Climatic  data for the project area such as  temperature, relative humidity, sunshine hours, wind speed and rainfall have been collected and reviewed Consistency  tests, data rectification and other adjustments  have Deen performed as  necessary, data gaps  have been filled using interpolation and correlations methods as appropriate.
The FAO Penman-Monteith method is maintained as the sole standard method for the computation of crop reference evapotranspiration (ET ) from meteorological data. This section
0
describes how the monthly ETO is determined from temperature, numidity, wind-speed and sunshine hours data collected at Banir Dar station. The ET  calculation nas been carried out by 
0
means of a computer
The FAO Penman-Monteith equation determines  tne evapotranspiration from the hypothetical grass  reference surface and provides  a standard to which evapotranspiration for various  crops growing in the Arjo-Dedessa project command area can be related
The methods  for calculating evapotranspiration from meteorological data require various climatological and pnysical parameters. Some of the data are measured directly  in Banir Dar meteorological station. Other parameters  are related to commonly  measured data and can be derived with tne nelp of a direct or empirical relationship. This  section discusses  the source and computation of all aata required for the calculation of the reference evapotranspiration by means of the FAO Penman-Monteith method
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The meteorological factors  determining evapotranspiration are weather parameters  which provide energy  for vaporization and remove water vapour from the evaporating surface The principal weather parameters  to consider are presented below. The data obtained from the Beaele, Dedessa and Jimma stations  are assumed directly  applicable to the Arjo Dedessa Irrigation Project with application of appropriate information transfer mechanisms.
4.2    Meteorological Data
4.2.1    Meteorological Observation Stations
Five meteorological oDservation stations are located in and around the Arjo-Dedessa Irrigation
Project area. These meteorological data are obtaineo from the National Meteorological
Services Agency (NMSA). Out of these Jimma is Class 1 station that include observations of
rainfall, temperature relative humidity, sunshine duration, wind speea, and evaporation
Bedeie and Dedessa are also Class 1 stations but do not include sunshine duration. In
addition. Agaro and Dembi are Class 3 stations that include observations of rainfall and
temperature. The longest record that covers 50 years of meteorological data is available at
Jimma station that includes rainfall and temperature data since 1952
Agaro ana Dembi stations  are locateo within the cachment area of the proposed dam site Jimma station is  located at approximately  at 10 km from the divide of Dedessa catchment. Bedelle station is  located close to the proposed imgation command area of the project Deaessa station is  located further downstream of the command area. The details  like location, altitude, year of establishment along with their ciass are available in Table 4.1
Meteorological data available at the five observation stations  located in and around the project area have Deen collected. The types  of meteorological data available at these stations  along witn the length of data are given in Table 4.2.
Jimma Airport meteorological station is taken to be the most reliable Class I station from which meteorological information relevant to the project area has  been derived. The data from Jimma station has  been used for both the catchment study  ana estimation of meteorological variables at the irrigation command area. The necessary  adjustment for the differences  in elevation has been made in transferring the data. Meteorological information from Agaro and Dembi stations 
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whicn are located within the dam site catchment have been used for catchment study, in addition to Jimma station. Similarly, meteorological data of Bedelle and Dedessa nave Deen used in addition to the aata obtained from Jimma station for estimating rainfall and evapotranspiration at the proposed irrigation command.
in summary, climatologicall data obtained from Bedele, Deoessa and Jimma stations  were found to be the most reliable and relevant for use in the analysis of rainfall for the Arjo Dedessa irrigation project. Bedele is  geographically  the closest station to the command area. Dedessa station and the command area are located at the same elevation (i.e, both 1330 m asl). Jimma station (which is  Class  I) has  the longest record of all the stations  within the neighbourhood of the command area so as  to De index  station in extrapolating and interpolating missing and snort term of climatic data relevant to the Arjo Dedessa catchment and command area
4.2.2    Air temperature
In the project farm area, the mean monthly  temperature variations  tnroughout the year are minor, oeing 20.0°C in December to 25 4°C in March. The mean monthly  temperatures  of the command area is  given in Table 4.3 and graphically  illustrated by  Figure 4.1. Temperature data have Deen jsed in estimating evapotranspiration rates from reference crops.
Agrometeorology  is  concerned with the air temperature near the level of the crop canopy  In traditional and modem automatic  weather stations  the air temperature is  measured inside shelters  (Stevenson screens  or ventilated radiation shields) placed in line with World Meteorological Organization (WMO) standards  at 2 m above the ground. Minimum and maximum thermometers  record the minimum a nd maximum air temperature over a 24-hour penod.
Due to the non-linearity  of humidity  data required in the FAO Penman-Monteith equation, the vapour pressure for a certain period should be computed as  the mean between the vapour pressure at the daily  maximum and minimum air temperatures  of that penod The daily maximum air temperature (Tmax) and daily  minimum air temperature (Tmjn) are, respectively, the maximum and minimum air temperature observed during the 24-hour period The mean daily air temperature (Tmean) is only employed in the FAO Penman-Monteith equation to calculate the
21
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slope  of  the  saturation  vapour  pressure  curves  (A),  estimating  saturation  vapour  pressure (e°(T) and aTK4 (Stefan-Boltzmann law).
The soiar radiation absorbed by the atmosphere and the heat emitted by the earth increase the air temperature. The sensible heat of the surrounding air transfers  energy  to the crop and exerts  as  such a controlling influence on the rate of evapotranspiration. In sunny, warm weather the loss of water by evapotranspiration is greater than in cloudy and cool weather
4.2.3    Air humidity
Mean humidity values vary between 56.63 percent in Marcn to 88 63 percent in September The mean monthly  humidity  of the command area is  given in Table 4.3 and graphically illustrated by  Figure 4.2 Data of humidity  have been used in estimating evapotranspiration rates from reference crops
The relative humidity (RH) expresses the degree of saturation of the air as a ratio of the actual (e ) to the saturation (e°(T)) vapour pressure at the same temperature (T). Relative humidity is 
a
the ratio Detween the amount of water the ambient air actually holds ana the amount it could nold at the same temperature. It is dimensionless and is commonly given as a percentage. Although tne actual vapour pressure might be relatively  constant throughout the day, the relative humidity  fluctuates  between a maximum near sunrise and a minimum around early afternoon The variation of the relative humidity  is  the result of the fact that the saturation vapour pressure is determined by the air temperature. As the temperature cnanges during the day, the relative humidity also cnanges substantially.
While the energy  supply  from the sun and surrounding air is  the main driving force for the vaporization of water, the difference between the water vapour pressure at the evapotranspiring surface ana the surrounding air is  the determining factor for the vapour removal. Well-waterea fields in hot dry arid areas consume large amounts of water due to the aDundance of energy and the desiccating power of the atmosphere. In numid tropical regions, notwithstanding tne high energy  input, the high humidity  of the air will reduce the evapotranspiration demand. In such an environment, the air is already close to saturation, so that less additional water can be stored and hence the evapotranspiration rate is lower than in and regions.
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4.2.4
Wind speed
Mean
wind  speed  values  vary  between  0.48  meter  per  second  in  November  to
1  08  meter  per
second in April. The mean monthly  wind speeds  of the command area are given in Table 4 3 and graphically  illustrated by  Figure 4.3 Average wind speed recorded at Jimma station in meters  per second (m/s) is  taken as  wind speed information relevant for the Arjo-Dedessa command area as there is no reliable data at other climatic stations nearby. Time series aspect of the wind aata is  not considered as  it exhibits  unacceptable erratic  variation within the record period. Using the mean values  against the time series  data has  been tested for Bahir Dar station and resulted in equal result for monthly  and annual evapotranspriation estimates However, the mean wind values  produced an estimated coefficient of variation (CV) of 2.2% instead of 2.4% estimated from the time series
Wind is  characterized by  its  direction and velocity. Wind direction refers  to the direction from wnich the wind is  blowing. For the computation of evapotranspiration, wino speed is  the relevant vanable. Wind speed is  measurea with anemometers. The anemometers  commonly usea in weather stations  are composed of cups  or propellers  which are turned by  the force of the wino By  counting the number of revolutions  over a given time period, the average wind speed over the measunng period is computed.
The process  of vapour removal depends  to a large extent on wind and air turbulence which transfers  large quantities  of air over the evaporating surface. When vaporizing water, the air above the evaporating surface becomes  gradually  saturated with water vapour If this  air is  not continuously  replaced with drier air the driving force for water vapour removal and the evapotranspiration rate decreases.
4.2.5     Solar radiation
Mean sunsmne duration is  8.3 hours  in December and is  reduced to 3.7 hours  during July  The mean monthly  sunsmne durations  of the command area are given in Table 4.3 and graphically illustrated by  Figure 4.4. Data of sunshine hours  have been used in estimating evapotranspiration rates from reference crops
The   relative   sunshine   duration   (n/N)   is   another   ratio   that   expresses   the   cloudiness   of   the atmosphere. It is the ratio of the actual duration of sunshine, n, to the maximum possible
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duration of sunshine or daylight hours  N. In the absence of any  clouds, the actual duration of
sunshine is equal to the daylight hours (n = N) and the ratio is one, while on cloudy days n and
consequently the  ratio may  De zero.
In the absence of a direct measurement of R ,
5
the relative
sunsnme duration, n/N, is  often used to derive solar radiation from extraterrestnal radiation. As with extraterrestrial radiation, the day length N depends on the position of the sun and is hence a function of latitude and date.
The evapotranspiration process  is  determined by  the amount of energy  available to vaporize water Soiar radiation is  the largest energy  source and is  able to change large quantities  of liquid water into water vapour The potential amount of radiation that can reach the evaporating surface is  determined by  its  location and time of the year Due to differences  in the position of the sun, the potential radiation differs  at various  latitudes  and in different seasons. The actual solar radiation reacnmg the evaporating surface depends  on the turbidity  of the atmosphere and the presence of clouds  whicn reflect and absorb major parts  of the radiation When assessing the effect of solar radiation on evapotranspiration, one should also bear in mind that not all available energy  is  used to vaporize water Part of the solar energy  is  used to heat up the atmosphere ano the soil profile.
4.3    Penman-Monteith Equation
From   the   original   Penman-Monteith   equation   and   the   equations   of   the   aerodynamic   and canopy resistance the FAO Penman-Monteith equation can be expressed as follows.
ETo = 0 408 A (P nOry [900/(T -r 273)1
v
- £=)
(2.1)
A + y (1+ 0.34 bj) where
ET0 = reference evapotranspiration [mm day  ],
1
R  = net radiation at the crop surface [MJ nrf
n
2
day ],
1
G = soil heat flux density [MJ m z
day' ],
1
1
s
a
T = air temperature at 2 m height [°C],
u 2 = wind speed at 2 m height [m s' ],
e  = saturation vapour pressure [kPa],
e  = actual vapour pressure [kPa] = e  RH
s         mean.
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e
5
- e  = saturation vapour pressure deficit [kPa],
a
A = slope vapour pressure curve [kPa °C ], y = psychrometric constant [kPa C ]
RH = relative humidity divided by 100 and
Rn           — Rns " Rnl
(2.2)
Rns         = 0 77 Rs
(2.3)
R  = (0.25 + 0.50 n/N) R
(2 4)
s
a
R  = ctT   (0.34 -0.14 e   ) (0 135 Rs/Ro - 0.35)
nl               k                                          a
4                                  05
(2 5)
R   = [0.75 + 2 (Altitude)/100000] R
so
a
(2.6)
The calculation procedure consists of the following steps
1.   Derivation of some climatic parameters from the daily maximum (Tmax) and minimum
(Tmin
) air temperature, altitude (z) and mean wind speed (u ).
2
2.   Calculation of the vapour pressure deficit (es  - e ). The saturation vapour pressure (e )
a
s
is denved from Tmai<  and Tmtn
, while the actuai vapour pressure (e ) can be denved from
a
the dewpoint temperature (Taew), from maximum (RHma,) and minimum (RHmin) relative humidity, from the maximum (RHmax), or from mean relative humidity (RHmean).
3.   Determination  of  the  net  radiation  (Rn)  as  the  difference  between  the  net  shortwave radiation (Rns) and the net longwave radiation (Rm). In the calculation sheet, the effect of soil heat flux (G) is ignored for daily calculations as the magnitude of the flux in this case is relatively small. The net radiation, expressed in MJ m'2  day ’, is converted to mm/day (equivalent evaporation) in the FAO Penman-Monteith equation by using 0 408 as the conversion factor within the equation.
4 ET0 is obtained by combining the results of the previous steps
The following values were selected from FAO 1998 (Crop Evapotranspiration - Guidelines for computing crop water requirements - FAO Irngation and drainage paper 56).
o Psychomemc constant (y) for different altitudes (z),
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o Slope of vapour pressure curve (A) for different temperatures (T),
o Saturation vapour pressure [(e°(T)] for different temperatures (T),
o Daily extraterrestrial radiation (R ) for different latitudes,
a
o Mean maximum possible daylight hours (N) for different latitudes,
o oTk    (Stefan-Boltzmann law) at different temperatures (T)
4
The
estimated  mean  daily  and  monthly  reference  crop  evapotranspiration  magnitudes  (in  mm)
from
1991 to 2004, based on Penman-Monteith Equation, are presented by Tables 4.3 ano 4 4.
respectively ano graphically illustrated by Figure 4 5
The results of the meteorological analysis including the rainfall are provided in the annexture A Table 4.1:         Table Details of Meteorological Observation Stations located in and around the project area
S.No
Station Name
Latitude
North
Longitude
East
•
Deg.      Min.
Deg.    Min.
Altitude Period
(m)
1 Agaro 07 51 36 36
2 Beaelle 08 27 36 20
3       Dedessa                  09         33        36         06
4       DemDi                     08         04        36         37
5       Jimma                     07         40        36         50
1700
2005
1300
1950
1725
1980-2004
1967-2004
1971-2004
1954-2004
1952-2004
Table 4.2: Types of Climatic Data available at the various Meteorological Observation Stations
1      Dioessa               30
2      Bedele                 28
3      Dembi                 20
4      Agaro                  21
5      Jimma                 50
Yrs refer to rainfall series
No
Station name        Yrs
RF        Tm
RH
ws
SD
1 hr
1 day
Rday
Class
XXX X 1
XXX X 1
XX
XX
XXXXXXXX1
3
3
RF       monthly rainfall
Tm      average temperature RH      relative numidity WS      wind speed
SD       sunshine duration
1 hr maximum 1-hour rainfall 1 day maximum 1-day rainfall Rday number of rain days
26
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Table 4.3:
Summary of Meteorological Characteristics at Project Area
Jan       Feb     March    April      May     June     July      Aug      Sept      Oct       Nov      Dec
Monthly Mean Temperature in oC
Average    21.9   23.15    25 4    25.05   24.03   22 09   21.32   21.19   21.83   22.35 22.144 19 99 CV      0.048   0.044   0.036   0.065   0.071   0 029   0 028   0.031   0.027   0 038 0.0544 0.066
Skew 0.071 -0.58 0.067 -3.628 -3.23 0.117 0.275 0 007 0.93 0.353 -0.118 -0.02 ' Min 19.5 20.44 23.63 16.26 15.89 20.96 19.99 19 88 21.06 20 19 19.081 16.92 Max 24.6 24.9 27.37 27.72 26.19 23 41 22.72 22.34 23.2 24.25 25.051 22.88
Relative Humidity (%)
i
Average   64.77   58.97   56.63   67 97   75.72   81.07   87 46   88.52   88 63
84.55 79 366 72 44 '
CV      0.099  0.127   0.084   0.073   0.053   0.047   0.061   0.048    0 03    0 053 0 0705 0 089 Skew    -0.27   -0.27    -0.37   0.474    -0.2    -0.87    -2.92       -2      0.249    0 19 0.287 -0.13 i
Min 51.5 43.2 45.09 57 42 65.23 65 8 61.77 72.23 82.49 74.24 67.667 55 37 Max 77.3 71.68 64 08 82.17 86 18 90.3 98.1 97 53 95 67 94.73 93.187 85 13
Wind Speed (m/s)
Average 0.62 0.8 1.0 1.08 1 04 0.86 0.62 0.51 0.5 0.51 048 0.51
Sunshine Hours (hrs/oay)
Average   8.155   7.638   7 452   7.287   7.624   6.061   3.703   4.059   6 164   7.855 8.3245 8.306 CV      0.125  0.166   0 145   0 165   0.157   0.189   0.243    0.23     0.22    0.139 0.2139 0.104
Skew -0 47 -0.36 -0 27 -1.12 0.141 -0.36 0.248 -0 42 -0.27 0.138 -3 525 0.971 Min 6.05 4 905 4.592 3.304 5.428 3.364 2.277 1.6 2.622 5.778 0 1121 6.634 Max 10 9.919 9.744 9 44 10.15 8.12 5 445 6.2 9 12 10 08 10.201 11 02
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Table 4.4:
Summary of Estimated Mean ETo of Arjo Dedessa Project Area
Jan      Feb       March April       May      June     July      Aug      Sept      Oct     Nov     Dec
Dailv: Estimated ETo (mm/day)
Average    3.7     4.11     4.62     4.51     4 33     3.58     2.96     3.11     3.81     4.03   3.79    3.44 CV       0.05    0.06     0.05     0.07     0 08     0.08     0 08     0.08     0.09    0 06   0 12    0.05
Skew -047 -0.77 -0 -0.95 -0.65 -0.19 0.33 -0 51 -0 18 -0.27 -3.11 0.88 Min 3.23 3 38 3.99 3.44 3.35 2.97 2.58 2.44 2.88 3.5 1.95 3.11 Max 4.03 4.49 5.24 5 13 5.06 4 15 3 46 3.59 4 49 4 47 4.24 3.96
Monthly Estimated ETo
(mm/month)
Average     115     115      143      135      134      107     91.8     96 5      114     125    114     107 CV       005     0.06     0.05     0.07     0.08     0.08     0 08     0.08     0.09    0.06   0.12    0 05
Skew    -0.47 -0.77         -0      -0.95    -0.65   -0.19    0.33    -0.51    -0 18   -0.27  -3.11    0.88 Min       100     94 8      124      103      104       89        80       75.7     86.5     109    58 6    96.4 | Max       125     126      162      154      157      125      107      111      135     139    127     123
Estimated Eto (mm/day)
(form average values of data)
1
Average   3.69    4.08     4.58     4 48     4.28     3.57     2.95     3.10     3.75    4.00    3.79    3 44
Estimated Eto (mm/month) (form average values of data)
Average     114     114      142      134      133      107       92        96       113     124    114     107
Note: Total annual ETo = 1397 mrr.
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Table 4.5: Magnitude of ETo at given non-exeeaance probability level
May 2007
1
Non-Exd
(mm/day)
Probaiility Jan      Feb     Mar    April    May     June    July    Aug        Sept    Oct      Nov       Dec
(%)
55         3.72 4 14 4.65   4.56   4.37  3.61  2 99  3.14   3 85  4 06   3 84  346 60         3 75 4 18 4 68   4.60   4.42  3.65  3.02  3.18   3.89  4 09   3.90  3.49 65         3 77 4.21 4.71   4.64   4.47  3 68  3.05  3.21   3.94  4 12   3 96  3 51
I
I
70
80          3.86 4.33 4.83   4.80   4.63  3.81  3.16  3.32   4.09  4.23   4.16  3.59
85          3.90 4.38 4 88   4.86   4.70  3.87  3.21  3.37   4.16  4.28   4.25  3.63
90          3.95 4.45 4.94   4.95   4.79  3.93  3.27  3.44   4.24   4.34   4.35  3 67
95          4.02 4 54 5.03   5.07   4.93  4.04  3.35  3.53   4.36  4 43   4.51  3.74
Avg        3.70 4.11   4.62    4.51    4.33   3.58   2.96    3.11    3.81   4.03    3.79   3.44
75
3  3 . . 8 83044..229544..7795  44.7649  44..5572  33.7772 33.0129  33..2248  43.0949  44..1195  44..0029  33..5563
Non-Exd
(mm/month)
Probaiility Jan Feb Mar April May JuneJuly Aug Sept Oct Nov Dec Annual
(%)
55       115   116   144    137    136   108   93    97 4   116   126    115    107   1405
60       116   117   145    138    137   109   94    98.4   117   127    117    108   1412
65       117   118   146    139     138   111   95    99 5   118   128    119    109   1420
70       118   119   147    141     140   112   96     101    120   129    121    110   1428
75       119   120   148    142     142   113   97     102   121   130    123    110   1436
80       120   121    150    144     144   114   98     103    123   131    125    111   1446
85       121    123   151    146     146   116   99     105    125   133    127    112   1457
90       122   125   153    148     149   118  101    107    127   135   131    114   1471
95       125   127   156    152     153   121  104    109    131   137    135    116   1492
Avg 115 115 143 135 134 107 92 96.5 114 125 114 107 1397
Non-Exd
Growth factor (Xp)
Probaiility Jan      Feb      Mar April             May      JuneJuly           Aug Sept Oct
Nov   Dec     Annual
90
(%)
55 1.01 1.01 1.01 1.01 1 01 1.01 1.01 1.01 1.01 1.01 1.01 1.01 1.005
60       1.01  1.02  1.01   1.02    1.02  1.02   1.02   1.02 1.02    1 02   1 03 1.01    1.01
65       1.02  1.02  1.02   1.03    1.03  1.03   1 03   1.03 1.03    1.02   1 04 1.02   1.016
70       1.03  1.03  1.03   1.04    1.04  1.04   1.04   1 04 1.05    1.03   1.06 1 03   1.022
75       1.04  1 04  1.04   1 05    1 06  1.05   1.05   1 06  1 06    1.04   1 08 1 04   1.028
80       1.04  1.05  1 05   1.06    1 07  1.07   1.07   1.07 1.07    1 05    1.1  1.04  1.035
85       1.05  1.07  1.06   1 08    1 09  1.08   1.08   1.08 1.09    1.06   1.12 1 05   1.043
1.07
1.08
1.07
1.1
1 11
1.1
1.1
95
1.09
1.1
1.1   1.11
1 09
1.08
1.15 1.07
1.053
1 12
1 14
1.13
1.13
1.13 1.14
Avg
1
1
1
1.1
1 19 1 09
1.068
1
1
1
1
11
1
11
1I
---------------------------------------- ------------------------------------------------ ------------- 29
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Temperature (oC)
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Figure 4.1:      Mean Monthly Temperature at Arjo Dedessa Project Area
May 2007
Figure 4.2: Mean Monthly Relative Humidity at
Arjo Dedessa Project Area
30
Figure 4.3: Mean Monthly Wind Speed at Arjo Didesa Project Area
Figure 4.4:
Mean Monthly Sunshine Hours at
Arjo Dedessa Project Area
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Figure 4.5:
Mean Monthly ETo at Arjo Dedessa Project Area
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5.
RAINFALL ANAL
YSIS
5.1 I
ntroduction
The
rainfall  data  obtained
from
B
edel
e,
Dedessa
and
Jimma
sta
tions  were  found
t
o
be
the
most
reliable  and  relevant
for
use
in
the
analysis
of
rainfall
for
the  Arjo  Dedess
a
ir
riga
tion
project. Bedele is  geographically  the closest station to the command area. Dedessa station ana the command a rea a re I ocated at the s ame e levation (i.e. b oth 1 330 m a si). J imma station (whicn is  Class  I) has  the longest record of all the stations  within the neighbourhood of the command area so as  to be index  station in extrapolating and interpolating missing and shortage of rainfall data relevant to the Arjo Dedessa catchment and command area.
The rainfall in the Arjo Didessa Catchment as well as in its surrounding is uni-modal type Most of the rainfall is  concentrated in the May  to September covering with virtual drought from November tnrougn March. The five wettest months cover 63 percent of the total annual rainfall The dry  season, being from November to February  (four months) has  a total rainfall of about 7% of the mean annual rainfall
The mean monthly rainfall for stations in the project area is given in Table 5.1 and their pattern is  graphically  illustrated in Figure 5.3. The length of rainfall data collected from Jimma is relatively  more reliable compared to the data set collected from other stations  because of its long record length and shorter time interval of observation. Didessa and Bedele stations  also provide more relevant rainfall data that can be adopted for the command area since Bedele is close to the project area and Didessa station is located within the same climatic zone as that of the project area.
5.2 Rainfall Internal and External Consistency
Though a good data base has  Deen established for rainfall, considering the data of the three stations  namely  Dedessa. Jimma and Bedeie, it is  customary  in Hydro-meteoroiogical studies to firm up tne consistency with statistical analysis.
The trend in the annual rainfall pattern is  a relevant aspect with respect to the behavior of the rainfall and to compare such behavior with those of other relevant stations involved in the study with a view to firm up external consistency. Accordingly, a 3 year moving average analysis
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was taken up for each of the 3 stations. The results are shown in the figures 5 1 (a), (b) and <c)
These show similar trends.
Similarly  an analysis  with respect to the cross  correlation structure among the 3 stations  was carried out. The cross  correlation matnx  depicts  the following status  (Table 5.2) at annual time resolution level, which is not abnormal.
Then the single mass curve analysis was taken up for each of these 3 stations (Figures 5 2
(a), (b) and (c)
These also do not indicate any abnormality to reject this data set
As  such,  these  rainfall  data  were  used  in  its  different  forms  for  various  spectrums  of  the analysis
5.3 Estimation of Rainfall Reliability Level
Using the rainfall and irrigation water available for the command area requires  the magnitude ana reliability  level of rainfall corresponding to various  rainfall time intervals. Annual, monthly and half monthly intervals are chosen durations for the Arjo-Dedessa irrigation project
Rainfall reliability  level and magnitude can be analyzed by  making use of theoretical distributions, in this  study  the Extreme Value Type III (minimum) distribution was  utilized The distribution is  also known as  the Weibull distribution or as  Gumbel's  Limited distnbution of the Smallest Value. Naturally  rainfalls  are bound by  zero or other higher values  on the left The Weibull (or EV3) distribution can be expressed as:
(5.1)
where
Xp = E + (U-E) [-ln(1-p)]VA
Xp = magnitude of rainfall corresponding to probaoihty level of p.
The moment estimates of the parameters E (the lower limit), U and a (i.e., E, U and A) can be obtained from the following equation
U = Xm + Cv.Xm Y(a)
E = U - Cv.Xm.Z(a)
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where
Xm
= mean value,
Cv
= coefficient of variation = standard deviation divided by the mean,
Y(a)
Z(a)
= (2-Cs)/6
= [8+(3-Cs) ]/9
3
and
A
= 3/(1 +Cs)
Cs = skew coefficient calculated from data
The estimated monthly and half-monthly parameters of Weibull Distribution are given in Table
5 3 ana 5.5, respectively.
The  following  algorithm  were  used  in  the  denvation  of  annual,  monthly,  and  half-month  55  to  95 percent reliability levels.
1. Averages, standard deviations, standard deviation, skew coefficient of annual, monthly 
and half-monthly averages were calculated.
2 Weibull Distribution parameters (namely U. E and A) corresponding to annual, monthly 
and naif-monthly rainfalls were calculated from the statistics.
3. Magnitudes of rainfalls corresponding to 55 to 95 percent reliability levels were
estimated.
The results so obtained are given in Tables 5.4 and 5.6 for monthly and half-monthly time intervals, respectively.
The   half   monthly   rainfall   magnitudes   as   a   percentage   of   mean,   corresponding   to   various reliability levels are shown in Table 5.7.
5.4 Estimation of Maximum Rainfall Frequencies
For internal drams  and smaller control works, the need for various  return penod rainfall and with different durations  were found to be necessary  In general, maximum rainfall magnitudes 
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of  intensity  corresponding  to  various  return  periods  (or  probability  levels)  can  be  estimated  by applying the following form
l T = Im [1+CV.K(T)]
<5 4)
where
l T = rainfall intensity corresponding to return period of T years (mm), Im = mean of annual maximum intensity of rainfall (mm/hrj,
CV = coefficient of variation of annual intensity of rainfall. K(T) = frequency factor
For Extreme Value Type I (or Gumbel) Distribution,
K(T) = -0 779 {0.577 + ln.ln[T/{(T -1}]}
The maximum annual 24hr rainfall service is given in Table 5.8.
(5.5)
The  results  of  the  maximum  24-hr  and  1-hr  rainfall  frequencies  are  presented  in  Table  5.9.  The 1 -hr rainfall intensities were estimated by the formula derived for Ethiopia expressed as.
I h = I24 (0.523 + 0.15 In D)
(3.6)
where
l h = maximum rainfall intensity corresponding to duration D (mm/hr),
In = natural logarithm
D = duration of lh (hr).
I24 = maximum rainfall intensity corresponding to duration 24 hours (mm/hr)
i he rainfall magnitudes for higher durations, 2 days & 3 days have also been analysed using the EVI frequency distribution. The results for various return periods are shown in Table 5 10
More  details  of  the  analysis  are  available  in  the  annexure  A  “Results  obtained  from meteorological Analysis"
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The annual rainfall available at different years are given below
200Z
Near year
=
1453 mm
75 % year
=
1148 mm
80 % year
=
1090 mm
95 % year
=
853 mm
Table 5.1: Mean Monthly Rainfall
Description
Jan
Feb
March
April  May
June
July
Aug
Sep
Oct
Nov
Dec
Total
Didessa
3
6
26
49    158
274
312
277
209
104
28
8
1454
Bedeie
18
23
65
105   239
291
310
303
302
156
41
12
1864
Dembi
25
44
101
126   223
303
307
367
290
145
52
29
2013
Agaro
24
36
88
93    149
232
234
231
174
127
54
30
1471
Jimma
33
49
88
133   172
219
208
210
182
103
68
36
1502
Table 5.2: Cross Correlation Matrix of Annual Rainfall
Dedessa
Jimma
Bedeie
Dedessa Jimma Bedeie
1
0.11
1
0.24
0.48
1
Table 5.3: Parameter Estimates of Weibull Distribution
Jan Feb Mar April May June July Aug Sept Oct Nov Dec Annual
y(a) 0.5 0 6 0 6 0.4 0.5 0.5 0.8 0.4 0.4 0 5 1.1 0.8 0.4 z(a) 0.2 0.2 0.2 0.3 0.2 0.3 0.1 0.3 0.3 0.2 -0.1 0.1 0.3
U    2.4
2.1    2.2    3.6     2.4     2.9     1.3     3.7     3.4     2.4    0 9   1.3       3.2
E  18.3  21  9  61  2  81.5  201.1  267.3252.9257  7245.0  131  0  30.0  13.9  1541
-12.9-15.0-17 4-55.3 -9.8
7.3 154 1 35.9 60.9 -29 9 3 8 -4 4                   575
U = Xm +Cv'Xm'y(a) E = U- Cv'Xm'z(a) X = E + (U-E)'(-ln(1-1/T)*(1/a)
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Table 5.4 Monthly Rainfalls Corresponding to Different Reliability Levels
May 2007
Reliability
Level Jan Feb Mar April May June July Aug              Sept Oct Nov Dec         Annua/
(%)
55     10.8 12.2 40.9 58 1    150    213    219    221     212  91 65 18.6 7.58      1353 60      8 84 9.79 35 8 51.7   137    198    211     210    203  81 66 16.36.12       1304 65        6.92 7.4 30.8 45.3   124    184    204    200    194   71 76 14 24.74       1253 70           5 5.03 25.8 38.6   111    169    197    190    184  61.82 12 2 3 43      1202 75      3 04 2.63 20 7 31.5  97.9    154    190    178    174   51.68 10.4 2.16      1148
80      0.99 0 16 15.5 23.8   84.2    138    183    166    164  41.138.830 92        1090
85      0      0 9.97 15.2       69.4    120    177    152    152  29 86 7.36 0           1025
90      0      0 3.87 4.84       52.9    99 7    170    135    138   17.29 6.02 0            951
95      0 0 0 0
32.7    73.7    163    113    119   1.974 4.82 0            853
Avg 15.318.453.6 69.5 180.82431)245.9238.3228.6115.531.412.7 1453 Table 5.5:        Parameter Estimates of Half-Monthly Rainfall
Month             Parameters of Weibull distribution
1.1
1.2
2.1
2.2
3.1
3.2
4.1
1/a         y(a)          W     I u |         E
0.8          0.1           1.5          8.6           -4.3 0.9          0.0          1.1          8.1           -2.6
1.2         -0 1          0.9          7.7           -4.0
0.8          0.1           1.5         11.0          -6.1
0.6          0.2          1.8         24.3         -14.8
0.6          0.2          2.0         37.7         -11.7 0.6          0.2          1.9         26.5         -13.5
4.2          0.5          0.2          2.4         54.5         -25 6
5.1          0.6          0.2          1.9         87.6         -11.2
5.2          0.6          0.2          2.0        112.7          7.5
6.1          0.5          0.3          2.8        134.3        -19.8
6.2
7.1
7.2
8.1
8.2
9.1
9.2
10.1
10.2
0.5          0.2          2.5          135          10 4
0.7          0.2          1.7          130          40 7
0.9          0.1           1.2          126          80 9
0.5 0.3 2.9 128 5.2
0.5 0.3 2.7 131 374
0.6          0.2          2.2          128          49.2
0.4          0.3          3.6        119.6         -6.2
0.5          0.2          2.4         83.5         -17.7
0.7          0.1           1.6        47.1          -117
11.1         0.8          0.1           1.3         21.5          -3 2
11.2
12.1
12.2
1.2         -0.1          0.9         10.3          -3 0
1.1          0.0          1.0          5.8           -3.3
1.3         -0.1          0.9          5.1           -3.7
Annual
0.4          0.3          3.2       1541.2      575.1
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Table 5.6. Half-Monthly Rainfall Magnitudes at Different Reliability Levels
May 2007
Month
1.1
1.2
2.1
2.2
3.1
Avg
7.5
7.8
8.8
9.6
20.6
33.0
3.2 22.7
4.1 46.7
4.2         78.2
5.1        102.6
5.2        119.8
6.1 123.2
Reliability level
55% | 60% |65% 70% 75% 80% 85% 90% 95%
4.41      343      2.49     1.58    0 69       0         0         0          0
4        3.09     2.24     1 45     0.7        0         0         0          0
2.46      1.38     0.41        0         0         0         0         0          0
5.52      4.22      2.98     1.77     0.6        0         0         0          0
13.2      10.5     7.87     5.25    2.64       0         0         0          0
24.4     21.1      17.9     14.6    11.4    8.08    4.61     082        0
15.2      12.4     9.67     6.99    4.32    1 61       0         0          0
34.9       30       25.1     20 1    15.1    9.86    4 25       0          0
59.6      52.8     46.1     39.5      33      26.3    19.4    11.9     3.32
84.27 77.2 70.28 6342 56.51 49 43 42.02 33.96 24.5
101 92.5 839 75.1 65.9 56.3 45.7 33.6 183
106 98.2 90.7 83.2 75.5 67.4 58.7 48.9 36 8
6.2          122      103.9    97 46    91.26   85.17  79.13  73.04  66.78  60.14    52.6
7.1
123.9
110
106
102
992
96
93
90.1
87.2
84.2
7.2
116.5
102
95.7
88.9
82
74.9
67.3
59
49.3
37
8.1
121 8
110
104
99
93.6
87.9
82
75.6
68.2
59.1
8.2
120
108
103
97 6
92.7
87.6
82.4
76.9
70.8
63.5
9.1
108.5
97 9
92.1
86.1
80
73.4
66.3
58.4
48.9
36 1
9.2         73.7      58.7      52.5      46.2      40      33.6      27      19.9      12      2.37
10.1
10.2
11.1
11.2
12.1
12.2
41.8
19.7
118
6.1
6.6
1453
29.2      24.9       208     16.8    12.8    8.77    4.68    0.38        0
13.1      11.1       9.3      7.54    5.83    4 16     2.5     0 82        0
4.15      2.92      1.83     0.85       0         0          0         0          0
2.02      1.21      0.46       0         0         0          0         0          0
0.83        0           0          0         0         0          0         0          0
1353     1304     1253    1202   1148   7090   7025   950.5     853
Annual
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Table 5.7:        Half-Monthly Rainfall Magnitudes in Percent of the Mean Corresponding to Different
Month      Avg
Reliability level
_______ ______ !
I 55%      60%     65%     70%    75%    80%    85%    90%
95% --------- 1
1.1          100        59         46         33        21        9         0         0         0          0
1.2          100        51         40         29        19        9         0         0         0          0
2.1          100        28         16         5          0         0         0         0         0          0
2.2          100        58         44        31        18        6         0         0         0          0
3.1          100        64         51         38        25       13        0         0         0          0
3.2
100
74
64
54
44
35
24
14
2
0
4,1
100
67
55
43
31
19
7
0
0
0I
4.2
100
75
64
54
43
32
21
9
0
0
5.1
100
76
68
59
51
42
34
25
15
4
5.2
100
82
75
68
62
55
48
41
33
24
6.1
6.2
7.1
7.2
8.1
8.2
9.1
100        84         77         70        63       55       47        38       28            15 I 100        86         80         74        68       61        55       48       40        30
100        85         80         75        70       65       60       55       49        43
100        89         86         82        80       77       75       73       70        68
100        88         82         76        70       64        58       51        42        32
100
100
90 85 81 77 72 67 62 56 49
90 86 81 77 73 69 6^ 59 53
9.2 100 90 85 79 74 68 61 54 45 33
10.1 100 80 71 63 54 46 37 27 16 3
10.2 100 70 60 50 40 31 21 11 1 0
11.1         100
11.2         100
12.1         100
12.2         100
66         56         47        38       30       21        13        4          0
35         25         16         7         0         0          0         0          0
33         20          8          0         0         0          0         0          0
13          0           0          0         0         0          0         0          0
Annual
100
93         90         86        83       79        75       71        65        59
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May 2007
Year (mm/d)
Year (mm/d)
Year     (mm/d)
1967      47.1                1980      45.6                 1993       50.1
1968      47 0               1981
1994        57 8
1969      64.0               1983       50.0                 1995        61.0
1970      57 0               1984       51.7                 1996       60 1
1971      70.0               1985      62.2                 1997       104 5
1972      45.2               1986      64 6                 1998        63.5
1973 35.9 1987 58 4 1999 63 0
1974 51 8 1988 53.2 2000 47.9
1975 36.4 1989 46.8 2001 69 0
1976 47.1 1990 49.5 2002 57.0
1978
1991       87.8                 2003
1979      45.0               1992       51.6                 2004        39.1
Average 54.14 CV        0.306
Skew 2E-04
Table 5.9 Maximum Rainfall Magnitudes and Frequencies
Return Frequency
Peiod (T) Factor (K)
Rainfall Magnitude (mm)
24-hr                    1-hr
2 -0.16
5 0.72
10                  1 30
15                  1.64
20                  1.86
25                  2.04
30                  2.20
40                  2.40
50                  2.61
51                        27
66                        35
76                        40
82                        43
85                        44
88                        46
91                        48
94                        49
98                       51
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Table 5.10 Maximum Rainfall Magnitudes for Higher Durations
May 2007
Return
Period, T        EVI Factor (Years)               K(T)
Max 2day
Rainfall (mm)
--------------- I
Max. 3day
1day Avg. of Max.
3 day Rainfall
Rainfall (mm)                  (mm)
2
5
10
15
20
25
50
100
-0.164
0.719
1.304
1.634
1.865
2.043
2.591
3.135
76 9
92.7
29.8
94.6 112.7 37.8
106.3                     125 9                         43.2
112 9                      1334                          46.2
117.5                     138 6                         48.3
121.0                     142 6                         49.9
132.0                     155 0                          54 9
142.9                     167.3                          59.9
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Figure 5.1(a
): Trend Analysis of Annual Rainfall at Jimma Station
Figure 5.1(b): Trend Analysis of Annual Rainfall at Beaelle Station
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1970
1975
1980
1985
Year
1990
Figure 5.1(c): Trend Analysis of Annual Rainfall at Dedessa Station
E
E
c
«
a
c
c
<
©
8©
3
E
E
3
o
1960        1965        1970         1975        1980         1985         1990         1995         2000         2005
Years
Figure 5.2(a): Single Mass Curve of Jimma Rainfall
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Years
Figure 5.2(b): Single Mass Curve of Bedelle Rainfall
Years
