Land and Water resources study for irrigation purpose

1. i
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SPATE IRRIGATION POTENTIAL ASSESSMENT
THE CASE OF HARGETI RIVER WATERSHED
M.SC. THESIS
BY: - FERID HUSSEN HARUN
ARBA BMINCH UNIVERSITY, INSTITUTE OF TECHNOLOGY, SCHOOLOF POST
GRADUATE STUDIES, DEPARTMENT OF WATER RESOURCE AND IRRIGATION
ENGINEERING
OCTOBER 2015
ARBA MINCH, ETHIOPIA

2. ii
SPATE IRRIGATION POTENTIAL ASSESSMENT
THE CASE OF HARGETI RIVER WATERSHED
BY: - FERID HUSSEN HARUN
A THESIS SUBMITTED TO THE DEPARTMENT OF WATER RESOURCE AND
IRRIGATION ENGINEERING,
INSTITUTE OF TECHNOLOGY, SCHOOL OF POST GRADUATE STUDIES, ARBA
MINCH UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR
THE
DEGREE OF MASTERS OF SCIENCE IN IRRIGATION AND DRAINAGE
ENGINEERING
OCTOBER 2015
ARBA MINCH, ETHIOPIA

3. iii
ADVISOR’S APPROVAL SHEET
SCHOOL OF GRADGUATE STUDIES
ARBAMINCH UNIVERSITY
ADVISORS‟APPROVAL SHEET
This is to certify that the thesis entitled” SPATE IRRIGATION POTENTIAL ASSESSMENT
THE CASE OF HARGETI RIVER WATERSHED” submitted in partial fulfillment of the
requirements for the degree of master‟s with specialization in IRRIGATION AND
DRAINAGE ENGINEERING, the graduate program of the department of water resources
and irrigation engineering, institute of technology, school of graduate studies, Arba Minch
university and has been carried out by Ferid Hussen Harun, Id.No RMs/249/05, under my
supervision. Therefore I/We recommend that the student has fulfilled the requirements and
hence hereby can submit the thesis to the department.
Dr. Tilahun Hordofa
Major Advisor

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5. v
Declaration and Copy Right
I, Ferid Hussen, declare that this thesis is my own original work and it has not been
presented and will not be presented by me to any other University for similar or any other
degree award. This Thesis has been submitted in partial fulfillment of the
Requirements for M.Sc. degree at the Arba Minch University and deposited at the University
library to be made available to readers under its rules
Ferid Hussen
Signature_________
Date __________

6. vi
APPROVAL PAGE
This thesis entitled with “Spate Irrigation Potential Assessment: The Case Study of
Hargeti River Watershed” has been approved by the following advisors, Examiners,
Department head, Coordinator, and Director of Graduate Studies in partial fulfillment of the
requirement for the degree of Master of Science in Irrigation and Drainage Engineering.
Submitted By:
Mr. Ferid Hussen Harun _____ _________
Name Signature Date:
1. Dr. Tilahun Hordofa _________ ______
Major Advisor Signature Date
2. External Examiner _____ ________
Signature Date
3. Internal Examiner _____ _______
Signature Date
4. Chairperson _____ ________
Signature Date
5. Dep‟t head _____ _________
Signature Date
6. Mr. Demelash W. _____ ________
PG .Coordinator Signature Date
7. Anto Arkato (PhD) _______ _______
SGS Signature Date

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ACKNOWLEDGEMENTS
First and for most I thank my Almighty Allah, for through Him I had my wellbeing and
passed every hurdle in my study time and in my life at all.
My sincere and special thanks indebted to my supervisors Dr. Tilahun Hordofa for his
supervision, encouragement and guidance he has provided me throughout my study. His
critical comments and helpful guidance give me a chance to explore further. I have learned a
lot from him.
My deepest gratitude goes to my second supervisor Mr. Ermias Alemu (PhD candidate). His
kind support and encouragement give me strength right from the start to the last minute of the
research work.
I would like to gratefully acknowledge the Ministry of Water, Irrigation and Energy for
giving me the opportunity to learn M.sc program and financial support to do the research.
I gratefully acknowledge all offices and personalities who have given me data for my study.
Spatially ministry of water Resources, and Oromia Irrigation Development authority western
Branch.
I would like to extend my thanks to Abdulhakim west Hararghe OIDA manager help me
giving data related to my research, Feysel the Mieso district Irrigation Development
Department team leader for his kind co-operation during field visit and information he has
provided me.
I am very grateful to my beloved wife Ashut Imran and my daughter Imaan Ferid for their
patience and encouragement while I was too far from them.
The Last but not the least, I would like to thank my lecturers for giving me all the basic
science and their courage to help everybody. My thanks also go to every staff in School of
graduate Studies program and the University.

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9. ix
LISTS OF ABBREVIATION
CN Curve Number
DEM Digital elevation model
DFID Dipartment for internation document
ETc Actual Evapotranspiration
ETo Reference crop evapotranspiration
FAO Food and Agriculture Organization
GIS Geographic Information System
HEC-HMS Hydrologic Engineering Center Hydrologic Model System
ICID International commission on Irrigation and Drainage
IFAD International Fund For Agricultural Development
IWMI International Water Management Institute
Kc Crop coefficients
LQs/LCs Land Quality and Land Characteristics
LUT Land Utilization Type
N Not Suitable
OWWDSE Oromia Water Works, Design and Supervision, Enterprise
S1 Highly suitable
S2 Moderately Suitable
S3 Marginally Suitable
SCS Soil Conservation Service
Tmax Daily Maximum Air Temperature
Tmin Daily Minimum Air Temperature
Ra Extra- Terrestrial Radiation

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Table of Contents
1 INTRODUCTION ................................................................................................................. 1
1.1 Background ...................................................................................................................... 1
1.2 Statement of the Problem................................................................................................. 2
1.3 General Objective............................................................................................................. 3
1.4 Research Question............................................................................................................ 3
1.5 Scope of the Study............................................................................................................ 3
2 DESCRIPTION OF THE STUDY AREA ............................................................................ 4
2.1 Location of Study Area .................................................................................................... 4
2.2 Topography ...................................................................................................................... 4
2.3 Land Use and Land Cover................................................................................................ 5
2.4 The Soil Map of the Study Area....................................................................................... 7
2.5 Agro-Climate.................................................................................................................... 7
3 LITERATURE REVIEW ...................................................................................................... 9
3.1 General Concepts of Spate Irrigation............................................................................... 9
3.2 Spate Irrigation In Ethiopia.............................................................................................. 9
3.3 Hydrology of Spate Irrigation........................................................................................ 10
HEC-HMS Hydrologic Model................................................................................ 11
3.3.1
3.4 Land Evaluation ............................................................................................................. 12
3.5 Evaluating Land for Irrigated Agriculture ..................................................................... 12
Principles................................................................................................................. 12
3.5.1
3.6 Irrigation Water Demand ............................................................................................... 13
3.7 Previous Studies ............................................................................................................. 15
4 MATERIAL and METHODS .............................................................................................. 16
4.1 Data Availability and Analysis ...................................................................................... 16
4.2 Climate Data................................................................................................................... 16
Precipitation............................................................................................................ 16
4.2.1
Temperature ............................................................................................................ 16
4.2.2
4.3 Soil Data......................................................................................................................... 16
4.4 Crop data ........................................................................................................................ 17
4.5 Land Use / Land Cover .................................................................................................. 17
4.6 Methodology .................................................................................................................. 17
Data Pre-Processing and Checking......................................................................... 17
4.6.1
Precipitation Data Quality and Consistency ........................................................... 17
4.6.2
Filling Missing Data ............................................................................................... 18
4.6.3
4.7 Preparing Input Data for HEC-HMS Basin component................................................ 18
4.8 Basin Parameter.............................................................................................................. 20
Curve Number......................................................................................................... 20
4.8.1
Potential Maximum Retention of sub watersheds (S)............................................. 21
4.8.2
Initial Abstraction (Ia)............................................................................................. 21
4.8.3
Time of concentration (Tc) ..................................................................................... 21
4.8.4

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Lag Time (TL) ........................................................................................................ 21
4.8.5
4.9 HEC-HMS Simulation ................................................................................................... 22
4.10 Land Evaluation Procedure ............................................................................................ 22
4.11 Irrigation Water Requirement....................................................................................... 23
4.12 Estimating Irrigable Area............................................................................................... 24
5 RESULT AND DISCUSSION ............................................................................................ 25
5.1 Testing Rainfall Data For Consistency .......................................................................... 25
5.2 Basin Parameters of the Study Area ............................................................................ 26
Hydrologic Soil Group............................................................................................ 26
5.2.1
5.3 Surface Runoff Potential................................................................................................ 29
5.4 Land Evaluation Results ............................................................................................... 30
Temperature, Soil and land slope suitability........................................................... 30
5.4.1
Land Cover Suitability............................................................................................ 32
5.4.2
Slope Suitability...................................................................................................... 33
5.4.3
The Potential Irrigable Land ................................................................................... 35
5.4.4
5.5 Irrigation Water Requirement ........................................................................................ 36
5.6 Irrigable Area Based on the Available Water ................................................................ 37
6 CONCLUSIONS AND RECCOMENDATION ................................................................. 38
6.1 Conclusion...................................................................................................................... 38
6.2 Recommendation............................................................................................................ 38
7 REFERENCES .................................................................................................................... 40
8 APPENDIX.......................................................................................................................... 42

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LIST OF TABLE
TABLE 2-1 LAND USE LAND COVER OF STUDYAREA ...................................................................6
TABLE 4-1 CRITERIA FOR SOIL HYDROLOGICAL GROUP ...........................................................20
TABLE 4-2 CRITERIA FOR SELECTION OF CURVE NUMBER .........................................................21
TABLE 4-3 LAND USE/LAND COVER SUITABILITYCRITERIA.......................................................23
TABLE 5-1 AREAL WEIGHTS OF STATIONS AROUND HARGETI CATCHMENT...............................25
TABLE 5-2 LOCATION MAPS OF STATIONS AND THEIR AREA COVERAGE IN THE CATCHMENT. ..26
TABLE 5-3 HYDROLOGICAL SOIL GROUP..................................................................................27
TABLE 5-4 LAND USE COVER OF HARGETI WATERSHED AND ABA BORDADE CATCHMENT.......28
TABLE 5-5 CALCULATED BASIN PARAMETERS .........................................................................28
TABLE 5-6 MONTHLYRUNOFF AVAILABILITY .........................................................................29
TABLE 5-7 SUITABILITY OF SOIL...............................................................................................31
TABLE 5-8 LAND USE LAND COVER SUITABILITY ......................................................................32
TABLE 5-9 SLOPE SUITABILITY RANGE OF THE STUDY AREA FOR SURFACE IRRIGATION .......34
TABLE 5-10 PROVISIONAL IRRIGABLE AREA............................................................................36
TABLE 5-11 EXISTINGCROPPINGPATTERN OF THE STUDY AREA...........................................36
TABLE 5-12 POTENTIAL IRRIGABLE LAND BASED ON MONTHLY SURFACE RUNOFF
AVAILABILITY...................................................................................................................37