Figure 5.2(c):       Single Mass Curve of Dedessa Rainfall
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6.      MONTHLY STREAMFLOW ANALYSIS
6.1    Hydrological Observation Stations
Hydrometric  stations  on  the  Dedessa  river  and  the  neighbouring
rivers 
withi
n
the  Abbay  b
asin
the  Omo-Ghibe  basin  have  also  been  identified  The  hydrological
data
are
o
btained  from
the
Hydrology Department of the Ministry of Water Resources (MoWR)
There are two hydrological observation stations  located on the Dedessa River These are Dedessa near Arjo town (Station No 114001) and Dedessa near Dembi town (Station No 114014). Station 114001 with catchment area of 9981 km2 is  located about 44 km downstream of the proposed dam site and has  become operational since 1960 where as  Station 114014 with a catchment area of 1806 km2 is located about 137 km upstream of the proposed dam site and has become operational since 1985.
Besides  the two hydrological observation stations  located on the main Dedessa river several hydrological observation stations  are located on its  tributaries. In addition, hydroiogicai observation stations  on the neighboring Dabana near Abasina ( Station No. 1 14005), (Gilgei Ghibe near Assendabo (Station No. 091008), and Gojeb near Shebe (Statior No 091012) have been found to be relevant to the study.
The  list  of  hydrological  observation  stations  for  which  data  have  been  collected  along  with other details like their location and catchment area is available in Table 6.1.
6.2    Extension of records
Streamflow gauging stations have been installed on the Dedessa River near Ago town iStation 14001) since 1960 and near Dembi town (Station 14014) since 1985 Before the streamflow analysis, data obtained from Station 114001 (Didessa near Arjo) ano Station 114014 (Didessa near DemDi) were checked for temporal and spatial homogeneity The investigation of nomogeneity was concentrated mainly on the outliers of the monthly data senes of the record Extremely hign or low values of each series, that has occurred at time T(i) in each month M(i). was checked against the records of the month M(i-1) and M(i+1) that has occurred at the same year T() so as to judge, whether the relation is still more or less the same as that of the other years. Whenever the outliers were rejected by this test, again another test was performed with
------------------------------------------------------------------------------------ - -------------------  4b
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other  data  series  of  Station  114005  (Dabana  near  Abasina),  Station  91008  (Gilgei  Gnibe  near Assendabo) and Station 91012 (Gojeb near Shebe) for the same period T(i).
The data were checked for its  consistency  before use for different analysis. The investigation will concentrated mainly  on the outliers  of the monthly  and daily  data series. Extremely  high or low values  that occurred at a given time were checked against records  of other near by  rivers (such as  Dabana). If the outliers  are found to be inconsistent with others, then they  were replaced by  new values  that were generated regionally  from data set obtained from other stations.
6.3    Synthetic flows
In this  section, analysis  of monthly  flows  is  made with the intension of improving information required fro reservoir storage design. Reservoir storage design on the basis  of generated (synthetic) flows is preassumed.
It was  realized that the specific  sequence of historic  events  was  a random occurrence that would certainly  never occur again in the same way  To get some idea about other possible sequence within the population, in order to improve reservoir design, generating a long streamflow series  is  a mghly  accepted procedure by  hydrologists. However, it has  been pointed out synthetic  (generated) flows  do not improve poor records  out merely  improve the quality  of designs made with whatever records are available.
Mean monthly  discharges, coefficient of variation of monthly  flows, summary  of regional monthly  flow characteristics, statistics  of monthly  flows  at Arjo Deaessa Dam Site are shown by Tables  6.2, 6.3, 6 4, 6.5 respectively. The monthly  stream flows  at different reliability  level are available in Table 6.6.
In order to maintain the historical skewness  in the generated flows, the Weibull distribution has been fitted to tne standardized residuals  of the monthly  series  Accordingly, the estimated parameters  of the random generator that were used in the Thomas-Fiernng model are presented in Table 6.7.
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Mone   details   on   various   results   are   shown   in   the   annexure   B   Results   obtained   from hydrological analysis."
The flows at the dam site at annual level are as below
Mean    year    =          2328 Mm3
75 % year
=
1729 Mm3
80 % year
=
1625 “
90 % year
=
1384 “
95 % year
=
1224 “
Table 6.1:          Availability of Streamflow Data in the Region
SI Nc
St.
No
Station name and Location             Lat
North
Long
East
Area
2
JKm )
Flow
(Mm’/yr)
Runoff
lT L
m
1 114001 Dedessa near Arjo 841 36.25 9981 3826 383
2 114014 Upper Dedessa near Dembi 8 02 36.28 1806 1221 676
I
3      114005      Dabana near Abasina
Gilgel Gibhe near
4      091008      Asenaabo
5      091012      Gojeb near Shebe
Table 6.2: Mean Monthly Flow (in Mm’/secj
9.02 36.03 2281 1870 820
7 45 37.11 2966 1211 408
7.25 36.23 3494 1803 516
I
1st No
Jan Feb March April May June July                         Aug       Sep       Oct       Nov      Dec
1
114001 114014 114005 091008 901012
Annual
I
41.9 26.7      26     33 5 63.6 216             646      1050     902      526      148       80.7   3761 12.2    9.5    11.5 16.9 36 4 112.4           228 9 306.9 262.8 154.3            48.4     20.5   1221 1 35.4 19.8      16.3 17.0 35.1 107.0 258.8 433.0 473.4 313.9 103 3                         56 6   1870 14.7 13.5     12.2 15.9 33.9 100.3 216.5 319.2 277.8                      137    60.2     24 5   1211 |
31 3 22 1     22 1 31 3 86.4 169.2 323.7 415 6 400.9 202.3                       82.8     46.5 J___________________ —
i 1803 J
Table 6.3:       Coefficient of Variation of Monthly Discharges
St. No
Jan Feb March       April     May      June July       Aug      Sep       Oct       Nov      Dec
114001
114014
114005
091008
901012
0.51 0.57 0.66 0.68 062 0.45 0.35 0.3 0 33 0.67 0 62 0.59
0.47 0.5 0.48 0.56 0 69 0 53 0.29 0.27 0 30 0.56 0.81 0.53
0.28 0.42    0.33     0.43     0.60   0 47   0.20     0 16     0.25     0 44     0 30     0 34
0 46 0 58    0.78     0.45     0.43   0.36   0.22     0.28     0.27    0 61     0.79     0.58
0.79 0 36    0.34     0.43     0 63   0 44   0.31     0 26     0 34      049     0 54     0 70
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Table 6.4 Summary of Regional monthly flow characteristics
May 2007
Param   Year    Jan Feb Mar April May June Jujy Aug Sep Oct | Nov Dec_|
cv 194
Skew    151
0 51 0.68 0.595 0.58 0 61 0 47 6.33 0.29 0.32 0.58 0 66 0.57
1 80 1 66 1.503 0 86 1 65 1.05 0.12 0.7 0.59 0.94 2.19 2 02
R
B
194    0 38     0.57 0.527 0.45 0 49 0 66 0 53 0.56                 0.51     0.5 0.56 0.51
194
0 34     0 76 0 46 0.44 0.52 0.51 0.37                0.5      0.56 0 91 0.64 0 44
_____
Table 6.5 Table Statistics of monthly flows at Arjo Dedessa dam site
Table 6.6;
Reliability
Level
(%)
55
60
65
70
75
80
85
90
95
Avg
Reliability Level Vs Monthly Streamflows at Dam Site
(in Mm3j
Jan Feb Mar Ap£ May |jun            Ju| Aug Sep Oct Nov Dec A nnual
20.2 12.7 14.1     19 3 37.5131 4    371 1 568.8 480.4 239.0  75.8 35.5 2114 19.0 11.6 13.0     17.4 34 7122.3    348 4 542.6 454.6 216.6  69.9 33.2 2019 17.9 10.6 12.0 15.6 32.0 113.5 325.3 516.7 429.0 194 7 64 5 31.1             1924 16 9 9 6 11.0       13.8 29 5104.9    301 3 490.8 403 3 173.1  59.6 29.2 1828 16.0 8.7 10.1       11.9 27 1  96.4    276.0 464.5 376.9 151.6  55.0 27.4 1729 15.0    7 8 9.2 10.1 24 9      87   8 248.5 437 3 349.4  129 7  50.9 25 7 1625 14 2    6.9   8.3    8 1 22.6 78.9 217.8    408.3 319.8  107 0  47 0 24 1 1512 13 3    6 1   7 4    6 0 20.4 69   5 181.2 376 4 286 7    82.5  43.5 22.6 1384
12.5    5.2   6.5    3.5 18.2 59   0 132.1 337.9 246 0 54440.221.2           1224
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Table 6.7 Characteristics of Random Numbers Used for Flow Generation
May 2007
aram
Jan  Feb   Mar      Apr
May      Jun        Jul         Aug      Sep       Oct        Nov      Dec
werage   0.00   0.00   0 00     0.00     0 00     0.00     0.00     0.00     0.00     0 00     0.00     0 00 cv       0.51   0 68   0.60     0.58     0 61     0.47     0.33     0 29     0 32     0.58      066     0.57
Skew 1 80 1 66 1.50 0.86 1.65 1 05 0.12 0.70 0.59 0.94 2.19 2 02
0.88
1/a       0 933       7 0.834 0 620 0 883 0.683 0 373 0 567 0 530 0 647 1 063 1 00^ 0.05
y(aj 0.033             7 0 083 0 190 0 058 0 158 0 313 0.217 0.235 0 177 -0 032-0.003
1.15
z(a) 1.081             6 1.262 1 978 1.162 1 713 3.543 2.241 2.444 1 860 0 948 0 993
I
Weibul Distribution X = E + (U-E) *(-in(1-F)(1/a)
U = Xm +Cv'Xm*y(a)
E = U - Cv'Xm'z(a)
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7 ESTIMATION OF FLOODS FOR UNGAUGED CATCHMENTS
May                          —
In the hydrologic  analysis  for dams, weirs, bridges  and drainage structures, it must oe recognized that there are many  variable factors  that affect floods. Some of the factors  that need be recognized and considered on an individual site by site basis are:
o rainfall amount and storm distribution;
o catchment area size, shape and orientation
o ground cover;
o type of soil;
o slopes of terrain and stream(S);
o antecedent moisture condition,
o storage potential (overbank, ponds wetlands, reservoirs, channel, etc.), and
o catchment area.
in  general,  three  t  ypes  of  estimation  f  loods  magnitudes  (namely:  t  he  Rational  Method,  SCS methoa and Transferring Gauged Data method) can be applied for the project area.
7.1 Rational Method
The  Rational  Method  can  be  applied  to  small  catchments  if  they  do  not  exceeo  12.8  kmz   (or  5
square mile) at the most (Gray  1971). The consequences  of applying the Rational Method to larger catchments  is  to produce an over estimate of discharge and a conservative design. The metnod is  nevertheless  frequently  used in standard or modified form for much larger catcnments. This  is  because of its  relatively  simplicity. The vast majority  of catchments producing flooas  imposed on the commana drainage system lie within the validity  of the Rational Method and it has  been used as  the principal method of estimating design discharges of dykes, culverts, drainage channels, etc.
The Rational Methoa is Dasea on the following formula:
Qm = 0.2778 C.I.A.Fr
where
Qm - peak flow corresponding to return period of T years in m /sec.
= a 'runoff coefficient expressing the ratio of rate of runoff to rate of rainfall (see Annex C1 and C2),
3
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2
I = average maximum intensity of rainfall in mm/hr, for a duration equal to the time of concentration.
A = drainage area in km ;
Fr = is the areal reduction factor (this factors improves the catchment limitations 
imposed on the use of rational method).
Coefficient of runoff C for the formula are given by many soil and water conservation texts (see Annex C.1). Information on rainfall intensity I in a time of concentration (time period required for flow to reach the outlet from the most remote point in the catchment) is  required and can be estimated by  the following formula. The selection of the correct value of C presents  some difficulty. It represents  a parameter that can influence runoff including; soils  type, antecedent soil conditions, land use, vegetation and seasonal growth. Therefore, the value of C ’ can vary from one moment to another according to changes, especially soil moisture conditions
(72)
where
Tc = (1/3080)xL’ 155 h ° 385 (Kirpich equation)
Tc = time of concentration (in hours),
L = maximum length of main stream (in meters),
H = elevation difference of upper and outlet of catchment, (in meters).
The area reduction factor (Fr) is  introduced to account for the spatial variability  of point rainfall over the catchment. This  is  not significant for small catchments  but becomes  so as  catchment size increases. The relationship adopted for ‘Fr’ is based on that developed for the East African condition (Fiddes, 1997). The relationship can be expressed as;
where
Fr = 1 - 0 02 D'033 A 050
D = duration in hours, A = drainage area in km ;
(73)
2
This  equation  applies  for  storms  of  up  to  8  hours  duration.  For  longer  durations  on  large catchments the value of D can be taken as 8 for use in the above formula.
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7.2   SCS Method
A  relationship  Detween
accumulated  rainf
all  and  ac
cu
mulated  ru
noff  was  derived
Dy  SCS  (Soil
Conservation  Service).
The  SCS  runoff
equation
is 
therefore
a  method  of  es
timating  direct
runoff from 24-hour or 1-day storm rainfall The equation is: Q = (P - la) /(P-la) + S
2
(7.4)
wnere
Q = accumulated direct runoff mm
P = accumulated rainfall (potential maximum runoff), mm
la = initial abstraction including surface storage, inception, and infiltration prior to
runoff, mm
S = potential maximum retention, mm
The relationship Detween la and S was  developed from experimental catchment area data. It removes  the necessity  for estimating la for common usage. The empirical relationship used in the SCS runoff equation is:
la = 0.2xS
(7.5)
Substituting 0.2xS for la in equation 7.4, the SCS rainfall-runoff equation becomes.
Q = (P - 0.2S) /(P-»-0.8S)
2
(7.6)
S is related to soil and cover conditions of the catchment area through CN CN has a range of 0 to 100 (can De obtainea from Annex C3 and ERA 2002), and S is related to CN by:
S = 254x[(100/CN)-1]
(7 7)
Conversion  from  average  antecedent  moisture  conditions  to  wet  conditions  can  be  done  by multiplying the average CN values by Cf [where Cf = (CN/1OO) 04]
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7.3   Transferring Gauged Data
Gauged data may  be transferred to an ungauged site of interest provided such data are nearby (i.e., within the same hydrologic  region, and there are no major tnbutaries  or diversions between the gage and the site of interest). These procedures  make use of the constants obtained in developing the regression equations  These procedures  are adopted from the work of Aomasu (1989) as follows.
Qu = Qg.(Au/Ag)°70
(7.8)
where:
Qu = mean annual daily maximum flow at ungaugeo site (m /s),
3
2
Qg = mean annual oaily maximum flow at nearDy gauged site (rrr/s),
Au = ungauged site catchment area (km ),
Ag = gauged site catchment area (km ),
The  estimate  daily  (or  the  24-hr)  annual  maximum  flood  could  be  converted  into  a  momentary peak as;
2
Qp = Cf. Qu
(7.9)
Here, Cf is factor estimated as Cf = 1 + 0.5/Tc (where, Tc is time of concentration).
7.4    Estimation of Weighted Average
In general, the Rational method, SCS method and Transferring Gauged Data are recommended for relatively small, medium and large catchments  respectively  However, it is very  important to establish a smooth pattern of transition from small to medium and from medium to large catchments.
Accordingly the recommended weighted average estimate of peak flood can De given as.
Qw = WiQ, + W .Q  + W .Q
22           33
(710)
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where.
May 2007
Qi, Q2, and Q  are mean annual momentary peaks estimated by Rational SCS ano
3
Transferring Gauged Data methods, respectively
W,.W and W3 are weighing factors of mean momentary peak estimates by Rational.
2
SCS and Transferring Gauged Data methods respectively
and
W, = 12.5/(12.5+Au)
(711)
W3 =(Au/Ag)°70
(7 12)
W = 1 - (Wi + W )
23
(7 13)
Where Ag and Au are gauged and ungauged site catchment areas, respectively.
7.5   Synder Method of Constructing Synthetic Hydrograph
The Synder method has been used extensively to provide a means of generating a synthetic unit hydrograph. The following steps are used:
Step 7 Determine the lag time, T , of
L
the unit hydrograph. The lag time is the time from the
centroid  of  the  excess  rainfall  to  the  to  the  hydrograph  peak  Synder  derived  the  following empirical equation for lag time:
TL =Ct(L.Lca)03
(7 14)
where,
TL = lag time (in hrs),
L = length along the main channel from outlet to divide (in km),
Lea = length along the main channel from the outlet to the point opposite the catchment area centroid in km, and
Ct = an empirical coefficent ranging from 1.36 to 1 66. For Ethiopian condition. Ct can be estimated as Ct = 1 + 0.33x S °1
S = slope of the main stream.
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Step 2: Determination of hydrograph duration The relationship developed by Synder for the duration of the excess rainfall. Tr in hours, is a function of the lag time computed above
T  = T /5.5
rl
(5.15)
This  results  in  an  initial  value  for  Tr  of  TL/5.5.  However  a  relationship  has  been  developed  to adjust the computed lag time for other durations This is necessary because the equation
above results in inconvenient values of unit hydrograph duration              The adjustment relationship IS.
Tjadj) = T *0.25(T
l                      rn-Tr)
(7.16)
wnere T (adj) is the adjusted lag time for the new duration. T
L
RN.
(7 17)
32
The unit peak discharge can be determined from the following equation; Up = (1/2940)x(0.94 - la/P)x(6.08 - In Tc)35
where,
Up = unit peak discharge (in m /s/km /mm),
Tc = time of concentration (in hrs),
The peak discharge Qp is computed from;
Qp = Up.A. (P - 0.2S)2 /(P+0 8S)
and the time from rise of the hydrograph to the peak, Tp, is compured from Tp = 0.5 Trn + T (adj)
L
(7.18)
(5.19)
Finally, the hydrograph can be constructed using T/Tp and Q/Qp values presented in Table C5
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Tables 5.1 to 5.3 show estimated mean floods at  seven
relatively large catchments crossing the
command area from the left and right bank directions.
Table 5.1 Location of Proposed Cross Drainages and Catchment Characteristics
Caclim- ent
Area       Stream  Max. Elev Min.
Length
Elev.
Stream
Slope
C :(for
Rational
Method)
CN scs
Method
(km') (kmj (m asb            (m asl)
(%)
l     CDR-16   27. J 5      15.50     24o0         1336      0.0725         0.24             71
2     CDR-19      40.25    13.50     2360         1339      0 075t>        0.24             71
3     CDR-28       33.00    17.40     2480         1338      0.0656         0.23             71
4      CDL-3        29.60      9 00      1780         1340      0.0489         0.22             71
5     CDL-25     300.00    44 00     2480         1335      0.0260         021              70
6     CDL-28       61.00    27.00     1900         1335      0 0209         0.21              70
7     CDL-33       70.00    17.50     1990         1330       00377         0.22             71
Table 5.2 Characteristics of Flood Hydrographs
Cachm- ent
Base
Flow
Ct
Tc (time
of cone.
Tr
T L(adj)
Tp (peak
time)
Tp(adj)
Tb
(km)
(m'7s)
(hrs)
(hrs)
(hrs)
(hrs)
(hrs)
(hrs)
1 CDR-16 0 935 1.43 1.50 0.27 6.32 6.15 6.76 90.95
2     CDR-19    1.387      1.43       1.33       0.24       5.80         5.65           6.19          89.39
3     CDR-28    1 137      1.43       1 71       0.31       6.81         6.62           7 32          92.43
4      CDL-3      1.020      1.45       1.15       0.21       4.63          449            4.97          85.88
5     CDL-25     10.34      1 48       4 98       0.90      12.62       12.06         14.09         10987
6 CDL-28 2.102 1 49 3.72 0.68 9.48 9.06 10.58 100.44
7 CDL-33 2.412 1.46 2.12 0 39 7.03 6.79 766 93 09
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May 2007
Cachment
Q(D
Rational
Method
Q(2)
scs
Method
Q(3)
Admasu's
Method
Qavg
(Weighted
Average )
Unit
Runoff
(km)
(hr)
(mm hr);
(lt/s/km )
2
1        CDR-16           34.94            18.98            10 35      19.10
2 CDR-19 55 45 30.37 12.32 29.74
3        CDR-28           37.95            21.15            10.72             21.02
4         CDL-3            43 25            23.20            9 93               23.11
5        CDL-25          127 43           90.45            50.25              79.28
6        CDL-28           35.63            22.24            16.48             21.93
7        CDL-33           62.30            37.56            18.14             35.94
703
739
637
781
264
359
513
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8 FLOOD FREQUENCY ANALYSIS
8.1
In
troduction
In  flood
frequency  ana
lys
is,  the  objecti
ve
is 
to  estim
ate  a  flood
magnitude  correspon
ding
to  any 
required
return  period
of
occurrence.
Th
e
resulting
relationship
between  magnitude
and
return
period is  referred as  the Q-T  relationship. Return period. T, may be defined as  the time-interval (on the average) for whicn a particular flooa having magnitude Q- (also known as  qunatile) is expected to be exceeded.
A  reliable  estimate  of  the  entire  Q-T  relationship  cannot  be  obtained  from  small  samples  ot  at- site  data  The  benefits  of  regionalization  in  flood  frequency  analysis  have  been  recognized  at least  since  the  work  of  Delrymple  (1960).  Nowadays,  the  regionalization  approach  to  flood trequency analysis (particularly the inaex-flooa metnod) is becoming more popular
An essential prerequisite for the index-flood method is the standardization of the flood data from sites with different flood magnitudes. The most common practice, used also in this study is to standardize data by division by an estimate of the at-site mean, thus
Xi = Qi/Qm
(8 1)
Where  Xi  is  the  ith  standardized  flow.  Qi  is  the  i,h   annual  maximum  flow.  Qm  is  the  average value of at-site annual maximum flow senes.
Then the quantile QT is estimated as
Qt =
Qm.Xj
(8.2)
Thus, the mean annual flood is the moex-flood The parameters of the distribution of X are obtained from the combined set of regional data.
in  this  study  two  distributions  have  been  used  for  flood  frequency  analysis.  These  distributions are.
(a)       Generalized Extreme Value (GEV) distribution (Jenkinson. 1969)
(b)       Log-Logistic (LlG) distribution (Ahmed et al., 1988)
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8.2 Estimation of Probability Weighted Moments
May 2007
Probaoility weighted moments (PWM) are useful for estimating the parameters of distributions whose inverse forms can explicitly be defined such as GEV and LLG (Greenwood, et Al
1979; and HosKing, 1986). Accordingly, probability weighted moments (PWMs) for unbiased sample estimates can be calculated as:
N
m
10k = . l/N)ZX,.(1-F,)k i=1
(8.3)
where
Xi = flood having ranked order of i
Fi = (i - 0.35)/N = plotting position of the rth ranked flood
N = record length
The regionally averaged proDability weighted moments were computed as follows:
1.  The standardized PWMs were computed for each site as:
Xi = Qi/Qm
where Xi is the i“' standardized flow, Qi is the ith ranked flow and Qm is the average of the data set
2.      For eacn annual maximum flood record the first two probability weignted moments, PWMs, i.e. m10k. k = 1 ana 2) were computed using Equation (1).
3.     For each k, weighted average values of PWMs over M sites included in the region were calculated as follows.
M
E X,.Nj.(m10k))
MWk = _Ei__________________ _ M
Z X,.Nj J=1
(8 4)
These M,Ok values were then treated exactly as sample estimates of PWMs for the regional standardized annual maximum flood population. LLG and GEV were fitted to the standardized regional PWMs.
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PWMs
M1OO= 1OOOO
M1O1  =  0.411964 M102 = 0.250375
8.3 Generalized Extreme Value Distribution
Jenkison (1969) introauced the Generalized Extreme Value (GEV) distribution for modeling floods. It has  become more important in hydrology  since it was  recommenced by  NERC (1975) for modeling annual maximum streamflows of Bntisn rivers.
The GEV distribution is defined as:
X = u + (a/k) {1 - (-In F) }
k
The snape parameter k, can be estimated as:
k= 7 859 C + 2.9554 C2
where
C = (Miqq — .Midj________ L - In 2
(2.M1oo-6.Mioi-t-3 M102) In 3
the scale parameter
a =        k.(M,oo - 2.M_wi)
(1-2*).r(1-rk)
and the location parameter u = Mi00-(a/k).{1-r(1+k)}
GEV Parameters C =                 -0.00061
Gama =       1 0023
u =      0.879428
a=        0.253011 k =      -0.00483
8.4 Log-Logistic Distribution
(8.6) (87)
(88)
(8.9)
(8.10)
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Log-Logistic (LLG) distribution was introduced for flood frequency analysis by Anmed et ai (1988)
The LLG distribution is defined as
X= a + b.{F/(1-F)}c
The parameters c, b, and a can be estimated as follows
The snape parameter
c = Mioo-6.M_ioit6.Mio2
Mioo"2.M 101
the scale parameter
D =            Miqq-2.Miqi
c.G
and the location parameter
a =  Mioo — b G
where
G= ncj/sinn cj
LLG Paameters        G= 1.051033
a= -0.01767
b= 0.968257
c= 0.173014
8.5    Regionally averaged quantiles
< 811>
(8.12)
(813)
(8.14)
(8 15)
Generally  the differences  between estimates  of standardized quantiles  by  GEV and LLG distributions  increases  with increase in return periods. In all cases  clear differences  are observed for the large return penods  where LLG distribution gives  larger quantiles  compared to GEV distribution Estimated flood quantiles  oased on GEV and LLG distributions  are presented in Tables 8.1 and 8.2, respectively
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8.6   Choice of Distribution
Robustness  as  a criteria has  received widespread attention for choice of distribution for an annual maximum flood (AMF). Robustness  is  assumed to test whether a distribution and method of parameter estimation, considered jointly, are insensitive to departures  from assumptions  made in their use. In this  regard, LLG/PWM has  been found to be more robust than GEV/PWM (Admasu 1989).
Often, a compromise has  to be reached between flexibility  and sensitivity  to outliers. One may need to compromise on some kind of mid-way  solution The compromise could be to use a three-parameter distribution such as  GEV and LLG However, for this  purpose. LLG has  been found to be more attractive than GEV.
In addition, LLG is  less  sensitive (compared to GEV) to changes  in the small values  of the annual maximum floods  Therefore, LLG/PWM is  better than GEV/PWM for modeling AM samples that display a dog-ieg shape when plotted on probability paper
In general, LLG/PWM nas  been found to be more appropriate for modeling annual maximum floods  (AMF) compared to otner distributions. Therefore, LLG/PWM has  been applied for estimating design floods required for the project.
Thus, Dased on probability  weighted moments  method and using LLW distribution on a regional flood frequency  approach, the return period floods  have been arrived at for the proposed dam site. The monetary  peaks  discharges  at various  levels  of probability  of exceeaance (return periods) are summarized below
10 yr return period flood = 575 m /sec
20 yr return period flood = 654 m /sec
50 yr return period flood = 771m /sec 100 yr return period flood = 87lm /sec 500 yr return period flood = 1155 m /sec 1000 yr return period flood = 1303 m /sec 10000 yr return period flood = I948m /sec
3
3
3
3
3
3
3
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Table 8.1 Estimated Flood Quantiles Based on GEV Distribution
May 2007
T
Return
period
Xt
Growth
factor
Mean Max. Daily Discharge
Gauging Gauging     Wama at
Site (1)     Site (2)
Junction
Dam
site
Momentary Peak
Gauging   Wama at
Site (2) Junction Dam site
(years)    (ratio)
(m /s)
3
(m /s)
3
(m /s)
3
(m /s)
3
Gauging
S.i*t 5e (1)
(m7s)       (m3/s)     (m3/s)
2 0.95 670 214 238 354 788 272 264 392
5 1.23 869 278 309 460 1022 353 342 509
10         1 42
20         1 60
50         1 83
100        2 01
200        2.19
500        2.43
1001        320         356       530       1178        406         395         586
1129        361         402        597       1329        458         445         661
1296        414         459       686       1526        526         509         759
1422        455         505       752       1674        577         559         833
1549        495         550       819       1822        629         609         907
1716        549         610       908      2020        697         676        1005
1000 2.61 1844 589 655 975 2170 749 726 1080
2000 2.79 1972 631 700 1043 2321 801 776 1155
5000       3.03      2143        685         761       1134 10000      3.22      2273        727         808       1203
Average 1 707 226 251 374
2522 870 842 1255
2675 923 895 1331
832 287 278 414
Note The analysis is basea on regional flood frequency analysis based on Gene distribution with parameters estimated by probability weighted moments method
Table 8.2 Estimated Flood Quantiles Based on LLG Distribution
Value (GEV)
T
Return
period
(years j
2
5
10
20
50
Xt
Growth
factor
Mean 1
Max. Daily Discharge
Momentary Peak
Gauging Site
i
Gauging
Site (2)
Wama at
Junction
Dam
site
Gauging
Site (1)
Gauging
Site (2)
Wama at
Junction
Dam
site
(ratio)
(m /s)
J
(m /s)
3
(m /s)
3
(m /s)
3
(m /s)
3
.m/s,
(m /s)
3
m /s
0 95 672
1 21 854
1 39
1 58
1.86
982
1118
1317
100
200
500
1000
2000
5000
10000
Average
3.55
4.17
4Z1
1     707
1488
1680
1972
2225
2511
2947
3326
215            238         356
273            304         452
314            349         519
357            397         591
421            467         697
476            527         787
537            597         889
630            700        1043      2320         800
711            791         1177      2619         903
803            891         1329      2956        1020
942           1047       1559      3468       1196
1063          1182       1760      3915       1350
791          273
1005         347
1156         399
1315         454
1550         535
1751         604
1977        682
226            251         374
264         394
336         500
386         575
439         654
517         771
584         871
662         984
776        1155
876        1303
987        1471
1159       1726
1309       1948
832         287
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May 2007
The   probable   maximum   flood   is   defined   as   the   most   severe   flood   considered   reasonably possible to occur It is customarily obtained by using unit hydrographs and rainfall information
Annex  C4 gives  the recommended reservoir flood standards  for three main categories  of reservoirs. Category  A has  the most stringent standards, since for such a reservoir a breach in the aam would endanger the lives  of people congregated in a town or village downstream. The worst conditions  are envisaged, the spillway  already  taking the average daily  inflow when the proDable maximum flood (PMF) arrives  ana the wave surcharge allowance must be tor heights greater than 0.6 m. Categories B ana C have decreasing standard requirements
In Ethiopia, the study  of design floods  on the basis  of PMF requires  further investigation The challenging problem is  particularly  that of storm rainfall and the varying temporal pattern of intensities  throughout a storm’s  duration; the occurrence of the peak  intensity  is  a variable to De considered for further study  at national level. The initial state of the catchment is  also of great significance in the generation of an extreme flood. A thorough knowledge of a catchment and of its  varying responses  during adverse conditions  is  essential for an engineering hydrologist to evaluate design floods  and such situation need to be investigated at an institute level.
However in such a situation where there is  maximum rainfall data, Hersfieid (1961) suggests the use of following equation to estimate 24-nr PMP in region so as  to superimpose it on design unit hydrograph to give the PMF
PMP24 = Pm +K.Sn = Pm (1+K.CV)
Where
PMP24 - 24-hr probable maximum precipitation
Pm - mean of the 24-hr annual maximum over the period of record Sn = standard deviation of the 24-nr annual maximum
CV = Pm/Sn = coefficient of variation
K = a constant equal to 15
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The mean annual maximum 24-hr rainfall for Bedele and Jimma are 55.5 mm and 51.3 mm. respectively: and also the coefficient of variation for Bedele and Jimma are 0.198 and 0 20 respectively For the Arjo Dedessa dam catchment
Pm = (55 5+51 3)/2 = 53.4 mm
CV = (0 198*0 201 )/2 = 0 20
Sn = 0.20x 53.4 = 10 68
K =15
Then
PMP24 = Pm +K.Sn
= Pm(1*K.CV)
-4 0l*Pm
= 4 01x53.4 = 214 mm/day
Total volume of daily rainfall
Vp= A PMP24 = 5310*214 = 1129 5 Mm3
Assuming runoff coefficient C that corresponds to the occurrence of continuous rainfall to be 0.68. the estimated rainfall depth that produces probable maximum flood becomes
Vpe= C.Vp = 0 68-1129.5 = 768 5 Mm3
Using the catchment charactenstics given in Table 12 1 and applying the dimensionless hydrograph given by Table C4. the flood peak component due to the probable maximum rainfall becomes 3502 m /s Assuming the a Dase flow of 188 m /s the total peak flood becomes:
Qp = base flow * peak due to storm = 188* 3502 = 3690 m /s
Cumulative volumes of Probable Maximum Floods (PMF) derived from probable maximum 24- hr rainfall is given by Table 9.1 while design flood hydrograph derived from estimated PMF is given by 9.2
3
3
3
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TaDle9 1 Table Cumulative Volume of Probaole Maximum Flood
May 2007
Time         Cum. Volume        Time        Cum. Volume           Time I     Cum. Volume (hrs)      (Mm3)     (%)   (hrs)     (Mm3)        (%) _        (hrs) '   (Mm3) 1%) J|
0.00      0 000        0 00       103 50     687 8        89 5      207.00       765 3
99 6
4.50       0440        0 06       108 00     698 7        90.9      211.50       765 8         99.6
900       2 936        0 38       112.50     708.3        92 2      216 00      766.1         99 7
13 50     9 389        1.22       117.00     716 4        93 2      220.50       766.5         99 7
18 00     21.87        2 85       121 50     723.2        94.1      225.00       766.8        99.8
22 50     42 15        5.48       126.00     729 1        94 9      229.50      767.1         99 8
27 00     71.51        9.31       130 50     734 4        95 6      234 00       767 3         99.8
31 50     110.5        14 4       135.00     739 0        96 2      238.50       767 5         99.9
36 00     157.6        20.5       139 50     743 0        96 7      243 00       767 7         99 9
40.50     210 4        27 4       144.00     746.5        97 1      247.50       767 9         99 9
45 00     266.4        34 7       148.50     749.3        97 5      252.00      768 1         99.9
49.50 322 6 42 0 153.00 751 7 97 8
54.00 376 4 49 0 157 50 753 6 98.1
58.50 426.4 55.5 162.00 755.5 98.3
256.50       768.2        100.0
261 00       768.3        100 0
265.50       768.4        100 0
63 00     471 6        61 4       166 50     757.2        98 5      270.00       768 5        100 0
67.50 511.8 66 6
72.00 546.4 71 1
76.50 576.0 75.0
81 00 601 7 78.3
85.50     623.9        81 2
90 00     643.4        83 7
94 50     660.4        85.9
171.00     758.6        98.7      274 50       768 5        WOO 175.50     759 9        98 9
180 00     761 0        99 0
184.50     762.0        99 2
189 00     762.9        99 3
193.50     763 6        99 4
198 00     764.3        99 4
I
I
99 00     675.1        37 9      202.50     764.8        99 5
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Table 9.2 Design Flood Hydrograph Derived from Estimated PMF
May 2007
Tl            0/             Ti
------- ~r
Qi           Ti
Qi
Ti
Qi
Ti
■4-----------------------
(hr)
------------■
Q> J
(hr)
(m3/s)      (hr) I im3/s)
Uli
^3/S)
(hr)
(m3/s)
0.00        188      45.00     3690     90.00     1309    135 00     451       180.00      251
2 25 216 47.25 3655 92 25 1239 137.25 433 182.25 248
4.50 241 49 50 3620 94.50 1169 139 50 419 184 50 244
6.75 339 51 75 3515 96.75 1099 141 75 402 186.75 241
900 451 54 00 3410 99.00 1028 144.00 384 189.00 237
11.25 573 56.25 3270 101 25 958 146.25 367 191.25 234
13.50 748 58.50 3130 103.50 923 148.50 349 193.50 230
15.75 958 60 75 2990 105 75 853 150.75 332 195 75 230
1800 1169 63.00 2815 108.00 818 153.00 314 198 00 227
20.25 1449 65 25 2674 110 25 783 155.25 297 200 25 223
22.50      1694
24 75      2009
27 00      2289
67.50 2499 112 50 748 157.50 314 202.50 220
69.75 2324 114.75 678 159 75 307 204 75 220
7200 2149 117 00 643 162.00 300 207 00 216
29.25 2604 74 25 2009 119 25 608 164.25 290 209.25 216
31 50 2885 76.50 1904 121.50 573 166.50 283 211 50 213
33.75 3095 78 75 1764 123.75 552 168 75 279 213.75 213
36 00 3305 81 00 1659 126 00 531 171.00 272 216 00 209
38.25      3445     83.25     1554    128 25     514     173.25     269
40.50 3585 85 50 1484 130 50 496
42 75 3655 87.75 1379 132.75 472
175.50     262
218.25 209
220.50 209
177.75     258      222 75       206
b8
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10.1 Estimation of Sediment yield
May 2007
Suspended sediment data from Stations  14001, 14014 and 14005 were obtained These discharges  are given in Annex  E5. Suspended concentration rales  varying between 45 mg/lt to 1670 mg/lt were observed from Didessa river
Relationships  between water discharge and sediment loads  at various  sites  in the region are presented in Table 10 1. At-site and regional approach has been used to to estimate sediment rates  from the estimated streamflows  at the dam site Accordingly, the following relationship nas been derived
Gs = 0 078 Q15
C0 1)
?
Where
Gs = sediment load (in gm)
Q = monthly mean discharge (in lt/s/km ).
Careful assessment regarding reservoir sedimentation will be required in the site as the life of
the storage created by a dam is dependant of the sedimentation situation. Accordingly 
reservoir piannmg will include assessment of the probable rate of sedimentation in order to
predict the useful life of the proposed reservoir
in estimating reservoir sedimentation matenals  onginating as  oed load will be assumed to have a density  of 1 4gm/cc  and matenal cameo in suspension will be assumed to have a density of 1.2 gm/cc. The oed loaa at the dam sites shall be assumea to be 15 percent of the suspended load
Monthly  total  sediment  load  (suspenaed  and  bea  load)  and  accumulated  total  sediment  load  at the reservoir site are given py Table 10.2 and 10.3 respectively
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10.
2
Dist
ribution
of se
dime
nt
in the r
es
erv
oir
So
far
the
sediment
load
likely 
to
deposit
in
the
reservoir
nas  been
estimated
But
estimating
the sediment inflow to the reservoir is  not enough as  how high the sediment will accumulate in the reservoir is  also important Accordingly  Area-Increment method has  been used for this purpose. The method is expressed as:
(102)
Where
Vs = Ao(H - Ho) * Vo
Vs = sediment volume to be distributed
Vo = sediment beiow the new zero elevation
H = original reservoir depth from the stream bed level
Ho neight to wnicn the reservoir is completely filled with sediment, i.e , = neight of the new zero elevation
Ao surface areas of the reservoir at the new zero elevation ano is the = area correction factor.
The results so obtained from the analysis of distribution of sediment in the Arjo-Dedessa Reservoir are given in Table 10 4
Table 10.1 Relationships between water discharge ana sediment load
No
Station
Area
(km )
2
Module
103Vyr
Loss
t/km2/y
Vales of C in;
Qs =C.(Qw)1 5
3005 Guder at Guder 524 77 90 0.025
4007 Little Angar near Gutin 1975 176 89 0.096
4005 Dabana near Abasina 2881 453 157 0.059
4002 Anagar near Meqemie 4674 702 150 0.061
6002     Aboayjat Sudan Border
172254 335170       1946        0.165
Arjo Dedessa Dam site                                5278        776         147        0.078
____________
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3
Table 10.2:    Monthly Total Sediment Load at the Reservoir Site
(in lOOOjn } _____________________________________ _____  ______
Jan Feb March April May June July Aug Sep Oct Nov Dec Annual
Avg     2 487   33   1 14   1 71  4 51 27.2 131 1  248.5     211 5 720 7    19 29 6 87  775.6
Stddev   1 711   01   1 11   1 72    4.2 17 6 62 72  98 19       92 6 99 01      14 7 4 95  304.5
CV      3.634   01   5.75   5 31  4 91 3 42 2 526  2.086     2.311 4 349    4.024 3.8     2.07
Skew    7.366.29     8.83   7 54  11 4 7 48 3.696  0 678     3.509 7 051    10.92 8.77   4.57
Table 10.3 Accumulated Total Sediment Load at the Reservoir Site
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Table 10.4: Distribution of Sediment in the Arjo Dedessa Reservoir
May 2007
r
50 years sediment load
Ho = 2.03 m
A - 4 C*) U-2
—
100 years sediment load
Ho = 3 42 m
Ao = 3.15 Mm2
tm asJL
Original
area
Mm')
Original
capacit
y
1
Mm )
— •
Depth
imj
Sedime
nt
volume
3
(Mm )
Revised
area
(Mm’)
Reviseu
capacit
Mm )
Eiev
m asl)
Original
area
1
(Mm )
Original
capacity Depth
Sediment
volume
(Mm')
Revise
d area
| (Mm1
Revised
capacity
12
3456712
3.           L5              6            7
_.
1346  56.76 629.8     27     38 7   55 24  591 1  1346 56 76 629 8       27        774    53.61    5524 I 1343 48 13 466.4     24     34.2   46 61  432 2  1343 48.13 466.4       24         68     44 98     398.4
1340  39 92  331 8    21     29 6   38 41   302 2  1340 39 92 331 8      21        58.6    36 78    273 3
1337  32.17   224     18     25 1   30 66   198.9 1337 32 17    224      18       49.1    29 03     174 8
1334  24 93  140.7    15     20 5   23 41   120.2 1334 24.93 140 7       15       39 7    21 78      101
1331  18.24 79 64    12      16     16 72  63 67  1331 18.24 79 64      12       30.2    15 09     49 4