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LIST OF FIGURES
FIGURE 2-1 LOCATION MAP OF THE STUDY AREA ......................................................................4
FIGURE 2-2 THE ELEVATION MAP OF THE STUDY AREA...............................................................5
FIGURE 2-3 LAND COVER MAP OF STUDYAREA (SOURCE- OWWDSE, 2010).............................6
FIGURE 2-4 SOIL TYPE OF STUDYAREA. (SOURCE:-OWWDSE, 2010) .......................................7
FIGURE 2-5 AGRO CLIMATIC ZONE OF STUDY AREA. (SOURCE:OWWDSE, 2010) ..................8
FIGURE 5-1 DOUBLE MASS CURVE OF KORA STATION ............................................................25
FIGURE 5-2 HYDROLOGICAL SOIL GROUP OF STUDY AREA .....................................................27
FIGURE 5-3 MONTHELY RUNOFF GENERATED FROM HARGETI CACHMENT..............................29
FIGURE 5-4 AREAL RIANFALL SIMILARITYWITH RUNOFF........................................................30
FIGURE 5-5 LAND USE/LAND COVER SUITABILITYFOR IRRIGATION..........................................33
FIGURE 5-6 SLOPE SUITABILITYMAP FOR SURFACE IRRIGATION............................................34
FIGURE 5-7 IRRIGATION SUITABILITY MAP...............................................................................35
FIGURE 5-8 CROP WATER DEMAND VS EFFECTIVE RAINFALL .................................................36

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LIST OF APPENDIX
APPENDIX FIGURE 1 FLOW DIRECTION .....................................................................................42
APPENDIX FIGURE 2 FLOW ACCUMULATION.............................................................................43
APPENDIX FIGURE 3 STREAMS..................................................................................................44
APPENDIX FIGURE 4 CATCHMENT POLYGONS...........................................................................45
APPENDIX FIGURE 5 IRRIGATION SUITIBLITYMAP FOR SURFACE IRRIGATION ...........................46
APPENDIX TABLE 1 SOIL SUITABILITY FOR LOWLAND MAIZE AND SORGHUM...........................58
APPENDIX TABLE 2LAND USE/LAND COVER............................................................................59
APPENDIX TABLE 3 EVAPOTRANSPIRATION..............................................................................60
APPENDIX TABLE 4 DUTYOF IRRIGATION................................................................................69
APPENDIX TABLE 5HYDROLOGICAL SOIL GROUP......................................................................79
TABLE 6 AGRO -CLIMATIC ZONE OF STUDYAREA. (SOURCE: OWWDSE, 2010) .....................80
APPENDIX TABLE 7 MONTHLY RAINFALL OF SELECTED ...........................................................80

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ABSTRACT
Assessing availability of water source and land for irrigated agriculture is very important to
reach at a proper decision on the demand and supply of irrigation development. This study
was initiated with the objective of assessing surface runoff potential , land suitability
evaluation for irrigation and crop water demand of Hargeti river watershed for spate
irrigation development .The surface runoff potential was calculated by the soil Conservation
Service Curve Number ( SCS -CN) method.Crop water demand was estimated using
Hargreaves method. To identify potential irrigable land, irrigation suitability factors such as
soil type, slope, and land cover/use, were taken into account. The surface runoff potential
Hargeti sub catchment was assessed monthly based, the result shows there is high temporal
variability of runoff observed. The irrigation suitability analysis of these factors indicates that
54 % of soil is marginally suitable. whereas based on slope suitability 7 % and 31% of the
study area is in the range of highly to marginally suitable for surface irrigation system
respectively. In terms of land cover/use, 63 % and 35% of land cover/use is in the range of
highly to marginally suitable. The overall analysis of these factors gave 29,200 ha of irrigable
land by surface irrigation system. Based on analysis of surface runoff potential and water
demand for selected crop, the potential irrigable land by spate irrigation is 3682ha, thus the
potential can be enhanced through additional water harvesting activities.
Key Word: Surface Runoff potential; Irrigation Suitability; Spate Irrigation

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1 INTRODUCTION
1.1 Background
Ethiopia is a country where the majority of its population is dependent on traditional
agriculture. This traditional agriculture mainly depends on rainfall. Arid and semi-arid region
of the country is characterized by, inadequate and irregular nature of rainfall. Rapid
population growth and insufficient rainfall are the major problems of rain fed agriculture in
arid and semi-arid part of the country. Consequently, food insecurity turns to famine, hence,
has an adverse impact on the economy of the country. Therefore, an effort must be made
toward achieving more agricultural production through irrigation development to balance the
growing demand for food.
With high population growth, practicing only rain fed agriculture in water stressed areas
cannot achieve the required level even for subsistence agriculture. (Seleshi, 2010) These
factors combined with the increasing degradation of the natural resource base, aggravate the
incidence of poverty and food insecurity in rural areas.
Therefore, systematic approach for irrigation potential assessment is necessary. Spate
irrigation is one of those alternatives that will provide seasonal streams that convey runoff
generated in adjacent highland areas. These are the only water source for livelihoods of
economically marginal people in the lowland area. Spate irrigation is an ancient form of
water management, involving the diversion of flashy spate floods running off from
mountainous catchments, using simple deflectors of bunds constructed from sand, stones and
brushwood on the beds of normally dry wadis. Flood flows, usually flowing for only a few
hours with appreciable discharges, and with recession flows lasting for only one to a few
days, are channeled through short steep canals to bounded basins, which are flooded to depths
of 0.5 m or more. (Steenbergen, 2005)
In Ethiopia, spate irrigation is as elsewhere in Sub Saharan Africa on the increase. Its
popularity is part of a larger movement towards higher productivity, farm systems aren't
exclusively raining dependent. Spate irrigation is also linked to the increasing settlement of
the lowland areas. In some areas, spate irrigation is also a response to a trend of perennial
rivers no longer being perennial, the result of catchment degradation, but moving to a semi-
perennial state with more flash floods. ( Steenbergen et.al•, 2011)

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Currently spate irrigation became the main concern of most regions like Tigray, Oromia,
Amhara, Afar and SNNS. The area currently under spate irrigation is estimated at 140,000 ha,
but the potential, particularly in the lowland plains is much higher (Alemayehu, 2008.) .This
shows that there is the possibility to assess additional potential for spate irrigation.
An assessment of spate irrigation potential involves the availability of water and land
suitability. Land suitability must be assessed and classified with respect to specified kinds of
land use.i.e.Cropping, irrigation and management systems. It is obvious that the requirements
of crops and irrigation and management methods differ, so the suitability of any land unit
may be classified differently for various uses. It can be useless or misleading to indicate
suitability for irrigated agriculture in general, if the land developer needs to know about its
potential for a specific irrigated crop or irrigation method (ICID, 2010).
Therefore, the planning process for irrigation development has to be integrating information
about the suitability of the land, water resources availability and water requirements of
irrigable areas in time and place (FAO, 1997). Determining the suitability of land for surface
irrigation requires evaluation of soil properties and topography (slope) of the land within a
field (Fasina et al. 2008.)
1.2 Statement of the Problem
Water scarcity is one of the major constraints for development of agriculture in arid and
semi-arid part of Ethiopia .With the explosion of population in country, the need to increase
food production through only rain fed agriculture becoming imperative. In the study area,
occurring of erratic and unreliable rainfalls have left more of the population reliant on a
pastoral way of life, where some population were practice traditional flood based farming that
comes from highland area. In addition, Population pressure, and natural calamities, in the
study area have led to increased use of spate water. Despite the burning need and the
prevailing problem, little is done in Hargeti river watershed to use spate water for irrigation.
However, the amounts of surface runoff potential for spate irrigation and land suitability were
not identified.
Therefore, in order to overcome these uncertainties, conducting proper irrigation potential
assessment is a priority towards irrigation development in the area. This initiates to assess
spate irrigation potential of the study area.

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1.3 General Objective
The general objective is to assess water resource potential of Hargeti river watershed and its
land suitability for spate irrigation for supporting crop production and improved livelihood of
economically marginal people.
Specific Objectives of the Study
1. To estimate surface runoff potential of the study area.
2. To Evaluate land suitability for irrigation.
2. To estimate irrigation potential from runoff generated in the catchment.
1.4 ResearchQuestion
1. What amount of surface runoff water is generated from the catchment and how it can
help to farmers?
2. What is the irrigable land potential of the area from the available runoff potential?
1.5 Scope of the Study
This paper was only intended to assess surface runoff potential of Hargeti sub-catchment, to
assess land suitability for irrigation with some selected crops and to estimate irrigation
potential with available water in the catchment.

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2 DESCRIPTION OF THE STUDY AREA
2.1 Location of Study Area
The study area for this present work is Hargeti river watershed .It is sub basin of Awash river
basin, which is spreads 8° 52' N and 9° 16' N latitude and40° 23' E and 40°45' E longitude.
The geographical extent of this catchment is 1041 Km2.
(fig 2.1).
Figure 2-1 Location Map of the Study Area
2.2 Topography
As shown figure: 2.2 below the altitude of the area in the catchment ranges from 2684 m to
1022m above sea level .High elevation observed in the southern part, whereas lowland started
from middle and extended toward southern part of the catchment.

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Figure 2-2 The Elevation map of the study area
2.3 Land Use and Land Cover
Based on the study conducted by OWWDSE in 2010, the land use was classified as cultivated
land, dense bush shrub land, and dense shrub land, rock surface with scattered shrubs,
irrigated agriculture, open bush shrub land, open shrub land and settlements. About 60.75 %
of the area is occupied by agricultural cultivated land, 31.77% area covers dense shrub land,
3.45% dense shrub land (Table 2.1 and fig 2.3).

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Table 2-1 Land use land cover of study area
Land use land cover Area KM2
Area (%)
Cultivated Land 633 60.75%
Dense Bush Shrub Land 36 3.45%
Dense Shrub Land 331 31.77%
Exposed Rock Surface with scattered shrubs 1 0.10%
Irrigated Agriculture 7 0.67%
Open Shrub Grass Land 1 0.10%
Open Shrub Land 26 2.50%
Settlements 7 0.67%
Figure 2-3 land cover map of study area (Source- OWWDSE, 2010)

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2.4 The Soil Map of the Study Area
Soil map of the study area was prepared by OWWDSE in 2010 using FAO soil classification
method. Seven soil types are identified in the catchment. These are Eutric Cambisol, Vertisol
cambisol, Epileptic leptosol, chromic luvisol, rock surface, Eutric vertisol and pellic
vertisol.The dominant soil types are Epileptic leptosol, Eutric vertisol a Eutric Cambisol.
Figure 2-4 Soil type of study area. (Source:-OWWDSE, 2010)
2.5 Agro-Climate
The distribution of agro-climatic zone of the study area is shown in Table 2.3 and figure 2.5.
It is shown that 76.9% of the area is classified as hot to warm sub-moist lowland. It covers
the lowland area of most part of Mi‟eso woreda. The average annual rainfall of the study is

23. 8
673.3 mm and the temperature varying between 17o
c and 31.6o
c has rainfall distribution of
bimodal nature.
Figure 2-5 Agro Climatic Zone Of Study Area. (Source: OWWDSE, 2010)

24. 9
3 LITERATURE REVIEW
3.1 General Concepts of Spate Irrigation
Spate irrigation is carried out in hot arid and semi-arid regions where evapotranspiration
greatly exceeds rainfall. It is an ancient form of water management, involving the diversion
of flashy spate floods running off from mountainous catchments, using simple
deflectors constructed from sand, stones and brushwood on the beds of normally dry wadis.
Flood flows, usually flowing for only a few hours with appreciable discharges and with
recession flows lasting for only one to a few days, are channeled through short steep
canals to bunded basins, which are flooded to depths of 0.5 m or more (Lawrence, et al.,
2005). This type of agriculture is very risk-prone and requires high levels of co-
operation between farmers to divert floods and manage the distribution of flood flows.
As indicated by Elaskari, ( 2005) , the high risks and uncertainties of spate irrigation
arises from the uncertainty of spate floods; that in dry years there might be too little or no
flood water to grow any crop, exceptionally large floods that can cause substantial damage to
the schemes. (FAO, 2010)
3.2 Spate Irrigation In Ethiopia
The definition of spate irrigation in Ethiopia differs from place to place. Generally, the
meaning of the word spate is using seasonal floods to compensate for rainfall
shortages and erratic rainfalls that could have affected seasonal harvests. In areas of
traditional spate irrigation practices, they have local names for spate irrigation. In southeast
Ethiopia, „Gelcha‟is used for spate irrigation with a literal meaning of „divert the flood into
the farm.‟ „Telefa‟is used in the northern parts of Ethiopia with the literal meaning of
„diversion.‟ (Van Steenbergen et al, 2009). Some spate irrigation systems in Ethiopia have
been in use for several generations, but in almost all areas spate irrigation has developed
recently. Particularly in the arid parts of the country: in East Tigray (Raja, Waja), Oromia
(Bale, Arsi, West and East Haraghe), Dire Dawa Administrative Region, in SNNP, Southern
Nations, Nationalities and Peoples Region (Konso), Afar and in Amhara (Kobe) region . (
van Steenbergen et.al•, 2011).

25. 10
3.3 Hydrology of Spate Irrigation
For developing a spate system, it is important to understand the entire hydrology of the
system, the base flow, sub-surface flow and the pattern of spate floods that will dictate the
potential yield of spate irrigation systems. Spate hydrology is characterized by variation in
size and frequency of floods, which directly influence the availability of water for agriculture.
Spate floods have very high peak discharges that are generated in wadi catchments by
localized storm rainfall. The extreme characteristics of wadi hydrology make it very difficult
to determine the volumes of water that are to be diverted to fields and hence the potential
cropped areas. Despite its uncertain character in amount and duration, floodwater is the only
source of water for spate irrigation. Flood water used for spate irrigation is diverted from a
stream where it flows by constructing different types of structures across the stream
bed most commonly spur-type deflector and bund type diversion in traditional systems
and permanent structures like weir in modernized systems. Spate Floods are mainly
characterized by a sudden rise to peak flow and a relatively longer recession period
which is attributable to high intensity rainfall characteristics which vary in space and time
over a catchment (FAO, 2010).
Alike conventional irrigation systems spate irrigation system also constitutes different
structures that serve the purpose of flood water diversion, control and distribution. After
diverting the flood water to the main canal by constructing diversions across the
stream bed the flood water distributed over the command area through main canal and/or
distribution canal networks. This depends on a water distribution method that is accepted by
the users. The four most commonly used floodwater distribution methods are available; the
field-to-field method, individual field off-take, extensive and intensive water distribution
methods. Detail description of different types of hydraulic structures constructed in
traditional and/or modernized spate irrigation systems and descriptions of the methods
of water distribution can be found in (Steenbergen, et al. (2010).
The proportion of the mean annual runoff (MAR) that can be diverted to the fields is an
important parameter in determining the potential command area, although in spate schemes
the areas that are irrigated can vary widely from year to year. MAR is conventionally
expressed as a runoff depth from the catchment, in mm, but can easily be converted to a
volume by multiplying it by the catchment area. The proportion of the runoff volume that can
be diverted for irrigation depends on the diversion arrangements and the patterns of spate
flows that are experienced. This is difficult to estimate without extensive long-term site-

26. 11
specific flow data. (FAO, 2010). An important consideration in water resource assessment
is to estimate how much flow is available at the outlet of river catchments. The
volume of water reliably available on an annual or seasonal basis can be determined from
the available data in case of gauged rivers and for completely un gauged rivers the runoff
coefficient method can be employed . (Goldsmith, 2000) According to (DFID, 2004) ,
when this is the case, then data from the gauging site should be used to estimate mean
annual runoff off (MAR) at un gauged site, provided that the requirements set out below are
met.
I. Catchment characteristics should be similar,
II. The distance between the centroids of the catchments should be less than 50 km,
III. At least ten years of mean monthly flows should be available.
Another method of runoff estimation technique is SCS CN runoff methods, which is
developed by USDA-SCS. The major factors that determine CN are the hydrologic soil group
(HSG), cover type, treatment, hydrologic condition, and antecedent runoff condition (ARC). (
USDA-SCS., 1985). The detail explanation of SCS Runoff Curve Number (CN) method is
described in NEH-4 (SCS 1985).
HEC-HMS Hydrologic Model
3.3.1
HEC-HMS is a hydrologic modeling software developed by the US Army Corps of
Engineers Hydrologic Engineering Center (HEC), It is a physically based and conceptual
semi distributed model designed to simulate the rainfall-runoff processes in a wide
range of geographic areas such as large river basin water supply and flood hydrology to
small urban and natural watershed. The system encompasses losses, runoff transforms,
open channel routing, analysis of meteorological data, rainfall-runoff simulation and
parameter estimation. HEC-HMS uses separate models to represent each component of
the runoff process, including models that compute runoff volume, models of direct
runoff, and models of base flow. Each model run combines a basin model,
meteorological model and control specifications with run options to obtain results.
(Arlen, 2000)

27. 12
3.4 Land Evaluation
A full use of land and water resources in the development of irrigation facilities could lead to
substantial increases in food production in many parts of the world. The process whereby the
suitability of land for specific uses, such as irrigated agriculture is assessed is called land
evaluation. (FAO, 1985)
Land comprises the physical environment, including climate, relief, soils, hydrology and
vegetation, to the extent that these influence potential for land use. It includes the results of
past and present human activity, e.g. reclamation from the sea, vegetation clearance, and
adverse results, e.g. soil salinization. Purely economic and social characteristics, however, are
not included in the concept of land; these form part of the economic and social context.
(FAO, 1976)
Decisions on land use have always been part of the evolution of human society. In the past,
land use changes often came about by gradual evolution, as the result of many separate
decisions taken by individuals. In the more crowded and complex world of the present, they
are frequently brought about by the process of land use planning. Such planning takes place
in all parts of the world, including both developing and developed countries (FAO, 1976).
3.5 Evaluating Land for Irrigated Agriculture
Principles
3.5.1
The FAO Framework indicates that it is necessary to evaluate land and not just soils. The
suitability of soils for irrigated crops is useful information, but it is inadequate for making
decisions about land use development. Therefore, all relevant land characteristics, including
soils, climate, topography, water resources, vegetation, etc. and socioeconomic conditions
and infrastructure need to be considered. (FAO, 1976).
The main objective of land evaluation for irrigated agriculture is to predict future conditions
after development has taken place. Essentially a classification of potential suitability is
required, which takes account of future interactions between soils, water, crops and
economic, social and political conditions. Some factors that affect land suitability are
permanent and others are changeable at a cost. The costs of necessary improvements may be
determined, so that economic and environmental consequences of development can be
predicted. Typical examples of permanent features are temperature, soil texture, depth to
bedrock and macro-topography. Changeable characteristics, which may be altered

28. 13
deliberately or inadvertently typically, may include vegetation, salinity, depth to
groundwater, micro relief, and some social and economic conditions. (FAO, 1985)
The evaluation must take account of the local physical, political, economic and social
conditions. The success of irrigation when it is introduced may depend as much on factors
such as pricing policies for crops, labour supply, markets, accessibility, land tenure, etc. as on
climate and soils. To avoid any misunderstanding all the factors, which are relevant in the
local situation, should be explicitly stated rather than assumed however, not all conditions
need to considered: only those that can usefully be taken into account in classifying land.
(ICID, 2010).
The land suitability must be sustained use, that is, permanently productive under the
anticipated irrigation regime. Either there should be no land degradation anticipated or the
cost of prevention or remedial action to control erosion, waterlogging, salinization etc. should
be included in the comparison of inputs and outputs. The evaluation, where more than one
apparently viable alternative exists, should compare more than one kind of use. Comparison
may be, for example, between the present use and the proposed uses, or between different
crops and irrigation methods. The reliability of the evaluation is enhanced by comparing
inputs and outputs for several alternatives to ensure that the land use selected is not only
suitable but the best of suitable alternatives. (FAO, 1985)
It is evident that an interdisciplinary approach is required, because no one discipline can
cover all aspects of land suitability evaluation. Land evaluation can be carried out using
general economic considerations to establish a context for selecting appropriate crops and
management, and to establish the criteria for boundaries between suitable and unsuitable
land. To make a quantitative evaluation of the project or farm level, however, requires formal
analysis in financial and economic terms (FAO, 1985).
Finally, land evaluation is an iterative process leading to successive refinements and the need
for surveys and investigations that are appropriate in scale and intensity during the different
stages from reconnaissance to detailed project planning, and thereafter in successive phases
of project implementation. (FAO, 1985).
3.6 Irrigation Water Demand
Assessment of water resources for irrigation purpose consists of obtaining information on the
distribution of water availability along with irrigation water requirement. The water need of
crops is influenced by climate, which is referenced crop evapotranspiration (ETo).

29. 14
The only factors affecting ETo are climatic parameters. As a result, ETo is a climatic
parameter that can be computed from weather data. ETo expresses the evaporative demand of
the atmosphere at a specific location and time of the year and does not consider crop and soil
factors. Several empirical and semi-empirical methods have been developed over the last 50
years to estimate reference crop evapotranspiration from climatic variables. Some of the
methods that have been developed are the Blaney-Criddle, Radiation, Modified Penman and
Pan Evaporation methods. (Frenken, 2002) .
The FAO Penman-Monteith method is now the sole recommended method for determining
reference crop evapotranspiration (ETo). This method overcomes the shortcomings of all
other previous empirical and semi-empirical methods and provides ETo values that are more
consistent with actual crop water use data in all regions and climates. Estimation of ETo with
the FAO Penman-Monteith method is Estimation method is applicable under all
circumstances, even in the case of missing climatic data. (FAO, 1990).
The equation uses standard climatological records of solar radiation (sunshine), air
temperature, humidity and wind speed for daily, weekly, ten-day or monthly calculations.
The selection of the time step with which ETo is calculated depends on the purpose of the
calculation, the accuracy required and the time step of the climatic data available. Some of
the data are measured directly in weather stations. Other parameters are related to commonly
measured data and can be derived with the help of direct or empirical equations. (Frenken,
2002).
An alternative equation for ETo when weather data are missing, when solar radiation ,
relative humidity and/or wind speed data are missing, estimation of ETo should be done by
Hargreaves methods. This method needs only Temperature data. (FAO, 1990)
Temperature is probably the easiest, most widely available and most reliable climate
parameter. The assumption that temperature is an indicator of the evaporative power of the
atmosphere is the basis for temperature-based methods, such as the Hargreaves-Samani.
These methods are useful when there are no data on the other meteorological parameters.
Hargreaves-Samani model Hargreaves and Samani proposed in 1982 (Hargreaves and
Samani, 1982) requires only maximum and minimum daily air temperature and it can be
applied on 24-hour, weekly, 10-day, or monthly time steps. (Mohammadi V. et.al,2013).