1328  12.19 38 24     9      114    10 68  26.82  1328 12 19 38.24        9        20 8    9.046     17 44
1325  6.911   13.6      6      6.88   5 395  6.724  1325 6.911    13.6      6         114    3.765    2.239
1322  2.619  2.322     3      2.33
150 years sediment load
Ho = 4.69 m
Ao = 4.90 Mm2
1322 2.619 2.322        3        1.92
-
200 years sediment load
Ho = 5.89 m
Ao = 6.73 Mm2
Etor
Original
Original capacit
area Depth
Sedime                       Revised
nt Rewsed capacit D riginal Original
1
Sedime
Revised   Revised
(Mm’j
17 >
__
volume   area (Mm^)     (Mm2)         W)
Elev area capacity
(m asl)  (Mm1)        (Mm’]
Depth      volume    area
r
capacity
333
(Mm ) (Mm ) (Mm )
1234
567123
4                                     ------- F
1346   56.76 629.8    27     116   51.86  513.3  1346 56.76 629 8       27      155   50 02      474 7
1343 48 13 466 4 24 102 43.24 364.6 1343 48 13 466.4 24 135 41 4 331.5
1340  39.92 331.8    21     87 1   35 03  244 7  1340 39.92 331 8      21       115   33 19      217 1
1337  32.17   224      18     72.4   27.28   151 5 1337 32.17    224      18     94.5  25 44       129.4
1334  24 93  140 7    15     57 7   20.03  82.96  1334 24.93 140 7       15     74 3   18 19      66 37
1331  18 24 79.64    12      43     13.34   36 6   1331 18.24 79.64      12     54.1    11.5       25.52
1328  12 19 38.24     9      28 4   7 297  9 887  1328 12 19 38.24        9       33.9   5 457      4 326
1325 6.911   13 6      6      13.7
1325 6 911    13 6      6       13.7
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11.   WATER QUALITY
May 2007
The water quality status of the Dedessa river is evaluated using the data collected from MoVVR database Abbay  River Basin Master Plan Stuoy  Report (1998). The samples  were taken as part of the supporting measurement for tne aquatic  study  and appear to represent the only available data on water quality  within the catchment. Table 11.1 shows  water quality measurements  taken for Dedessa at two sites. The samples  were taken as  part of the supporting measurement for the aquatic  study  and appear to represent the only  available data on water quality  within the catchment. The samples  snown in Table 111 were taken after the start of the rainy  season and presumably  all tributaries  of the river exhibited adequate water quality at the time of sampling
Total Dissolved Solids (TDS) and Electrical Conductivity (EC)
Total dissolved solids  characterized mainly  by  major anions  ana cations  are directly  related to tne electncal conductivity  of the water The low Electrical Conductivity  (EC) and TDS value in general shows  that the water is  soft in nature and has  low salinity  Moreover, the low conductivity  is  sign of low fertility  of the water with regard to aquatic  life. Electrical conductivity (EC) measurements  were very  low at all the sampled sites. EC is  the ability  of the water to conduct electric current and directly related to the amount of cations and anions in the water
PH
The pH value is the measure or the concentration of hydrogen (H+) and hydroxyl (OH-) ions in the water It is to determine the acidity or alkalinity of the substance.
Sodium and Potassium
The Na’ and K’ reading expressed in terms  of Sodium Adsorption Ratio (SAR) is  the useful parameter for the evaluation of the water body  for irrigation purpose. For irrigation water it is important to measure the sodium adsorption ratio as follows
SAR = -------------- ----------------- (9 1) [(Ca** + Mg*’)/]0 5
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The  higher  the  SAR  value  of
the
water
the
I  ess  suitable  will
be  for  irriga
tion  purposes  The
maximum  computed  value  am
ong
the  re
adin
gs  is  0.29  which
is  less  than
10  This  illustrates 
that the water is very much suitable for irrigation purpose.
Chloride
The chlonde concentration of the rivers stipulated in Tables 11 1 is very low (1 0 to 2 0 mg/l) at times  of sampling Hence the parameter was  in conformity  with the standard set by  EPA (250mg/l for aquatic species).
Table 11.1 Water quality results for sites on the Dedessa river
Sampling
Sample date
Elevation (m asl)
at Bedele bridge    at Gimbi bridge      Comment
13/08/96
1300
14/08/96
1200
TDS (gm/l)
20
20
N
EC (Os/cm)
60
50
N
pH
6.74
6.97
N
Na”
3.3
3.0
N
K*
1.9
2.5
N
Ca” (mg/l)
64
9.6
N
Mg” (mg/l)
2 43
1.4
N
Cl (mg/l)
1.0
2.0
N
SAR
0.29
0.25
N
WO Result for Major Rivers (BCEOM 1996, Cited By BCEOM Abbay River basin study 1998)
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 ___ 
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12.
DESIGN
FLOOD
12.1 Syntheti
c Hydrograph
Among  several
known  methoas  of  unit
hydrograp
hs,
the
one  de
velop
ed
by 
Synder
(1938)  is 
most   commonly
used.   The   method   is
derived
fro
m
drainage
bas
ins 
in
the   Ap
palachian
Mountain   region
s   in   the   United  States 
ranging
in
are
as   from
25
km
to
25,000
km  The
relations   of   unit   hydrograph   characteristics   and   catchment   characteristics   are   expressed   as follows
(12.1)
Where
Tp = lag time from the mid point of the rainfall-excess duration Tr to the
peak of a unit hydrograph (hr),
Ct = coefficient depending on basin characteristics
Lc = nver distance from the station to tne point of interest nearest the
centroid of the drainage area (km)
L = nver distance from the station to the upstream limits of the drainage
area (km)
The  catchment  characteristics  (sucn  as  L,  Lc  Area.  Slope)  of  Desessa  at  the  Arjo-Dedessa Dam Site is given by Table 12 1
The U.S Soil Conservation Service (SCS) developed a dimensionless hydrograph that has its 
ordinate values expressed as the dimensionless ratio, Ti/Tp Qi is the discnarge at any time Ti
The shape of the unit hydrograph dimensionless hydrograph, and Tp is the period
corresponding to peak as shown in Annex Table C5. For a given catchment, once the value of
Tp is defined using Equations 12.1, the unit hydrograph can be constructed
12.2 Flood Routing Through the Reservoir
The dam is  located where failure may  probably  be confined to the irrigation command and the dam itself No excessive loss  or human life would be expected For sucn condition, a design flood corresponding to al0,000-year return period has  been proposed The volume of flow in 1000-year return perioa flood hydrograph is about 400Mm3
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The data used to complete surcharge storage due to the design flood and routing calculations were inflow hyorograph for all selected design storms, elevation-storage relations  for proposed storage facility and stage-discharge relations for all outlet control structures
The step-by-step method of reservoir routing method has  been used. The data required for the method to construct the outflow hydrograpn is: (a) the inflow hydrograph, (b) the elevation capacity  relation curve of the reservoir and (c) the outflow-elevation curve or the outflow equation.
Using these data a design procedure is  used to route the inflow hydrograph through the storage facility  with different surcnarge storage and spillway  crest (outlet) geometry  until the desired outflow hydrograph nas been achieved
A  spillway  with  ogee  shaped  crested  weir  has  been  assumed  The  equation  generally  used  for such broad-crested weir is
where:
Q=
Q = CLH15 discharge, in m /sec
(12.2)
3
C =     broad-crested weir coefficient
L =      broad-crested weir length,   m
H =     head over weir crest, m
If the upstream edge of a weir is so rounded as to prevent concentration ana if the slope of the crest is  as  great as  the loss  of head due to fnction, flow will pass  through critical depth at the weir crest: thus gives an average C value of 2.2
The following procedures were used to perform routing through the reservoir
SteP  7    Developing   an   inflow   hydrograph,   stage-discharge   curve   for   the   proposed   storage facility
Step  2:   Selecting  a  routing  time  period,  Dt,  to  provide  at  least  five  points  on  the  rising  limb  of the inflow hydrograpn
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Step 3. Using the storage-discharge data from Step 1 to develop storage characteristics cu
that provide value S (♦/-) (Q/2).Dt versus stage
Step 4 For a given time interval. 11 and I2 are known Give the depth of storage or stage, H1, at the beginning of that time interval. S1 - (Q1/2).Dt can be determined from the appropriate storage characteristics curve
Step 6 Determining the value of S2 + (Q2/2) Dt from the following equation
3
S2 + (Q2/2).Dt = [S1 - (Q1/2).Dt] * [11 + l2)/2.Dt] where
S2 = storage volume at time 2. m /sec Q2 = outflow rate at time 2, m3/sec Dt = routing time period, sec
S1 = storage volume at time 2. m3 Qi = outflow rate at time 1 m3/sec 11 = inflow rate at time 1, m3/sec 12 = inflow rate at time 2. m3/sec
(123)
Step   6.   Enter   the   storage   characteristics   curve   at   the   calculated   value   of   S2   f  (Q2/2).Dt determined in Step 5 and read off a new depth of water, H2
Step  7  Determine  the  value  of  Q2,  which  corresponds  to  a  stage  of  H2  determined  in  Step  6 using the stage-discharge curve.
Step 8. Repeat Step 1 througn 7 by setting values of 11 Q1. S1, and H1 equal to the previous l2, Q2, S2 and H2, and using a new I2 value This  process  is  continued until the entire inflow hydrograph has been routed througn the storage basin.
Since Equation (12.3) contains  two unknowns, stepwise trial and error procedure is  used Results  of routed aesign floods  based on LLG distribution, half-PMF  and full-PMF are presented by  Table 12.2, 12.3 and 12.4, respectively  Tne elevation - area capacity  curves  of the reservoir are snown in Figure 12.1 The 10000yr return period design inflow and outflow hydrographs are shown in Figure 12.2 Such inflow and outflow hydrographs for smaller return
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periods  like
10.  20.  50  and  100  year  return  periods  are  shown  in  Figure
12.3.  The  average
hydrograph of maximum flow at the dam site is available in Figure 12 4
12.3  Routed Design Flood at the Coffer Dam
Velocity Formula
The velocity equation through the pipe outlet is given by
< 1O4J
where
V = (2gHl)05
A = cross-sectional area of barrel (or pipe), V = velocity through the barrel.
Hl = total nead loss through the barrel,
Hl = (1.5 + f L/D) V /2g
L = length of the barrel/pipe
D/4 = R = hydraulic mean radius of tne barrel D = diameter of barrel/pipe
V = velocity througn the barrel/pipe f = coefficient of friction
2
(12.5)
Manning's Formula
It is one of the most common formula, which is commonly used for the analysis of problems of flow through cnanneis. but often used for the analysis  of pipe flow problems  too According to this formula tne discharge througn pipes is given by
V = (F/n).D  S
M     1/2
(12.6)
Where
V = velocity through the pipe
n = Manning s rougnness coefficient (a value of 0.065 has been selected for old concrete pipe),
D = diameter of the pipe.
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S = slope of the hydraulic gradient or energy slope = h /L.
May 2007
t
F = is constant equal to 0 39685
L = length of the pipe fm).
h L = head loss through the pipe (m)
Equation 12 5 can be arranged to express the relations for head loss through a pipe.
h L = L [(n/F).V/D '
232
]
(127).
Combined Formula
Combining Equation 12.5 and 12 7 the above two expressions for velocity reduced to
Hl = {1,5/2g+L [(n/F) D '
23
22
)] } V
and
also
V = (H /{1 5/2g + L. [(n/F) D'
l
273]2})05
Q = A. (H /{1 5/2g + L. [(n/F) D
l
273]2})°5
= (kD /4). (H /{1 5/2g + L. [(n/F) D'
2
273 2
05
l
] })
(12.8) (12.9) (12.10)
Where A is cross-sectional area of pipe in m2
Substituting n = 0 0165, g = 9 81 in Equation 12.8 can be expressed as.
Hl = {0 076453+ L. [0 041577 D'
273 2
] }^2
V = (H /{0.076453-L [0 041577 D’
L
273]2})0 5
Q = (0 7857 D ).(H /{0.076453+ L. [0 041577 D’
2
L
273 2
] })
05
Results of routed design flood at Coffer Dam of Ago Didessa Reservoir are presented in Table
12.5.  These results  are  available  for  10,  20 50 and  100  year  return period floods. According to the criteria, the appropriate results could be adopted tor designs
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Table 12.1 Catchment Characteristics
May 2007
Arjo Dedessa Catchment Characteristics
Area (km2;
Length (km)
Centroid distance (km) Max elevation (m asl) Minimum elevation (m asl) Elevation difference (m;
S (m/m)
Ct
Tc (hrs) Tl (hrs) Tr (hrs) Tuadj) (hrs) TP (hrs)
Dimension
5278
199
141
3012
1315
1697
0.0085
1.53
24.00
33.00
4.40
38.00
45.00
Table 12.2 Routed Design Flood at FRL Corresponding to 1352 m
(a) Based on LLG distribution
Max Surface Surcharge
Ljmj Qout (m /S)
3
H m                   Area (km ) Storage (Mm )
2
3
50                     871
75                    1031
100                   1154
125                    1253
87 06
85 20
84.01
83.14
1340 1
1288.0
1255 0
1231.4
150
1333
2.54
82.47
1213.1
175
1399
3.97
3.39
3.02
2.75
Peak inflow = 1950 m3/s
2.36
81.91
1198.3
(b) Based on Half-PMF
L(m)              Qout (m3/s)
Hm
()
Max Surface
Area (Km )
2
50
75
798
941
100                    1051
125                    1140
150                    1212
175                    1273
3 75
3.19
2 84
2.58
2.38
2.22
Peak inflow = 1780 m3/s
86 34
84.56
83 43
82.61
81.97
81 45
Surcharge
Storage (Mm
13198
1270 3
1239 1
1216.9
1199 7
1186.0
80
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(c) Based on PMF
Qout (m /s)
May 2007
Max Surface             Surcharge
2                     Storage (Mm ) 3                              H (m)                 Area (Km )
50                     1668
75                     2008
100                   2265
125                   2466
150                   2626
175                   2756
6 13
5.29
4 73
4 32
3 99
3 71
93.95
91.28
89.50
88.16
87 10
86 24
1539.8
1461.3
1409.5
1371.3
1341.2
1316.8
Peak inflow = 3690 m3/s
Table 12.3 Routed Design Flood at FRL Corresponding to 1555 m
(a) Based on LLG distribution
Max Surface Surcharge
Limy Qout(m /si
3
Area (Km . Storage iMm )
2
3
50
75
812
964
100                    1083
125                    1180
150                   1261
1329
175
(b) Based on Half-PMF
3.79
3.24
2.89
2.64
2 44
2.28
Peak inflow = 1950 mis
96.26
94 57
93 48
92.70
92 09
91.59
1601.8
1546 7
1511.9
1487.1
1468.0
1452 6
Max Surface              Surcharge
L(m)
Qout (m /s)
3
H (m)
Area (Km ;
2
Storage (Mm )
3
50
746
3.58
95.61
1580.6
75
881
3.06
93 98
1527.9
100
988
2.72
92.95
125
1495.0
1075
2 48
92.20
150
1148
1471.6
2.30
91 63
175
1208
1453.7
2.14
91.16
----------11439.2
Peak inflow = 1780 m3/s
---------------------------- 1
---------------------------------------------- ---------- -------- ----------------------------------------------------------- 81
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M
N
N
N
N
Arjo Dedessa Irrigation Project Meteorological and Hydrological Aspects (c) Based on PMF
------------------------------------------------------------ —r--------------------------------------------------------------- - --------------- -I
L (mj                          3
Qout (m /s)
Surcharge
Storage (Mm3)
r---------
1
-------
50                     1540
75                     1867
100                   2118
125                   2320
150                   2483
175                   2618
H (m)
5.81
5 04
4.53
4 14
3 84
3 59
Max Surface
Area (Km2)
102.52
100 13
98 54
97 36
96 41
95.64
1811 9
1730 7
1677 1
1637.8
1606.8
1581.3
Peak inflow = 3690 m3/s
Table 12.4 Routed Design Flood at FRL Corresponding to 1356m
(a) Based on LLC distribution
L(m)              Qout (m /s)                 H (mj
3
Max Surface
Area (Km )
2
3
Surcharge
Storage (Mm )
50 800 3.75 99.11
75 951 3.21 97 49
100 1069 2.87 96 45
125 1165 2.62 95.71
150 1246 2 42 95 12
175                    1314
2.27
94.65
1693.0
1637 1
1602.0
1577.0
1557 7
1542.0
Peak inflow = 1950 m3/s
ri
(b) Based on Half-PMF
N
1
L(m) Qout (m /sj H(m)
3
Max Surface
Area (Km )
2
—
Surcharge
Storage (Mm )
3
ri
50                      735
75                      869
100                     975
125                    1061
150                    1134
175                    1195
3.55
3.03
2.70
2 46
2 28
2 13
il
9849
96 93
95.94
95.23
94 68
94.23
1671.5
1618.2
1584.9
1561 2
1543 1
1528 5
Peak inflow = 1780 m3/s
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(c) Based on PMF
May_2007___
i------------ r
L (m)
Qout (m /s)
3                              H (m)
Surcharge Storage (Mm
--------------- —
11
50                    1515
75                    1838
100                   2088
125                   2289
150                   2453
175                   2588
5.75
4 99
4.48
4 11
3 81
3.56
Max Surface
Area IKm2)
105.09
102.81
101.30
1905.2
1823.3
1769.3
100 17                     1729.8
99.28
98 53
1698.5
1672.9
Peak inflow = 3690 m3/s
Table 12.5. Routed Design Flood at Coffer Dam of Arjo Didessa Reservoir
T= 1C
yrs, Peak = 654 m /s
, —“1
3
T = 20 yrs, Peak = 654 m /s
D
(m)
0
Elev
D
(m)
Q
Elev
(m3/s)
(m asl)
im3/s)
(m asl)
5.0
210
1337.98
5.0
211
1338.22
5.5
223
1333 01
5.5
225
1333.29
6.0
239
1330.00
6.0
243
1330.32
6.5
258
1328.06
6.5
263
1328.40
2x4 0
220
1334 18
2x4.0
222
1334.45
2x4.5
243
1329.86
2x4.5
247
1330.19
3
T = 50 yrs, Peak = 771 m /s
3
T = 100 yrs, Peak = 871 m /s
("v L
D
Q
Elev
D
Q
Elev
(m3/s>
(m asl)
(m)
(m3/s)
(m asl)
5.0
213
1338.59
5.0
215
1338.89
5.5
229
1333.70
5.5
232
1334.05
6.0
248
1330 79
6.0
253
1331 19
6.5
271
1328.90
6.5
277
1329.32
2x4 0
225
1334 86
2x4.0
228
1335.20
2x4.5
253
1330.69
2x4.5
257
1331.10
Note Length of pipe, L = 400 m
S3
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I
I
I
M
M
4
M
4
1
4
ri
ri
J
J
4
Elevation-Arca-Capacity Curv® for Arjo Dtacssa Reservoir
Area (Sq. Km)
Figure 12.1 Elevation-Area-Capacity Curves of Arjo Dedessa Reservoir
Inflow and Outflow Hydrographs at Arjo Didessa Reservoir
Time (hrei
Figure 12.2: Inflow and Outflow Flood Hydrographs at Arjo Dedessa Reservoir
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Elevation (m)□ischarege (m3/»)
Dischir.ge (m3/»)
Arjo Dedessa Irrigation Project Meteorological and Hydrological Aspects
May 2007
inflow and Outflow Hydrograph* at Arjo Dlde»*a Coffer Dam. T
inflow and Outflow Hydrograph* at Arjo Didessa Co FT ar Dam. T
• 20 year*
O 25                    50           75          100         125         150         t75         200
Tww(hr*|
Inflow and Outflow Hydrograpns at Arjo Didessa
Collar Dam. T ■ 50 year*
inflow and Outflow Hydrograpns at Arjo Didessa
Coffer Dam. T = 100 years
Tima (hr*)
Figure 12.3:      inflow and Outflow Flood Hydrographs at Arjo Dedessa Reservoir
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Average Hydrograph of Maximum Flows at Arjo Didessa Dam site
15                    20                     25
Tmm tmonlht)
30
35
Figure 12.4: Average Hydrograph of Maximum flows at Arjo Dedessa Dam Site
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May 2007
Determining design capacity  of Arjo Dedessa reservoir required reservoir simulation study  The factors  that has  been considered in the analysis  include the following. This  particular section deals with the dam/ reservoir simulation for establishing the viability of contemplated irrigation
o Useable flow between reservoir and diversion,
o Spill past diversion weir
o Fiow into the reservoir,
o Evaporation from the reservoir.
o Rainfall on the reservoir
o Total irrigation demand, and
o Irrigation water release from tne reservoir
The  simulation  sample  is  provided  in  annexure  B  -  8  the  description  of  various  column, referred to there in are as below
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Column
Abbrev
Unit
Description
Col [1]
Year
Year
Col [2]
Month
Month
Col [3]
Inflow
Mm3
Natural  inflow  to  the  reservoir  as  simulated  by  Thomas-
Feiring model (monthly flows for 1000 years)
Col [4]
DF
Mm3
Natural  flow  (corresponding  to  75%  reliability  level)
between the dam site and diversion site
Col [5]
Eo-Rf
Mm
Evaporation minus rainfall over the reservoir Eo is 
evaporation at 75% exceedance level as estimated from
ETo and Rf is monthly rainfall at 75% reliability level
Col [6]
IWD
Mm3
irrigation water requirement (given by Table 13 1)
Col [7]
(Eo-Rf)
Mm3
Col [5] convened to volume covering the entire
command area
Coi [8]
SL
Mm3
Seepage loss (assumed to be 1 % percent of the
existing storage in the reservoir)
Col [9]
IWR
Mm3
Irrigation water release from the reservoir (Col[6]-Col[4J)
Col [10]
CS
Mm3
Change in storage between the ends of the previous
and current months
Col [11]
Storage
Mm3
Reservoir storage at the end of month
Col [12]
Area
Km2
Reservoir  average  surface  area  between  beginning  ano
end of month
Col [13]
Level
m asl
Reservoir storage at the end of month
Col [14]
Spill
Mm3
Spill from the reservoir between beginning and end of
month
Col [15]
STRQ
Mm3
Total annual storage requirement
Col [16]
T.Spill
Mm3
Annual spill from the reservoir (sum of Col[14] from
month 1 to 12)
The d etails o f s imulation i nputs a re p rovided i n t he T abies 1 3.1 a nd 1 3.2. The a Dstract o f t he detailed irrigation targeted simulation runs are provided in Table 13 3. With these parameters the contemplated irrigation (Table 13.1) are successful at various reliabilities shown in Table 13 3
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Table 13.1: Irrigation Water Requirements for Various Scenarios
3
(for 13700 ha in Mm )
May 2007
Phase I
Phase II
Month
Roti
Rot2              Roti
Rot2
Sep 8.38 843 12.43 12.45
Oct 10.41 10 69 13 19 13.72
Nov 2.89 2.90 3.16 3.29
Dec         11.04          12.49          14 02          16 07
Jan          19 00          22 18          24 64          28 61
Feb         23.25          27.87          29.98          34 92
Mar 18 49 22 15 22 99 26.41
Apr 4.98 521 5 09 5.30
May          2.01            2.01            2.01            2 01
Jun          21 64          21 64          32 42          32 42
Jul           5.97            5.97            8.95            8 95
Aug 6.89 6.89 10 33 10.33
Total 134.93 148.43 179.22 194.49
Tabie13.2 ReservokCharacteristics at Dead Storage Level Description
Uni)    Qunatit•fy   1
Minimum drawdown level Minimum nver bed level Area at dead storage level Dead storage
m.a.s.l              1350.0 m.a.s.l              1320.0       |
km2                             67.88
Mm3
874.7
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Table 13.3
Storage Reservoir Characteristics and Reliability Levels
Description
Unit
i          n] 75% I
Reliability level
80
% 85% 90%
Phase I, Rot 1
Dam heighqat spillway
c.l)
Spillway crest level
m
mas.I
30.89     30.98     31.08     31.24
I I
95%
I
31.42
Area at normal water level           km2
Live storage
Total storage
Mm3
Mm3
Spill over the spillway                  Mm3 Spill to live storage ratio
Phase I. Rot 2
Dam heightfai spillway c.l)
m m.a.s.l
Spillway crest level
km2 Area at normal water level
Mm3 Live storage
Mm3 Total storage
Mm3 Spill over tne spillway
Spill to live storage ratio
Phase II. Rot 1
Dam height(ai spillway
|C.I)
Spillway crest level
m
m.a.s.l
Area at normal water level           km2
Live storage
Total storage
Mm3
Mm3
Spill over the spillway                  Mm3 Spill to live storage ratio
Phase II, Rot 2
Dam heighqat spillway
c.l)
m
Spillway crest level
Area at normal water level Live storage
Total storage
Spill over the spillway Spill to live storage ratio
m.a.s.l
km2
Mm3
Mm3
Mm3
1350.89 1350.98 1351 08 1351.24        1351 42
70 797    71.094    71 424    71.952     72.546
67.3        74.4        82.3        95 1        1094
942.0      949 1       957.0      969 7      984 1 1800 0    1799.0    1754.0    1703.0    1640 0 26 74      24.17      21 30      17.92       14.98 I
31.05     31.14     31.24     31.41      31.59 I
1351.05 1351 14 1351.24 1351.41 1351.59 71.325 71.622 71.952 72.513 73.107 |
80.0        87.1        95.1        108.6      123.1 954 6      961 8      969 7      983.3      997.8
1786.0    1785.0     1740 0    1689 0     1626.0
22.34      20 49      18.31       15.55      13.21
31.14     31.22     31.33      31.5      31.68
1351 14 1351.22 1351.33 1351.50 1351 68
| 71.622    71.886    72.249    72 810     73.404
87 1        93.5        102.2      115.9      130 4
961 8      968.1       976.9      990.5     1005.0
1755.0    1754.0    1709.0    1658.0     1595.0
20 15      18.77      16.72      14.31      12.24
31.32     31.39     31.52     31.69     31.87
1351.32 1351.39 1351.52      1351 69 1351 87
72.216 72 447 72 876 73.437 74.031 101 4 107.0 117.5 131.2 145.7
976.1      981.7      992 1     1005.8    1020 4
1739.0    1738.0    1693 0    1642 0     1579 0 ' 17.14      16.24      14 41      12 52      10 84
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14.
DEDESSA SUB-BASIN MODELING
14.1
. Modeling for Arjo Dedessa dam for i
rrigat
ion
The
simmlations  discussed  in  previous  sections
is  fo
ra
com
prehens
ive
ana
lysis 
of  Dedessa
dam.
which  is  the  main  focus  of  the  TOR  A  de
tailed
Ms-E
xcel
based
mod
el,
using
1000  years 
of monthly  data of inflows, generated synthetically, were incorporated in the various  runs  to obtain the results, as  indicated in the Table 13.3. As  can be seen from the water requirement available at Table 13.1, for the ultimate development phase II, of the Dedessa dam, the optimal water abstraction is  for RoT  2. scenario cropping pattern Based on various  combinations  of the simulation runs, which are very  exhaustive, it could be stated that there could be two net phases  of development. The designs  however need to be made for the phase II development. The firmed up geometry  of the reservoir at Dedessa dam for these two phases  could as  below. This  is  for the success  of irrigation at 80% reliability. The following abstracts  are based on the results of simulation considering only contemplated irrigation.
□ For pnase I development of Deaessa dam
■      Irrigation command
■      Full reservoir level
■      Storage at full reservoir
■      Deaa storage level
■ Volume at Dead stage level
■      Live storage
13,700 na 1351 14 m 961.8 Mm3 1350.00 m 874.67 Mm3
87 10Mm3
■
River bed levei
1320.00m
■
Area at Dead storage level
67 88 km2
■
Area at full reservoirs level
71 14km2
■
Irrigation Demand
148 43Mm3
□ For phase II development of Dedessa dam
■ Irrigation command
13 700 ha
■ Full reservoir levei
1351 39 m
■ Storage at full reservoir level
981 7 Mm3
• Dead storage level
1350.00m
• Volumes at dead storage level
874 67 Mm
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Live storage
107.00 Mm3
■      River bed level
1320.00 m
Area at dead storage level
67 88 Km2
Area at full reservoir level
72.07 km2
Irrigation Demand
194 49Mm3
Thus  both the above pnases  satisfy  contemplated irrigation with 80% reliability, in the phase I and phase II, the cropping patterns  envisagea are different However, for the final design of Deadesa dam, it has to be based on phase II development with tne above aam features if the development is for irrigation only.
14.2 The sub basin modeling
When the aspect of the development of Dedessa sub basin as  a wnole, including the present proposal of Dedessa dam. is  taken for considerations, the need for the simulation of the sub basin becomes  relevant. The details  and components  of such sub basin simulation modeling could be for the following objectives
•      To  explore  the  possibility  of  power  generation  at  Dedessa  dam  Since  only  a  small fraction  of  the  total  inflow  is  to  be  used  for  irrigation,  looking  at  power  development options at the site by raising the oam height is an important consideration
•     In  such  a  scenario  as  above,  that  is,  full  scale  upper  optimal  development  of  Dedessa dam,  it  becomes  a  necessity  to  check  that  this  optimal  water  abstraction  does  not jeopardize  future  developments  tn  the  whole  of  the  Dedessa  sub-basin  This  requires basin  modelling  at  a  larger  scale  considering  contemplated  developments  upstream  and downstream
In this report, simulation exercise has Deen carried out to address the first objective. A tailor made sub basin modeling was carried out by developing a Fortran source code named
Arjosim to quickly undertaxe simulation exercise of various components with alternatives.
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Meteorological and Hydrological Aspects 14.2.1 Power Generation in Dedessa Dam
May 2007
The Deaessa aam with its  phase II configuration, could irrigate 13,700ha at 80% reliability Since, left and right bank  main canals  take off from the dam, no incidental power can be generated as  such. Hence, power development options  are sought by  raising the dam height to have additional storage for separate power releases. The FRL for optimal phase II irngation development is  1351 39 m. Two scenarios  for Higher FRL values  are considered with FRL of 1353 m, and 1356 m. For each FRL considered four different power release options  are taken up for the simulation as  depicted in Table 14 1 It should be noted that the given releases  are total monthly  releases  for irrigation and hydropower That is, the given total releases  less  the monthly i rrigation r equirement shall b e u sed f or power g eneration. T here will b e a s eparate outlet for power at the same level as that of irrigation outlet, that is, at 1350.00m.
The reservoir characteristics at the two FRls considered for the simulation are. Full Reservoir Level = 1353 m
■ Storage at full reservoir level
•    Live storage
•    Dead storage level
•    Volume at oead storage level
•    Area at full reservoir level
Full Reservoir Level = 1356 m
■   Storage at full reservoir level
■   Live storage
■   Deaa storage level
■   Volume at dead storage level
■   Area at full reservoir level
1092.51 Mm3 217.33 Mm3
1350 00m 874.67 Mm3
77.88 km2
1341.16 Mm3
466 49 Mm3 1350.00m
874.67 Mm3 87.85 km2
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 Hydrological Aspe
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The effective
turbin
e center was fixed
at
1322.0
0 m elevat
ion. This of
cours
e, needs 
to be
finalized   as 
per
ground   condition
and
dam
head/or
otherwise,
other
location
based
powerhouse Also, tne plant factor adopted in the basin simulation runs  is  unity, and with unrestncted i nstalled c apacity. B ased o n a ctual b udget a nd p ower requirement a nalysis d y Hydropower and Dam design engineer these installed capacities could be changed or power generation could be restricted The results presented in the Hydrological simulation are with these assumptions on turbine center level and plant factor However, at detailed design stage with these firmed up figures, the sub basin models could be re-run in short time
The power duration curves for the vanous runs are shown in Figures 14 1 (a1) to 14 1 (b4). These figures  are useful to reckon the monthly  power generation at various  exceeoance probability  levels  at proposed FRLs  of 1353 and 1356. With respect to annual energy production the results are presented in the Table 14.2 for Dedessa dam. This piture of energy generation is after satisfying irrigation needs fully at 80% reliability However the quantum of energy and power are of not very attractive type.
14.2.2 Optimal Power Generation
With FRL upto 1956, as seen above, though irrigation is successful, the power generation scenario is not attractive, hence the simulation model Anjosim' was, slightly recoded for
maxing simulations for increased FRL considerations and exploring the possibility of power generation at a higher levei. though the exercises are beyond the scope of the present TOR. A large number of runs ot Arjosim were undertaken under 3 different domains of preposition
These are.
Domain 1. k eeping t he p ower o utlet a t a i ower I evel o f 1 346 m a nd i ncreasing t he F RL i n stages, with various monthly power release patterns.
Domain 2: keeping the power outlet at 1346 m and increasing the FRl in stages as above, but with model in built decision support basea power releases
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Domain 3: keeping the power outlet at the same level as that of irrigation outlet (of course a separate power outlet) and increasing the FRL in stages, with decision support based power releases by the model
Domain 1 Simulations
A set of 12 different runs were attempted within the FRL ranges from 1370 to 1376 m. and with different monthly power release pattern. Some of the optical ones are.
i. With FRL 1370, the 97% power is 11.22 MW
ii. With FRL 1372, the 97% power is 13.30MW
ni. With FRL 1374 the 97% power is 13 62MW
Beyond FRL 1374. there were no encouraging improvements in power generation
Domain 2 Simulations
These runs totaling to 10 were made with decision support based power releases in built in the model This obviously increases the power generation for the set of FRLs. The optimal runs indicated the following situation.
i With FRL at 1372, the 97% power is 16.49MW
n With FRL at 1374, the firm power is 17.20MW
in. With FRL at 1376, the firm power is 17.90MW
iv With FRL at 1378, the firm power is 19.50 MW
Domain 3 Simulations
Here in addition to decision support power releases, the outlet was best at 1350W instead of 1346M adopted in the previous domains. This improved the situation. Some of the salient model runs yielded the following scenarios.
i. At FRL 1370 the firm power at 97% is 17MW n At FRL 1372m, the 97% power is 18.1 MW ni. Al FRL 1374m, the 97% power is 18 95MW lv. At FRL 1376m, the 97% power is 20MW
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14.2.3 Reduction In flows at Dedessa Sub-basin
May 2007
In either of the cases, covering 8 runs  of simulation, there is  no detrimental effect on the
downstream flows  of Dedessa sub basin. The maximum consumptive utilization is  only  for
irrigation, which is only 194.49Mm  annually, as the additional
3
releases made for power are not
for consumptive uses  The power releases  flows  downstream. Thus, a net reduction in the
sub basin flows will be up to a datum of 195mm , even without accounting for any regeneration
from irrigation. The sub basin of Dedessa contributes at its end annually to Abbay a auuatum
3
of 14,033mm3 (BCEOM Master Plan study). This will get reduced to 13,838mm  because of
3
the
proposed arjo Dedessa project, which is only a negligible reduction of 1.39%. As such, the Arjo Dedessa Dam proposal is not going to jeopardise the overall developments of the sub basin considering various identified projects of the sub basin.
14.2.4  Conclusions
The simulation runs could be made for furtner different scenario. At this stage, it could be saia that the optimal power generation would be with FRl at 1376 m and with power outlet at 1350 m. The tail race is assumed to De at 1322 m in all the runs. With a plant factor of 0.6, the installed capacity could be arouno 33MW. Hydroiogically, the simulations can be perrormea funner without any constraints, provided that there are no geological, geothechmcal, design, environmental, social and other constraints  The power generation at different reliability percentages are shown in the Figure 14.2 for the last run.
However to form up power generation, even at higher FRLs, a prefeasibility study is required for exploring the possibilities of increasing the height of dam and establishing the technical feasibility and economic viability for generation of hydro-power
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Table 14.1:       Total Monthly Release (Irrigation plus Power) options for various FRL values
considered
__________________
Options            FRL = 1353 m                FRL = 1356 m
Option i        75 MmJ for all months          Twice of monthly irrigation releases
Option II
L
75 Mm  - May to
3
September & 50 Mm  -
3
Three times monthly 
irrigation releases
Oct. to April
Option III
L
75 Mm  - May to
3
100 Mm3 for all
September & 40 Mm  -        months
3
Oct to April
Option IV
150 Mm  - May to August
3
& 40 Mm3 - Oct. to March, 75 Mm3 in Sept & April
75 Mm3 - September to April & 100MCM - May. to August
Table 14.2: Annual Energy generations at Dedessa dam for the various options
FRL              Release
Scenario
i
Options         Mean Level
Annual Energy Production (GWh) at Exceedance
___  Probability Levels of__________ 50%         75%         90%          95%         97%
1353 m              I
II 28 0 28.9 26.5 24.3 22.7 20.5
III 25.3 25.9 25.5 22.9 21 3 19.6
IV 436 44.7 433 40.1 36.3 28.3
32.0         32.3         29.8          27.3          25.2          228
1356 m               I
II               24 5         24.5         24.3         24.0          23.8         23 6
III 540 55.2 50 6 45 9 42 9 39.2 I
IV               47.6         48.5         47.5         43.8          40 9         38.1
11.9         12.0         11.9         11.8          11.7         11.7
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(a. 1) Power duration curve for FRL = 1353m - Option I
(a.2) Power duration curve for FRL = 1353m - Option II
(a.3) Power duration curve for FRL = 1353m - Option III
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(a.4) Power duration curve for FRL - 1353m Option IV
(b.1) Power duration curve for FRL = 1356m - Option I
(b.2) Power duration curve for FRL = 1356m - Option II
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(b.3) Power duration curve for FRL = >3560, - Option III
(b.4) Power duration curve for FRL = 1356m - Option /V
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15. RECOMMENDATIONS ON TRAINING NEEDS
May W7
It  is  very  heartening  development  that  the  wafer  resources  exploitation  tor  optima*  ut  uza. towards  economic  stability  is  getting  the  major  thrust  in  Ethiopia  With  phase  of  actrv soon,  the  rich  river  basins  will  be  impounded  in  different  storages  associated  with  a  number  o runoff  the  river  schemes  either  for  irrigation  or  power  or  in  a  multi  objective  sense  As  suet the  present  scenano.  the  hydrological  planning  and  design  are  in  the  usage  However    wr.e' the  basins,  in  the  near  future,  become  stuffed  with  many  projects  then  the  real  time  operation of   those   projects   will   be   the   dire   necessity   Judicial   operation  of   a   multi   reservoir   project system  has  a  lot  of  benefits  in  combating  floods  tiding  over  drought,  reduction  in  water  losses and  others  However,  such  real  time  operation  would  require  a  complete  knowledge  (in  the hydrological  sense)  of  the  basin  system,  and  hydrology  and  simulation  techniques  (simulation coupled  with  optimization  models)  Such  a  scenario  of  real  time  operation  will  have  to  be backed   up   by   flood   forecasting   networks,   advance   prediction   of   seasonal   rainfall   adequate telemetry  (for  transfer  of  data),  dedicated  computers,  telecommunication  soft  ware  in  addition to  subject  matter  (hydrology/simulation)  software  The  personnel  heading  such  operations  in  a basin, and those working in such a team need to be trained in the above mentioned aspect so as t o u ndertaxe o peration which has i mmerse a dvantages H ence. 111 s r ecommenaec t hat expens   on   Hydrology   and   Hydrological   modeling   should   be   identified   for   undergoing   such trainings  in  Institutions/umversities  in  appropriate  countries  Though  there  could  be  many  such institutes,  the  consultant  feels  for  such  multi  system  operation,  adequate  expertise  is  available in  countries  like  U  S  A  and  India,  wnere  many  institutions.  Universities.  River  basin  authonties ano  research  stations  could  be  identified  for  offering  such  trainings  Such  trained  personnel with  expertise  in  hydrology  will  be  able  to  head  future  river  basin  authonties  for  optimal  real time operation of the systems
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references
Admasu  Gebeyehu  1988  Regional  Analysts  or-  Some  Aspects  o<  Stream'  uw
.naracte'  «9C*
m Ethiopia (Unpublished Draft Report) August’988
Admasu Gebeyehu 1989 Regional flood Frequency Analysis PhD them P • 
Technology. Bulletin No TRlTA-VBI 148. Stockholm Sweden
BCEOM 1999 Abbay River Bam Integrated Development Master Plan Project Pheae 2 Data Collection Site Investigation Survey and Analysis Section n Sectora Shx>es 
Volume III Water Resources Part I - Climatology and Part II - Hydrology BCE OAZ 
French Engineering Consultants - in association with ISL and BRGM
ERA (Ethiopian Roads Authority). 2002 Drainage Design Manua' Hydrology
Fiddes   D,   1977   Flood   estimation   for   small   East   African   rural   catcnments   Proceetf.ng Institution of Civil Engineers. Pari 2. 63 21-34 (1977)
Gray. D M Editor in Chief. 1971 Handbook on the Pnnciples of Hydrology
Haan. C T, 1977: Statistical Methods in Hydrology. The Iowa State University Press Ames Hersfield D M 1961 Estimating the probable maximum precipitation ASCE J Hyd Drv 8' 
No Hy 5. 99-116
Matalas  N.C  1963  Probability  Distribution  of  Low  Flows  Statistical  Studies  in  Hydroiog. Geol Survey Prof Paper 434-A
Shaw Elizabeth M 1988 Hydrology in Practice International Van Nostrand Reinhold USBR (Unitea States Department ot the Interior Bureau of Reclamation). 1964 Land and
Water Studies of the Blue Nile Basin Ethiopia Appendix III - Hydrology WAPCOS (Water and Power Consultancy Services (India) Ltd ). 1990 Preliminary Wate*
Resources Development Master Plan tor Ethiopia Final Report Volume III Annex A Hydrology & Hydrogeology Addis Ababa
I'V
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ANNEXES
Annex A: Results obtained from the Meteorological Analysis
A1:
May 2007
I
I
M
°i
Year
1961
May June      July__ Aug ; Sept _ Oc_I__ Nov_ Dec