30. 15
Where
Ra = extra-terrestrial radiation (MJm−2 day−1)
Tmax = daily maximum air temperature (0
C)
Tmin = daily minimum air temperature (O
C)
3.7 Previous Studies
.Kebede (2010) conducted GIS-based surface irrigation potential assessment of river
catchments for irrigation development in Dale woreda, Sidama zone, SNNP. Identification of
suitable sites for irrigation was carried out by considering the slope, soil, land cover/use and
distance between water supply and the potential command area as factors.Negash (2004)
conducted a study on irrigation suitability analysis in Ethiopia a case of Abaya-Chamo
lake basin. It was a Geographical Information System (GIS) based and had taken into
consideration soil, slope, land use and water resource availability in perennial rivers in the
basin to identify potential irrigable land. Harssema ( 2005) made a study on GIS-Based
Surface Runoff Modeling and Analysis of Contributing Factors; in this study three surface
runoff models were applied, including; (i) the index method, (ii) the SCS curve
number method and (iii) a semi physical approach to assess the distribution of surface
runoff in the watershed of the Nam Chun Watershed(Thailand). Ephrem (2013) conducted
runoff sediment yield of potential Bililo spate irrigation by the SCS method through SWAT
model. Whereas Navee (2013) conduct spate irrigation potential on Rod-Kohi watershed in
Pakistan using GIS and remote sensing to ward better water management strategies for
productive enhancement of agriculture in the country.

31. 16
4 MATERIAL and METHODS
4.1 Data Availability and Analysis
The data collected in the study are mainly to meet the requirement of the methods.
These data include meteorological, hydrologic and spatial data of the area under the study.
Meteorological data for this study were obtained from the National Meteorological
Agency (NMA) of Ethiopia and the collected data are from four stations located in and
around the area under study.
Spatial data collected includes Digital Elevation Model (DEM), land use, land cover,
soil types and geologic formation of the area. In addition to these Soil maps and Land,
use/cover map of study area prepared by Oromia water work, design supervision, Enterprise
(OWWDSE) in 2010 was collected from Oromia Irrigation Development Authority, (OIDA).
4.2 Climate Data
The following metrological stations are located in and near Hargeti catchment. Daily rainfall
and temperature data were obtained for these stations. In this study meteorological data
obtained from four stations are analyzed on daily and monthly basis.
Precipitation
4.2.1
From (1989-2008) daily data of the above-mentioned meteorological data for all stations
were collected from NMA. Then long term daily average data were derived from it. These
average data were used to compute runoff on HEC-HMS model and to compute crop water
demand using Hargreaves method.
Temperature
4.2.2
From (1989-2008) maximum temperature and minimum temperature around the study area
was obtained from NMSA (national metrological service. These average data were used to
compute crop water demand using Hargreaves method.
4.3 Soil Data
Soil map of the study area at scale of 1:50,000 prepared in 2010 were obtained from Oromia
Water Work Design, Supervision Enterprise.

32. 17
4.4 Crop data
Crop environmental requirements was prepared for Ethiopia by FAO in 1985, this data
was obtained as a word document.
4.5 Land Use / Land Cover
Land use/Land cover map at scale of 1:50,000 prepared in 2010 were obtained from Oromia
Water Work Design, Supervision Enterprise.
4.6 Methodology
Data Pre-Processing and Checking
4.6.1
Collected data can contain errors due to failures of measuring device or the recorder. So,
before using the data for specific purpose, the data have to be checked and errors have to be
removed the data have to be checked and errors have to be removed the data have to be
checked and errors have to be removed. The analysis was extended to hydrological and
meteorological data to prepare input data for water resources assessment and irrigation
water requirement estimation ..
Precipitation Data Quality and Consistency
4.6.2
Since precipitation, time series is the very important data required by the model used in this
study analyzing its quality and its consistency is essential. Quality control on available data
from each station is made to identify outliers caused by either instrumental or human errors.
Spatially homogeneous historical records were required for various hydrological applications.
Several factors other than climatic variations could also affect the spatial consistency of
records at a given station. (Subramanya K. -, 1984)
Commonly used data consistency checking method in this study was the double mass
analysis to check the spatial consistency of the rainfall data as it has wider applications in
hydrological studies and is considered to be reliable (S.L., Dingman, 2002)
The method assumes that stations have regional consistency over long times. Inconsistency
was detected by plotting accumulated annual rainfall of reference stations against
accumulated annual rainfall of the evaluation station and inspecting for abrupt changes in
slope. Slope changes are considered significant if they persist for at least five years. Kora
station used as a reference station for the double mass analysis.

33. 18
As indicated by Dingman, (2002), the adjustment procedures of the double mass analysis
method is followed to correct the observed values of these stations.
Filling Missing Data
4.6.3
Alike other meteorological data, a primary data processing on precipitation data is made by
visual inspections to identify missing data and outliers using graphical plots. The available
precipitation data from all stations have some missed data, which necessitate filling processes
for further analysis. The available methods for filling missed data include Normal ratio, and
Arithmetic average. In this study the normal ratio method is sued for filling the missing
data. This method is used when the normal average precipitation of other nearby stations
vary more than 10% of the normal average rainfall of the station where the data is missed.
Normal ratio method can be computed using the following equation bellow to estimate the
missed value on day„t‟. (Subramanya K. -, 1984) .
⌊ ⌋ Equation 4.1
Where Px is the missed precipitation data, P1,P2,….Pm are recorded precipitation
values in neighbor stations in day t, Nx is the normal average precipitation of station „x‟,
N1, N2, …. Nm is normal average precipitation of each neighbor stations and M is the
number of surrounding station.
4.7 Preparing Input Data for HEC-HMS Basin component
The process of generating input data for the basin component has the following tasks:
Terrain Pre-processing, Project Setup, Basin Processing, Stream and Sub basin
Characteristics, and Hydrologic Parameter Estimation.
I. Terrain Pre-processing
The main steps involved in terrain process are, DEM reconditioning, Fill sinks, Flow
Direction, flow accumulation, streams definition, stream segmentation, catchment grid
delineation, catchment polygon processing, drainage line processing and adjoin catchment
processing must be completed through the arc hydro tool. Finally, the results of terrain
processing were used for the following steps.
II. HMS Project Setup
The HMS Project Setup menu (Main View toolbar) contains a set of functions allowing
defining and generating a new project.Geo-HMS manages the input/output to the tools by

34. 19
using tags that are automatically assigned by the functions to the selected inputs and outputs.
HEC-GeoHMS is a set of Geographic Information System (GIS) procedures, tools, and
utilities that allow the user interactive data management and processing for use in the HEC
Hydrologic Modeling System (HEC-HMS). It allows the user to delineate sub basins from a
DEM and calculates physical characteristics used for computation of hydrologic parameters.
The GIS sub basin and stream themes are then used to generate hydrologic schematic from
which input files for HEC-HMS can be generated. The first step in the Project Setup is the
Start new project function in which the user specifies the Project Name, Extraction Method,
and Project Data Location. The add Project Point tool is then used to specify the outlet
location for the desired study area, resulting in a project area of all land draining to this
Project Point. After this is complete, the generate Project‖ function is applied and a new data
frame is created with the appropriate data being automatically imported.
III. Basin Processing
This step can be used to adjust the layout of the watershed and sub basins to be analyzed. The
first function that can be performed is Basin Merge. This function will merge several
smaller sub basins to together into one larger sub basin after vectorization. Because HEC-
HMS applies to lump models within each hydrologic element, hydrologic parameters
have to be calculated from the sub-basins and reach segments, and not for the
individual grid cells. After the reach segments and their corresponding drainage areas have
been delineated in the raster domain, a vectorization process is performed using raster-
to-vector conversion functions. The next step in the analysis process is to determine
the hydrologic characteristics of the modified sub basins and stream segments from the
previous step. The first two functions under this category are River Length and River Slope.
These populate the River attribute table with the length, upstream elevation, downstream
elevation, and slope of each stream segment feature. The average slope can also be calculated
for each sub basin using the Basin Slope function; however, before this can be done a slope
grid must first be created using the Slope function under Terrain Preprocessing.
The next part of this process incorporates the Longest Flow Path function. This uses the DEM
and Flow Direction grids created in the Terrain Preprocessing step to determine the longest
flow path for each sub basin. This function results in the creation of a new data file. Overall,
this step populated the attribute table for the River and Sub basin layers with their
respective lengths and slopes and created three new vector data files (Longest Flow
Path, Centroid, and Centroid flow Path) for further use.

35. 20
IV. Hydrologic Parameter Estimation
The final step in the analysis process is the Hydrologic Parameter Estimation, which
uses the data created in previous steps to determine the hydrologic parameters of the sub
basins that can then be exported into HEC-HMS for further hydrologic analysis. The first
step in this process is to Select HMS Processes, which specify the methods to be used in
HEC-HMS.The above Result of HEC-GeoHMS procedures are found in appendix figure 1, 2,
3 and 4.
4.8 Basin Parameter
Curve Number
4.8.1
a) Determination of Hydrological Soil Group
Hydrologic soil group of the study area was assigned through the following criteria listed in Table 4-
1.
Table 4-1 Criteria for Soil hydrological group
Hydrological soil
group
SOIL TEXTURE PROPERTY
A
Sand, loamy sand or sandy loam
type of soil
Low runoff potential and high
infiltration rate
B Silt loam, loam, or silt
Moderate infiltration rate and , fine
to moderately coarse texture
C Sandy clay loam Low infiltration rate
D
Clay loam, silty clay loam, sandy
clay, silty clay, clay
High runoff potential, low
infiltration
Curve numbers of the study area were calculated by using land use and hydrologic soil
group data described by Anderson land use codes, percentage of the hydrologic soil
group (A, B, C and D) . Criteria for selection were shown in Table 4.2.
a) Joining of the reclassified soil map and land use/land cover map
Reclassified soil map and land use land cover map were joined through union function on
ArcGIS. Then values of curve numbers were entered manually according to the criteria
shown in table 4-2. Finally weighted of curve number for the 2-sub watershed, Hargeti and
Arba Bordade were calculated.