1962    20 0      21 8     24 9      22 5     23 2    21 0    20 0    20.0     21 3     22 1     20.2     190
222       21 8      24 7     24 0     23 2    21 5    20.7    20 2    21 6     22 0     21 9     19 7
Jan      Feb   March   April
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
21 7
23 2     24 3      16.3
15.9    21 6
21 1     20 8     21 4
21 7
24 6
21 3
I
21 7
22.9     25 4      24 6
23 7    21 5
20 4    20 4     21 4
22 0
21 5
20 8
21 5
21 8     24 8      24.8
23 5    21 6
21 3    20 8     21.5
22.4
23 2
20.5
22 7
23 6     25.3     24 8
24 1    21 7
21 4    20 8     21.5
22 3
22 0
18 8
N
195
22.5     25 1      24 8
23 7    21 2
20 7    20 5    21.3
21 1
23 0
18 7
19.9
224      23 6      24 5
24 1    21 6
21 6    21 1    21.2
21 4
21.2
19 6
224
23.2     25.1      24 6
24 0    22 0
20 7    20 7    21 5
21 7
21 2
169
18.2
N
N
21.5
22.9     25 0      24 9
24 3    22 0
21 4    20 8     21 6
22.8
22.4
19 8
21 6
20.4     23 9      24 7
23.7     21 1
21 0     19.9    21 1
21.7
18 2
21 5
23 1      24.2      24 9
23 2    21 0
21 8     21 3    21.6
22 3
22 8
20 2
22 7
22 6     25.8      26 8
24 1    21.8
21 3    20 8     21 5
21 7
21 7
17 4
21 2
23 3     25 3      23.9
239     21 8
20 8    21.3     21.3
21.2
19 1
19.0
21 0
23 6     25.9     24 8
23 7    21 7
20 5    20 2     21.3
21 9
20 4
18 9
20 6
23 9     24 8      24 3
23.1    21 0
21 0    20 8     21.6
22 4
22.5
23.0
23.5     24.9      25 3
24 4    21 4
21 0    21.3     21.9
23.5
22.3
23 0
197
20.9
21 1
22 8     26.1      25.6
23.8    21.9
20 9    21.2     21 1
20 9
20 4
22.2
23 5     24 7      24 2
24 2    21 9
21.3    21.6     22 0
22 3
21 6
20 9
22 3
24 1     26.1      25 8
24 4    22.3
21 1    20 8     22.0
22 0
22 4
22 6      262      25 1
24 7    22.3
20 6    21 1     21 5
22 0
22 7
22.0
21.6
23.0
22.3
19.5
19.2
22.3     23 8      24 9
23 5    21.9
21.2     20.7     21.6
21 8
20 6
20 3
23.6     26 1       256
250     22.8
22 3    21.8     21 7
22 4
18 6
20 6
20 6     25.4      26.2
24 5    21.9
20 9    20 7     21.1
20.2
21.5
23 4
20.6
21.5
22 9      257      25 1
24.0    21.7
20 6    20 4    21.5
22.1
19 7
21 5
24 7     23 9      24 6
24.6    22 0
21 3    21 1    21.2
21 7
22 0
20 4
21 8
23 0     25 4      25 1
24 2    22 6
22.2    21 6     21.9
23.1
22.7
20.6
20.2
22 4
24 5     25.1      25 8
25.3    22 5
21 3     21.6     21 9
22 5
18 8
21.3
22.3     24 6      24 5
23.3    21.9
21 3     21 6     21 7
22.0
21 9
21 0
21 9      24 8     25.1
21.6
186     224
21 4    21 4     21 9
22 1
22 4
20 9
ri
23.0
236      25 1     25 1
24 6    226
21.3     20.8     22 0
21 4
22 1
22 6
21.6
22 3
226
23 4
24 6
21 9
21 6
23 0
23.2
21 9
24.2
24 1 252 252
23 5 24.3 256
24.2 26.8 24 9
24 5 26 4 26 5
24 1 26 3 25.9
224 26 9 25.5
24 9 27 4 27 7
22 8 26.2 26 3
22 9 26 6 266
24.3 26.0 264
23 6 26.9 25.9
24 5 26 4 25.7
24 2 26.2 26 5
21 4
182
24 6 22 3
24 4 22.7
24.3 22.3
25.3 23 1
24 7 21 9
24 4    23.1
262     23 4
249      22.8
255 22.6
25.5 230
25 8 22 8
25.8 23.2
25.6 22.8
21 1     21.3     21.8
21 4     21 4     21.8
21.1     21 5    21 8
21 9 22 1 22.3
21 7 21.8 22 4
22.3 22.3 23.2
22 4 22 3 23.1
21 6 21.3 22 9
21.9    21 8     23.0
22.0     22.2     23.0
22 7     22.2     22.8
22 0 222 22 7
21 5 22 1 22.5
22 7
22 9
22.0
23 0
22 4
24 0
24 2
23 5
24 0
24.2
23.3
23 0
22 6
21 8
21.7
23 3
23.3
22.0
25.1
22 0
21 0
23 5
23.6
23 1
23 5
23 2
21.3
196
20 0
22.2
202
22 9
19 1
19.8
20 8
21 6
22 7
206
21 8
4
4
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A2:      Estimated Minimum Temperature at Arjo Dedessa Project Area (in C)
Year     Jan     Feo   March   April    Ma?    June    July    Au£    Sept  1 Oct        Nov      Dec
1961 97 ' 10 5 13 8 14 7 14 9 14 6 14 7 14 3 14.5 13 0 10 3 8 0
1962 88 10 5 13 9 138 150 14 3 14 2 14.2 14 4 13 0 9 5 7 7
1963 95 112 136 99 10 3 14 7 15 0 14 7 14 4 12.8 11 6 8 6
1964 95 11 1 142 150 153 14 6 14 5 14 4 14 4 13 0 10 1 8 5
1965 9 4 106 139 15 1 15 1 14 7 15 1 14 7 14 5 13 2 10 9 8 3
1966 99 11 4 14 2 15 1 15 5 14 8 15 2 14 7 14 5 13 2 10 3 76
1967 85 109 14 1 15.1 15 3 14 4 14 7 14.5 14.3 12 5 10 8 7 6
1968     8 7       108       132       150      15.5     14 7     153      14 9     14 3      12 6       10 0        8 0
1969     98       11 2      14 0      150      15 5     14 9     14 7     14 6     14 5      12 8       10 0        6 9
1970     94       11 1      14 0      152      15 7     14 9     15 2     14 7     14 5      13 5       9 3         74
1971 95 99 134 15 1 15 3 14 3 14 9 14 1 14 2 13 2 10 2 7 4
1972 94 11.2 135 15.2 14 9 14 3 15 4 15 1 14 6 13 2 10 8 8 2
1973 9.9 10 9 14 4 163 155 14 8 15 1 14 7 14 5 12 8 10 2 7 1
1974 9 3 11 3 142 14 6 154 14 8 14 8 15 1 14 3 12 6 90 7 7
1975
1976
1977
1978
1979
1980
9.2 11 4 14 5 15 1 15 3 14 8 14 6 14 3 14 4 12 9 96 7 7
90 11 6 13.9 14 8 14 9 14 3 14 9 14 7 14 5 13 2 10 6 80
10 1 11 4 14 0 154 158 14 6 14 9 15 1 14 8 13 9 108 8 5
92        110      14 6      156      15.3     14 9     14 8     15 0     14.2      13.2        98         8 3
97       11 4      138      14 8      156     14 9     15 1     15 3     14 8      13 2       10.2        8.5
9.8      11 7      14 6      157       158     15 1     15.0     14 7     14 8      13 0       10 3        79
1981 98 109 14 7 15 3 160 15 1 14 6 14 9 14 5 13 0 102 78
1982 99 108 13 3 152 15 1 14 9 15 1 14 7 14 5 12 9 10.8 84
1983 89 11 4 14 6 156 16 1 15.5 15 8 15 5 14 6 13.2 10 5 7.6
1984     90        100      14.2      16 0     15 8     14.9     14 8     14.6     14 2       119       11 0        84
1985 94 11 1 14 4 15.3 155 14 8 14 6 14 4 14 5 12 7 104 80
1986 94 12 0 134 150 158 150 15 1 14 9 14 3 12 8 10 3 8.3
1987 95 11 1 14 2 153 156 154 158 15.3 14 8 13 6 10 7 8.2
1988 98 119 14 0 157 163 153 15 1 153 14 8 13 3 9 7 76
1989 9 3 108 13 8 14 9 15 0 14 9 15.1 15 3 14 6 13 0 10 3 8.8
1990     9.2      10 6      13 9      153      12 0     152     15.2     15 2     14 8      13 0       106        8 5
1991 10 1 11 4 14 0 15.3 159 154 15 1 14 7 14 8 12 6 10 1 7 4
1992 9 7 11 6 14.1 15.4 15.8 15.1 150 15.1 14 7 134 10 3 8 6
1993     9.9      11 4      136       156      15 7     15.4     15.2     152      14 7      13 5
1994     9.5      11 7      150       152      15 7     15.2     150      152      14 7      13 0       11 0       8.1
10 2        7.9
1995     9.8      11 9      14 8      162      16 3     157     15 5    15 6     150
1996     99       11 6     14 7      158      160     14.9     154      15.4
13.6       11.0       9 0
1997    10 2     10 8     15 1      156      158      157     158      15.8
15 1      13 3       10 4        8 2
1998    10 8     12.1      15 3      169      16.9     159     15 9    15.8
15.6      14 2       11 8       9 3
1999     96       11.0     14 7      16.0     16.1     15.5     154     15.1
156       14 3      10.3       7 8
2000      95           11 1      14 9      162      164     15 4     156      154      15 5      14 2      11 1        8 4
154       13 9       9 9         8 0
2001    10 1     11 8      14 6      16 1      16 5     15.6     15 6     15 7     15 5      14 3      11 1        8 8
2002  | 102       11 4      15.0      15 8      166     15.5     16 1     15 7     154       13 8      10 9       9 2
2003     9.6       118       148      15 7     16.7     158     156      15 7     15.3      13 6      11 0       8 4
2004    10 6     11.7      14 7      16.2     16.5     15.5     15 3     15.7     15.2      134       10 9        88
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A3: Estimated Maximum Temperature at Arjo Dedessa Project Area (in )
1962 31 2 33 0 35 8 31 6 31 8 27 9 25 8 25 8
1963 33 9 35 2 34 9 22 8 21 7 28 8 27.2 26 9
1964     33 9     34 7     36 6      34 4     32 4     28 6     25 3     26 4
1965   I 33 6     33 1      35 7      34 7     32 1     28 8     27 5     26 9
1966    35 4      35 8     36 5      34 7     32 9    28 9     27 6     26 9
1967 30 4 34 1 36 2 34 7 32 4 28 2 26 7 26 5
1968    31 1      33 9     34 0      34 3     32 9     28 8    27 8     27 3
1969    35.0     35 2     36 1      34 4     32 8     29 2     26 7     26 7
1970    33 6     34 6     36 0      34 8     33 3     29 2    27 6     26 9
1971 33.7 31 0 34 5 34 6 32 4 28 0 27 0 25 7
1972 33 6 35 0 34 8 34 8 31 7 27 9 28 1 27 5
1973 35 4 34 2 37 1 37 5 32 9 29 0 27.5 26 9
Year Jan Feb March 1961     34 7      33 0     35 6
April     May   June    July _  A4 33 6     31 7    28 6    26 7     26 1
Sept Oct Nov Dec
24 4      30 9   ' 33 5        31 4
24 2     31 1       30 9       30 4 24 2      30 6       37 6      34 0 ' 24 2      31 0       32 9      33 3
24 3      31.5      35.5       32 8 j 24 4      31 4       33 6       30 1 24 1      29 6      35 1       29 9 I 24 0     30 1       32 4       31.3
24 3      30 6       32 4       27 0
24 4     32.1       30 2       29 1
23 9      31 5      33 1       29 1
24 5      31 4       34 9      32 3
24 4      30 5      33 1       27 8
1974    33 1      35 3     36 5      33 5     32 7     28 9     26 8     27 6     24 1      29 9      29 2       30 3
1975    32 8     35 7     37 3      34 8     32 4     28 9     26 5     26 1     24 2      30 8       31 2       30 2
1976    32.2     36 2     35 7      34 1     31 5    27 9     27 0     26 9     24 4      31 5       34 5       31 5
1977     35 9     35 6     35 9      35 4     33 4    28 5     27 1     27 6     24 8      33 0       35.2       33 4
1978     32 9      34 5     37 5      35 9     32 5    29 2     27 0     27 4     23 9      31 4       31 9      32 6
1979    34 7      35 5     35 6      33 9     33 1     29 1     27 5     27 9     24 9      31 4      33 1       33 4
1980     348      36 5     37.5      36 1     33 4     29 6     27 3     26 9     24 9      30 9       33.6       31 2
1981     35 0      34 2     37 8      35.1     33 8     29 6     26 6     27 2     24 4      30 9      33 1       30 6
1982     354      33 7     34 3      348      32 1     292      27 4     26 8     24 4      30 7       352       32 9
1983    31 7      35 7     37 6      35 8     34 2     30 4    28 8     282      24 6      31 5      34 1       29.8
1984     32 2      31 2     36 5      36 7     33 5    29 1     27 0     26 7     23 9      28 4       35 8       33 0
1985     336     34 6     37 0      352      32 8     28 9     26 5     26 4     24 3      30 3       33 8       31 4
1986    33 6      37.5     34 5      34 4      336     29 3     27 5     27.3     24 0      30.5       33 6       32.6
1987     340      34 8      36 5      35 1     33 1     30 1    28 6     27 9     24 8      32 5       34 7       32 3
1988     35.0     37 2     36 1      36 1      346     29 9     27 5     27 9     24 8      31 7       31 5       30 1
1989     332      33 8     35 4      342      31 9     29 1     27 5     27 9     24 6       309       33.5       34 5
1990     32 8      33 2     35 7      352      25 4     29 8    27 6     27 7     24 8      31 1       34 3       33 4
1991 35 9 35 8 36 1 352 33 7 30 1 27.5 26 9 24 9 30 1 32 7 29 1
1992     34 5      36 5     36 3      353       336     29 6     27 2     27 5     24 7      32 0       33 3       34.0
I 1993     35 3      35 5      35 0      35 9     33 4     30 1    27 6     27 7     24 7      32.2       33 2       31 3
1994     33 7      36 7      38 6      34 8     33 3     29 7     27 3     27 8     24 7      31 0       35 7       31 9
1995 34 8 37 2 38 0 372 34.6 30 8 282 28 5 25 3 32 3 35 6 35 5
1996 35 3 36 5 37 9 36 3 33 8 29.2 28 0 28.2 25 4 31 5 33 7 32 3
1997 36 5 339 38 8 35 7 33 4 30 8 28 7 28 9 26 3 33 8 38 3 36 6
1998 38 4 37 7 39 4 38 8 358 31 1 28 9 28 9 26 1 34 1 33 6 30 5
1999 34 2 34 5 37 8 36 8 34 1 30 4 27 9 27 6 25 9 33.0 32 1 31 6
2000 33 7 34 7 38 2 37 3 348 30 1 28 3 28 2 26 0 33 7 36 0 33 2
2001 35 9 36 8 37 4 37 0 34 9 30 5 284 28.7 26 0 34 1 36.2 346
2002
36 2      35.7      38 7
36.2      35 2
30 3
29 3     28 7
25 8
32 8
35 3       36 2
2003
342     37 1      38 0
36 0     35 3
30 8
28 4     28 7
25 7
32 3
35 9       33 0 |
2004
37 8      366      37 8
37 2      350
30 4
27 8     28 6
25 5
31 8
35 5       34 8 |
105
Water Works Design & Supervision Enterprise
In Association with Intercontinental Consultants and Technocrats Pvt. Ltd.Arjo Dedrssa Irrigation Project
Meteorological and Hydrological Aspects
A4 Estimated Relative Humidity at Aqo Dedessa Pro/ect Area (tn percent)
Year     Jan      Feb   March   April    M ?y »June              Aug          Sept Oct 1961      67         52        46         70        71        78       87        87        82        82
m*j :ao-.
Dec
72
1962      77         69        64         73        86        85       94       94        96        95        88        M
1964      71         66        57         63        75       82        88       88       92        84        73
1963      65         72        63         82
84        85       89       91        89        83        87        85
75
1965      67         52        50         68        69        78       83        85        84        82        86        ’4
1966      65         68        58        71         73       78        86        90        85        84        80        69
1967      65         50        57         66        76       81        91        89       92        85        89        73
1968 55 66 54 68 75 81 88 85 89 81 76 72
1969 72 68 64 69 75 82 88 89 88 8u 77 65
1970      71
62
64
69
74        79       86
92
89
86
72
66
1971      60
48
50
64
76       81        87
90
87
87
82
76
1972      64
65
56
70
74        79        89
85
86
80
83
75
1973      65
59
57
68
76       81        62
88
89
83
77
63
I 1974      54
49
53
58
78       81        90
90
93
83
72
63
1975      52
59
51
70
74        83        86
93
90
84
73
66
1976      55
55
57
68
79       81        92
91
91
91
93
82
1977      72
66
58
57
66       81        89
88
87
86
82
74
1978      58
61
58
64
75        77       87
86
84
84
75
55
1979      68
65
61
64
70        77       84
85
86
79
69
67
1 1980      59
55
53
68
76       81        86
87
85
79
75
65
j 1981      54
46
56
63
72        76       88
88
83
82
77
64
1982      67
62
55
65
75       80        88
90
90
87
86
79
1983      66
63
61
70
79       78       85
89
89
88
82
72
1984      59
49
47
61
76       80        88
88
86
74
82
75
1985      68
50
51
67
78       80        90
89
87
81
77
70
1986      58
60
57
69
73       85        87
87
88
82
73
72
1987      59
56
63
69
79       81        83
89
86
85
79
75
1988      72
64
49
62
75       82        90
91
93
87
73
66
1989      63
61
60
75
73        79       91
88
91
84
82
35
1990      67
70
62
68
77       81        90
90
91
80
80
71
1991      68
69
60
80
74        83        90
91
89
82
75
75
1992      68
67
54
69
79       84        90
94
88
89
84
79
1993      69
63
56
75
80        85        89
89
90
86
82
69
1994      57
53
55
67
78       86        86
98
89
75
80
72
1995      60
58
57
72
79       90        98
90
92
84
81
79
1996      72
43
63
73
80        83        89
98
87
81
69
70
1997      73
53
53
72
76       81        86
89
87
88
89
80
1998      74
66
62
64
79        66        74
74
93
92
78
6?
1999      61
48
53
65
76        80        90
89
89
92
73
68
2000      55
48
45
67
77       81        89
72
89
93
84
74
2001      67
57
58
69
81        90       91
92
89
88
82
2002      71
56
62
64
75
71        81        85
88
87
84
2003      71
60
60
66
78
79
65        78        90
89
90
84
2004      66
77
59
55
73
70
76       81        87
89
89
91
78
78
It*
Water Works Design & Supervision Enterprise
In Association with Intercontinental Consultants and Technocrats Pvt LtdArjo Dedessa Irrigation Project
Meteorological and Hydrological Aspects
A5 Estimated Mean Daily Sunshine Duration at Arjo Dedessa Project ea
May W
(in hrs/day)
Year     Jan       Feb    March 1961      83         7 3       7 1 1962     6 7         69        82
April May_ June Jij»y
68         54       6 5       4 3
7 8        90       63        29
1963 72 6.2 8 4 68 7 3 4 4 2 8
1964 96 8 3 7 7 80 8 7 58 30
1965 9 1 8 3 86
1966 78 82 7 1
1967 79 96 84
6 5 8 3 34 4 3
8 5 7 8 53 4 2
72 9 1 8 1 4 9
1968 8 1 80 7 7 8 1 68 68 2 3
1969 82 76 7 5 73 76 6 1 3 7
Aufl Sep* • Mcv Dec
6 2       9 1       9 2       fl 9       7 4
20 6 3 6 5 7 6 7 $
3 8 58 8 0 9 1 8 3
30 6 8 9 1 9.0 100
5 5       7 9       74       84       8 1
3 8       60        92        98       8 3
e 1 *-     8 3       8 5       76       90
3 2 5 7 65 10 1 83
4 1 62 7 9 8 3 83
1970 100 95 97
1971      82         76        7 5
1972      92         88        74
1973     8.5         89        85
1974      79        8 1        73
1975      94         8.3        75
1976      90         8 7        78
1977 62 63 66
1978 94 58 7 5
1979 6.3 66 60
1980 6 1 53 58
1981 8.5 86 46
78        94       8 0       4 8       4 7       7 5       7 9       8 3       83 . 73         76       6 1       3 7       4 1       62        7 9      8 3      83
94        8 3       64        54       4 a       8 0       8 fl       99       7 7
84       10 1      7 3       32       4 1       7 2       95       9 5      90
67        9 1       5 9       4 8       4 8       58       8 6      0 1       83
64        7 1       50       3 1       1.6      4 1       7 5       84       92
8 7        68       7 1       3 7       4 1       52        66       6 7       3 1
72        7 4       58       3 7       4 1       6 3       6 9       82       83
76        7.8      6 1       23       38        55        68        89       7 1
70        6 7      5 1       24       3 8       42       5 8       78       7 5
6 5        74       5.8       36       3 9       59        79        78       86
59         79       58       3.7      4 5       26        65        96       79
1982      74
60
83
65
7 1       68        39       3 7
67
7 5       66       73
1983      80
76
7.1
80
66        78       5 4       36
56
66        84       82
1984     8 1
99
81
8.9
66       60       4 7       4 3
70
10 1      86       3 1
1985      86
76
75
68
64        59       28       3 1
58
76       8 7       78
1986      69
6.2
65
53
72       3 7       3.3       4 0
41
7 4       94       82
1987     8 1
78
62
83
58       56       4 9      42
74
76        83      110 1
1988      84
76
95
84
83       7 0      2 7      49
55
85       102      9 1
1989      86
84
73
7.2
96       7 3      3 7       5.1
63
8 3       82       66
1990      92
49
6.3
33
54       4 6       3.7       39
59
95        89       92
1991      83
73
71
68
54       65       4 3      62
91
92        89       74
1992     6 7
69
82
78
90       6 3       29       2 0
63
65        76       7 5
1993      72
62
84
68
7.3      4 4       28       38
58
80       9 1       83
1994      96
8.3
77
80
8 7       58        30       30
68
9 1       90      10 0
1995     9 1
83
86
65
83       34        43       55
79
7 4       84       8 1
1996      78
82
71
85
78        53       4 2       38
60
92        98       83
1997      79
96
84
72
9 1       8 1       4 9       52
83
8 5       76       90
1998     8 1
80
77
81
68        68       2 3      3.2
57
6 5      10 1     83
1999      82
76
75
73
76       6 1       3 7      4 1
62
79        83       8 3
2000    10 0
95
97
78
94        80       4 8      4 7
75
79       83       83
2001      82
76
75
73
76       6 1       37       4.1
62
79        83       83
2002      92
88
74
94
83       64        54       4 8
80
88        99       7 7
2003      85
89
85
84
10 1      73       3.2      4 1
72
2004      7 9
81
95        95       90
73
67
9 1       59       4 8      4 8
58
86       0 1       8 3
IO
Water Works Design & Supervision Enterprise
In Association with Intercontinental Consultants and Technocrats Pvt ltdArjo Dedesea Irrigation Project
Meteorological and Hydrological Asp?< ts
A6: Estimated Mean Daily ETo of Arjo Dedessa Project ee
Ma? M
(in mm/day)
Year Jan Feb March April
1961    3 73      3 93     4 49      4 26      373     3 64        •.J  * J 54     4 43     427      386
Maj
JijfWl
J '6      Aug     Sept     Oct      Nov     Dec
3 24
1963    3 48      3 72     4 66      3 44     3 36    3 1 *.    2 71       3       3 63     3 98     4 22     3 56
1962    3 23      3 75     4 66      4 32     4 43
3 49     2 63      2 5      3 72     3 63     • 4       3 19
1964 3 95 4 18 4 65 4 66 4 52
1965 3 84 4 13 4 83 4 25 4 43
3 45     2 72     4 79    3 87     4 25     3 86     3 82
1966    3 68      4 22     4 47      4 73     4 35     3 4      307        3        3 7      4 31       4 ‘      3 35
2 97     3 1      3 43     4 13     3 88     3 92     3 45
1967 I 3 45        4 44      4 77      4 45      4 6      3 95
3 71     2 63      2 9      3 59     3 59     4 06     3 4
3 56    2 91      306     3 72     3 94      3 7      3 19
4 01     3 21     3 22    4 Ob    4 0-4    3 56     328
3 49     2 93     301     3 69       4        3 75     329
3 55     3 39     3 28     4 17     4 23      4 2      3 34
3 84    2 81     3 09     3 97     4 32     4 01     3 34
3 51      3 3      3 29     3 62     4 07     1 95     3 35
3 3      2 73     2 44      3 2      3 87     3 64     3 49
3 68 2 93 3 06 3 5 3 69 3 48 3 38
3 46 29 3 1 3 78 3 87 3 86 352
3 57 2 58 3 04 3 53 3 74 3 79 3 23
3 38 2 64 3 07 3 3 3 5 3 64 3 34
3 32     4 22     4 03     3 72    3 46
1968    3 53      4 06      4.5       4 64      4 1
1969 I 3 71        4 06      4 5       4 43     4 28
1970   4 01      4 45     5 06      4 58     4 76
1971    3 66        39       4 49      4 49     4 24
1972    3 86      4 34       4 5       5 03     4 34
1973   3 81       4 3      4 87      4 92     4 91
1974 3 58 4 18 4 53 4 24 4 61
1975 3 82 4 27 4 66 4 34 4 09
1976 ’ 3 73        4 38     4 65      4 75     4 02
1977 I 34           3 85     4 34      4 49     4 24
1978    3 85      3 62     4 64       4 7      4 39
1979 ' 3 36 3 89 4 18 4 37 4 08
1980    3 29      3 63     4.21      4 39     4 32     3 56     2 93     3 05      3 ’       3 98     3 66     3 44
1981 3 78 4 25 399 4 13 4 42
1982 36 3 74 4 63 4 32 4 13
3 53 2 91 3 2 2 88 364 4 01 3 3
3 77 2 98 2 98 3 87 3 86 3 49 33
1983 354 4 14 4 55 4 76 4 15 4 06 3 43 3 03 3 61 3 7 3 82 3 32
1984 358 4 31 4 73 5 02 4 08 3 55 3 14 3 11 3 87 4 3 398 34b
1985
1986
3 73
3 43
4 04 4 59 4 36
394 4 31 4 03
3 93
4 22
3 53 2 71 281
3 04 2 85 3 08
3 63 3 86 3 88 332
3 22 3 82 4 01 ! 4-
1987
367
4 14     4 31      4 74
3 83
35      3 27     3 16
4 06       4        3 83     396
1988
3 76
4.2       5 04      4 82
4 58
3 78    2 71     3 34
3 59     4 17     4 02      ! 48
1989
3 72
4 18     4 42      4 39
4 64
3 83     2 97     3 38
3 77     4 06     3 74     3 24
1990
3 82
3 38     4 31      3 57
3 35
3 25     2 92     3 07
3 69     4 37     3 92     3 67
1991
3 79
4 05     4 43      4 31
382
3 72     3 06     3 59
4 49     4 22     3 84    3 11
1992
3 42
3 94     4 71      4 62
4 65
363     2 73     2 59
3 78      3 7      361     3 38
1993 '
3 54
3 75     4 68      4 29
4 25
3 21     2 72      304
3 67     4 09     3 91      3 4
1994
3 94
4 3       4 79      4 65
4 55
35      2 75     2 83
3 91     4 26     4 06     3 75
1995
3 92
4 34     4 96      4 34
4 53
2 98    3 11     3 52
4 21     3 94     3 92     3 59
1996
3 68
4 29     4 57      4 88
4 37
3 35     3 09     3 03
3 77     4 31     4 09     3 46
1997
3 77
4 43     4 95      4 46
4 65
4 07     3 23     3 46
4 41     4 32      3 9     3 85
1998
391
4 33      4 8       4 93
4 24
3 85     2 66      296
3 74     3 83     4 12     3 M
1999
3 68
4 07      4 67      4 57
4 36
3 63     2 98    3 11
3 83    4 11      3 7      3 42
2000
4 03
4 45      5 24      4 79
4 86
4 15    3 31     3 35
4 19     4 16     3 92      3 5
2001
3 78
4 21      4 66      4 64
4 42
3 65     2 M     3 16
3 84     4 19     3 92     3 57
2002
4
4 39     4 75      5 13
4 59
3 71     3 46      34
4 34     4 24     3 54
2003
3 75
4 49     4 92      4 82
5 06
3 88     2 85     3 16
4 08     4 47     4 19     363
2004
384
4 28      4 58      4 51
4 83
36      3 22     3 35
3 72    4 21     2 lk>     36*
S
Water Works Design &. Supervision Enterprise
In Association with Intercontinental Consultants and Technocrats Pvt LtdArjo Dedessa Irrigation Project
Meteorological and Hydrological Aspects
A7: Estimated Mean Monthly ETo of Arjo Dedessa Project Area
May 20C7
(in mm/month)
Year Jan Feb March April 1961 116 110 139 128
May 
116
June 'July   Aug   Sept Oct     Nov
Dec      Annual
1962 100 105 144 130 137
1963 108 104 145 103 104
1964 122 117 144 140 140
1965 119 116 150 128 137
1966 114 118 138 142 135
1967 107 124 148 133 143
109 94 2 110 133 132
105 81 6 77 4 112 112
93 2 84 92.9 109 124
116 100 1403
104 99 1308
127 110 1303
1968    109      114    140      139      127    111    81 4   89 9     108    111    122     105         1358
1969    115      114    140      133      133     107    90 1    94 8     112    122    111      99          1369
1970    124      124    157      137      148     120    99 4   99 7     122    125    107     102         1466
104    84 3   86 6     116    132    116
89     96 2    106     124    120    118
102    95.1   93 1     111    134    123
118 97 7 103 127 125 111
1971    113     109     139      135      132     105    90 8   93.2     111    124    113
119 1420
107 1410
104 1408
107 1444
102 1366
1972    120     122     140      151      135     106     105    102     125    131    126     104         1466
1973    118     120     151      148      152     115    87 2   95 9     119    134    120     104         1464
1974    111     117     140      127      143     105    102    102     109    126    58 6     104         1346
1975    118     120     144      130      127     99     84 7   75 7     96      120    109     108         1332
1976    116     123     144      143      125    111    90 8   94 8     105    115    104     105         1375
1977    105      108    135      135      132     104     90      96      113    120    116     109         1362
1978    119      101    144      141      136     107     80     94 2     106    116    114     100         1359
1979    104     109     130      131      126    101    81 9   95 3    98.9    109    109     104         1299
1980 102 102 130 132 134 107 90.9 94 5 111 123 110 107 1343
1981    117     119     124      124      137     106    90 1   99 2    86.5    113    120     102         1338
1982    112     105     144      129      128     113    92 3   92 5     116    120    105     102         1358
1983    110     116     141      143      129     122    106     94      108    115    115     103         1401
1984    111      121    146      151      127     107    97 4   96 6    116    133    120     107         1432
1985    116     113     142      131      122     106    84 1   87 1     109    120    116     103         1349
1986
1987
1988
1989    115     117     137      132      144     115     92     105     113    126    112     100         1408
1990    118     94 8    133      107      104    97 4   90 6     95      111     136    117     114         1318
1991 117 113 137 129 118 112 94 8 111 135 131 115 96 4 1411
1992    106     110     146      139      144     109    84 5   80 3     113    115    108     105         1360
1993    110     105     145      129      132    96 4   84 4   94 3     110    127    117     105         1355
106     110     134      121      131    91.3   88.2    956    96.5    118    120     107         1320
114     116     134      142      119     105    101     98      122    124    115     123         1412
117     118     156      145      142     113    84 2    103     108    129    121      108         1443
1994
122     120     149      139
105    85.2   87 8     117    132    122
116
1437
1995
122      121    154      130
894    96 4    109     126    122    118
111
1439
1996
114     120     142      147
141
140
135
101    95 8     94      113    134    123
107
1425
1997
117     124     153      134
144
119
1505
1998
121     121     149      148
132
122 100 107 132 134 117
115 82.6 91.9 112 119 124
104
1419
1999
114     114     145      137
135
109    92 4   96.3     115    127    111
106
1402
2000
125     124     162      144
151
137
142
125    103    104     126    129    118
109
1518
2001
117     118     144      139
110    92 4     98      115    130    118
111
1429
2002
124     123     147      154
111     107    106     129    135    127
110
1515
2003
116     126     153      145
157
150
117    88 2     98      122    139    126
112
1498
2004
119     120     142      135
108    100    104     112    130   61 7
112
1393
___________________ ____________________________
Water Works Design & Supervision Enterprise
In Association with Intercontinental Consultants and Technocrats Pvt. Ltd.
109w
N
I
I N
I ri I
I
I
i
l
I
l
i
I
I
Arjo Dedessa Irrigation Project
Meteorological and Hydrological Aspects
A8: Estimated Mean Monthly Rainfall at Arjo Dedessa Project Area
(in mm)
rVear Jan Feb March April May_ June July
1967    156    0      96 3     21 7     172     172     140 1968      0       57 6   0 75     36 4    93 8     169     186
I 1969 37 7 35 9 53 7 140 121 144 159
1970
1971
29 2 30 51.3 21 2 149 154 249
11 3 0 32 20 7 30 8 142 193 180
1972 156 11 1 15 89 1 53 166 186
1973 0 9 97 5 66 29 4 236 155 186
Auq Sept Oct Nov Dec Annual
220     220    111 5    151    0 12       1320
207      192    90 97    21 7    14 5       1070
212      165    56 39    7 39      0          1132
162      256    107 2    4 44   4 04       1217
135     262    188 2    32 3   14 1        1210
157 170 49 48 69 9.24 990.6
233      143    58 82    12.2   5.77       1075
1974   38 7  7 98   31 8     5 14     287     205     242      168     212    72 78    4 62   16 7
1975   23.5 55 1   21 1     60 4     116     124     189
159     141    131 3    115    12.5
1976 23 7 162 90 3 55 8 154 154 192 215 273 88 66 36 5.37 1978 3 35 66.5 103 122 154 206 206 181 122.6 0 58 12.5 1979 156 8 89 17 256 975 202 235 159 154 64.94 31.2 12.5 1980 156 17.8 57.3 118 164 100 136 176 246 49 87 28 7 0
1292 I
1045
1303
1181
1024
1110
'983     156  8.23   27 6     356     149     213     296
270      177    113 9    57.2      0          1362
1984    156    0      31 6     69 8    234     249     443      198     230    8 716    26 8    5 77       1514
1985   2 79    0      12.3     105     257     341     242     212      315     48.2     32 5   37 7       1607
1986      0    392    46 9     56 4    37 5    315     274     244      191    103 8    35.9    046       1345
1987   2 89  17 2    886      799      123     282     488      328      183    1 16 4   42.3    34 3       1785
1988   14 1  42 7    74 3     15.3     335     325     177     297      343    259.9     154    3.87       1903
1989   25 6 26 7    76 3      108     245     284     316     332     297    189.3    61 3   47 1        2008
1990   8 77  37 8   50 4     83.3    90 6     438     228     319     241    73 89    33 4    3.12            1607 I
1991    264  791    68 2     74 4     139     106     364
309     222    98 59      35       13         1464
1992   24.8 32 8    106      105     222     225     267     291      250    104 7    53.6     158        1697
1993
1994
1995
1 04   31     69.5      100     213     313     217     347      166    149 4    2.03      0          1609 11 2  1 15   20 1     53.9     127     227     255     228      279    8 467    13 7      0          1223
0    22 9    75.5      109     222     195     229     310      279    86 46    11.2    22 3       1563
1996   45 5 19 1    162      71 7     338     225     245      197     215    74 57    44 6    7 56       1645
1997    396  0 97    56.6      139     293     314     205     291      234      213     40 4    2 54       1830
1998     13    84     81 1     15.2     162     280     264     272      239    235 9    67.2    1 04       1638
1999   31 7 2.91     15      92.3     393     427     257     239      309    197 3    8.89   42 1        2014
2000      0      0      3 69      105     195     345     222     260      274      255     34 4   7 39       1702
2001      0     32      655      60 3     327     346     298     292      312    206.3    19.9   24.1            1983 I
2002   17 7  2.19    39 7     42.2     106     252     274      153     224    59 11    1 84   53.1        1226
2003 5 84 53 5 117 121 58 9 358 232 300 155 51 59 11.5 1 86
2004 4 96 2.1 61.2 51 5 150 353 326 243 249 193 9 40 7 13 1
1466
1689
I
Average
15.3  18 4    53 6     69.5   180 8  243.0  245.9  238.3  228 6   115.5   31 4    12.7
CV       0.85 0 96    0 68     0.55    0.49    0 37    0.31     0 25     0.24   0.591     0.9     1 13
1452.9
0.209
Skew
Max
0.62 0.78 0 74 0 1 0.62 0.38 1 44
45.5 57 6 161 7 139 9 392 7 437 6 487 6
Min        00    0.0      08       5.1     37 5   100 3  136.2
0.07     0.17   0 635    2.31    1 48        0 26
346 6 343.1 259 9 150 7 53 1 2014.5
135.3 141.3 8.5 06 0 0 990.6
Water Works Design & Supervision Enterprise
In Association with Intercontinental Consultants and Technocrats Pvt. Ltd.Arjo Dedessa Irrigation Project
Meteorological and Hydrological Aspects
A9: Estimated Mean Half-Monthly Rainfal at the Project Aiea (in mm/hr)
May 2007
□
11     1 2    2 1    2 2    3 1    3 2    4 1    4 2    51      52      6.1    6 2     7.1     7 2    8 1             9 1    9 2     10     10                        12 1
I--
—
12    Total
Year
| 1967
’ 1968
| 1969
1970
1971
1972
1973
7 8   7 79    0       0    22 4  73 9    0    21 7  75 2  96 97   112  60 8   68 4   71 7   110   110   132   87 7   110   1 92  75 7    75    0 12     0         1320 0       0     57 3  0 29    0    0 75  1 27 35 1    31     62 8   81 4  87 4   82 5    104   121  86 1   76 5   115   76 8  14 2    0     21 7   10 3  4 25   1070
26 1  11 6  14 7  21 2  37 6  16 1  6 75  133    18   103 1  72 3  71 9   55 2    103   106   106   83 6  81 7    36    20 4  3 46  3 92     0       0
1132
2 1   27 1  7 27  22 7  23 6  27 7  1 73  19 5  34 3  114 3 49 4   104   127 4   122  81 7  79 8  94 4   162    50    57 3  4 44     0       0    4 04
1217
11    0 27  032     0    4 62    16   30 4  0 46 42 1   99 86  62 2   131    63 4    116  61 4  73 9   125   137   104  84 3  26 8  5 48  3 17    11
1210
7 8   7 79  4 31  6 84    0      15   36 5  52 6  25 5  27 53 78 1   87 9   87 2     99   89 7  67 2  94 2  75 8  25 7  23 8  61 3  7 69     0     9 24
990 6
0       0     9 97    0       0     5 66  25 4 4 04   140   96 39  96 2  58 9   91 6   94 2  108   125  78 8  64 1  57 1   1.73   122     0       0     5 77
1075
1974
30 6
8 12  2 26  5 72  199   119  0 29  4 85   188   98 87   102   103   119 5
123   101   67 5
102   110  44 4  28 3     0
4 62  4 62
12.1   1292
1975
0
23 5  47 7   74    0 69  20 4  5 14 55 2  67 5  48 89  80 8  43 3   75 2
113  62 1  96 9
92 5  48 8  86 9  44 4   115
0     6 06
6 46'  1045
1976
23 7
0     10 3  5 89  57 9  32 4  32 2  23 5  78 8  74 81   72    81 8   102 9
89 1  51 9  163
198   74 2  40 1  48 6    32
3 98  2 89
2 48   1303
1978
3
0      35      0     56 4  10 1  12.4 90 9 49 1   73 14  87 8    66     79.7
127  71 2  134
84 8  96 5    72    50 5  0 58
0     6 06
6 46   1181
1979
78
7 79  8 89    0     0 46  16 5  11 6   14   57 2  40 35  99 6   102    145
90 3  85 5  73 6
97 2    57    40 4  24 5   156
156   6 06
6 46   1024
1980
78
7 79  8 89  8 89  27.7  29 6  28 6  89 8  64 2   100 3  41 6  58 7   65 6
70 6    99    76 5
138   109  26 3  23 5  11 9
169     0
0      1110
1983
78
7 79  7 98  0 25  187   8 89  20 7  14 9  54 3  94 53  89 7   123   168 1
128   134   136
89 9  86 7  78 7  35 2  44 2
13      0
0      1362
1984
78
7 79    0       0     4 73  26 9  17 3 52 5  53 9   180 3  138   111   232 6
211   51 8  147
66 7   163   7 16  1 56   152
11 6  4 96
1514
1985
03
2 49     0       0      1 5   108   57 5  47 8   121   136 6  168   173   94 1
148  82 6   130
160   155   37 2   11    24 9
7 58  36 9
1607
1986
1987
1988
0       0     2.75  36 4  152   31 7  28 1  28 3  1 24   36 22   195    119   147 6   127   110   134   114  77 1    85    189   28 2  7 68  0 23  0 23   1345 0     2 89     0     172   48 1  40 5  6 93  72 9   192   104 3  158   124   224 5   263   215   112   116   66 8  81 4   35    31.2    11    34 3     0      1785
94    4 73  2 66    40     57    173   0 98  14 3   145   190 2  172   154    75 1    102   175   122   179   164   155   104    154     0       0     3 87
1903
1989  186   7 03   26     07    43 9  32 5  65 3  42 7   148   96 74  182    102   208 4   107   186   145   194    104   91 5  97 8  29 5  31.8   198   27 3
1990
1991
1992
0    8 77  13 1  24 7  21 6  28 8    0     83 3  60 3   30 3    253    185   123 1   105   108  211   98 1   143   53 4  20 4  32 4   1 03  3 12     0
2008 j
1607 ,
14 2 122 0 7 91 37 6 30 6 1 27 73 2 89 9 49 04 133 93 1 195 1 169 179 131 144 77 9 97 3 1 27 10 5 24 5 12 7 0 29 1464
0     24 8  17 7   152   25 2  80 6  3 34   102   152   70 12  82 1   143   161 3   106   159   131    102    148   81 4  23 3    29    24 6   1 15  14 7 | 1697
1
Hi
Water Works Design & Supervision Enterprise
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00 oo
Ob ------ -Arjo Dedessa Irrigation Project
Meteorological and Hydrological Aspects
May 2007
(in mm/hr)
1.1 | 1.2 2.1 2.21 3.1 | 3.21 4.1 I 4.2             5.1     5 2     6.1     6 2     7 1     7.2 \ 8.1      8.2     9.1     9.2      10      10    111 11 12 1 12
Year
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Average
CV
Skew
Max
Min
0    1 04 6 64 24 4 3 06 66 4 63 6 36 6 93 7 119 7 86 2             227    79 7    137 149 197          104   61 9 83 9 65 5 1 39 0 65 0                  0
11 2   0      0    1 15 1 3 18 8 29 2 24 7         55    71 64 105       122 109 7 145 116          111    166    112    7 24    1 23 9 52 4 16      0      0
0      0    5 6 17 3 0 75 5 0 52 109              116 105 9 63 4        131 123 9 105 177          133    125    1 54   40 8 4 5 7 5 95 5 3 1 96 20 4
9 2 36 3 4 09 15 78 8 82 9 266 45 1             146 192 4 159 66 1 84 7              160 100 966 93 2            122    58 2 16 4 8 48 36 1 0 69 6 87
2 1 37 5 0 097 28 1 28 5 72 8 66 6 71 7 221 5 152                      161   78 6    127 165 126          148   85 8    119    94 2 253 15 1 0 06 2 48
11 2 1 84 1 94 646 24 6 56 5 889 633 69 7 92 18 142                  138 141 7 122 131          142    118    121    92 9    143 62 3 4 92      0    1 04
283 3 35 0 291            0     15    19 73.3 227          166    209    217    99 2    158 141 98 2         146    162    148    48 9 8 89 0 26 6 15 5
0      0      0      0 2 31 1 39 28 4 76 2 76 9 118 6 215                 129 99 4       123 149 112          139    135    168    87 1 252 9 15 2 89 4 5
0      0 23 7 8 3 1 24 64 3 36 9 23 3 96 3 230 8 122                   224 118 2 180 126 165              187    124    96 4    110 7 27 12 7 14 4 9 75
12 5 5 19 0 2 19 8 37 31 3 37 7 4 49 19 8 86 64 139                    114 156 4 118 51 7 102            95 4    129    35 3 23 8        0    1 84 3 29 49 8 2 3 84 17 8 35 7 39 2 77 6 68 8 52 3 20 3 38 67 165                  193 127 5 105 133 166             85 9 69 1 23 7 27 9 6 64 4 91 1 4 0 46
0 2 4 76 1 4 0 7 10 6 50 6 9 7 41 8 28 5 121 9 148 204 256 7 69 6 91 1 152 132 117 168 25 7 11 3 29 4 9 24 3 88 16
7 5 7 8 8 8 9 6 20 6 33 0 22 7 46 7               76 2 102 6 119 8 123 2 122 0 123 9 117 121 8 120 0 108 5 73.7 41 8 197 11 8 6 1 66
1 18 1 28 1 48 1 21 1 03 0 74 0 95 0 72 0 68 0 511 0 46 0 41 0 425 0 31 0 36 0 29                         0 3    0 32 0.58 0 86 0 94 1 26 1 57 1 5
1 27 1 82 2 47 1 27 0 95 0 83 0 95 0 63 0 94 0 84 0 41 0 57 1 039 1 64 0 36 0 47 0 72                              0 1    0 63 1 11 1 42 2 61 2.15 2 9
30 6 37 5 57 3 40 0 78 8 82 9 72 8 133.1 226 7 230 8 252 9 226 8 256 7 263 1 216 210 9 198 4 164 1 168 3 143 0 75 7 75 0 36 9 49 I
00 00 00 0.0 0.0 03 00                        05       12     27 5 133 433 552 69 6 51.7 67 2 66 7 43 3                             7.2      1 2    00 00 00 00 990.6
Total
1609
1223
1563 1645 | 1830 j 1638
2014
1702
1983
1226
I 1466
89
1452.9 0.209
0 26 3 2014 5
112
Water Works Design & Supervision Enterprise
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0
Meteorological and Hydrological Aspects
Annex B:     Results obtained from the Hydrological Analysis B1: Estimated Monthly Flows at Arjo Dedessa Dam Site
May 200/
3
___ _Jin Million m )___ ___________ ____________
. _.    . —
f Year Jan Feb  Mar Apr May Jun Jul Aug Sep JOct jNov Dec Annual
I
I
I
I
I
I
I
I
I
T
1961  30 74  28 02   25.73  68 61   49 78   207 7   751.5   972 5    900      661     291 8   101 4     4089
1962  34 68   18 98   1947   5.073   21.39   157.2  397 6   560 6   700 8   512 2   64.92   31.95 \ 2525
11963  22 72    123    12.28   30.86   111 6  235.3   429 5   826.3   622 8   223 9    111 8   97.23 | 2736
1964  7 642  24 32  17 86  24 21   41 69    167     670    784 4   705 4   621 4     307    42 03      3413
1965  33 05   16 1   11 28   34.56   21 07   122 1  532 7   633 6   410 3   573.5    194 6   90 12 j 2673
1966  42 41    40.3   39 61    5361   4741    134 3  547.5   654 6   726 3   49.32   25.38   11.62     2372
1967  6.806  5.364  15.57   14 73   19 24  82.14  452 6   764 7   719 5   634.8   400 8   120.1     3236 1969   30 4   29 71  46.01   28.69   55 55  253.9    607      857    565 3   174.2   53 81   26 41     2728 1970  20.38  5 351  9.245  24 21   34 36  209.3   593 4   635 7   673 2   121 1   110.2   35 46     2472 1971   22 1   10 44  7 454   9 019   40 6    175.5  525.6   708 6   568 4   450 3   184 8   60.15      2763 1972   31.3   18 92   1343   25.78   42.79   85.61   512 9   746.2   430 7   125 4   71.09   29.98      2134 1973   1544  7 121  3.221   4 586   82.96   181.5  156.2    633    839 1   354 5   90 45      37        2405 1974  21 79  10 31  9.887   6561   71 15    19C    409.5   770.6   195 6   83 73   72.32     279       1869 1979  10.27  7 805   6815  16 56   35 18  94 19   340.6   497 5    371     157 1   57 07   25.13      1619 1980   1073  9 737  6.839  49.56   144 9  366.1  584 3    777      745    235.5   62.71    52 8  I   3045
1981  47 75  27 57  29.73  25 58  40.74   38.71  412.8    633    540 6   315.2    19 85   7 138     2139