36. 21
Table 4-2 Criteria for selection of curve number
Cover type and hydrologic condition
Hydrological
condition
Curve numbers for
hydrologic soil group
A B C D
Desert shrub—major plants include
saltbush, Greasewood, creosote bush,
blackberries, bursage, Palo Verde,
mesquite, and cactus
Good 49 68 79 84
Poor 63 77 85 88
Fair 55 72 81 86
Residential district by average lot
size(1/8 acre or less town)
77 85 90 92
Small grain contour cropped for
cultivating agriculture land
Poor 63 74 82 85
Pasture, grassland, or range—
continuous forage for grazing
Poor 68 79 86 89
Fair 49 69 79 84
Good 39 61 74 80
Brush—brush-weed-grass mixture
with a brush the major element
Poor 48 67 77 83
Fair 35 56 70 77
Good 30 48 65 73
Wood
Poor 45 66 77 83
Fair 36 60 73 79
Good 30 55 70 77
Potential Maximum Retention of watersheds (S)
4.8.2
Potential maximum retention value (S) watersheds are estimated using the following formula.
Initial Abstraction (Ia)
4.8.3
Initial abstraction value (Ia) for the watershed is computed using the following formula.
Time of concentration (Tc)
4.8.4
( )
Lag Time (TL)
4.8.5
The lag time for the watershed is computed using the following formula

37. 22
4.9 HEC-HMS Simulation
The standard SCS curve number method is based on the following relationship between
rainfall depth, P, and runoff depth. After the basin, parameters of Hargeti and Arbaa Bordade
watershed were launched on the HEC-HMS.
1. The areal rainfall data prepared for each sub watershed are entered into HEC-HMS
using the time series function.
2. All estimated sub watershed parameters (CN, Initial abstraction, Lag time) are
entered HEC-HMS using the basin model.
3. The time series data and the meteorological model are connected using the
Metrologic model on HEC-HMS.
4. The control specification is prepared before the simulation begins.
5. Finally, a simulation run is created and run.
4.10 Land Evaluation Procedure
Deciding the land utilization types (LUTs) with respect to its suitability for a given land use
is important to decide the alternative land uses (i.e. LUTs or farming systems) of interest and
prepare to evaluate each of these separately. LUTs for the study area are selected based on
farmers‟ practices in the area, land conditions and results of land evaluations conducted in the
area before. The following LUTs were selected for land evaluating.
1. Irrigated lowland maize by spate irrigation
2. Irrigated lowland sorghum by spate irrigation
Developing the land suitability class specification for various agronomic, management, land
development, conservation, environmental and socioeconomic factors, it is important to
select the relevant 'class determining' factors that can be expected to have some influence on
the suitability of land for the given LUT and that may vary from land unit to land unit.
For each selected 'class-determining' factor, it is important to determine the appropriate land
use requirement or limitation. Quantify 'critical limits' corresponding to S1, S2, S3, N1 and
N2 levels of suitability for individual land use requirements and limitations. These are the
specifications for each factor in terms of the requirements and limitations of the LUT.
In the study area appropriate land use requirements or limitations for the above selected
crops were obtained from FAO, 1985 combining individual class determining factor ratings
to obtain a tentative land suitability classification for each LUT on each land unity through

38. 23
the maximum limitation, method. The criteria adopted to evaluate land use/ land cover
suitability is shown in the Table 4-3.
Table 4-3 Land use/land cover suitability criteria
Category Name Description of land cover types
S1 Highly suitable Cultivated—dominantly, moderately,
Grassland—open, bushed, shrub bed, Bush
land—open, riparian
S2 Moderately
suitable
Woodland—open, Bush land—dense,Forest—
open
N Not suitable Cultivated—Irrigation, state farm, Woodland—
dense
Bamboo and Urban area
4.11 Irrigation Water Requirement
The following procedures were followed to estimate irrigation water requirements for
study areas.
a) Estimating Reference Evapotranspiration (ETo)
Due to lack of meteorological data, Daily ETo values for the study area was calculated by
Hargreaves method, which is temperature, based using the following equation.
⌊ ⌋
⌊ ⌋
⌈ ⌉
⌊ ⌋
b) Estimating Crop Evapotranspiration (ETc)
The cropping pattern shown in the table below was proposed after considering farmers‟
practices in the area. KC values for selected crops were obtained from the FAO

39. 24
CROPWAT8. Finally, ETc values for Hargeti watershed was computed by multiplying Kc
values with ETO values.
c) Estimating Gross Irrigation Water Requirement
The gross irrigation water requirement is computed in two conditions.
1. When daily ETc its value is greater than effective rainfall, the net irrigation
requirement is computed as follows.
Net Irrigation requirement = ETc-Effective rainfall-Soil moisture reserve of the previous day.
2. When daily ETc its value is less than the daily effective rainfall value
The net irrigation requirement is zero and the unused amount of the effective rainfall is used
to fill the soil moisture reserve 50mm Maximum soil, water-holding capacity. Finally the
gross irrigation water requirement is computed using 50% overall efficiency criteria for
surface. The result is shown in the appendix.
4.12 Estimating Irrigable Area
Potential irrigable land can be shown in two conditions
1) In terms of the available water, Irrigable land of the study area is estimated through
dividing the estimated daily discharge plus soil moisture reserve in watershed by daily
gross irrigation requirements.
2) In terms of land suitability for surface irrigation method.
Conceptual Framework
 Hydrological
data
 Metrological
Soil
map
Land
use/land
cover data
Metrological
(Climate)
data,
Available
Surface Runoff
Agronom
y data
DEM
Slop
map
Crop water
requirement
Irrigation
demand
Land suitability
Potential irrigable
area
Irrigation potential

40. 25
5 RESULT AND DISCUSSION
5.1 Testing Rainfall Data For Consistency
The double-mass curve analysis revealed that there is good direct correlation between
the cumulative rainfall at Kora station with the cumulative average rainfall at the three
stations .The result indicates that the rainfall data at Kora station is consistent as below figure
5.1 Visual inspection of the double mass curves indicated no significant inconsistency.
Figure 5-1 Double Mass Curve Of Kora Station
Due the absence of hydro-meteorological stations in Hargeti catchment the required data
obtained from nearby stations (kora, Asebot, arba bordade and Bedessa) are used in
this study. The analysis shows whether observation of the reference station represents area
precipitation in the catchment. Meteorological data for the study area is also derived from
stations around it. Such data are calculated based on their areal contribution which is
determined by Thiessen polygon method. Area weight of each station is presented in
Table 5-1 and Figure 5-2 shown that the relative position of stations and their area
coverage. Areal precipitation generated for the study area was listed in Appendix
Table 5-1 Areal weights of stations around Hargeti catchment
NAME Area (Km2
)
Areal
Weighed Area (%)
BEDESA 123.77 0.12 11.83
ASEBOT 309.65 0.30 29.75
KORA 532.48 0.48 47.59
ARBA BORDE 76.81 0.07 7.42
TOTAL 1042.71

41. 26
Table 5-2 Location maps of stations and their area coverage in the catchment.
5.2 Basin Parameters of the Study Area
Hydrologic Soil Group
5.2.1
In the study area hydrologic soil groups of „B‟ and „D‟ were found. The study
obtained that „D‟ type of HSG predominantly covers (86.6%) the study area which
mainly falls under heavy texture such as, Verti cambisol, Eptiliptic leptosols, Chromic
Luvisol, Pellic Vertisoland Eutric Vertisol. Only Eutric Cambisol falls under the B group,
which covers 13.4% of the study area. Runoff is higher in the D group as compared to B
group due to heavy texture and low infiltration capacity exhibited in-group D, shown in Table
5-3.

42. 27
Table 5-3 Hydrological Soil Group
Major Soil Hydrological soil group Area(Km2
) Area %
Eutric Cambisol B 139.8 13.421
Vertic Cambisol D 13.7 1.318
Epileptic Leptosol D 499.6 47.965
Chromic Luvisol D 124.2 11.927
Rocky Surface D 0.7 0.069
Eutric Vertisol D 176.7 16.968
Pellic Vertisol D 86.8 8.332
Figure 5-2 Hydrological Soil Group Of Study Area

43. 28
A. Land Use, Land Cover
According to Table 5-4 shown below the dominant land, covers are cultivated land, which
covers the middle part of the catchment. Such land use types results in high runoff volume.
Table 5-4 Land use cover of Hargeti watershed and Aba bordade catchment
Land use, land cover Area(km2)
Area (%)
Cultivated Land 633 61
Dense Bush Shrub Land 36 3
Dense Shrub Land 331 32
Exposed Rock Surface with scattered shrubs 1 0
Irrigated Agriculture 7 1
Open Shrub Grass Land 1 0
Open Shrub Land 26 2
Settlements 7 1
B. Curve number values
According to the table shown below, the curve number value of Arba boarded and Hargiti
catchment 76.3 and 73.8 respectively. This is because most of the catchment‟s soil is a clay
texture with low infiltration capacity and the major land use in the area is cultivated. Both
conditions result high curve number value.
Other basin parameters that are required to simulate HEC-HMS were also calculated for the
study area as shown in table 5-5 below.
Table 5-5 Calculated basin parameters
Watershed Name Arba bordede Hargeti
Average watershed slope (%) 14.3 31.5
Longest flow path in meters 45300.0 26282.0
CN 76.3 73.8
SS 78.9 90.2
Tc 8.6 4.0
Lag time 5.1 2.4
Initial abstraction 15.8 18.0

44. 29
5.3 Surface Runoff Potential
The result of total Annual surface runoff potential in Hargeti watershed, amount to 115
million meter cube (115MM3). As shown in figure and table below, there is high temporal
variability in runoff. High runoff volumes are shown in the months July, August and
September whereas very little runoff volumes are exhibited in the months of January,
February and December. Almost 50% of the annual runoff is observed in the months of July,
August and September.
Figure 5-3 Monthely Runoff Generated from Hargeti Cachment
Table 5-6 Monthly runoff Availability
MONTH MM3
PERCENTAGE
Jan 0.27 0.23
Feb 0.58 0.50
Mar 5.44 4.73
Apr 13.26 11.52
May 10.94 9.50
Jun 10.88 9.45
Jul 19.80 17.21
Aug 18.40 15.99
Sep 17.69 15.38
Oct 10.77 9.35
Nov 5.13 4.46
Dec 1.92 1.67
0
5
10
15
20
25
jan
feb
mar
apr
may
jun
jul
aug
sep
oct
nov
dec
Available Runoff(MM3)
Available Runoff (MM3)