1982  35.71    19.2   19 63  13.95   34 68   180.3  451 6   571.2   414.6   455 6    107 4   53.96     2358
1983   25 9   20.13   23 4   16 88    398    111.5  361 4    687    668 2   617 6   282 5   69.26      2924
1984   2301  10 61   8.146  6 854   21 69   134 7  449.2   401.2   311 8   78.36   12 69   4 808      1463 1985  7 152  3 462  1 775   8.54   47.33   123 1    280      559    504 1   155 7   48 31   25 72      1764
1986   10.49 6.052  11 02  9.993   9 685  86 35  288 9   296 2   438 4   132.9   50 52   28 15      1369
1987  7 756  3.775  8.501    12.5    27 82   157 2  412 8    633    402 9   231 4   97 47    38.7      2034
1988  24 16   1749   1479  5.553   28.08  203.6   354.6  689 1   905.1   315.2   114.9   46.11      2719
1989     25     14 84  13.97  24.24   2058   87 63   174 3  301 1   651.3   315.2   65 15   70.31     1764
1990  31.93 19 11   23 19  44 03   31 91   1144   219 3   1043   669 7   280.5   46.23   23.01      2546
1991  ' 16 3   12 32  10.51   18.94  44 17   113.8  5174    964 2   486.9   310.9   29 61    21 7      2547
1992  14 62   1523  9 435  14.96   42.85   116 8  235 1   497.2   338.1   482.9   99 78    41.9      1909 1993   25.4    17 72  16 74  39.56   79.86  226.9  383 1   698 7   377 8   243 8   107 6   36 17     2253 1994  23.32  12.45   1062  11 34   45.32   160 1  341.3   736.3    514    93.66   41 38   21 09     2011 1995  12 16  7 787  10 15  14 06   29 04  60.34   143.8  343 1    291    93.56   36.44    82 8      1124 1996  29.25  18 44  26.36  21 96   107 7  271 3  462.2   515.2    358    225 1   71 87   49 76     2157
2001
( 50 8   37.86  45 32  41.35   97 36  291 4  473 1   630 3   602 2   403.8   130.5   63.78     2868
2002  59 09  36 38  37 91   45 85   35 1     127    292.1   356 4    346    126.2   7005    47.88     1580
0
0
0
2003  33 66   2305  38 53  53 75   36 41  87 39  347.2   393.2
540 6   315.2   90 27  46 11     2005
2004   31.2   25.55  20 75  20 73  49 47  146 8  336 3   385 2
384 9   322.3   85.26   46 11     1855
0
0
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Meteorological and Hydrological Aspects
May 2007
B2:
Regional monthly coefficient of variations (Cv)
Station
114001
114014
/earl Jan Feb Mar April >MayTjune July i Aug | Sep ' Oct^Nov_iDec
20     0 47       0 46      0 48    0.56   069     0 53     0 27      0 33       0 28      0.56   0
114005
114004
114003
35     051       0.57      0.66    0 68    0 62    0 45     0 35       0 3        0.33      0 67   0 62     0 59 81     0.53
23     0.28       041      0 33    0 43     0.6    0 47      0.2       0 16       0.25      0 44     0.3      0 34 I 22     0 33       0 42      0.45    0 55    0.56    0 43     0 57      0.38       0 43      0.64    0 35     0.33 1
21     0 51       0 83      0 57    071    0 66    0 58
0 35      0.25       0 36      0 56   0 46     0 55
B3:     FRegional mon
91008    38     0.68        1.3        0 7       0 6    0 61    0 46     0 29      0.32       0 28      0.64      1        0.86 91012    35     0 61       0 49      0 76    0 49    0 57   0 42      03        0 29       0 32      0 52     08       0.59
thly coefficient of skewness
Station  Year Jan
Feo Mar April MaypJune July Aug     Sep     Oct i Nov    Dec
114001 35 0.63 0 74 1 07 0.94 1 63
114014 20 1.35 0 31 0.47 0.81 0.85
114005 23 0 33 1 48 0.59 -0 1 2.18
0.89 0.13 0 04 0.25 0 99 1.37 0 96
1 03 -0.5 0.93 0.89 0.67 26 1 98
1.54 0 07 0 45 0 81 0 42 0 52 1.09
91008 38 2 73 0.29 3.26 0 77 1 14 0 81 0 17 1 14 1 13 0 77 3.14 2 85
91012 35 3 17 4 94 1.22 1.5 2 34 1 15 0 43 0.94 005 1.6 2.86 2.79
B4:     16 Regional monthly coefficient of correlations JRj Station  Year   Jan     Feb     Mar Apnl   May June July      Aug
Sep     Oct  Nov    Dec
114001 35 -0 1 0 83 0 89 0.59 0.3 0.78 045 0 53 0.44 0.45 0 74 0 78 114014 20 0.36 0 5 0.77 0.56 0.62 0 81 0 46 0 54 0.28 -0 04 0 65 0 78 114005 23 0 84 0.5 0 35 0.3 0 64 0.38 0.48 0 68 08 0 83 0.25 0 16 114004 22 0.8 0 52 0.21 0 52 0.6 0.58 0 58 0 69 0 61 0 77 0.37 0.14
114003  21     0.84        0 3       0 18     0.52   0 45    0 73 0.68          0 66       0.58      0.82   0.56       0.1
91008   38     0.27      0 33      0.37     0.27   0 53    0.59    0 54      0.55        046       0.45   0 77      0 62
91012   35     0 12      0 83      0 72     0 48   0.41    0 72 0 53          0 41       0 48     0.31    0 44      0 65
____
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Water Works Design & Supervision Enterprise
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Meteorological and Hydrological Aspects
May 2007
B5:
Standardized probability weighted moments
Station             Name of Station
Location
Deg N. Deg E.
Area
(km 2)
Record
Length,N
Whoi
PWMs______ _
mio2_
t
i
1  114001   Dedessa near Arjo Upper Dedessa near
9981       29 36 25
8 41
0 40739 0.243171
2
3
4
5
6
7
8
9
114014
114005
91008
91012
114007
Dembi
Dabana near Abasina Gilgel Ghibe
Gojeo near Shene Angar Gutin near Neqemte
1806 15 0 420504 0.262951
2881 18 0 414042 0 253945
36 23   3494       34       0.408619   0 248091
1975 I
20       0  421145  0 254033
t
114004   Wama near Neqemte
114003
115008
Siffa near Neqemte Aleltu at Nejo
8 02
9.02
7 45
7.25
8.53
8 52
9.30
36 28
36.03
37.11
2966       37       0 400025
0.240847
844
951
155
21 0 419805
20 0 416527
7
10 101001 SoratMetu
8 19 35.36   1622       17
11 91013 Ghibe-Limu near Limu             8.35 37 13    663        10
12 91001 Great Grube near Abelt            8 14 37 15  15460
19
0 400261
0 401323
0 425296
0 424754
0.411964
0.254029
0.251324
0.247582
0 244658
0 261749
0 260656
Weighted Average                                        255
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Water Works Design & Supervision Enterprise
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Meteorological and Hydrological Aspects
B6. Mean Monthly Total (Suspended and Bed) Sediment Load
1
at Arjo Dedessa Dam Site (in 1000 m )
May 2007
Year Jan Feb March April May June July Aug Sep Oct Nov Dec Annual
1961 2 11 1.75 1.27 5.73 3 11 33 4 315 523 476 372 32.3 15.3 1781
1962 2.56 0.94 081 1.07 3.18 22 4 114 216 319 189 6.92 2 41 878.9
1963 13 0 47 0.39 1.6 11 3 40 8 129 403 264 50 4 16 5 14.3 932.5
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973 07 0.2 0 05 0.08 7 04 26.9 123 246 425 105 11 8 3.05 949.6
1974 1 22 0 35 0.28 0 13 5.51 29 119 360 205 102 8 23 1 94 833.7
1979 1.91 1 29 0.65 0 59 1 79 9 43 88.9 179 115 28 6 5 63 1.64 434.5
1 78   1 32      0.71        1.07     2.34     23.6      262     370     322     387     19.7    3.74        1397
2.37   0 72      0 34       1.91      079     14 3      182     263      135     227     40 1     12 7       880.6
354    3 13      2.54       3.86     2 88      224      190     277     338      102     40 8    9 14       995.4
0 64   0 57      0.57       0.49     3 18     22 4      140     356      333     352     71 4    20 1        1300
5 73   2 22      0 52       0.22     2.26     2.27      123     265     299     102     104     2.97       815.6
2.07    1 92      3.22       1 42    3.71     46.1      224     427      205     102     5 13     1 78        1024
1 09   0 75       04         0.23     1 72     33.8      216     246      205     102     16 1     2 85       826.7
1 25   0.36      0 18       0 22     2.25     25.5      178     315     228     154     36 9    6 64       948.3
2.17   0 88      0 45         1 2     2.44     8.09     171      342      146     19.9       8       2 18       704.9
1980
1982
1983
1984
1985
1986
1987
0.39    0.3       0 15        341      172     82.8     211      365      352     54.6    6 55     5.39        1098
2.69   0.96      0.83       0 45     1 74     26.7      140     223     138      157     15.5     5 58       711.7
1 61    1 03      1 09       0 61     2 18     12.3     97 7     300     296     339     29 6     8 32       1089
1.33   0 35        02         0.14     0.82     16 7      138     127     87.3    9 39    15 5    5.24       402.1
0.2    0.06      0 02        0.2      2.87     14.5      65      216     188     28.2    4 31     1 71       520.8
0.38   0 15      0 33       0.26     0 23     8.21     68.3      78      151     21 9    15.5    5 24         349
023    0 07      0.22       0.38     1.23      224     91 7     301      132     53.1     13.3     3.28       618.6
1988    1 44   0 78      C 52        0 1      1 24     32 4     94 8     246     205     102     17 3    1 31       703.4
1989    2 38   0.63      0 48       1.08     0 76      8.4      30 4    80.1     284      102     6 96     8.52       525.4
199C    2 24   0 95      1 08       2 82     1.53     12 9      44      246     205     102     15 5    5 24       639.8
1992 0 64 0.62 0 26 0.5 245 13.3 49 1 179 99 4 172 13.8 3.72 534 7
1993
1 56
0 84
0.64
2.37
6.63
38.5
107
308
119
57 7
15.5
2.94
660.6
1994
1 36
0 48
0.31
0.32
2 68
22
89 2
335
194
12.5
3.37
1.24
662.4
1995
0 48
0.23
0 29
0.45
1.31
4.63
224
98 7
78.2
12.5
2.75
5.24
227
1996
1 78
0 87
071
0 93
10 7
51.2
145
189
109
102
15.5
4.9
631 5
2001
4.72
2 83
3 15
2 55
91
57 5
150
261
250
129
21 1
7 29
899 3
2002
601
2 66
2.37
3 01
1 78
15.2
69 5
105
103
20 1
7 82
4 61
341.1
1 2003
2 44
1.28
2.43
3.88
1 89
8 37
123
123
205
102
15.5
5.24
594.5
2004
2 16
1 43
09
0 84
3.08
19.2
87 1
119
122
90 2
10.7
5 24
461.9
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B7:Eleveation-Area-Capacity Relationships Elevetion  Area Volume Elevetion
(masl)         (km2)         (Mm3) (mas!)
May 2007
of Arjo Dedessa Reservoir
Arcs
Volume
(km )
2
(Mm )
3
1320           0 54             00
1321            0.99             0.8
1322           2.39             2.5
1323           3 78             5.5
1324           5.11             100
1325           6.64            15.9
1326           8 03            23.2
1327           9.46            31 9
1328           10.87          42 1
1329          12 67           53.9
1330          14 40           67 4
1331           15 89           82.5
1332          17 74           99 4
1333          19 46          118 0
1334          23 59          139 5
1335          26 66          164.6
1336          29.05          1925
1337 31 73 222.9
1338 34.24 255 8
1339 36.62 291.3
1340 3945 329 3
1341          41.97          370 0
1342          44.25         413.1
1343          47 05          458.8
1344 49.95 507 3
1345 53 11 558.8
1346 56 31 613.5
1347 59 15 671.2
1348 61 56 738 8
1349          63.97          808.7
1350          67 88          874 7
1351           70.62          943.9
1352          74 35         10164
1353 77 88 1092.5
1354 81 28 1172.1
1355 84 51 1255 0
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
87 85
1341.2
90.75
1430 5
94 18
1522 9
97.23
1618 6
100 54
1717.5
103 64
1819 6
106.39
1924.6
109 00
2032.3
111 91
2142.8
115.05
2256 3
117 68
2372.6
120.20
2491 6
122 76
2613 0
125.28
2737.1
127 69
2863 5
130 25
2992.5
133 03
3124 2
135.45
3258 4
138 08
3395.2
142.38
3535 4
145.27
3679.2
148.00
3825 8
150 75
3975.2
153 73
4127 5
156.02
4282 3
159.09
4439 9
162.13
4600.5
166 96
4765 0
173 01
4935 0
178.58
5110 8
183 38
5291 8
188 10
5477.5
193.28
5668.2
197 36
5863 6
201 96
6063 2
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Sample Simulation Results of Arjo Dedessa Reservoir
Year
1
Month
2
Eo-Rf
(mm)
5
IWD
(Mm3)
6
(Eo-Rf)
(Mm2)
7
SL
(Mm3) (
8
T
IWR
Mm3)
9
404 Sep
404 Oct
404 Nov
404 Dec
404 Jan
404 Feb
404 Mar
404 Apr
404 May
404 Jun
404 Jul
404 Aug
405 Sep
405 Oct
Inflow
(Mm3)
3
577 4
333.3
102 7
47.7
22.5
12.3
16 3
16.8
40.1
160 9
400.3
647 4
717 9
777.8
DF
(m3/s)
4
00             0            0 0
0 0           111          00
00           143          46 2
00            135          60 0
00            146          74 0
00           147          85 0
00           164          50 4
0.0           146          7 4
00            80             00
00              0              00
00              0              00
00 1 0 82 10
10 6       1 0
100        1 0
10 7        1 0
10 4        09
109         08
94         08
51         08
00         08
00         1 0
- " T
cs
(Mm3)
10
00 00
46 2
60 0
74 0
85 0
50 4
74 00 0.0 00
"
Reservoir Status
Storage
(Mm3)
11
Area
(km2)
12
Level
(m as!)
13
Spill
(Mm3)
14
STRQ
(Mm3)
15
-----~----
T. Spill
(Mm3)
16
576 4          1006 3        74 1
324 1          1006 3         74 1
44 9          1006 3        74 1
-23 4           982 9          73.1
63 2          919 7          70 4
-84 0          835 8          66 7
459           789 9          64 6
1351 9     576 4 1351 9     324 1 1351 9       44 9
1351 5       00
1350 7       0 0
1349 4       0 0
1348 7        00
-0 9 789 0 64 6 1348 7 0 0
34 1 823 1 66 1 1349 2 0 0
160 1 983 2 73 1
399 3 1006 3 74 1
1351 5        0 0 1351 9      376 3
00              0              00
0.0             0              00
00            111            00
00         1 0
00         1 0
82         10
00
00
00
646 4          1006 3        74 1
1351 9      6464            789
716 9 1006 3 74 1 1351 9 716 9
768 6 1006 3 74 1 1351 9 768 6
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1n
405        Nov 405        Dec 405         Jan 405        Feb 405        Mar 405         Apr 405        May 405         Jun 405         Jul
405         Aug 406         Sep 406         Oct 406         Nov 406         Dec 406         Jan 406         Feb 406         Mar 406         Api
3
405.1
193.8
70.5
48.7
46 9
31.3
43.5
149.4
466.8
.]   5             6           7 00           143         46 2
00           135         60 0
0.0           146         74 0
00           147         85 0
0.0           164         50 4
00           146          74
00            80           0.0
00             0            00
00             0            00
00             0            00
00             0            00
00           111           00
00            143         46 2
00            135         60 0
00            146         74 0
00            147         85 0
00            164         50 4
00            146          74
8
9
«
106        1 0
100        1 0
108        1 0
10 8       1 0
11 7        09
10 3        09
57         09
00 1 0
0.0 1 0
10
46 .2
60 0
74 0
85 0
50 4
74
00
00
00
.. n
13
347 3          1006 3         74 1
122 8          1006 3         74 1
-153           990 9          73.5
-48 1           942 8          71 4
162           926 6          70 7 12 6           939 2          71 3 36 9           976 1           72 8 148 4          1006 3         74 1 465 8          1006 3         74 1
14            15 1351 9      347 3 1351 9      122 8
1351 7         00
1351 0         00
1350 8        0.0
1350 9         00
1351 4         00
1351 9       118 3
1351 9      465 8
640.7
516.8
402.5
166.2
71.5
31.7
24 8
17 0
13.5
00         1 0
00         1 0
82         1 0
106        1 0
100        1 0
108        1 0
106        1 0
11 3        09
97 08
00
00
00
46 2
60 0
74 0
85 0
50 4
74
639 7          1006 3         74 1
5158          1006 3         74 1
393 3          1006 3         74 1
108 4          1006 3         74 1
0 5            1006 3         74 1
-54 1           952 1           71 8
-71 7 880 5 68 7 -45 6 834 9 66 7
-4 5            830 4           66 5
1351.9 G39 7
1351 9 5158
1351 9       393 3
1351 9       108 4
1351 9        05
1351.1         00
1350 1         00
1349 4         00
1349 4        0.0
926 6
_____________________________________________________________________________________________ ___ ________________ 119
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Sfl.     (.......continued)
May 2007
EZ
3
11    zzi      r«_[   15
I
406        May 406         Jun 406         Jul 406         Aug
' 407 Sep 407 Oct 407 Nov 407 Dec 407 Jan 407 Feb 407 Mar 407 Apr 407 May 407 Jun 407 Jul 407 Aug
45.8
135.6
403.5
668.9
564 2
381.5
160.8
73.1
32.4
23 5
23.1
24.7
44 2
130.6
359 7
565 6
4 J  5             elVIZ.
00            00            00                         53
00             0             00                        00
00             0             00                        0 0
0.0             0             00                        00
00             0             00                        00
00           111           00                        82
00           143         46 2                      106
00           135         60 0                      100 00           146         74 0                      108 00           147         85 0                      106 00           164          504                       11 3 00            146           74                         98 00            80            00                         54
00             0             00                         00
00             0             00                         00
00             0             00                         00
08
09
10
10
10
10
10
10
10
10
09
08
08
09
10
10
10
00
00
00
00
00
00
46 2
60 0
74 0
85 0
50 4
74
00
00
00
00
39 6 870 0 68 2
134 7          1004 7         74 0
402 5          1006 3         74 1
667 9          1006 3         74 1
563 2          1006 3         74 1
378 3          1006 3         74 1
103 0         1006 3         74 1
2 1            1006 3         74 1
53 5           952 8          71 8
-73 0 879 8 60 7
-39 5 840 3 66 9
6 7             847 0          67 2
38 0 885 1 68 9
129 7          1006 3         74 1
358 7          1006 3         74 1
564 6          1006 3         74 1
1349 9         00
1351 8         0 0
1351 9       401 0
1351 9       667 9         830 4        2087
1351 9      563 2
1351 9       378 3
1351 9       103 0
1351.9        2 1
1351.1         00
1350 1         00
1349 5         00
1349 6         00
1350 2         00
1351 9         8 5
1351 9      358 7
1351 9      564 6         840 3        1978
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Annex C: Standards
Cl:      Commonly used values of runoff coefficients
Class Des
cription of catchment
iRunoff percen g
A
Flat, cultivated and blck cotton soils
B Flat, partly cultivated stiff soils
C           Average catchment
D           Hills and plains with little cultivation
E Very hilly and steep with little or no cultivation
^5
C2:         Runoff coefficient for pervious surfaces by selected hydrologic soil
groupings and slope ranges
Terrain Tunp
---------- ---------- -----------------------
Soil 7■ype
|A
iB
c
D
l Flat, <2%
0.04 - 0.09            0 07 - 0 12           0.11 - 0 16            0 15-0.20
Rolling, 2 - 6%                  0.09-0 14             0 12 - 0.17
Mountain, 6-15%               0 13-0.18            0 18 - 0.24
Escarpment. >15%           0 18-0 22             0.24 - 0.30
0 16 - 0.21             0.20-0.25
0 23 - 0.31            0.28 - 0.38
0 30-0 40            0.38 - 0.48
Note Where A. B. C. and D are defined as shown in C3
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C3: SCS Curve Numbers for Various Conditions’
Cover Description
Curve numbers for
hydrologic soil group
r--------------w T
Cover type
Hydrologi
c
condition
A
1
Bc
D
|
Fallow Bare soil                                                                  77            86           91            94
Crop residue cover (CR)
Pasture grassland, or range- continuous forage for grazing2
Meaoow-contmuous grass, protected from grazing
* Brush-weed-grass mixture with
Poor 76 85 90 93
Good 74 83 88 90
Poor 68 79 86 89
Fair                   49            69            79
84
Good                 39           61            74            80
- Poor
35            59            72            79
48
67            77            83
Drush the major element3 | Woods-grass combination5
Woods5
Fair Good Poor Fair Good Poor Fair Good
35 56 70 77
304 48 65 73
57 73 82 86
43 65 76 82
32 58 72 79
45 66 77 83
36 60 73 79
304 55 70 77
Farms—buildings, lanes, oriveways.     —                      59            74            82            86 and surrounding lots
Arid and semi-arid rangelandse Hyd
cond7
ABcD
Mixture of grass, weeds, and low-             Poor                  —            80            87            93 growing brusn. with crush the minor     Fair                    —            71            81            89
element
Mountain Drush mixture of small trees ano brusn
Good — 62 74 85
Poor — 66 74 79
Fair
—            48            57            63
Small trees with grass understory              Poor                  —            75            85            89
Good                 —            30            41            48
Fair
—            58            73            80
Brush with grass understory
Desert snrub brusn
Good                 —            41            61            71
Poor                  —            67            80            85
Fair
Good — 35 47 55
Poor 63 77 85 88
—            51            63            70
Fair
55
72
Good
81
49
86
68
79
84 J
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C3:(,,, continued)
Average runoff condition, and l  = 0.2S
a
Poor' < 50% ground cover or heavily grazed witn no mulch
Fair 50 to 75% ground cover ana not heavily grazed
Good > 75% ground cover and lightly or only occasionally grazed
3 Poor < 50% grojnd cover
Fair 50 io 75% ground cover
Good > 75% around cover
uui i iii iy.
4l „
i
Fair         Woods grazed but not burned, and some forest litter covers the soi Good      Wooas protected from grazing, litter and brusn adequately cover soil Poor < 30 % ground cover (litter, grass, and brusn overstory)
Fair 30 to 70 % ground cover
Good > 70 % ground cover
Soil Groups
Group A Sand, loamy sand or sanay 10am. Soils having a low runoff potential due to gnrigahveinisfiltration rates These soils primarily consist of deep well-drained sands and
Group  B  Silt  loam,  or  loam.  Soils  having  a  moderately  low  runoff  potential  due  to moderate  infiltration  rates.  These  soils  primarily  consist  of  moderately  deep  to  deep, moderately well to well drained soils with moderately fine to moderately coarse textures Group C Sandy clay loam. Soils having a moderately high runoff potential due to slow infiltration rates These soils primarily consist of soils in which a layer exists near the surface that impedes the downward movement of water or soils with moderately fine to fine texture
Group D Clay loam, silty clay loam, sandy ciay, silty clay or ciay Soils having a high runoff potential due to very slow infiltration rates. These soils primarily consist of clays with nigh swelling potential, soils with permanently-high water tables, soils with a clay pan or ciay layer at or near the surface, and snallow soils over nearly impervious parent material
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Meteorological and Hydrological Aspects C4:     Reservoir Flood Standards
May 2007
___ i   flood   inflow   Wind   speed,
Dam design
Min standard,
Category of reservoir       Initial        General condition
Spilling
long
term av
A: Breach endangers in     Daily
lives in commentary      inflow        PMF
Rare            I   Min. wave overtopping J surcharge
Larger of 0.5 PMF or 10,000 year flood
B Breach may endanger lives not in a community,
Larger of
0 5 PMF or 10 000 year
extensive drainage       Full            flood
Larger of 0 3 PMF or 1,000 year flood
C: Breach witn negligible risk to life and causing limitea damage
Full
Larger of 0 3 PMF or 1,000 year flood
Larger of 0.2 PMF or 150 year flood
Average annual max hourly wind Wave surcharge allowance > 0 6 m
Av. Annual max hourly wind. Wave surcharge allowance >04 m
/Vore For the purpose of PMF the ordinates of the computed PMF hydrograph
are multiplied Dy the proportion indicated
I
I
i
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C5:         Ratios of the basic dimensionless hydrograph of theSCS ITTp              Qi/Qp              Ti/Tp              Qi/Qp              TiflTp                Qi/Qp
0                 0               1.05             0 99 0.05           0 008             1 1              0.98
2.6 0 13
2.7 0.11
0 1 0.015 115 0.95 2.8 0 098
0.15 0 043 1.2 0 92 2.9 0 088
0.2 0 075 1.25 0 88 3 0.075
0 25 0.11 1 3 0.84 3.2 0 056
0.3 0 16 1.35 0.80 3.5 0.036
0 35 0.22 1 4 0 75
0.4 0 28 1 45 0 71
3 7 0 027
4 0.018
0 45            0.36             1.50             0.66              4.2              0.014 0.5             0.43             1.55            0.61               4 5              0.009
0.55            0.52              1 6              0.56              4.7              0 007 0.6              0.6               1 7              0 49                5               0 004 065             0.69              1 8              0 42
07              0 77              1.9              0.37 0 75            0 83              2.0              0.32
0.8 0.89
0 85 0.93
2.1 0 28
2.2 0.24
0.9             0.97              2.3              0.21 0.95            0 99              2.4              0.18
1                 1                2.5              0.16
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Meteorological and Hydrological Aspects
C6:
Guidelines for Interpretations
of Wate
r Quality for Irrigation
Water parameter
SSyymmbbooll
2
Unit  Usual range in irri Unit- Us1-1?!K
gation water
SALINITY
Salt Content
dS/m
Electrical Conduct^ity
ECW
dS/m
0-3
(or)
Total Dissolved Solios
TDS
mg/l
0 - 2000
mg/l
Cations and Anions
Calcium
Ca”
me/l
0-20
me/l
Magnesium
Mg”
me/l
0-5
me/l
Sodium
Na’
me/l
0-40
me/l
Chloride
er
me/l
0-30
me/l
NUTRIENTS-
Potassium
K’
mg/l
0-2
mg/l
MISCELLANEOUS
Acid/Basicity
pH
1-14
6.0-8.5
Sodium Adsorption Ratio-
SAR
(me/l) .
22
0-15
Source. FAO. 1994 Water Qualify for Agriculture. Irrigation and Drainage Paper No. Rev 1 Reprinted. 1994
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Annex D:               Meteorological Data
D1: Details of Meteoroioaical Observation Stations 
May 2007
I--- -------
Latitude           Longitude
---------------------. I
|!
Station Name            North
East
S.No.                                 Deg.     Min.       Deg    ' Min
Altitude
(m)
Class
rerioa       L---------- -
I
Pl            Agaro                     07        51        36         36           2030        1980-2004           1
2            Arjo                         08        45        36         30           2565        1972-2004           3
3            Bedelle                   08        27        36         20           2030        1967-2004           1
4            Deaessa                 09        23        36         06           1200        1971-2004           1
5            DemDi                    08        04        36         27           1950        1954-2004           3
6            Gimoi                     09        10        35        47           1970        1978-2004           1
7            Jimma                    07        40        36         50           1725        1952-2004           1
8            Kone                      08        41          36         47           2000        1979-2004           4
10          Nekemte                09        05        36         28           2080         1971-2004           1
11         Wama                    08        59        36         40           1450        "'980-1987           3
D2:      Types of Climatic Data available at the various Meteorological
9            Meko
08        41        36         02           2000        1980-1989           4
S.No.   Station Name
Altitude
(m)        ’Yrs      RF
TM        RH
WS       SD
EP
1       Agaro                      2030         25           X                X            X            X              X                X
2       Arjo                         2565         33          X                X
3       Bedelle                    2030         38          X                X             X                             X           X
4       Dedessa                  1200         34          X                X              X           X
5       DemDi                     1950         51           X                X
6       GimDi                      1970         27           X                X             X             X              X
X
7       Jimma                     1725         53          X                X             X            X              X           X
8       Kone                       2000         26           X
9       Meko                       2000         10          X
10      Nexemte                 2080         34           X                X             X            X              X
11      Wama                      1450          8            X                X
_            __     _   _
’ Data length refers to Rainfall and Temperature data.
Yrs
RF 
Tm
RH
WS
refer to rainfall series monthly rainfall average temperature relative humidity 
1 day
wind speed_____________ _ ____ Rday number of rain days 
sunshine duration maximum 1-nour rainfall maximum 1-aay rainfall
J
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D3: Mean Monthly Rainfall at Bedele Station
May 2007
Annual
Year
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976 1978 1979 1980 1983 1984 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Jan    )Feb |l | 00
0       100 67       59 54       50 20        1
0        20 0        19
68       13 44      101 41       29
57 00 00 08 00 2        34
17        2
0        17
48       34
53        2 13       15 28        3
00 0        33 16        4 7        66 63
MarchjApril |May |june jjuly lAugHjeptjQglll
152      33       181      221      212      381      380       167
Nov |Dec
1
55       163
0
323      380      324       137
81       198     210       250      275      368      286
98
89      258      258       266      432      280      444       186
41
42 178 116 263 337 287 287 110
10 51 337 269 322 403 248 102
53       246       334      311      234      455       326
55
9       497       355      351      292      368       126
37       105     202       215       327      276      245       228
156       97
0
267       333      373      472       154
115 179 204 267 370 303 281 204
29 44 169 350 408 276 267 113
0       208      285       174      236      304      363
86
48        62       237       369      499      468      306       197
45        66       291      275      469      211      242
9
80       141     243       222      218      357      200       183
33 106 225 281 250 258 276
102 130 257 292 257 318 353
21
77
208 83 317 232 290 203 128 70
50 142 340 307 221 304 232 309
87 57 203 332 314 327 291 245
13      147     431       441       319
242      324       328
4
87
63
123      256      420
*86      273      286       242
72       322       390      297      329      370      211
38       169      298      296      202      253
63
84       131       37       320      278      258      197        52
46
81       248      447       299      268      273       168
253         0
35         22
70
07
56         25
122        26
21          10 8          29
20          0
62          9
41        72
00
50          0
99          0
25          5
10 17          0 10         24 45         13 38          4 59          1 8          39
29          8
29         14
3          46
13          3 62          15
1980
1539
1897
2322
2101
1788
1790
2171
1796
1993
1926
1655
1706
2293
1637
1680
1484
1837
1670
2001
1942
2321
1827
2155
1450
1446
1917
Average
CV
Skew
Max
Min
18 23
1 28 1 28
1 05 1 6
68 101
00
65      705     239
370 
0.242
303     302
0.77 0.58
7 09 0 68
0.434
0.098
291
0.312
-0.91
0.21
0.266
756
0.563
0 837  0.56   0 345  0.375
208    258
497     447     499    468     472     328
0
9
0
0       186    202     128       9
41        72
7 256    7 114
2973      1.172
253        46
00
1864
0.14
0.18
2322
1446
____________________ _______________ _____________________________________ 128
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Meteorological and Hydrological Aspects
04: Mean Monthly Rainfall at Jimma Station
May 2007
pn mr
Year Jan
"J
Feb March Aprril May June July Aug Sept Oct Nov Dec
1953       33        49        88
1954        8          49        88        733        93        210       194        214         152          27           68         JO
733       7 72      283       399        211         256         116           1
3
nr
1955 33 49 88 135 94 298 235 244 169 103 36 23
1956 91 25 100 109 96 183 288 254 215 50 16 96
1957       29          4           83         290       142       226       169        195         249         118           3             3
1958 1        0          52         117        215       225       278       185        189          82           68            25           11
1959       43         86          53         138       141       292       203        215         288          87            16           42
1960 81 140 86 138 103 170 272 138 151 130 68 32
1961       11         39         104        145       284       279       135        210       212          38           68         28
1963       0          86          98         225       197       237       272        262         243          97          221           73
1964       40         57        131        116       106       206       221        206         225         164          24           109
1965 43 4 39 203 102 249 205 191 58 107 116 25
1966 21 73 100 153 122 161 307 172 139 56 17 13
1967       4          15         198        82        157       273       207        283         250         132         215           2
1968 3 74 63 105 154 233 173 248 210 31 59 55
1969       55         61         199        91         109       165       189        185         104          85            35            5
1970      78        135        91         188       103       288       197        263         148         149          68          36
1971       18          3           58         81        267       153       205        204         201         124         107          44
1972      12         74         127        115       101       161       159        193         167          58           183           0
1973 28 11 7 149 148 180 297 160 181 57 10 10
1974       5          56         76         103       320       165      221        265         240          25            1             1
Annual
1743
1270
1507
1523
1508
1446
1604
1509
1494
2012
1606
1341
1333
1819
1408
1283
1743
1465
1350
1237
1479
1975       4          65         100       171       12C      198      252        194        151          98            7             55          1414
1976 36 85 107 112 189 324 211 233 190 93 118 25
1977 73 56 54 16 130 197 203 268 191 229 61 15
1978 5 71 42 138 204 222 184 215 203 64 57 38
1979 32 118 111 23 116 232 153 164 115 75 9 22
1980 23 42 100 301 108 189 96 164 141 109 27 28
1981 1 7 136 62 252 114 193 250 164 31 127 1
1982 105 43 61 136 211 223 141 192 157 94 212 37
1983 20 40 97 161 228 166 174 229 299 141 54 7
1984 24 11 32 83 191 183 211 166 187 12 138 50
1985      25         20          77         147       203       136      268        168         128          63           50           12
1986        0          48          82         115       151       256       233        134         163          89           14           47
1987      26         89         158         60        188       204       186        180         136         116          46           52
1988 81 59 31 87 182 165 185 294 220 172 2 0
1989 28 47 138 179 102 179 232 213 204 107 28 170
1990 25 46 133 56 194 320 280 280 245 23 93 19
1991 79 81 62 169 110 223 200 246 140 51 8 78
1992 28 56 56 162 144 287 212 344 175 180 70 36
1723
1491
1442
1169
1328
1337
1611
1614
1288
1297
1331
1440
1477
1627
1712
1445
1749
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May 2007
Year     Jan     [Feb     March Aoril      May
(... LUI -------- I ---------
June July
U.-------
Sept    Oct        Nov       Dec 'Aug
Annual
a
M
a
a
a
ri 1
1
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
9          81         110       237       237      225       189       263         164         17            3             0
33         28         87         153       213      274      255        155         177         11           18          11
8          27         74         193       115      163      181        216        141         54           30           96
35         22         135       203       175       183      231         91          245         24           93           40 65         49         69         178       274      237      122       276         148        337         243          36
103        22         97         93        174      223      248        307         200        201          47            1
30          1          84         72        214       575      136        102        131         198           1             2
0           1          39         194       238       154      266        159        255        244          47           25
16         13         86         117      341       299      312       161         183        163          76            4 69          5          11          90        137      242       150       235         165         80            8           138 29         61          87        111        12       272       187       151         239         92           30           15 51         28         46        131       162       128      216        219         210        133          67           89
1534
1415
1298
1476
2034
1713
1546
1622
1772
1330
1285
1482
Avg
CV
Skew
Max
Min
33 49 88 133 172 279 208 210 182 103 68 36
0.86    0 71     0.48     0.43    0.39    0.34    0 24     0 26      0 26      0.67      0 96      1.06
0 95    0 68     0 55     0.41    0 41    2 53    0 11     0 12      0 04      1 10      1.32      1 74
105     140      199     301     341     575     312      344       299       337       243       170
0         1          7         16       12      114      96        91         58         11          1           0
1502
0.13
0.83
2034
1169
ri
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D5: Mean Monthly Rainfall at Dedessa Station
May 2007
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D6: Mean Temperature at Bedele Station
_____ JinoC)_________              _______ -
May 2007
rear_ Jan Feb Mar
t
—
n
£ Apr Ma> — - - --
1971
1972
199       21   2    20 8      21   5    20.4
182
16   7     16 6
19   5    20 9      18.4      17 9      19.8        18 3
15    5     11554.8
1973       179       187       21 5      21.5       194       179
14 3
16 4       18   0     17    3     174
1974       17 7      19   8    19.3      20 2       18 7      18   2     16 9
1975       17.3      193       197
198       194
17 7
17 8
16.7
17 6
157
16.2
17.2
17 7
Dec
172
159
24.9 17.0
17 2       17 1
17 1 17 9
18 1 17.2
17 7 170
167
1976       179       18   1    19   1    18   8
1977       182       19.0
1978 173 18.4 19 3 18.9 18 5 17 5
16   0     16    1     19   7 16   0     16 5
17    3     17 5
1979
1980
21.0      20 5      197       19 5       79 192       19   1    176
174
1981       17   3    17   5    17   1 1982
170
1983
1984
7.5
19 1     20    1   176
21   4    21.2       22 0       197
174
18.0
166
17.2
178
169
16 8
173
169
18.3
17.3
174
17   0     176
187
174
190
19   4     20   8
18   6      18 9
1985       20.5      20   5   21   4    20    5   18   6    18   0     17.2        17 1        17 3
177
18 8
1986       19.9      20   6   20 8     20.9      21   4    18   1     174         17 8 1987       194       20   8   20   4
17 7 18 2 18 7
18 1 18 2 18.3
1988       197       20    3   20.8      21   6    19.6       18 1        170
17 3       17 5
18   3     18 2
1989       17.8      187       19 1      19 3      190
178
15.0
17.3
17 7       17.5
18.0
1990       18   1    18.7      19.5      20 2      19 3      18 5       174         174         178
18   2     18 9
196 18 9 184 190 179 17   8 19  1
1991       19   3    20.6      20 7     21.0      20 4      18.3                        174
18.2
18 4       18 7       20  0
1992       19  1    20   1    21 3      20   6   20 7       19 5       18   4     18 0       19    6     19  1       18 8       20    6 1993
1994
20 9      20 9     22.0       21.3      19 5
17.8        17.7        18 2        19 0        19 6        19 5
1995
1996
1997
1998
1999
2000
205       20 8      21 3      21 4       19 9       194        17.6        18.1        18 5        18 8        18 9        19.5
192       21 0      20 6       20 7      19.1       184         178         18 0        18 3        18.3        18 5        18 7
192       199       21.5       19 9      19 3       18.6        17.8        18.0        18 8
13 9      21.2      21 2       23.2      21.0       19.3        18 1         18.3        18.9        192         18.6        19.2
19 6      21 7      21 7      21 8      19.1       187        17 3        17 7        186        17 9         184        19.2
17 7        17.9        18 5        18 9        18 6        189
2001       19 1      20 9      20 7      21.2       199       18 0        17.5        17 7        18 6        19 4        18 7        192
2002       19.2      21 1       21 6      21.8      21 2       18 5        18 3        17.5       18 1        18.1         186        18 9
2003       20.0      21.5      21.1       21 2      21 9       187        17.6        18 1         186         190         196        19.6
2004       20 8      21 0      22 1       21.5      20 8       18 3        17.8        18 1        18 6        18 7        19 1        19.6
Average     187      79.7      20.6     20.6      796       78.0       17.3      17 4       77 9        78.0        78.3        78.9
cv     0 08     0.13     0 05     0.05     0.06     0.72       0.05       0.04      0 05        0.05        0.06       0.09
Skew      -1 21    -3 96    -7 79     -0.08    0.00    -4.24     -2 06     -0 86     -0.58     -0.94      -7 35       1 44
Min 13.9 75 17 1 18.4 17 0 79 14.3 15.7 16.0 15.5 15.4 15 9 Max I 20.9 21 7 22.1 23.2 21.9 20 4 18.4 18.3 19.6 19.4 19 7 24 9
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D7: Relative Humidity at Bedele Station (in°/o Vear Jan Feo Mar Apr May ’ Jun
May 2007
1987
1988 63 80 58 52 70 78
1989 51 53 67 62 68 80
1990 59 62 56 60 70 79
1991         55         46          56         67         78         8C           82           84           77           71            65           65
1992 68 65 58 62 66 75
1993
1994 53 48 48 57 78 83
1995 46 50 51 59 72 75
1996 59 54 63 62 75 82
1997        63
Aug        Sep |       Oct          Nov        Dec 80           80           69           58
89           84           83           76           63           50 83           85           84           72           64           75 82            80           80           70           69           60 77           81           74           72           69           64 85           72           81           61            66           61 85           83           78           69           69           67 83           84           80           72           68           64
1998        65         55
64
1999 59 50 49 55 76 76
2000         58
2001 62 62 65 65 73 83
2002        69         60         66         65          67          81
2003        62         55         63         60          57         81
2004        61          54         56         62          66         81
I
84            84           80           78           64           63
82           84           82           80           74           70
84            84           83           80           74           67     I 85           86           83
88            86           84           73           69           61 85           84           82           74           70           69
Average       60         57         58         61          70          78           84            83          81           69           63           60
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D8:     Wind Speed at Jimma Station
(in m/s)
Vear Jan Feb March April May
May 2007
June July Aug.
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999 200C 2001 2002 2003 2004
0.8          08           09           0.9           0 8 09         1 1         1 2         09         1 1        09         0 9          08           09           1 1           0 9 0 9         1 2         08          1.3        1 4        C 9       0.8          08           0.9          0 8           0.8 08         0 7         1 0         1 0        09         09         08           0.9          0.9          0.9           0.8 07         0 8          09          09         10         0 8        08           0 9          0 9          0 8           0 7
07         08           12         1 1        09         09         0 7          0 8          0 8          0 8           1 0
0.9        08           08         0.9        0.6        09         0 7          08           0 8          0 7           0 6
07         08          0.9         0.9        08         07         0 7          0 7          0 7          0.6           0 6
07         08           09          07        08         08         0.6          0 7          0 6          0 6           0 5
07         08          0 8         08        0 8        0 7        0 6          0 6          0 7           06           0 6
0.6        06          08          07        0 7        0 7        0 6          0 6          0.6          0 6           0 6
0.6
•             r          0.6        0.6        0.5          0 6          0 6           06           0.5
0.6
0 5        0.8         07         0.6        06         0.5        0.5          0.5          0 5           04           0.3          0 3
05 0.5 06 0.6 0 5 0.5 0 5 0 4 0.4 0 3 02
0 1 0 1 02 0.2 02 0 1 0 1 0 1 0 1 0 1 0 1
0.3
01
0.1        0 1         0 1         0 1        0 1        0.1        0 1         0 1          0.1          0 1           0 1          0 1
05         06          06          06        06         0.6        0.5          06          0 6          0 6           06
05
0 1        0 1         0 1         0.1        0.1        0.2        0 1         0.1          0 1          0 1           0 1          0 1
06        06          0 7         07        07         06         05          0 5          0 6          0.5           0.5
05
0.5        0.5         0.6         06        0.5        0 5        0.5         0.5          05           0 5           0.6          05
0 1        0 1         04         0.2        0.3        0.1        0 1         0.1          0.2          0.1           0 1          0 1
04         06          0.6         0.5        0.5        04         0.4          04           04           0 4           04
05
04 0.5 06 0 5 0.4 04 04 04 0 4 C 4 04 04 04 0 5 0 5 0.5 0 5 0 4 0.4 04 04 04 0.3 04 04 04 0 5 0 5 04 0 5 03 0.3 0 4 0 4 0 3
0.3        0.3         0 3         0.3        0 3        0.3        0.3         0.2          0.2          0 2           0.2
0.2        0.3         0.3         03        0.3        0.3        0.2          0 3          0 3          0.2          0.2
02         0.3         0.3         0 3        0.3        0.3        0.2         0.2          0 3          0.2          0.2
0.2
0.2
0.2
0 1        0.2         02          02         0.3        0.2        0 1         0.2          0.2          0 1          0.1          0 1
0 1        0.1         02         0.2        0 1        0.3       0 10       0 11         0 09        0 18        0 19        0 18
Average
CV
Skew
Max
Min
0 52      0 62       0 72      0 73      0 75     0 74      0 71         0 76       0 82        0 82        0 83
0 89
0 52 0 5 0 44 0 44 0 42 0 36 0 36 0.35 0.33 0 34 0.32 0 29
-0 04 0 16 0 1 0.29 0 63 -0 ■0.1 -0 0 02 0.3 0 31 0 08
0 1        0 1         0 1        0 1        0 1        0 1        0 1          0 1         0.1          0.1          0 1          0 1
09        1 2         1.2        1 3        1 4        0.9        0.9          0.9          09          1.1           1 0
09
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09' Sunshine Duration at Bedele Station (i n hrs/day)
Year           Jan       Feo     Mar        Apr       May
1987        79         72         69         8 5        5.6
1988        9 3        7 1         65         8 2         79
1989        8 5         82          79         7.9        7 4
1990        8.9         56         7 7         64         8 2
1991         79         8 1         68         6 3        7 1
Mav 2007
—
Jun          Jul          Aug         Sep
Oct J   Nov
6            6.3           57           84            8            8 3
6 4          2 6           4 2          5.1
97
1992
57         7 7        7 1         8 3
6 3.8 5 1 6.5 7 9 8 8
6 4 3 8 4 8 6 9.6 8 7
4 5 2 7 3 4 5.9 8 8 4
6 1 34 2 2 6 7 6 2 6 2
1993        7.6         66          75         55
1994
7 7         7 5        7 7         76
•
•            2 4           3 4           58           9•5
84
•
Dec 
—i 83 95 6.4
9I 7 83
9.3
•
1995
88
66
77
66
1996
•
•
7.9
•
•
•
37
43
67
9
79
7.8
1997
83
7.2
92
7.5
68
7
61
41
46
84
76
67
1998
7.5
77
64
87
64
67
2.9
33
47
54
84
92
1999
81
91
88
76
7.6
66
35
46
6.6
58
98
88
•
•
55
64
•
2000
9
88
9
61
78
8
2001
2002
•
82
75
91
84
61
56
31
69
88
83
76
2003
7.9
86
7.3
88
96
57
29
36
61
9.5
87
86
2004
75
79
6
5.7
74
43
4.2
45
35
8.2
83
77
Average 82              76         75         73         76          6 1          37           4 1          6.2          79           8.3
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Annex E. Hydrological Data
E1 List of Selected Hydrological Observation Stations—r-------L-o--n-g-n—_ua——e, r- Catch.
May 2007
s.
No
Latitude, N
Station
No.
Station Name
Deg      Min.   | Deg.
I  Min.
Area (km2)
-t—---------
I
I
1    114001      Dedessa near Arjo                       08    1 41           I 36                    25        9981
Period
1960-2004
2    114002     Angar near Nekemt
r 09       I 30      I 36
r 35 I
3742           1994-2004
3    114005      Dabana near Abasina              1 09      r 02     | 36            03        2881
1962-1984
4     114007     Angar near Gutin
____
5 114008 Yebu at Yebu 07 48
*
36
—
J---- ™-----
29             1999-2003
____
42          47             1979-2004
He
114013      Dabana near Bunno Bedelle       08        24         36         17          47
114009     Urgessa near Gembe                   07        50         36         39           19             1979-2004 1984-2003
08        03         36         27         1806           1985-2003
I-------------------
8     114014     Dedessa near Dembi (ToDa)
9        114016     Loko near Nekemt
09        22         36         36         375             1997-2004
10
114019     Temssa near Agarc
11
113004     Melke near Guaer
51         36         35         47 5            1989-2004 07 1              I
08        51
44          38              1998-2004
37
12
113038     indris near Guder                         08        56         37
45
111
1986-2004
13
101006 Uka at Uka 08 10
I
35
22
52.5
I
1980-2004
14       091008     Gilgeignibe near Asendabc
07 45
i
37
11
2966            1967-2004
15   091012     Gojeb near Shebe
07 1
25
36
23
3577            1970-2004
JL
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Annex E2: Mean Monthly Streamflow at Dedessan near Arjo Station
May 2007
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—.------------- -----------—r------------------I
E2‘             Continued)
Year
Jan
Feb
Mar
Apr-r---- Mav Uun jjul
[Aug j
r~ Sep
Oct
Nov
Dec
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
20 4    122     148     194     38 3        83        225         569         486        156        60 -
-    -          30 4 141 8       373        723         854         598
41 4    19.0
-
-
-
-
-
-
-
-
•
-
-
-
-
-
-
87 2
-
-
-
-
242 135 7
851 595 66 1 57.2 128 3 401 740 1045 1005 674 215 111 7
99 0 572 55 3 634 46 2 175 457 591 578 211 115 839
56 4    36 2    56 2    74.3    48 0       120-
652 -
•
--
52 3    40.2    30 3    287     65 2      202         526         639         643        538      140 -
Avg
cv
Skew
Max
Min
46.2    287     26.0    33.2     66.5       223         654       1007         889        581       177          90 9 0.47    0.52    0.66 0.71        0.59      046        0.34         0.30         0.32        0 68      0.51           0.50
0.66    0.65     114 0.94         1.54      0 74        0.22        -0.16         0 43        0.73      1.26           1.00
99.0     634     67.1     94.9 190.9    503.5 1176 1         1612.8     1502.5    1337 4    459.2         210.4
120       5.4      2.6      6.3    12.8     53.2      225 0       491 1       485.9      130.8      59.9            369
Mean annual flow = 3821 Mm3)
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E3: 41 Mean Monthly Stream flow at Dedessan near Dembi Station
May 2007
Million mli Jan
______________
I
Year
Feb
Mar
ApJr
Ma y I
Jun
Jul          Aug       Sep
________
Oct
______
Nov [      Dec
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
8 5       5 5       9 7       8 4        94         58          262         208           299            67      22 9           115
59       4 5       9 7       9.2     18 6       105          243          342           218         104     -4 4 1         27 1
17.9      157     12 5        64     23 9       153          217          392           489         142       52 0           18 8
11 0        76       4 5     11 5        82         31           167          253           272          142      24 8          13 8
18 3        58        56     22.7        99         52          252          564           362          126      20 9             9 4 72       6 3        66     12 5     29 5         76          305          522           263          140      13 4             8 9 78     15 3     12 9       8 8     36 6         78          138          269           183          218      45 2          17 1
11 2 172 16 6 37 6 80 8 252 334 378 204 110 48 7 14 7
12 3     13.5      168     22 5     37 8       112          274          381           282            59      26 6           16 4
12.9    12 1      16 5     23 8     48 7         87          190          272           331          101       32 5          33 7
129        94     16 5     23 8     48 6         87          190         272           331         101       32 5           33 7
21 2     13 8     23 2    30 1     55.2       142          219          343           204         262        188          56 1
28 1     13.6     20 3     12 7    31 1        110          272          415           299         329      88.8          21 1
130       6 5       8 3       9 5     54 9       148          242          245           214         302      48 4           18.3
102        56       4.5        97     41.2       119          290          309           242         209      82 0           21 9
12.7        96      112     14 5     55 5       226          330          322           296         212      59 6           22.5
6.5        69        66       9.0        65         63          192         255           195           68      27 7           14 9
74       4 0        92     24 0       6 7         59         241          223           324           82      20 3            100
13.0 130 13 7 33 0 98 5 198 208 208 145 39 18 8 18 8
__ ~
64 3 7 4.2 78 26.8
92            83          165           302          272       70 2          21 9
Average CV
Skew
Max
Min
12.2     9 47     77.5     16.9     36 4    112 4       232 4      316 9           273      154 3       48.4           20 5
0 47     0 46      0 48     0 56     0.69    0.526         0 27      0 326           0.28     0 561       0.81           0.53
1 35     0 31      0 47    0 81     0.85    1 028        -0 47      0 927          0.89     0 668          2 6          1 98
28 7     17 2     23.2     37 6     98.5       252          334          564           489         329   187 9           56 1 5.9      3 7       4 2       6 4       6 5         31            83         165           145           39      13 4            8 9
Mean annual flow = 1255 Mm3)
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Meteorological and Hydrological Aspects
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Annual Maximum Floods
(1
Year
n m3/s)
Dedessa
Upper
Dedessa
Dabana
near
Abasina
Angar near
Angar near
Gilgel Ghibe near
Asenoabo
Gojeb nearSbebe
neqem tc         Gutin
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
633
1173
893
789
850
951
814
1165
781
634
896
721
490
645
554
1083
369
480
502
574
771
750
646
804
353
525
525
744
312
601
213
206
212
243
354
228
200
151
189
262
164
175
226
175
211
244
271
300
370
267
467
264
434
449
247
196
257
180
314
341
238
202
248
151            132 198            272 130            176 330             127 151            231 167            HO 205             116
168
129
148
151
223
135
149
119
92
96
127
143
85
121
247
86
106
192
237
159
255
100
174
339         188 185         258 186        241 284        217
214
140
249
177
288
138
297
314
184
150
203
226
132
245
366
164
164
261
164
150
282
132
193
199
439
236
335
361
209
247
256
157
271
252
128
141
73
55
124
107
134
105
125
142
136
142
149
178
172
109
106
79
181
128
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Concentiation at Gumara Gauging Station
I Field II
sample I ab No River / Stream Station Date & Time Time
|
_
No
Sediment    F
G/height Flow Depth Width Concen Remarks
No *                   1
of Sampling (Sec)
(m)            (m’/s)                       'm'
(mg/l) i          AV
I
484          1
485          2
486          3
664          1
665          2
666          3
1057         1
1058         2
1059         3
1190        1
1191          2
1192         3
1223          1
Dedessa            Toba            15-Mar-90
Dedessa Toba 15-Mar 90 _
Dedessa Toba 15 Mat-90 _
0 43
0 43
0 43
Dedessa            1 oba           21 Mar-90                          0 50
Dedessa            Toba            21 Mar-90                          0 50
Dedessa            "loba            21 Mar-90                          0 50
Dedessa            Toba
2-Jul-90 1 81
_.
Dedessa Toba 2-Jul-90 1 81
Dedessa Toba 2-Jul-90 1 81
Dedessa Toba 22 Dec 90 50 0 40
Dedessa Toba 22-Dec-90 50 0 40
Dedessa Toba 22-Dec-90 50
Dedessa            Toba            16 Sep-90
I2 2 2 2 2
| 27
1224         2                                Dedessa            Toba            18-Sep 90
1225         3                                Dedessa            Toba            18-Sep-90
698         1                                 Dedessa            Toba            16-May-93           45
699          2                               Dedessa              Toba            16-May-93           45
700          3                               Dedessa              Toba            16 May-93           40 704         1                               Dedessa              Toba             12-Apr-93
705 2
06 3
Dedessa Toba 12-Apr-93
Dedessa Toba 12-Apr-93
0 40
2 46
2 46
2 46
0 46
0 46
0 46
0 64
0 64
0 64
4 16             0 26                    6 9 4 16             0.70                  13 8 4 16             0 36                  20 7
5 41             0 54                    7 0
5 41             0 80                  14.0
5 41             0 39                   6 1
9 14             8 40                    6 6
9 14             8 00                  13 3 9 14             7.00                  19 9
4 37             0 43                    7 0
4 37             0 74                  14 0
4 37             0 46                  21 0
98 50
98 50
98 50
2 89                   0 66             19.5 2 89                   0 61               6 5
2 89                   0 71             13 0
8 01
8 01
8 01
51 56
40 00
42 81
59 69
173 13
90.63
215 31
135 62
190 00
90 94
99 37
63.13
141 56
187 82
124.69
87.90
108 63
81 40
73 05 64 61
61 59
59 20
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E5: (... continued)
Field
No
sample
No
Lab.No
River /
Stream
Station
Date   &   Time of Sampling
Time
(Sec)
G/height         Flow jm’/sL
Depth          Width (m)       L L )
m
Sediment Concen
(mg/l)
Remarks
AV
541        1      179/04     Dedessa         Arjo        10 Aug-04      30       2 45
542        2                      Dedessa         Arjo       10-Aug-04      26        245
543        3                       Dedessa         Arjo        10 Aug 04      28        245
544        1       180/04     Dedessa         Arjo       11-Aug-04      32       2 56
545        2                       Dedessa         Arjo        11-Aug-04      28       2 56
546        3                       Dedessa         Arjo        11 Aug 04      27       2 56
559        1       185/04     Dedessa         Arjo         1-Sep 04       29        361
560        2                       Dedessa         Arjo         1-Sep-04       28       3 61 561        3                       Dedessa         Arjo         1-Sep-04       29       3 61
143 12 9.05ft 17 5
143.12 9.1ft 35 0
143 12 9 5ft 52 5
196 11       11ft         18 0
196 11       9 6ft        36 0
196 11       9 6ft        54 0
611 23      137ft        180
611 23 14 3ft 37 0
611 23 1 46ft 55.0
1417 50
1739 74
1740 74
1652 86
1718 12
1639 31
1360.22
1328 81
1438 44
142
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HYDROGEOLOGICAL
STUDIESArjo Dedessa Irrigation Project
Hydrogeological investigations
May 2007
TABLE OF CONTENTS
____________ ______ I
table of contents
list of tables
LIST OF FIGURES
1. INTRODUCTION 1 1 General
1.2 Location
I
.... 2
1.3 Physiography ......................................................................................................... 1.4 Methodology and approaches
2.  PHYSICAL HYDROGEOLOGY
2.1 Hydrogeological setup
2.2 hydrogeologic units
2.2           1 Fractured and/or weathered volcanic rocks
--................................................................... 6
2 2.2 Alluvial sediments - —......................................................................................................................
2.2.3 Delluvial sediments
2.3 INVENTORY AND WELu DATA
2.4 Hydrodynamic parameters of aquifers
3. GROUND WATER POTENTlAi.................................. .......................................... —---
3.1 Groundwater recharge estimation                      --
3.1.1 Base flow analysis
3.1.2 Water balance method -............................................................................................................. -
4.   A TER U A LITY
4.1 Water samples-..................................................................................................................
42 Sampling techniques and analysis
4.3        Pictorial representations of water quality analysis IS
4 3 1 Piper diagram -................................................. ... 18
4 3 2 Schoeller diagrams........................................................................................................................................ W
4.3.3 Stiff diagram ................................................................................................................................................. J9
4.4        agricultural/irrigation water quality23
5.  PIEZOMETERS OBSERVATION WELLS AND WELL FILED...
5.1 Distribution of Piezometers/Observation Wells -27
5.2 Future well field         ..................................................................................................................... 28
6.    waterlogging and drainage
6.1 Topographic features and soil characteristics ....................................... .......................................
62 Existing groundwater table—.........................................................................................
6.3    Future groundwater table and recharge from irrigation
7.      salinity and sodicity-------- --- ------------------------------------------------ -------------------- - ---- 8. exsiting and future prospect of groundwater-„...................................................... .......... ....
8.1 Existing groundwater development.................................................... ~................................................. 4
8.2 Future groundwater prospect
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C « Qo Oc Qo '4 O'Arjo Dedessa Irrigation Project
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LIST OF TABLES
9
Table 2.1 Details of boreholes in the study area..................................................
Table 3.1     Monthly total flow and Minimum flow of Dedessa river near Arjo12
Table 4 1     SAR and EC values in terms of irngation water suitability
Table 4.2 SAR and EC values for surface and groundwater in Arjo-Dedessa area
Table 5.1 Locations of the Proposed Piezometers................................................................. Table 6 1 Annual gross crop water requirement at primary canal head
Table 6.2 Estimation of wetted area for Arjo- Dedessa irrigation canal
27
Table 6.3 Seepage loss from unlined Arjo- Dedessa irrigation canal....................................... 33
LIST OF FIGURES
Figure       1       1       Location       map       of       Arjo-       Dedessa       irrigation       project3
Figure     1.2     A     map     showing     3-     D     view     of     Deoessa     river     Catcnment5
Figure   2.1   A   map   showing   hyarogeoiogic   units   of   Deaessa   river   cathment10
Figure            4            1            Location            of            water            sample            points17
Figure 4.2 Piper Trilinear Diagram for Water Samples20
Figure 4.3 Scnoeller diagram for water samples......................................................................21
Figure 4 4 Stiff diagram for water samples22
Figure 4 5 Electrical conauctivity (EC) in ps/cm and Total Dissolved Solids (TDSj in mg/L for24
Figure 4-6a Map Showing Contour for TDS
26
Figure             5.1             Proposed             Piezometers/Observation             wells             ->9
Figure     6     1     Profiles     along     different     lines     in     the     command     area37
Figure 6.2   A map snowing lines of profiles in the command area 38
Figure 8.1    A map showing groundwater potential areas 42
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1. INTRODUCTION
1.1       General
May 2007
Hydrogeoiogy refers to the occurrence, movement, chemistry (quality), etc of g o
in general. It nas a diversified application in developing, utilizing and m g g
groundwater Furthermore, different aspects of groundwater such as recharge d s g condition, aquifer type and set up, its interaction with surface water, etc are trea e
this discipline. The nature of groundwater and how it behaves, when subjected to nature man-made activities is studied for different purposes sucn as for water supply (domestic, agriculture and industry) and construction of surface and sub surface engineenng structures (e g., dam, tunnels, drainages, etc). In order to develop and manage groundwater, one has to know its potential, quality and movement.
Ethiopia nas diversified hydrogeological features tnat are attributed to its geology, structure, hydrometeorology, topography, etc The hydrogeology of the country has not been studied thorougnly so far With the exception of few areas such as Rift valley that has Deen mapped at scale of 1.250.000, the country has only small scale (1.2,000,000) hydrogeological map Hydrogeoiogy is usually applied for locating borehole sites in light of water supply Groundwater has Deen used without detail understanding of the resource In spite of ample groundwater resources of the country very little been studied and used so far Currently, however not only groundwater development and/or utilization but also its management is getting an attention.
Since any  development relies  generally  on proper utilization of natural resources, the government nas also given focus on water resource development both for domestic water supply and irrigation. As part of this water resource development, Integrated Master Plan Study of various River basins nas been undertaken in the country since some years The Abay River basin is one of them. Arjo-Dedessa irrigation project has been identified as one of the projects during the Aoay River Basin Master Plan study
Hydrogeological investigation and study that mainly focuses on g roundwater occurrence, movement, chemistry, etc nas been included as one of the components of the feasibility study and des.gn of the project. Accordingly, this study at Feasibility Study level has been undertaken.
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1.2       Location
May 2007
The project area is located within Dedessa River sub-basin which is in turn located
River basin. It is within the Western Oromia National Regional State, particua y 
junction of East Wollega, llubabor and Jima zones. The sub basin of the imgat o p j bordered by O mo-Gibe River basin on eastern side and Baro Akobo River basin on SW side. The total area of the catchment at the proposed dam is about 5,63
project location is shown in Fig. 1.1.
The project area can be reached from Addis Ababa through two alternative high ways take either to Bedele or Nekemt. The all- weather gravel road that takes from Nekemt to Bedele passes through the project area. Hence, in general the project area is about 480km from Aadis Aoaba through Jima and Bedele
2Fig. 1-1 Location map of Arjo-Dadessa Irrigation project
¥          P’cpmad w
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1
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Hydrogeological investigations
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1.3Physiography
The basin drams a part of Jim. high lands Including Goma (Agaro). Setema. Sig.mo, .
Sana, and pad of llubabo, Indudlng Boreeha. Dedessa. Gachl and Bedelle Woredas above the proposed dam. Arp. Nunu Kumba. Sibu Sire and Wama Bonaya woredas are also
within the catchment. The command area is drained by river Dedessa and othe
such as Wama River. The general slope of the basm/or catchment is toward NE, E and directions The area has generally a rugged topography with the highest
elevation is about 2890 a nd 1 030 m amsl respectively located at S igimo-Gera area and Dedessa river valley The river basin has mainly a dendritic drainage pattern 3
Dedessa river catchment is shown in Fig 1 2.
1.4 Methodology and approaches
In  order  to  undertake  the  hydrogeolgoicai  investigation  of  Arjo-Dedessa  irrigation  project area, the following methodology and approaches have been used:
•    Reviewing of the previous works and data available with different institutions such as MoWR, institute of Geological Survey. Regional Water Resources Bureau and
Offices, Regional Water Works Construction Enterprises.
•    Field survey to collect primary information on geology, hydrogeology,
geomorphology, ana other physical features of the area.
•     Preparations  of  inventory  for  water  supply  schemes  and  fixing  their  location  with GPS  measurement  of  water  level  for  wells;  estimation  of  discharge  for  springs, water sampling from springs, wells and streams/rivers for physicochemical analysis.
•     Interpretation  of  aerial  photos,  satellite  images  and  Topo  maps  (1:50.000  &  1: 250,000);  applications  of  various  GlS  and  remote  sensing  software  to  identify  and delineate lithology and geological structures, and finally to analyze, ano compile the spatial data, and to incorporate them as maps for various themes.
•    in-situ measurement of pnysical parameters of water quality indicators by using field water quality test kits (Ph, EC. TDS and Temperature meterj.
.  Finally,  preparations  of  hydrogeolog  al  maps  with  different
IC
thematic  layers  such  as 
hyarogeoiogic  units,  depth  to  groundwater  table,  water  quality,  groundwater  yeld based on all the collected and analyzed data.
4Fig. 1-2 A map showing 3-D view of Dedessa river catchmentArjo Dedessa Irrigation Project
Hydrogeological investigations
2. PHYSICAL HYDROGEOLOGY
2.1 Hydrogeological setup
May 2007
The t»s,n comprises rofcan.c lava flows ma.niy Basalts and igmmBrte as well as pyroclastic Ians on j,ma side, where as nn llobabor and Wollega sides, me outcrop is manly basalfc 
lava flows except within the Dedessa River Valley, where the outcrop is crysta
basement of venous granHes. gneisses and pegmafte The voidable rocks on Jim. Side are referred  fo  as  Lower  pan  of  Jim.  volcnlc.  composing  flood  Basalt  with  minor  salics  on the western, southwestern, eastern and southeastern part of the river catchment, e p y
on the nigh land. However, at the lowtand pad of the catchment along the Dedessa River, the outcrop is referred to as Alghe group comprising biotite and horn blende gneisses. granulite and migmatite with minor Meta-sedimentary gneisses
The  voicamcs  are  of  Late  Eocene-  Late  Oligocene  age.  where  as  the  gneisses  are  of Arcnean  age.  The  volcanic  rocks  (basaltic  lava  flow)  in  Bedele  area  is  referred  to  as Makonnen oasalt comprising flood basalts It directly overlies the crystalline casement that shows  the  unconformable  relation  for  the  two  outcrops.  It  is  Oligocene-Miocene  age Similarly, Arjo area is comprised by such flood oasalts of the so-called Makonnen basalt.
Based  on  tne  investigations  made  in  the  area,  various  aquifer  set  up  exist.  The  main aquifers are weatnered and /or fractured basaltic lava flows and other acidic volcanic rocks such  as  rhyolite  and  ignimbrite  The  aquifers  of  volcanic  origin  have  both  confined  and jnconfinea cnaracter; for example the volcanic rocks in Agaro area show both characters. The confining layer in this particular area is highly weathered volcanic ash of clay size as revealed from existing well drilling data. There are aquifers that are attributed to sediments especially alluvial sediments along river valley and streams, and colluvial sediments near mountains and escarpment. In addition to these, there are also minor aquifers attributed to weathered Dasement rocks (granites and granitic pegmatatites). This last aquifer types nave little significance in the area aue to their limited areal extent and limited aqu.fer productivity The presence of therma! springs, cold groundwater and saline springs in the area shows the diversification of the hydrogeologicai set up of the nver catchment. The aquifers of sediment and weatherea basement rocks origin are un confined. In addition to the lithological
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diversification, geological structures dynamics and quality of the area
Ma) 3DCT
™„,y tou-B
s,n. .can, roH on
(
Within Dedessa River valley, deep penetration of groundwater may be hindered y 
underlying massive basement crystalline rocks except where they 
geological structures as revealed by the presence of thermal springs in the
The . olcamc esn a nd day < o-m , he c onf.n.ng I aye- to- w ale- oea-.ng I onnalton , aqude- Aquifer in Agaro area can be mentioned as an example The volcanic lava flows ar high y weathered (fractured) enhancing the infiltration of precipitation (mawMy a
groundwater recharge Groundwater recharge in the area is very maximal due to d
reasons, among them are the high precipitation dense vegetation cover, and highly weathered and/or fractured volcanic lava flows
The mam groundwater recharge of the area istheSE. SW and the NE par of the nver catchment The pyroclastic falls of mainly volcanic ash composition is found at most parts of the river catchment such as in Setema and Atnago area The intercalations of the volcanic ash with fractured and/or weathered volcanic  lava flows  cause the emergency  of many springs in the river catchment of the area
However, the presences of thermal springs with in the Dedessa river valley are attributed mainly to geological structures, faults The physicochemical charactenstics of the therma' springs higniy vary from upstream to down stream along Dedessa River within the protect area Althougn it needs  further investigation to verify  the physico-chemical variation, the longer residence time of rock-water interaction while groundwater flows from upstream to down stream could be one possible reason
The topography of the area along with the prevailing hydro-meteorological conditions favors the existence of well demarcated groundwater recharge and discharge area
2.2 Hydrogeologic units
Groundwater occurrence, movement and quality  are mainly  governed by  the existing hydrogeologic  units  The phrase hydrogeolog.c  unit refers  to the rocks  (consobdated <x unconsolidated; form.ng the frame work for groundwater occurrence, movement and qua|,t>
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The hydrogeologic units in Dedessa nver catchment have Deen categorized following units. They have Deen shown on map available at Fig 2.1 discussed nere under in brief.
2.2 .1 Fractured and/or weathered volcanic rocks
May 2007
2
This comprises basaltic lava Hows, acidic lava flows and falls such as ignmbrites and
pyroclastic falls In this category of hydrogeologic unit, secondary porosities 
fractures produceo due to weathering and geological structures play immeasurab e
compared to the primary porosity/permeability The areal coverage of this hydrogeo g
unit in Dedessa river catchment is 8,189.35 Km  (79 56%).
2.2.2  Alluvial sediments
As t ne n ame implies i hese are c oncentrated a long r ivers a nd s treams. a nd it c omprises various  sediments  ranging in size from clay  through sand and gravel to ooulders  The areal coverage of this hydrogeologic unit in Dedessa river catchment is 1651 05 Km (16. 04%).
2.2.3  Delluvial sediments
These sediments  exist at t ne t ransition zone from the mountains/or plateaus  to the river valley  They  are derived from down slope moving earth materials  from mountains  mainly due to gravitational force. From hydrogeological point of view, there are no as  such demarcated properties  between alluvial sediments  and delluvials. However, for the convenience of description, this  hydrogeologic  unit has  been described separately  Delluvial sediments with in the project area have coverage of 452.91 Km (4 40 %).
2.3 inventory and well data
in order to undertake detailed investigation of the groundwater of the area, water supply schemes nave been inventoned and their geographical locations have been identified using GPS Borehole data have Deen collected for detailed analysis of hydrodynamic parameters though complete well data are not available in the area. Some of the measurements that have been undertaken for water supply sources during the field survey are phys.cal parameters ot water quality by using fieid test kits such as TDS. PH and temperature meter
2
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In addition to these pnmary data, secondary data have also been collected
,Q
quality a nd other Well d ata. S atellite images a nd a erial p hotos h ave b ee
identify geological structures and other lithological boundary demarcation that
verified by field work.
2.4 Hydrodynamic parameters of aquifers
As  it nas  Deen mentioned previously, the main aquifers  in Arjo-Dedessa project area are fractured and/or weathered volcanic  lava flows  (basaltic  and acidic  lava flows) and sediments  (alluvial and colluvial).The boreholes  in the fractured volcanic  rocks  and sediments  are either with partial well data or totally  without well data Table 2 1 shows  the borenoles drilled previously in the study area and their depths.
Taoie 2. i            Details ot boreholes in the study area
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9Fig- 2-1 A map showing hydrogeologic units of Arjo-Dedess* rtver
o
WELEGA
T7"; If ★ A\a
Jima Arjo
ILLU-ABA-BORRA
JJMMA
icuxxi
1WOL
AXKli
◄
c
“— 1Arjo Dedessa Irrigation Project
Hydrogeological investigations
3. GROUNDWATER POTENTIAL 3.1 Groundwater recharge estimation
May 2007
in  order  de.eiop  groundwater  of  an  area,  ds  potenua!  Induding  its  annual  replenishment, which is usually referred to as groundwater recharge, has to be known. Grpu
recharge  of  an  area  can  be  estimated  based  on  different  approaches.  One  of  the  best approaches   ,s   through    water    balance    method    In    order   to   employ   this   method   ol groundwater potential estimation, the necessary data have been acquired for a y suppementary   io   th.s   method,   base   flow   analysis   tor   Rwenslream   flow   (Dedessa   River) nave   been   jndertaKen   to   derive   some   coefficients   for   water   balance.   Hence,   in   the groundwater   potential   estimation   of   Dedessa   River   catchment   both   methods   have   been employed in order to come up with concrete result as much as possible
3.1.1  Base flow analysis
In order to employ  Dase flow analysis  approach for groundwater recharge estimation, the monthly  discharge of Dedessa River from 1961 —  2002 for a total of 15 years  have been used. The river flow aata is  not consecutive due to some missing data for some years. Accordingly  the mean monthly  minimum flow of Arjo-Dedessa on annual base is  shown in Table 3.1.
The difference between the total flow and the Minimum monthly  flow is  supposed to be the surface runoff. Accordingly, the surface runoff for Deoessa river catchment at the gauged station is  2,105,796,874 m3 Where as  the total minimum monthly  flow of the river is 1,962,092,938 m as  shown in the Table 3.1 The basic  assumption in deriving groundwater recharge from Dase flow analysis  is  that the monthly  minimum stream discharge is  equal to the case flow This  approacn has  been mentioned by  Wundt (1978) that the monthly minimum stream discharge best approximates the base flow, especially for humid climate
Therefore t ne b ase f low t hat i s supposed t o c orrespond t o t ne groundwater recnarge i s round to De 196.6mm. This  value is  obtained by  dividing 1,962,092,938m3 by  the area of the gaugea catchments, which is 9,981 km . This amount of ground water recharge is very
2
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minimal  as  it  amounts  to  only  aoout  13.53%  of  the  total  annual  precipitat which is 1452.9mm.
May 2007
Furthermore.  Oeser,  on  the  same  method,  the  surface  rundff  of  the  Rrver  catchment  has been estimated as the difference Deiween the total river flow of Dedessa and I
flow on annua, base and works out to 2.105.796.874 m’ that is attributed to surface runo
This  value IS used to denve the run off coefficient of (he river catchment to asses  the surfacerun offfor the e ntire D edessa c  atchmenl t hat will be used in the waterbalance approach of the groundwater recharge estimation in the next section.
Table 3.1 Monthly total flow ana Minimum flow of Dedessa river near Arjo
Parameters               _ ______________________-
Qtot
Qantn
Months
IVp/se
c
M3/month            M'/sec             M /month            M/se c
Difference
M/montn
L-
J                1764              47238048                    4 473                11980483           13 16                 35257565
,j
1■ F
--------------,
124              29994209
2.25                 544320C           10 15                 24551009
M                   10 44             27973924                    0 966                  2587334            9 48                 25386589
A
■5 54
40527302
4 557
11811744
11.08
28715558
M
29 14
78052326
10 364
27758938
18 78
50293388
J
98 47
255236832
45.433
117762336
53 04
137474496
J
263 37
705408958
137.365
367918416
126
337490542
A
423 39
1134009026
220.652
590994317
202 74
543014709
S             343 82           891191981                217 777              564477984        126.05               326713997
0             218.67           585697513                  58.377              156356957          160.3
429340556
N               68.32           177074554                  26 258                68060736          42 06
109013818
D
3565
95485139
13 792
36940493
21 86
58544646
Qtot
3
(m )
4,067,889,811
1.962,092,938
2.105,796,874
Q,o(=  total  monthly  discharge  (mJ).  Min  Q  =  Minimum  monthly  discharge  (M’/S)  Diff.  =  difference  between the total monthly discharge