45. 30
Only 6.3% of the total annual runoff is observed in the months of December, November,
January and February.
High temporal Ruoff variability is caused by temporal variability in precipitation and high
runoff producing characteristics of the catchment as shown in the figure 5-4 below. HEC-
HMS Simulation result for stream flow availability are found in appendix.Table -1
Figure 5-4 Areal Rianfall similarity with Runoff
5.4 Land Evaluation Results
Temperature, Soil and land slope suitability
5.4.1
As shown in Table (5-7), the temperature regimes of the study area are marginally suitable
for both the low land maize and sorghum. Based on soil suitability analysis ,Eutric cambisol
1&2, chromic luvisol-1,2&3 and Eutric vertisol-1&2 and Pellic vertisol are marginally
suitable for low land maize and lowland sorghum . Whereas Eutric cambisol -3 is unsuitable
due to steep slope.Verti cambisol is unsuitable due to its soil structure, which is unfit for
rooting conditions. Epileptic Leptosol-1&2 are unsuitable because soil unit is very
susceptible for degradation and soil depth is very shallow for selected crops rooting
condition. Epileptic Leptosol-3&4have the same limitations as Epileptic Leptosol-1&2, in
addition, these soils are also found in steep landforms, which make the area very susceptible
to degradation and difficult for management and mechanization. Chromic Luvisol are
suitable in most of the factors except that they are found on steep land forms which make the
area unsuitable due to high degradation hazard and difficulty for farm management and
mechanization.
0
20
40
60
80
100
120
140
160
jan feb mar apr may jun jul aug sep oct nov dec
Areal Rainfall Vs Runoff(mm)
Areal
Rainfall(mm)
Runoff (mm)

46. 31
Table 5-7 Suitability of Soil
Degradation Nutrient Rooting Toxicit
y
Manageme
nt
Soil
mapping
unit
mean
temp
Soil
Drainage
Soil
Unit
Texture
Slope
Texture
Ph
Organic
matter
Soil
Depth
Texture
Soil
Structure
EC
CaCO3
Slope
Texture
Over
all
suitability
based
on
limited
factor
Eutric
Cambisol-
1
S
2
S1 S1 S2 S1 S2 S1 S2 S2 S2 S2 S1 S1 S1 S2 S2
Eutric
Cambisol-
2
S
2
S1 S1 S1 S2 S1 S1 S2 S2 S1 S1 S1 S1 S2 S1 S2
Eutric
Cambisol-
3
S
2
S1 S1 S1 N S1 S1 S2 S2 S1 S1 S1 S1 N S1 N
Vertic
Cambisol
S
2
S1 S1 S2 S1 S2 S1 S2 S2 S2 N S1 S1 S1 S2 N
Epileptic
Leptosol-1
S
2
S2 N S2 S2 S2 S2 S1 N S2 S1 S1 S1 S2 S2 N
Epileptic
Leptosol-2
S
2
S2 N S2 S2 S2 S2 S1 N S2 S1 S1 S1 S2 S2 N
Epileptic
Leptosol-3
S
2
S2 N S2 N S2 S2 S1 N S2 S1 S1 S1 N S2 N
Epileptic
Leptosol-4
S
2
S2 N S2 N S2 S2 S1 N S2 S1 S1 S1 N S2 N
Chromic
Luvisol-1
S
2
S1 S1 S2 S1 S2 S2 S1 S2 S2 S1 S1 S2 S1 S2 S2
Chromic
Luvisol-2
S
2
S1 S1 S2 S2 S2 S2 S1 S2 S2 S1 S1 S2 S2 S2 S2
Chromic
Luvisol-3
S
2
S1 S1 S1 S2 S1 S2 S1 S2 S1 S1 S1 S2 S2 S1 S2

47. 32
Chromic
Luvisol-4
S
2
S1 S1 S1 N S1 S2 S1 S2 S1 S1 S1 S2 N S1 N
Eutric
Vertisol-1
S
2
S2 N S2 S1 S2 S2 S2 S1 S2 S1 S1 S2 S1 S2 S2
Eutric
Vertisol-2
S
2
S2 N S2 S1 S2 S2 S2 S1 S2 S1 S1 S2 S1 S2 S2
Pellic
Vertisol
S
2
S2 N S2 S1 S2 S2 S2 S1 S2 S1 S1 S2 S1 S2 S2
Land Cover Suitability
5.4.2
As shown in Table 5-8 and Figure 5-5, most of the catchment land cover is suitable for
irrigation because most of the land use in the area is already under cultivation. As a result,
there will not be any significant land clearing and preparation costs.
Table 5-8 Land use land cover suitability
Land Use Land Cover
Area
(km2)
Area (%)
Suitability
Range
Cultivated Land 658 63 S1
Dense Bush Shrub Land 367 35 S2
Exposed Rock Surface with scattered shrubs 17 2 N

48. 33
Figure 5-5 Land use/land cover suitability for irrigation
Slope Suitability
5.4.3
The slope has been considered as one of the evaluation parameters in the irrigation
suitability analysis. Based on the three slope classes (S1, S2, and N), the suitability of the
study area for the development of surface irrigation system is shown in Figure 5.6 and the
area coverage of the suitability classes is presented in Table 5.9

49. 34
Figure 5-6 Slope Suitability Map for Surface Irrigation
Table 5-9 Slope Suitability Range Of The Study Area For Surface Irrigation
Slope Range (%) Area (ha) % Suitability Class
0-2 7100 7 S1
2-8 32100 31 S2
> 8 65300 62 N
Total 104500 100

50. 35
The result in the above table 5.5 revealed that 7% and 32% land slope of the study area
which is 7100 ha and 32100 ha of the land , is under highly suitable to marginally suitable
for surface irrigation method. Whereas the remaining 62% of the land slope was not suitable
for surface irrigation.
The Potential Irrigable Land
5.4.4
As shown in the table: 5-10 and figure 5-7 below the result of land suitability analysis for
surface irrigation shows that 292Km2
land is marginally suitable. This marginally suitable
land is situated in the northern part of the catchment whereas the southernmost part of the
study as shown in figures below is not suitable for surface irrigation.
Figure 5-7 Irrigation Suitability Map

51. 36
Table 5-10 Provisional Irrigable Area
Area (ha) Area (%) Irrigation Suitability
29200 28 S2
74900 72 N
5.5 Irrigation Water Requirement
Irrigation water requirement were evaluated on monthly bases considering only two cropping
season as shown in Table 5-11. The result of crop water demand (CWD) as shown in figure
5.9 shows that that insufficient effective rainfall throughout the year observed thus significant
supplemental irrigation demand is needed.
Table 5-11 Existing Cropping Pattern of the Study Area
Growing period (day)
No Crop Area (%) LGP(day) Planting Harvesting
1 Tomato 100 144 9Augest 31Desember
2 Maize 50 125 Apri-1 3-Augest
3 Sorghum 50 125 Apri-1 3-Augest t
Figure 5-8 Crop water Demand Vs Effective Rainfall
0
50
100
150
200
250
300
350
400
450
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
CWD
EFFECTIVE RF

52. 37
5.6 Irrigable Area Basedon the Available Water
The potential irrigable land was estimated based on the available surface runoff generated
from Hargeti watershed. The analysis was based on monthly water demand and supply for
selected cropping pattern as shown in Table 5-11.The least irrigable area was selected as
potential irrigable area based on surface water resource potential. As shown in table 5-12
least irrigable area is found in the month of June for sorghum and maize cropping season
whereas December is the critical month for tomato cropping season. The result shows that
water resource potential is much better in sorghum and maize cropping season than tomato
cropping season. Potential irrigable land for lowland maize and sorghum cropping season
was found to be 2992.43ha and 689 ha for tomato cropping season. Totally, 3682ha of land is
irrigated by the above selected copping patterns.
Table 5-12 Potential irrigable land based on Monthly surface Runoff Availability
month Water demand m3/ month/ha Available Mm3/month potential
irrigable
land (ha)
Jan 0 0.27
Feb 0 0.58
Mar 0 5.44
Apr 0 13.26
May 2676.99 10.94 4086.03
Jun 3634.22 10.88 2993.15
Jul 1386.22 19.8 14285.53
Aug 356.77 18.4 51582.15
Sep 1471.02 17.69 12028.86
Oct 3423.25 10.77 3144.8
Nov 3372.12 5.13 1521.94
Dec 2783.04 1.92 689.2

53. 38
6 CONCLUSIONS AND RECCOMENDATION
6.1 Conclusion
This study was finalized by achieving three outputs the firs output is estimation of surface
runoff potential of Hargeti watershed, identification of potential irrigable land by spate
irrigation and estimation of crop water demand.
The result of water availability assessment indicates, high temporal Runoff variability due to
temporal variability in precipitation it show high runoff producing characteristics of the
catchment observed. High runoff volumes are shown in the months July, August and
September whereas very little runoff volumes are exhibited in the months of January,
February and December. Thus, the amount of flow varies from month to month.
The land suitability assessment result indicate 54% of soil and 38% slop of the study area
are in the range of marginally suitable for surface irrigation system In terms of land
cover/use, 63 % and 35% of land cover/use is in the range of highly to marginally suitable for
surface irrigation.
The total suitability analysis of the above factors revealed that potential irrigable land by
surface irrigation is 28% of the total area, which is, (29200ha). However, with monthly
available seasonal surface water from the catchment, 3682ha of land is irrigable within two
irrigation seasons according to the selected cropping pattern, water demand and available
surface water potential. The overall result of an assessment shows surface runoff potential of
the catchment can irrigate only 3682ha from total available land. Therefore,
6.2 Recommendation
With the available water resource and land, it is possible to increase potential of spate based
surface irrigation through water harvesting technique.
Surface irrigation land suitability analysis result indicates that only 28% of the study area is
suitable for surface irrigation. Land suitability analysis for sprinkler and drip irrigation should
be carried out to increase the land area to be irrigated.
The results of this study contribute important inputs that can be used for further
spate irrigation development within the catchment. However, detailed appraisal of land
suitability at large scale that includes assessment of the supply and quality of irrigation water,

54. 39
the environmental impact both within and outside the project area and financial/economic
analysis of the project is required for irrigation project implementation. Therefore, to take
care of the uncertainties, mechanisms such as increasing storage in the catchment in a form of
a pond and small dams, for provision of spate irrigation projects is important.
In this research, estimation of crop water requirement of identified command areas was
carried out by Hargreaves method, which is temperature, based. However, the future research
should be held by other method like, FAO Penman-Monteith method.

55. 40
7 REFERENCES
Alemayehu, T. (2008.). Ethiopia spate irrigation country profile. Oromia Water Works
Supervision and Design Enterprise. Addis Ababa, Ethiopia.
Arlen, D. (2000). Hydrologic modeling system (HEC- HMS).Technical reference manual.
U.S.Army Corps of Engineers, Washington, DC.
Chow V T, M. D. (1988.). Applied Hydrology. - New York : McGraw-.
DFID. (2004). Guidelines: Predicting and minimizing sedimentation in small Dams,
Zimbabwe and Tanzania.
Dingman. S.L (2002). Physical Hydrology. USA , Prentice Hall Inc.
El-Askari.K.(2005, - 2). Investigating the potential for efficient water management in spate
irrigation schemes using the Spate Management Model [Journal of Applied Irrigation
Science] // ./2005 : Vol. 40. - pp. 177-192..
Ephrem Kidane(2013). Assessment Of Runoff Potential And Sediment Yield Of Bililo Sub-
Catchment “The Case Of Bililo Spate Irrigation”
FAO. (1976). A Framework for land evaluation. Rome: FAO.
FAO. (1983). Guidelines: Land evaluation for rain fed agriculture. FAO soils bulletin no.52,.
FAO. (1985). land evaluation for irrigated agriculture.
FAO. (1990). Guidelines for computing crop water requirements). Rome, Italy.
FAO. (1997). Irrigation potential in Africa: A basin approach FAO Land and Water Bulletin
4.
FAO. (2010). Guidelines on Spate Irrigation. Rome: FAO Irrigation And Drainage Paper 65.
Fasina, A. S. (2008.). , Irrigation suitability evaluation and crop yield an example with
Amaranthus cruentus in Southwestern Nigeria. . African Journal of Plant Science Vol. 2 (7),
pp. 61-66, July 2008.
Frenken, A. P. (2002). Crop Water Requirements and Irrigation Scheduling. Harare,: Water
Resources Development and Management Office, FAO Sub-Regional Office for East and
Southern Africa,.