3.1.2 Water balance method
By water Balance it is meant equating or balancing the amount of water inflowing and out
flowing for a given system, such as hydrogeolog.c system, over a given duration for a g.ven
area Hence it ts a d ynamic system, ( Detay 1997). The hydrogeolog.c s ystem can be a
dramage basin/or catchment, groundwater basin, soil layer, or any surface water reservo.r
(natural or artificial).
Water oaiance is a valuao.e tool in the analysis of water availability i---------------
in  a  region.  The  method
can be employed for different purposes, computation of groundwater
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12Arjo Dedessa Irrigation Project
Hydrogeological investigations
transpiration, continuous record of soil moisture, and stream flow from a
May 2007
recoro and a few observations on the soil and vegetation, seasonal and geograp P
of .rogation oemand. the flux ot water to takes, prediction ot human e dec. o n h ydroiogrc 
cycle, 'Leopold and Dunne. 1978).
in this  study  the water balance method is aimed at estimation ot groundwater recharge T e basic  assumption that is  considered in this  case is  mat the surface water divide coincides with me subsurface drainage basin Accordingly, otner than the water that is  percolated within the limit ot the surface water divide, there ,s no Inter-aquifer flow (inflow or out flow) of groundwater
The basic equation of water balance is.
inflow = outflow *AS
Where AS is cnange in storage
For the study  area, the main inflow component is  precipitation, out the outflow components are evapotranspiration and surface runoff assuming all other components  such as  water abstraction oy  human for other purposes  to be negligible. Besides  this, the change in storage, can be considered to oe zero if the water balance is made Dy taking water year /or nydrologic  year Hence, the value of AS will be negligible/or zero since the calculation is  to be made or annual basis
Since rainfall record can be obtained from meteorological stations in the area, the main task left is  to estimate /or calculate the potential evapo-transpiration from which the Actual Evapotranspiration (AET) can be derived for the catcnment. In addition to this, the surface runoff has  also to De estimated/or calculated since there is  no actual measurement of this component in the study area.
The  surface  runoff  for  Ago-  Dedessa  river  catcnment  has  Deen  derived  (estimated)  as follows
The monthly  minimum stream flow has  been considered as  a base flow as  mentioned previously  and this  value has  been subtracted from the monthly  total runoff to get the component that forms over iand flow from which the runoff coefficient. Rc, ,s caiculateo
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Rc = D/PA
Where
Rc= Runoff coefficient
D = overland flow = 2,105,796,874 m
P = annual precipitation =1452.9 mm = 1 452m
May 2007
2
A = drainage area = 9.981.000.000 m  (dramage area at the over gauging
station But this does not mean that the total drainage area of the stud
Hence. Rc = 2.105,796.874 m3/1 4529 m x 9.981,000.000 m2 = 0.1453
This Runoff coefficient is used to estimate the surface runoff for the river basin (Dedessa
River) under study
In order to estimate the surface runoff of Dedessa area, the mean annual prec.p.tation
1452 9mm has been used
Hence, the sunace runoff for the entire Dedessa River catcnment becomes  0 1452 X
1  452m  X  10.293.303.358  08  m2   =  2,170.141.264.31  m3   Thus  the  surface  runoff  works out  to  210.83mm  This  value  is  only  aoout  14.51%  of  the  total  annual  precipitation,  in  the area  Note  that  the  total  area  of  the  studied  nver  catchment  at  the  out  let  of  the  command area is 10.293.303.358.08 m2
By  assuming, the coincidence of groundwater oasin with that of surface water divide and also by  assuming that there is  no artificial or natural intra-basin suDsurface or surface flow, the groundwater recharge of Dedessa river catcnment can oe estimated as follows
GWr = P - (Sr * AET)
Where GWr = Groundwater recnarge
P = Annual precipitations 1452.9mm
AET = Actual Evapo-transpiration
Sr = Surface runoff = 210.83mm
The  Actual  Evapotranspiration.  (AET)  can  be  estimated  based  on  different  methods  one  of them is tne empirical Tore method Turc method is represented by the following formula:
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2
AET = P/v[0 9 * (p/L) ]
Where P = annual mean precipitation in mm = 1452.9mm
T = annual mean air temperature in °C = 20
L = 300 * 25T * 0 05T3 [mm] = 1200mm
Hence, for Dedessa river catchment, AET = 944.57mm
Therefore, in order to estimate groundwater recharge for Dedessa River catchment, the value (AET = 944 57mm) obtained by Turc method is used in the water balance method of groundwater recharge estimation.
Hence  groundwater  recnarge  in  the  Dedessa  river  catchment  oecomes  as  follows GWr = P  (Sr * AET) = 1452.9mm - (944 57* 210 83) mm = 297.5mm
This  value is  about 20.48% of the total annual precipitation in the area. This  high recnarge rate may  be attributed possibly  to the relatively  better vegetation cover and to the highly fractured rock prevailing in the area
Finally  an average value from the two methods, the base flow analysis  method (196.6mm) and the water balance metnod (297.5mm), which is  247.05 mm, has  to be used as  annual groundwater recharge of the area. This value is about 17% of the total annual precipitation
in the area
15Arjo Dedessa Irrigation Project
Hydrogeological investigations
4. WATER QUALITY
4.1 Water samples
May 2007
Natural  water  interacts  with  environment,  and  also  it  is  affected  by  anthropogenic  p  o changing   its   chemical,   physical   and   biological   constituents.   The   utilization   of   this   water requires   an   understanding   of   such   constituents.   Hence,   the   water   should   meet   certain quality  standard  that  is  set  mainly  based  on  its  purpose  in  order  to  use  it.  Some  important physical  ano  chemical  parameters  have  been  determined  for  the  water  of  the  study  area  to compare  its  quality  with  certain  standards  set  by  different  Organization  such  as  WHO  for specific water uses
Water samples  from different sources  nave been taken for physicochemical and microbiological analysis  cased on the actual/existmg geology  hydrogeology  and geomoronology  of the area. Accordingly, a total of thirteen samples  have been taken from springs  and Wells. Fig 4 1 snows  the location of the water sample points. All the samples have been submitted to the laboratory  of WWDSE for analysis. In addition to these water samples  collected during the field work, previously  analyzed water quality  oy  different institutions nave been jsed for hydrogeological interpretation of the area.
Among the collected water samples, four samples  were taken from spnngs  and nine were trom ooreholes  The numbers  of samples  have Deen aetermined based on various conditions  such as  geological ana hydrogeological setup of the area and availability  of previously analyzed pnysico-chemical and microbiological data in the area
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16Fig 4.1 A map showing water sample points in Arjo
- Dedessa project area
400000Arjo-Dedessa Irrigation Project
Hydrogeological Investigations
4.2 Sampling techniques and analysis
A total of thirteen samples have been collected from i eren
May 2007
cniirces One duplicate
(t
sample ,s coUecled from spring in order <0 see the reproduce of the iaborb.ory
Natura, waler ,s samp.ed .n wew o< carrying out various anaiyses on ,t in order to undertake water quality analysis water samples have been collected tor physicochemica y collected water samp.es were from ground wa.er (spnngs and Welts) sources. The samples nave been taken with one liter capacity plastic Dotties. In order to compare
physicochemical parameters, some physical parameters such as 
(
Solids),  Temperature  and  PH  have  been  measured  at  field  in  order  to  compare with that of Laboratory
4.3 Pictorial representations of water quality analysis
4.3.1   Piper diagram
Dissolved
the result
The  Piper   diagram  plots  the  major  ions  as  percentages  of  milli-equivalents  in  two  base triangles The Piper trilinear diagram for water samples in Arjo- Dedessa is available at Fig
4.2  The  total  cations  and  the  total  anions  are  set  equal  to  100%  and  the  data  points  in  the two  triangles  are  projected  onto  an  adjacent  grid.  This  plot  reveals  useful  properties  and relationships  for  large  sample  groups  The  main  purpose  of  the  Piper  diagram  is  to  show clustering of data points to indicate samples that have similar compositions
The Piper diagram can be used to plot all samples  in the open database or selected sample groups  In addition, the symbols  representing the sample values  can be customized according to shape and color Other options  include individual multiplication factors  for each selected ion to prevent data point accumulation along a base line The highlighted sample points  indicate samples  that are selected in the database and are also highlighted on all other open grapmcal displays. According to the water samples  plotted in Piper trilinear diagram lor Arjo-Deoessa area, samples  can be categonzed based on their clastering as Ad-01. AD-10. AD-12 and AD-13 as  one category. AD-02. AD-03. AD-04. AD-05 AD-09 and AD-11 as  second category; AD-07 and AD-08 as  third category  and finally  AD-08 as loodh category  However. If we refine further the water type based on the chem.cat composition, they can be categonzed in to five categones.
i . 
.ss.et.tl.. fcrcd..^ C„„1U11B ud T
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18Arjo Dedessa Irrigation Project
Hydrogeological investigations
• Na-HCO3 type (Sample AD-01. AD-07, AD-08, AD-10. AD-12 and A
•    Ca- HCO3 type (Samples AD- 02 and AD- 11 >
•    Ca- Mg- HCO3 type (AD-03 AD- 06 and AD- 09)
•    Ca- Mg- Na- HCO3 type (Sample AD- 04)
•    Ca- Na- HCO3 type (Sample AD-06)
May 2007
The cation to amon ratio atso vanes for the different samples md.cat.ng various conditions of rock-water interaction.
4.3.2  Schoeller diagrams
These   semi-logarithmic   diagrams   were   developed   to   represent   major   ion   analyses   q ana io aemonstrate different hyarochemical water types on the same diagram. This type of graphical representation nas the advantage that unlike the trilinear diagrams, actual sample concentrations  are  displayed  and  compared  The  Scnoeller  diagram  in  AquaChem  can  be
used  to  plot  all  samples  in  the  open  database  or  selected  sample  groups  only.  Up  to  10
different parameters  can De included along the x-axis  and the symbols  representing the sample points  can De customized according to snape and color The highlighted lines indicate sDecific  samples  that are selected in the database and are also highlighted on all other open graphical displays. The Schoeller diagram for the water samples  of Arjo- Dedessa area is  available in Fig. 4-3. Water of similar source (type) shows  a similarly shaped curve; where as  water of different types  snow differently  snaped curves Accordingly  two major types  of water can De identified from the graph. Calcium bicarbonate types  (Samples  AD-02, AD- 03, AD- 04. AD- 05. AD- 06. AD- 09 and AD- 11) and the sodium bicarbonate types (Samples AD- 01. AD- 07, Ad- 08. AD- 10, AD- 11 and AD- 13).
4.3 3 Stiff diagram
The Stiff diagram method of water quality  representation uses  a scale for concentration of ions  in meq/L along the x-axis. The ions  are arranged along y-axis  in such a way  that the
cations (Na’ Ca ’. Mg *) are to the
22
left of the center of the plotting scale and the anions are
to the right of it. It >s shown for some of the analyzed samples in Fig 4 4. According to this figure  water  samples  of  the  project  area  can  be  categonzed  in  to  three  major  groups  Na HCO3   type   (samples   AD-01.   AD-07.   AD-08   AD-10.   AD-12   and   AD-13)   Ca-HCO3   type (samples AD-02. AD-03. AD-09 ano AO-ff); ano Ca- a-HCO3 .ype (samples aD-04 AD
N
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19ao                       80
00
eo
40
40
20
20
SO4
*
ueg&na:
O AD-01
□ AD-02
♦    AD-03
—       AD-04
X    AD-CS ♦    AD-06 o      AC-0" A      AD-Od V      AD-09
-r       AD-10
X   AD-71
♦ AD-12
AD-13
80 ..................'
30
♦AD-06
oo ........ ............
- 8C
<0 . ................. r................................. A
X
_________ •- £
x
S7 , . ,
80             80              40             20
20
Na-KHCO3
Cl
Fig. 4-2 A map showing Piper trilinear diagram for water samples in Arjo- Dedessa
CaI
Concentration (meq/l)
Legend
—•—          AD-01
-  4i — AD-02
.. -e ...        AD-03
------ ----      AC-34
—X—          AD-05
---- •----- AD-06
-  -e — AD-07
- -A • AC-06
-   e - AD-09
-   ■-
AD-10
■
AD-11
— AD-12
Mg
Ca
Na-K
Cl
SO4
HC03
Fig. 4-3 A map snowing Scnoeller diagram for water samples in Arjo-Dedessa areaNa —k
Ca -
Mg Ti
K
Cl
HC03 SO4 CO3
50
50
3 AD-07 3
10           5 AD- C2 '
10
Cl MCO3
SO
C03
Na
Ca
Mg
K
I
£
c:
HCC3 SO4 CO3
5
5
15 AD-03 ~
Na
Ca
Mg
K
Cl
rlC03
S04
C03
Na
Ca
Mg
K
5
’ AD- 05 ’
Fig. 4-4 A map shwing Stiff diagram tor water samp.es ,n Arjo- Deoessa Project area (Concent meq/L,Cl
Na
Ha
t
x
i
HCO3
Ca
>
HCO3
Ca
X
X
S04
Mg
ir
S04
Mg
T
C03
K
□03
K
—
5
5
10
15
X
iO
X
AD- 09
” AD- 08
•
• AO-12
I
iArjo Dedessa Irrigation Project
Hydrogeological investigations
4.4 Agriculturai/irrigation water quality
May 2007
Agricultural suitability of water depends on crop type, climate, soil type, and amount o irrigation water use. (Davis 1966) The mam parameters to be analyzed to evaluate
irrigation water quality are Boron. Sodium h azard. and Salinity These paramete
plants either directly (e.g by causing an adverse physiological effects) or indirectly (eg y 
limiting plant root nutrient or moisture uptake). Salinity is best estimated based on Elect ica Conductivity (EC) value Other direct indicator of salinity is Total Dissolved Solids (TDS)
Tne two parameters. TDS & EC are related by the following equation
TDS (mg/L) = 640 x EC (dS/m). wnere mg/L = milligram per litre. dS/m = deci Siemens per
meter
According  to  U.S  Department  of  Agriculture,  water  with  an  EC  greater  than  4dS/m  is considered as saline
Sodium nazard is  assessed by  the so-called Sodium Adsorption Ratio (SAR). It is  caused by  sodic  water Sodic  water is  water that has  high sodium concentration relative to the concentration of calcium ana magnesium Water is said to De sodic if its SAR is greater than 12 SAR is calculated as follows
SAR= [Na*]N0.5[Ca * * Mg *]
Where the concentration of each cation is  expressed in meq/L. If the concentration is 
22
expressed in mmol/litre. SAR = [Na*]/
[Ca * ▼ Mg *]
22
According to Todd (1980 ana references there in), the water quality evaluation for irrigation basea on SAR ana EC are as shown in Table 4 1.
Taoie 4.1 SAR ana EC values in terms ot imgation water suitability
Water class
Excellent
Good
Fair
Poor
SAP
< 10 —
10- 18
18-26
>26
Water ciass
Excellent
Good
Permissible           Doubtful
<250
250- 750
Unsuitable
EC (ps/cm/
750- 2000             2000- 3000
lO&'rr = w ns/cm
——---------- ----------------------- —
----------------------- !
>3000 —1
order ,o evaluate waler quality for imqation from Salinity anq Sodium nazard pom. of ..r. tor Arjo-Deoessa area. th. parameters  have Peen measured and catenated and they  are shown in Table 4-2.
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Table 4.2 SAR and EC values for surface and groundwater in Arjo-Dedess^
May 2007
1
‘ad-a
AD-*1
.pie
aO-7
_____ ___ ____ — TrCTn . AadD--i'oI M
1 
<310
OU*
2560
2370
S*e
3160
_2_1_6 ,
38 4
0 7       04
05H
According to SAR values obtained for the water samples, AD-01. AD-07. AD-10.
AD-13 are all sodic water and AD-08 is slightly sodic, where as. the remaining wa
samples are all non sodic. From .mgation water qualrty point of view. they range from
excellent quality to poor quality
But from salinity point of view, the quality varies from excellent to unsuitable, i.e.. from 418 ps/cm to 4450 ps/cm. In other words, it can be sa.d the salinrty ranges from medium salinity to very h.gh salinity F.g 4.5 shows values of TDS and EC for different water samples in the project area
Figure 4-5 Electncal conductivity (EC) in ^s/cm and Total Dissolved Solids (TDS) in mg/L for water samples in Aqo-Dedessa area
This graph oeatty .nd.ea.es me extern of selmtty for aj(feren, water samp|es
or tot the EC ano me TDS Contour map of the TDS is eveilaote al Fig 4 6 tor the pro,ear area For oescnpt.on one the water sarnp.es may  he categonzed tmo three cetegones based on tner, Eieemc eonductwity and TDS vetoes. According,y. seven sempies (7D O2
..
24Arjo Dedessa Irrigation Project
Hydrogeological investigations
May 2007
AD-03 AD-04. AD-05 and AD-06) have low salinity, four samples (AD .
and AD-13; have high salinity . and two samples (AD-01 and AD-10) are extreme y
This qualitative description doesn't follow the standard procedure of
fr
classification based on TDS and/or EC. but it is simpty for the sake of descnpt.cn Wa samples codec as AD-01. AD-10. AD-12 and AD-13 are al! from springs; all other water samples are from Dorenoles (drilled shallow Wells). Hence, it is possible to co
even if they are all from groundwater, they are from different aquifers. The mo water (having high TDS values) are mainly from weathered basement rocks (granite and granitic pegmatite), and deep-seated volcanic aquifers especially along fault lines ( 9 thermal springs).
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25002
Fi 9 *4 4
map 5how>ng the contour for Total Dissolved Solids (TDS - mg/L) for Arjo - Dedessa Project area
Rivef/Stream
60F,ff 4-6 4 map showing tha contour for Total Dissolved Solids (TDS - mg/L) for Arjo-Dedessa Project area
o
60Arjo Dedessa Irrigation Project
Hydrogeological Investigations
5. PIEZOMETERS OBSERVATION WELLS AND WELL FILED
5.1 Distribution of Piezometers/Observation Wells
In order to monitor groundwater quality and quantity of the area both befo
construction of the dam under investigation, a total of fourteen Piezometers/O
wells have Deen proposed and their sues have Deen located. The geographic configuration/distribution of the piezometers/Observation wells is selected
geoiogy hydrogeology, topography groundwater flow direction, etc of the area
depth of the piezometers to be constructed rarely exceeds 100 meters, PVC cas g recommendable In some cases the existing well depth at the immediate down stream o the proposed oam axis are 50 - 70 meters depth.
Table 5 1 shows the geographical coordinates of the proposed piezometers Table 5.1 Locations of the Proposed Piezometers
May 2007
------------- I
Geographical coordinates (UTM)
“■I
Ser No Piezometer Easting Northing
code
Altitude (m)
Pad-1
241283     |                945079
1332
PZ
2                 P.o-2                     239578                       942443
1348
3                P.o-3                     239229                       948568
1354
4              P*d-4                      232368                       945622
1345
5                P.o-5 L.
237407                       951746
_______
6                 P*o-6
I —-----------------
1391
228492                       944575
1374
7                Pad-7
230198
952870
1386
8                Pad-8
225779
947133
1324
9                Pad-9
220119
954111
1341
to            Pad-10                  217677
951707
1319
11              Pad-1 1
217135
961437
1332
Pad-12
12
1354
13              Pad-1 3
212716
4------------- 214654
95244a
956087
1323
| 14               Pad-1
213336
961320
1320
The construction of these p.ezometers  shall follow the standard procedures  althougn some sHe-specific  condit.ons  such as  hydrogeoiog.cal set up will also matter The location of the proposed Piezometers is available on the map shown in Fig. 5-1
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27Arjo Dedessa Irrigation Project Hydrogeological investigations
rXXZ Io..o^ale. s.o.a e ,n .He a.ea a.e oasaH.c -a "
May 2007
g
sa.es 
rhyolite ano ^e. ano a,^a.
-a ,
This can De verified by existing boreholes data in the area
Agarc area snow this situation.
Well field sites on which detail geophysical investigation shall be undertaken have identified based on geological, hydrogeological and geomorphologicai setting approacnes Test wells drilling and construction shall follow the detail geophysical investigation
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285-1 a map showing proposed piezometers, water points and water sampling points
-,
70000 Merors
Sibu Sire
iuto Wayu
Wama Boneya
Ljmu SexaArjo Dedessa Irrigation Project
Hydrogeological investigations
6. WATER LOGGING AND DRAINAGE
6.1 Topographic features and soil characteristics
The undulating and rolling topography in upper part of the project area grad y gentle slope of flat land in the bottom valley of Dedessa. especially the lower part command area becomes almost flat. This flat land is covered with sediments colluvial/delluvial and alluvial origin. This sediment is underlain mainly by base
May 2007
y
The   topography   and   land   characteristics   of   the   command   area   can   be   said   to   a level   (0-   1%).   nearly   level   (1-   2%   slope),   very   gentle   (2-   4%   slope),   and   gentle   (4-   6   x slope),   categories   as   about   35%   of   the   command   area   falls   under   first   two   categories   and about   23%   of   the   command   area   falls   under   the   last   two   categories   Though   the   command area   is   plain,   it   nas   a   rolling   topograpny   and   there   are   several   small   hills   dispersed   in   the command   There   are   rising   hills   also   on   the   outer   boundanes   of   the   command   area   on   ootn banks of river Dedessa
The major part of the area is  comprised of vertisol (47% of the command area) that has  very low permeability  Next to vertisols  are cambisols  and luvisols  covering 15% ana 8.68% of the area respectively  Hence this  soil type hinders  the infiltration of the most incoming rainfall during rainy  season On one hand this  nelps  to restrain the rise of the groundwater table through reducing infiltration, on the other hand the plain nature of the land wouldn’t allow the surface run off tc flow out easily.
6.2 Existing groundwater table
Groundwater level in the project area vanes  from 2 to 20m b g I In the command area the groundwater table is  2 meters  below surface during rainy  season except in few exceptional cases  of surface water logging. During dry  season the groundwater table was  found deeper than 5 meters  below natural ground surface The nse of the groundwater table can happen due to different natural conditions  and man made activities. The application of irrigation practice is  the major human interferences  for rise of groundwater table The method of irrigatton (drip furrow, etc) that is  practiced and the crops  proposed to be grown will determine the extent to which it may affect the rise in groundwater level of the area
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May 2007
6.3 Future groundwater table and recharge from irrigation
Whenever there is a major irrigation project with continued and intensive irng
there . always an app.ehens.on of rise of groundwater table If (be nse of the grounowa er
lapie is significant, and it continues unabated, it may cause serious adverse p
fertility of the land. Some of the factors that affect the nse of groundwater a
•    Topographic features
•    Land characteristics
•    Natural drainage system
•    intensity and amount of rainfall
•    Existing grounowater taole
•    Soil cnaracteristics
•    Crops and its water requirement
•    Seepage ana other losses from canal system
•    Sunace drainage system implemented and its effectiveness
The   estimated   annual   crop   water   requirement   at   primary   canai   nead,   for   various 
crops 
to
be
cultivated   in   the   command   area   of   the   proposea   Arjo-   Deaessa   project   comprises 
four
set
of
values    categorized    under    two    pnases    each    phase    having    two    rotations.    This
has 
De
en
snown in TaDie 6.1
Taole 6.1 Annual gross crop water requirement at primary canal head
Ser No              Phase
Rotation
GCWR (mm)
1I
1
987 40
21
II
1086 14
3                       II
1
1311 47
4                       II
II
1423.234
In order to assess  groundwater recharge from irrigation water, the maximum value of the Gross  Crop Water Requirement (GCWRj in the second phase of second rotation that is 1423.234 mm/yr has  been used Therefore, the groundwater recharge from the application of irrigation nas oeen estimated under two main situations as follows
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31Arjo Dedessa Irrigation Project
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1 According to groundwater recharge estimation made in this report.
annual precipitation in the area, only 17% is going for recharging the g o
If the same scenario is considered, the annual groundwater recharge Trom the
application of irrigation in the command area becomes 241.95 mm. This 
crude estimation since various factors among which the irrigation method ca
the groundwater recharge
2    Along    with    other    crops,    cultivation    of    paddy    has    been    proposed    in    the    command area   Paddy   is   the   only   crop   that   requires   constant   standing   water   in   the   field   for   its growth    and    development.    Thus    paddy    cultivation    results    into    percolation    loss,    and only    that    quantity    of    water    which    is    lost    through    percolation    has    the    cnance    and tendency   of   reaching   groundwater   It   may   be   noted   that   about   330   mm   of   water   is estimated    to    be    lost    through    percolation,    and    only    this    quantity    of    water    has    the scope   of   reacning   groundwater   wnich   may   add   to   the   rise   of   the   groundwater   The intensity   of    paddy   is   only   30%   in    phase-    I,   which    will   increase   finally   to   45%   in pnase-    II.    Considenng    the    entire    command    on    average,    the    annual    contributions    of irrigation    water    tc    the    groundwater    would    be    99mm    in    tne    Phase-    I,    which    will increase to 148.5 mm under phase- II.
Regarding other crops, they  are all dry  imgated i.e., no standing water is  required The irngation water applied tc  the field in case of all other crops  except paddy  will be contained as  soil moisture within the root zone. Very  small amount of water which will be lost below the root zone, will reach the groundwater Other losses  will be in form of surface runoff wmcn will be taken care Dy  sunace drainage system. As  such the addition to groundwater
□ue   to   irrigation   of   all   other   crops   except   paddy   may   be   cons.dered   very   negligible   and therefore, may be neglected.
Seepage loss <o the groundwater from the cana.s (mam canals, secondary cana.s and canals) has also oeen esl.ma.ed According United Sfa>es Bureau of Reclamation
(U S B R.,. seepage loss from unlined .mgarion cana. is 15 m’lsec per one million souare meter or wedeo area lot da, and da, .earn soiis. Based on this approaches, seepage loss from Arjo-Dedessa irngation canal is shown in Table 6.2 and 6 3
32Arjo Dedessa Irrigation Project
Hydrogeological investigations
Table 6.2 Estimation of wetted area for Arjo- Dedessa irrigation canal
Average
May 2007
I
Ser.
No
Canai
category
wetted
perimeter
(m /m)
Total length (m)
Area (m )
2
Total
Area
(m )
2
Rignt      L.eft
------------ i
Rignt
Lett
Rignt
------------ ~i
Len
2
I
1         Main canal   ------------
87115   10 211
4-- ——
—
740.512.00
42.800 00
----- i
60 180 00        279.639.00      "460 873.00
131.896.05
2         Secondary canal
3        Tertiary canal
Total
2 795      2.795        49.370.00         47.190 00        137,989.00
___
—
1.02        1.02
199,464 00       239.100.00        203.453.00
—
--------------------'
243.882 00
269.885.05
447.335.00
1,457,732.05
621.081.00         836,651.05
I
Table 6.3 Seepage loss from unlined Arjo- Dedessa irrigation canal
NO
Command area
(wing)
-------------------------------------------------------------------------
Wetted area of Canai (m2)
Main canal            Secondary          Tertiary
canal                   canal
1
Total         wetted area (m )
2
Total
seepage loss (mm)
r
Right Bank
279.639 00         137 989 00           203,453.00 L—
621,081.00
' 2       Lett Bank
460 873.00         131,896 05           243,882 00
836,651 05
3
Total area (m‘)
I
740,512.00
269,885.05               447.335.00
1 457,732.05
hr
3
ToUl Seepage (m )
23,320,796.31      6,400,809.75    10,609,354.73
40,330,960.80
226.26
In the seepage loss  calculation from the Main canal, only  75%, of the total area has  been considered The duration of the seepage loss  is  considered to be eight months  (October - May) ano twenty  four hours  a day  for the main canal; where as  for six  months  of twenty  four hours  for secondary  and tertiary  canal. The command area on which the seepage loss  has Deen averaged out is  tne gross  command area, i.e., 17,825 hectares  (178 250. 000 m 2) i.e.. the total seepage loss  of 40,330,960.80 m3 is  spread in the gross  command area which gave an average seepage loss of 226.26mm from the irrigation canal
Water Works Design & Supervision Enterprise
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Therefore, the total annual groundwater recharge from the application of imgatio
the sum of the seepage loss from the canals (226.26 mm) and from the paddy ir g (148 5 mm) that is 374.76 mm.
Although detail aquifer and soil sampling and analysis is required to come up
result of the porosity, its value has been estimated to be 35% in the command considering a range from clay to sand soils This parameter will De used to
groundwater level nse due to the application of irrigation.
Finally, by knowing the grounowater recharge from the application of irrigation, and the porosity of the aquifer and the soil matenals above it, the extent of the groundwater level rise due to the application of irrigation has been estimated under different scenarios as follows
Scenario I: No groundwater flows out of the catchment (stagnant condition) Annual grounawater recharge trom application of imgation, GR = 241.95mm Effective porosity of aquifer (sand) in command area, n  = 0.35 (35%)
May 2007
e
Groundwater level nse due to application of imgation. GWLr = GR/n =241 95mm/0.35 = 0.691 m.
e
However it snouia be notea that groundwater is always in a dynamic condition; hence, the stagnant groundwater condition never prevails in the area. Therefore, the stated value of groundwater level rise (0.691m) will never nappen.
Scenario II: Groundwater flows out of the catchment (dynamic system) Annual grounawater recharge trom application of imgation, GR = 241.95mm Effective porosity of aquifer (sand) in command area. n = 0.35 (35%>
e
According   to   base   flow   separation   method,   the   ratio   of   groundwater   outflow   from   the   entire nver   catchment   to   the   groundwater   recharge   of   the   catchment   from   precipitation   is   79   58% Hence,    the    remaining    20.42%    of    the    groundwater    recharge    contributes    to    grounawater    levL nse.   Similarly,   if   we   apply   such   dynamicity   to   the   grounawater   recharge   from   irrigation   water application, the groundwater outflow from the .mgat.on application becomes 192.54 mm
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Hence, if we reduce this amount from the recharge due to the applies mentioned above (241 95mm). the net recharge that contributes to the grou nse becomes only 49 4mm Therefore, under this scenario the groundwater le the application of irrigation will be
May 2007
_
z * Groundwater I evel r ise due to application of i rrigation.
0.141m.
r = G R/ru = 49 4 mm/0 35 -
Scenano III According to the paddy cultivation and seepage loss from canals, the annua
groundwater recnarge from the application of
irrigation is 3 4 76 mm as mentioned
7
if this is the case, the groundwater level nse due to the application of irrigation under stagnant groundwater condition becomes
Groundwater level rise due to application of irngation. GWLr = GR/n =374 74 mm/0.35 -
e
1070 74mm= 1.07m.
Scenario IV: (Scenario III under dynamic condition): This  Scenario assumes  that groundwater is  continuously  flowing out of the catcnment. Hence, only  20 42% (76 53 mm) of the groundwater recnarge from irngation water will contribute to tne groundwater level nse Therefore, the groundwater level rise under this Scenario becomes, GWLr = GR/n =
t
76 53 mm/0 35 = 218.66mm = 0.219m.
In conclusion, the assumption of stagnant groundwater condition Scenarios  (scenario I ana III), over estimates  the groundwater level rise due to the application of irngation Because it assumes  static)or stagnant groundwater condition that is  not the case in reality  since groundwater is  usually  in a dynamic  condition The second Scenario (Scenano II) relies  on groundwater recharge estimation from irngation water application equals  that from precipitation However groundwater recharge from irngation water application, particularly from paddy  irngation and canal loss  should be higher than from precipitation Hence, this scenano underestimates  the groundwater recharge. Therefore, according to this mvest.gat.on, the Scenano that works  best is  Scenario IV. Hence, the annual groundwater level nse due to the application of irngation water will be 0.219 m
However,  it  has  to  be  noted  that  the  existing  soil  in  the 10am soils as reveaiea from soil survey (sampling and
command    area    is    mainly    clay    and analysis) under the same project
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35Arjo-Dedessa Irrigation Project
The soil has an average hydraulic conductivity of 0 0000056 m/s, i.e. 0.482 m/day value is very small inhibiting the infiltration of any water (precipitation or irrigation) to Groundwater Hence, the contribution of groundwater recharge from the application
imgation should be less than the amount stated here. Therefore, the groundwater level rise
Que to the application of imgation cannot exceed 0.219m/year
Another factor that can reduce the contribution of irrigation application to groundwater recnarge is  the presence ot number of creexs  that are transversal to the trend of the command area and Dedessa River. Some infiltrated water from the imgation application will come out as regeneration through the creeks before reaching the groundwater table. Profile across some creeks and Dedessa nver in the command area is available in Fig 6.1 (a, b c, d and e). The lines along which the profiles nave been taken are also shown in the map Fig. 6.2.
Although there is no well documented well completion aata in the command area, the depth to groundwater in the area is beiow 5 meters during dry seasons except in some creeks such as Chuli area (eastern pan of command area) wnere the water table is about 2 meters beiow ground surface. Only few boreholes and their data exist in the Dedessa River valley of project area since it is  inhabited mainly  through resettlements  only  2- 4 years  ago hence, construction ot contour map depicting depth to groundwater is hardly possible under such data limitation since tney are entirely constructed for emergency purposes.
36From Pot: 232335.077, 944187 179
lo Pot; 213587.927. 956965.006
fig 6!
t)Wkfa<r*r^tofiwnstrMm "MM ^DMnnMr
1300 m
1370 m
1360 m
1350 m
1340 m
1330 m
1320 m
1310 m
1300 m
—
2.5 km                    5.0 km                     7.5 km
■W
10.0 km                     12.5 km
15.0 km                      17.5 km
20 0 km
22 72 kmFtorn Po» 219184 091, 943954 006
lo Pos: 226412.470, 954446.014IFrom Poo 210709.844, 952208 348
HOU m
To Pos: 210531.205, 957198.261
t) Mb khk$ Mb$9 river ivm W M to rigti M
1375 m
1350 m
*> . * . » •
—
2.0 km
3.0 km
4 fl km
5.0 km                       6.0 km
7.0 km
0 0 km
9.2? km10000
0
10000 MatarsArjo Dedessa Irrigation Project Hydrogeological investigations
May 2007
7.
SALINITY AND SODICITY
Sal
inity
of   soils/water   can   be   defined
in   terms 
of
elec
tncal   conductivity.
Particularly 
it
is 
the   electrical   conductivity   of   the
saturation
extra
ct.
However,   sodicity 
is   defined
of
e
xchangeaDle    sodium    percentage.
Salinity 
may 
be
categorized    into
two    based
o
sources,     primary     (innerent)     salinity     and     secondary     salinity     Primary     (inherent)     salinity derived     from     the     weathering/degradation     of     pnmary     rocks/minerals     It     usually     occurs     when evaporation    exceeds    precipitation.    Where    as    secondary    salinity    is    derived    from    the    upward movement    of    salts    from    saline    groundwater    through    capillary    size    under    the    situation    of    in adequate    leaching    This    situation    happens    mainly    under    shallow    groundwater    Mass    flow    to
the   soil   surface   through   capillary   rise   is   known   to   cease   when   the   water   table   is   below   2
meters   in   a   clay   and   silty   clay;   where   as   the   same   value   is   1   6   meters   in   coarse   textured soil
Water ana soil salinity  occur aue to different reasons. Among them are over irrigation that causes  groundwater level rise due to in appropnate provision of drainage and/or crop water requirement calculation, poor method of irrigation, capillary  rise of ground water due to naturally  high grounawater level below surface, etc  When such raised grounowater level is suojectea to evaporation loss, the chemical constituents  of the water will be left over and becomes  concentrated on the sunace leading to soil and/or water salinity. The leaching of some existing nutnents  in soil is  also the potential source of salinity  of water and soil in irrigation. In oraer to assess  the possibility  of salinity  for the project area in the future, data have oeen collected and have been evaluated. Among them are the existing ground water quality  (physicochemical characteristics  of groundwater), ana soil chemistry  Other Parameters  that have been given emphasis  here is  the meteorological parameters  that cause high evapotranspiration. However, the high rate of precipitation (rainfall) in the area can counteract the problem by  leaching the highly  soluble salts  such as  chionaes, sulphates and carbonate salts
The distribution of relatively saline water is SDoradic in thP ar =.
Q
i«
Total Dissolved Solids of the project area is available at Fig 4 5
Water Works Design & Supervision Enterprise
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39Arjo Dedessa Irrigation Project
Hydrogeological investigations
Hence, the hazard soil/water salinity during the design period of t P rtf all controlled naturally (through high precipitation and topography of the a through appropriate irrigation water management.
May 2007
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40Arjo Dedessa Irrigation Project
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8. EXSITING AND FUTURE PROSPECT OF GROUNDWATER 8.1 Existing groundwater development
May 2007
Presently,  the  majority  of  the  Woredas'  capital  town  and  the  rural  community  in  the  rive catchment    are    supplied    potable    water    from    groundwater,    either    through    borehole construction  or  from  spring  development  with  the  exception  of  Bedele  town  that  get  water from  Dabana  River  througn  the  treatment  of  raw  water  The  yieid  of  groundwater  from  some volcanic  lava  flow  shows  very  promising  result  both  for  current  and  future  water  supply  from groundwater  for  different  purposes.  Can  be  mentioned  as  examples  are  boreholes  for  Agaro town  wnere  the  yield  is  about  30lit/sec  from  a  single  borehole.  Furthermore,  the  aquifer  in this particular area has multilayer system attributing to a confined aquifer
Here, it is  vital to discuss  Agaro town as  an example The town is  entirely  supplied water from grounawater through boreholes. There are three new boreholes  and two old boreholes. Among these boreholes, four boreholes  are currently  functional, one from the old and three of the new borenoies.
in  addition  to  this,  the  Quaternary  sediments  in  the  nver  valley  are  the  potential  aquifers  for groundwater development, particularly shallow groundwater
Other  Woreda  towns  that  are  supplied  potable  water  from  groundwater  are  Arjo,  Atnago. Gatira and Atnago
8.2 Future groundwater prospect
The existing geological, meteorological, hydrogeological and geomorphoiogical conditions in the river catchment indicate there are areas that can be developed in light of groundwater for various water supply purposes. Accordingly, potential well field sites have been identified in order to develop groundwater These identified well field sites  nave to be verified based on geophysical investigations  and test well drilling before being entirely  developed. The likely limitation in the future groundwater development in the area is not the quantity but the quality  (relatively  high iron concentration). The map of potential groundwater areas  for future development is available at Fig. 8.1
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41Fig 8-1 A map showing Groundwater potential areas for future development
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Summery