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Goldsmith. (2000). Review note on soil erosion assessment. (Unpublished project
workingpaper), Zimbabwe and Tanzania.
ICID. (2010). Guidelines for Water Management and Irrigation Development. Institute of
Hydrology. Wallingford. H.R. Wallington Ldt.
Kassa Teka, V. R. (2010). Land Suitability Assessment for Different Irrigation Methods in
Korir Watershed,. Journal of the Dry lands. Northern Ethiopia
Kebede Ganole. (2010).GIS- based surface irrigation potential assessment of river catchments
for irrigation development in dale woreda, sidama zone, SNNP.
Mohammad V. Sheikh and M. (2013). Evaluation of Reference Evapotranspiration Equations
in Semi-arid Regions of Northeast of Iran. International Journal of Agriculture and Crop
Sciences.
Negash Wagesho, 2004. GIS based irrigation suitability Analysis: A case study in
AbayaChamo basin in southern Rift valley of Ethiopia. MSc thesis, Arba-Minch
University.Ethiopia.
Seleshi. (2010). Irrigation potential in Ethiopia: Constraints and opportunities for enhancing
the system. International Water Management Institute ( IWMI), Addis Abeba, Ethiopia.
Subramanya K. (1984). Engineering Hydrology [Book]. New Delhi : Tata McGraw-Hill.
USDA-SCS. (1985). National Engineering Handbook, Section 4 - Hydrology. Washington,
D.C.
Van Steenbergen, F. H. (2009). Status and Potential of Spate Irrigation in Ethiopia.

57. 42
8 APPENDIX
Appendix Figure 1 Flow Direction

58. 43
Appendix Figure 2 Flow Accumulation

59. 44
Appendix Figure 3 Streams

60. 45
Appendix Figure 4 Catchment Polygons

61. 46
Appendix Figure 5 irrigation suitiblity map for surface irrigation

62. 47

63. 48
Appendix table Simulated Flow
Date Time
Precip
(MM) Loss (MM) Excess(MM)
Direct
Flow
(M3/S)
Baseflow
(M3/S)
Total
Flow
(M3/S)
1-Jan-93 0:00 0 0.1 0.1
2-Jan-93 0:00 0.58 0.58 0 0 0.1 0.1
3-Jan-93 0:00 8.63 8.63 0 0 0.1 0.1
4-Jan-93 0:00 0.1 0.1 0 0 0.1 0.1
5-Jan-93 0:00 0.55 0.55 0 0 0.1 0.1
6-Jan-93 0:00 0.59 0.59 0 0 0.1 0.1
7-Jan-93 0:00 0.08 0.08 0 0 0.1 0.1
8-Jan-93 0:00 0 0 0 0 0.1 0.1
9-Jan-93 0:00 0 0 0 0 0.1 0.1
10-Jan-93 0:00 0 0 0 0 0.1 0.1
11-Jan-93 0:00 0.35 0.35 0 0 0.1 0.1
12-Jan-93 0:00 0.38 0.38 0 0 0.1 0.1
13-Jan-93 0:00 0.16 0.16 0 0 0.1 0.1
14-Jan-93 0:00 0.9 0.9 0 0 0.1 0.1
15-Jan-93 0:00 0.22 0.22 0 0 0.1 0.1
16-Jan-93 0:00 0.18 0.18 0 0 0.1 0.1
17-Jan-93 0:00 0.07 0.07 0 0 0.1 0.1
18-Jan-93 0:00 2.89 2.89 0 0 0.1 0.1
19-Jan-93 0:00 0.11 0.11 0 0 0.1 0.1
20-Jan-93 0:00 0.43 0.43 0 0 0.1 0.1
21-Jan-93 0:00 0.78 0.78 0 0 0.1 0.1
22-Jan-93 0:00 0.02 0.02 0 0 0.1 0.1
23-Jan-93 0:00 0 0 0 0 0.1 0.1
24-Jan-93 0:00 0.24 0.24 0 0 0.1 0.1
25-Jan-93 0:00 0.09 0.09 0 0 0.1 0.1
26-Jan-93 0:00 0 0 0 0 0.1 0.1
27-Jan-93 0:00 0.01 0.01 0 0 0.1 0.1
28-Jan-93 0:00 0 0 0 0 0.1 0.1
29-Jan-93 0:00 0.05 0.05 0 0 0.1 0.1
30-Jan-93 0:00 0 0 0 0 0.1 0.1
31-Jan-93 0:00 0 0 0 0 0.1 0.1
1-Feb-93 0:00 0.26 0.26 0 0 0.1 0.1

64. 49
2-Feb-93 0:00 0.39 0.39 0 0 0.1 0.1
3-Feb-93 0:00 0.39 0.39 0 0 0.1 0.1
4-Feb-93 0:00 0 0 0 0 0.1 0.1
5-Feb-93 0:00 0.2 0.2 0 0 0.1 0.1
6-Feb-93 0:00 0.43 0.42 0.01 0 0.1 0.1
7-Feb-93 0:00 0.19 0.19 0 0 0.1 0.1
8-Feb-93 0:00 1.87 1.78 0.09 0.1 0.1 0.2
9-Feb-93 0:00 1.02 0.94 0.08 0.1 0.1 0.2
10-Feb-93 0:00 1.21 1.09 0.12 0.2 0.1 0.3
11-Feb-93 0:00 0.38 0.34 0.04 0.1 0.1 0.2
12-Feb-93 0:00 0.17 0.15 0.02 0 0.1 0.2
13-Feb-93 0:00 0.28 0.25 0.03 0.1 0.1 0.2
14-Feb-93 0:00 0.55 0.48 0.07 0.1 0.1 0.2
15-Feb-93 0:00 0.27 0.23 0.04 0.1 0.1 0.2
16-Feb-93 0:00 0.02 0.02 0 0 0.1 0.1
17-Feb-93 0:00 0.42 0.36 0.06 0.1 0.1 0.2
18-Feb-93 0:00 0.21 0.18 0.03 0.1 0.1 0.2
19-Feb-93 0:00 1.21 1.02 0.19 0.2 0.1 0.4
20-Feb-93 0:00 0.5 0.41 0.09 0.2 0.1 0.3
21-Feb-93 0:00 0.87 0.71 0.16 0.2 0.1 0.4
22-Feb-93 0:00 0.05 0.04 0.01 0.1 0.1 0.2
23-Feb-93 0:00 0.73 0.58 0.15 0.2 0.1 0.3
24-Feb-93 0:00 0.52 0.41 0.11 0.2 0.1 0.3
25-Feb-93 0:00 0.67 0.52 0.15 0.2 0.1 0.3
26-Feb-93 0:00 0.15 0.12 0.03 0.1 0.1 0.2
27-Feb-93 0:00 2.8 2.11 0.69 0.9 0.1 1
28-Feb-93 0:00 0.2 0.15 0.05 0.3 0.1 0.4
1-Mar-93 0:00 0 0 0 0.1 0.1 0.2
2-Mar-93 0:00 0.6 0.44 0.16 0.2 0.1 0.3
3-Mar-93 0:00 1.6 1.14 0.46 0.6 0.1 0.7
4-Mar-93 0:00 1.99 1.37 0.62 0.9 0.1 1
5-Mar-93 0:00 1.59 1.06 0.53 0.9 0.1 1
6-Mar-93 0:00 1.46 0.95 0.51 0.8 0.1 1
7-Mar-93 0:00 1.41 0.89 0.52 0.8 0.1 1
8-Mar-93 0:00 0.83 0.51 0.32 0.6 0.1 0.7
9-Mar-93 0:00 1.32 0.8 0.52 0.8 0.1 0.9
10-Mar-93 0:00 1.28 0.76 0.52 0.8 0.1 1

65. 50
11-Mar-93 0:00 1.09 0.63 0.46 0.8 0.1 0.9
12-Mar-93 0:00 2.63 1.48 1.15 1.6 0.1 1.7
13-Mar-93 0:00 1.63 0.89 0.74 1.3 0.1 1.4
14-Mar-93 0:00 0.6 0.32 0.28 0.7 0.1 0.8
15-Mar-93 0:00 6.56 3.32 3.24 4.1 0.1 4.2
16-Mar-93 0:00 2.6 1.22 1.38 2.8 0.1 2.9
17-Mar-93 0:00 3.35 1.51 1.84 2.9 0.1 3
18-Mar-93 0:00 3.04 1.31 1.73 2.8 0.1 3
19-Mar-93 0:00 4.75 1.93 2.82 4.1 0.1 4.3
20-Mar-93 0:00 3.48 1.33 2.15 3.7 0.1 3.8
21-Mar-93 0:00 3.74 1.37 2.37 3.8 0.1 3.9
22-Mar-93 0:00 2.07 0.73 1.34 2.6 0.1 2.7
23-Mar-93 0:00 1.53 0.53 1 1.8 0.1 2
24-Mar-93 0:00 5.05 1.66 3.39 4.5 0.1 4.7
25-Mar-93 0:00 1.91 0.6 1.31 2.8 0.1 2.9
26-Mar-93 0:00 1 0.31 0.69 1.5 0.1 1.6
27-Mar-93 0:00 1.73 0.53 1.2 1.8 0.1 1.9
28-Mar-93 0:00 1.45 0.43 1.02 1.7 0.1 1.8
29-Mar-93 0:00 2.88 0.84 2.04 2.9 0.1 3
30-Mar-93 0:00 1.14 0.32 0.82 1.8 0.1 1.9
31-Mar-93 0:00 2.58 0.72 1.86 2.7 0.1 2.8
1-Apr-93 0:00 2.86 0.77 2.09 3.2 0.1 3.4
2-Apr-93 0:00 1.51 0.4 1.11 2.2 0.1 2.3
3-Apr-93 0:00 2.21 0.57 1.64 2.5 0.1 2.6
4-Apr-93 0:00 2.13 0.53 1.6 2.6 0.1 2.7
5-Apr-93 0:00 4.49 1.09 3.4 4.8 0.1 4.9
6-Apr-93 0:00 1.89 0.44 1.45 3 0.1 3.1
7-Apr-93 0:00 5.15 1.16 3.99 5.5 0.1 5.7
8-Apr-93 0:00 5.58 1.19 4.39 6.8 0.1 6.9
9-Apr-93 0:00 3.26 0.66 2.6 4.9 0.1 5
10-Apr-93 0:00 4.82 0.94 3.88 5.9 0.1 6
11-Apr-93 0:00 1.89 0.36 1.53 3.4 0.1 3.5
12-Apr-93 0:00 1.75 0.33 1.42 2.5 0.1 2.6
13-Apr-93 0:00 3.51 0.64 2.87 4.1 0.1 4.2
14-Apr-93 0:00 2.29 0.4 1.89 3.4 0.1 3.5
15-Apr-93 0:00 6.61 1.12 5.49 7.5 0.1 7.6
16-Apr-93 0:00 5.11 0.82 4.29 7.2 0.1 7.3
17-Apr-93 0:00 3.66 0.57 3.09 5.6 0.1 5.7
18-Apr-93 0:00 5.14 0.77 4.37 6.7 0.1 6.8
19-Apr-93 0:00 4.79 0.68 4.11 6.7 0.1 6.8
20-Apr-93 0:00 6.98 0.95 6.03 9 0.1 9.1