Arjo-Dedessa Irrigation Project Summary

Arjo-Dedessa Irrigation Project Feasibility Study Report

1. Project Overview

The Arjo-Dedessa Irrigation Project is a major development initiative in Ethiopia's Abbay Basin (Blue Nile Basin), focusing on water resource management for agricultural irrigation. The feasibility study was conducted by the Water Works Design & Supervision Enterprise in association with Intercontinental Consultants and Technocrats Pvt. Ltd.

Key Project Details:

Location: Dedessa River sub-basin within the Abbay Basin
Catchment Area: 9,981 km² at proposed dam site
Mean Annual Flow: 3,826 million m³ (at Arjo gauging station)
Project Components: Dam, irrigation system, and associated infrastructure

2. Hydrological and Meteorological Analysis

2.1 Climate Characteristics

The Dedessa catchment has a uni-modal rainfall pattern with:

Main rainy season: May to September (63% of annual rainfall)
Dry season: November to February (7% of annual rainfall)
Mean annual rainfall: 1,453 mm (project area)
Temperature range: 20.0°C (December) to 25.4°C (March)

2.2 Evapotranspiration

Reference evapotranspiration (ET₀) was calculated using the FAO Penman-Monteith method:

Month	Mean ET₀ (mm/day)	Mean ET₀ (mm/month)
Annual	3.83	1,397
Peak (March)	4.62	143
Lowest (December)	3.44	107

2.3 Streamflow Analysis

Key findings from the hydrological analysis:

Return Period	Annual Flow (Mm³)	Peak Flood (m³/sec)
Mean Year	2,328	-
75% Year	1,729	-
10-year	-	575
100-year	-	871
10,000-year	-	1,948
PMF	-	3,690

2.4 Sediment Analysis

Sediment yield was estimated using the relationship: Gs = 0.078 Q¹·⁵

Suspended sediment concentration: 45-1,670 mg/lt observed
Bed load assumed to be 15% of suspended load
Sediment distribution in reservoir calculated using Area-Increment method

3. Key Project Components

3.1 Water Resources Development

The project includes:

Dam construction on Dedessa River
Reservoir creation for water storage
Irrigation system development
Potential for hydropower generation

3.2 Agricultural Development

The irrigation project aims to support:

Large-scale agricultural production
Multiple cropping systems
Improved food security in the region

4. Conclusions and Recommendations

The feasibility study confirms the technical viability of the Arjo-Dedessa Irrigation Project, with:

Adequate water resources available in the Dedessa sub-basin
Favorable climatic conditions for irrigation development
Need for careful sediment management in reservoir planning
Potential for integrated water resources management including hydropower