66. 51
21-Apr-93 0:00 4.07 0.53 3.54 6.6 0.1 6.7
22-Apr-93 0:00 4.41 0.55 3.86 6.3 0.1 6.4
23-Apr-93 0:00 6.93 0.83 6.1 9 0.1 9.1
24-Apr-93 0:00 3.39 0.39 3 6 0.1 6.1
25-Apr-93 0:00 3.37 0.38 2.99 5.1 0.1 5.2
26-Apr-93 0:00 3.28 0.36 2.92 4.8 0.1 4.9
27-Apr-93 0:00 2.03 0.22 1.81 3.4 0.1 3.5
28-Apr-93 0:00 2.18 0.23 1.95 3.2 0.1 3.3
29-Apr-93 0:00 2.21 0.23 1.98 3.2 0.1 3.3
30-Apr-93 0:00 4.08 0.42 3.66 5.2 0.1 5.3
1-May-93 0:00 4.3 0.43 3.87 6.1 0.1 6.2
2-May-93 0:00 2.59 0.25 2.34 4.4 0.1 4.5
3-May-93 0:00 2.81 0.27 2.54 4.2 0.1 4.2
4-May-93 0:00 4.89 0.45 4.44 6.4 0.1 6.5
5-May-93 0:00 1.28 0.12 1.16 3.1 0.1 3.2
6-May-93 0:00 2.3 0.21 2.09 3.2 0.1 3.3
7-May-93 0:00 4.57 0.4 4.17 5.9 0.1 6
8-May-93 0:00 2.39 0.2 2.19 4.2 0.1 4.3
9-May-93 0:00 2.32 0.2 2.12 3.6 0.1 3.7
10-May-
93 0:00 4.43 0.37 4.06 5.8 0.1 5.9
11-May-
93 0:00 3.71 0.3 3.41 5.6 0.1 5.7
12-May-
93 0:00 2.59 0.2 2.39 4.3 0.1 4.4
13-May-
93 0:00 4.27 0.33 3.94 5.8 0.1 5.9
14-May-
93 0:00 1.94 0.15 1.79 3.7 0.1 3.8
15-May-
93 0:00 1.71 0.13 1.58 2.8 0.1 2.9
16-May-
93 0:00 2.21 0.16 2.05 3.2 0.1 3.3
17-May-
93 0:00 3.14 0.23 2.91 4.3 0.1 4.4
18-May-
93 0:00 3.69 0.26 3.43 5.3 0.1 5.4
19-May-
93 0:00 1.66 0.12 1.54 3.2 0.1 3.3
20-May-
93 0:00 2.48 0.17 2.31 3.6 0.1 3.7
21-May-
93 0:00 2.13 0.15 1.98 3.3 0.1 3.4
22-May-
93 0:00 2.99 0.2 2.79 4.2 0.1 4.3
23-May- 0:00 1.32 0.09 1.23 2.6 0.1 2.7

67. 52
93
24-May-
93 0:00 1.61 0.11 1.5 2.4 0.1 2.5
25-May-
93 0:00 2.19 0.14 2.05 3.1 0.1 3.2
26-May-
93 0:00 1.98 0.13 1.85 3 0.1 3.1
27-May-
93 0:00 3.21 0.2 3.01 4.4 0.1 4.5
28-May-
93 0:00 2.13 0.13 2 3.6 0.1 3.7
29-May-
93 0:00 2.18 0.14 2.04 3.4 0.1 3.5
30-May-
93 0:00 1.29 0.08 1.21 2.3 0.1 2.4
31-May-
93 0:00 1.84 0.11 1.73 2.6 0.1 2.7
1-Jun-93 0:00 3.48 0.21 3.27 4.6 0.1 4.7
2-Jun-93 0:00 2.93 0.17 2.76 4.6 0.1 4.6
3-Jun-93 0:00 2.68 0.16 2.52 4.2 0.1 4.3
4-Jun-93 0:00 4.45 0.25 4.2 6.1 0.1 6.2
5-Jun-93 0:00 3.16 0.18 2.98 5.2 0.1 5.3
6-Jun-93 0:00 1.75 0.1 1.65 3.3 0.1 3.4
7-Jun-93 0:00 4.23 0.23 4 5.6 0.1 5.7
8-Jun-93 0:00 1.32 0.07 1.25 3 0.1 3.1
9-Jun-93 0:00 2.3 0.12 2.18 3.3 0.1 3.4
10-Jun-93 0:00 3.3 0.17 3.13 4.6 0.1 4.7
11-Jun-93 0:00 2.39 0.12 2.27 3.9 0.1 4
12-Jun-93 0:00 2.45 0.12 2.33 3.8 0.1 3.9
13-Jun-93 0:00 2.05 0.1 1.95 3.3 0.1 3.4
14-Jun-93 0:00 2.41 0.12 2.29 3.6 0.1 3.7
15-Jun-93 0:00 1.15 0.06 1.09 2.2 0.1 2.3
16-Jun-93 0:00 1.8 0.09 1.71 2.6 0.1 2.7
17-Jun-93 0:00 3.54 0.17 3.37 4.7 0.1 4.8
18-Jun-93 0:00 2.08 0.1 1.98 3.6 0.1 3.7
19-Jun-93 0:00 2.23 0.11 2.12 3.5 0.1 3.6
20-Jun-93 0:00 3.68 0.17 3.51 5.1 0.1 5.2

68. 53
21-Jun-93 0:00 1.57 0.07 1.5 3.2 0.1 3.2
22-Jun-93 0:00 2.28 0.1 2.18 3.4 0.1 3.5
23-Jun-93 0:00 2.16 0.1 2.06 3.4 0.1 3.4
24-Jun-93 0:00 1.63 0.07 1.56 2.7 0.1 2.8
25-Jun-93 0:00 1.38 0.06 1.32 2.3 0.1 2.4
26-Jun-93 0:00 3.07 0.13 2.94 4.1 0.1 4.2
27-Jun-93 0:00 2.3 0.1 2.2 3.7 0.1 3.8
28-Jun-93 0:00 3.49 0.15 3.34 5 0.1 5.1
29-Jun-93 0:00 3.85 0.16 3.69 5.8 0.1 5.8
30-Jun-93 0:00 6.39 0.26 6.13 8.9 0.1 9
1-Jul-93 0:00 0.97 0.04 0.93 3.5 0.1 3.6
2-Jul-93 0:00 3.34 0.13 3.21 4.6 0.1 4.7
3-Jul-93 0:00 5.85 0.23 5.62 8 0.1 8.1
4-Jul-93 0:00 4.32 0.17 4.15 7.1 0.1 7.2
5-Jul-93 0:00 4.27 0.16 4.11 6.8 0.1 6.9
6-Jul-93 0:00 4.78 0.18 4.6 7.3 0.1 7.4
7-Jul-93 0:00 4.15 0.15 4 6.7 0.1 6.8
8-Jul-93 0:00 3.41 0.12 3.29 5.7 0.1 5.8
9-Jul-93 0:00 5.57 0.2 5.37 7.9 0.1 8
10-Jul-93 0:00 4.9 0.17 4.73 7.8 0.1 7.9
11-Jul-93 0:00 5.09 0.17 4.92 7.9 0.1 8
12-Jul-93 0:00 4.43 0.15 4.28 7.2 0.1 7.3
13-Jul-93 0:00 7.8 0.25 7.55 10.9 0.1 11
14-Jul-93 0:00 4.04 0.13 3.91 7.6 0.1 7.7
15-Jul-93 0:00 3.57 0.11 3.46 6 0.1 6.1
16-Jul-93 0:00 2.74 0.08 2.66 4.7 0.1 4.8
17-Jul-93 0:00 2.92 0.09 2.83 4.6 0.1 4.7
18-Jul-93 0:00 6.03 0.18 5.85 8.2 0.1 8.3
19-Jul-93 0:00 5.04 0.15 4.89 8.1 0.1 8.2
20-Jul-93 0:00 3.4 0.1 3.3 6 0.1 6.2
21-Jul-93 0:00 5.53 0.16 5.37 8 0.1 8.1
22-Jul-93 0:00 4.05 0.11 3.94 6.8 0.1 6.9
23-Jul-93 0:00 5.77 0.16 5.61 8.5 0.1 8.6
24-Jul-93 0:00 5.9 0.16 5.74 9.1 0.1 9.2
25-Jul-93 0:00 5.85 0.15 5.7 9.2 0.1 9.3
26-Jul-93 0:00 6.33 0.16 6.17 9.8 0.1 9.9
27-Jul-93 0:00 4.08 0.1 3.98 7.3 0.1 7.4
28-Jul-93 0:00 4.09 0.1 3.99 6.6 0.1 6.7
29-Jul-93 0:00 4.56 0.11 4.45 7 0.1 7.1
30-Jul-93 0:00 6.61 0.16 6.45 9.6 0.1 9.7
31-Jul-93 0:00 4.21 0.1 4.11 7.5 0.1 7.6

69. 54
1-Aug-93 0:00 7.61 0.17 7.44 10.8 0.1 10.9
2-Aug-93 0:00 3.58 0.08 3.5 7.1 0.1 7.2
3-Aug-93 0:00 3.58 0.08 3.5 5.9 0.1 6.1
4-Aug-93 0:00 3.94 0.09 3.85 6.1 0.1 6.3
5-Aug-93 0:00 2.77 0.06 2.71 4.8 0.1 4.9
6-Aug-93 0:00 2.31 0.05 2.26 3.9 0.1 4
7-Aug-93 0:00 3.85 0.08 3.77 5.5 0.1 5.6
8-Aug-93 0:00 4.71 0.1 4.61 7 0.1 7.1
9-Aug-93 0:00 4.72 0.1 4.62 7.4 0.1 7.5
10-Aug-93 0:00 5.1 0.1 5 7.9 0.1 8
11-Aug-93 0:00 2.32 0.05 2.27 4.8 0.1 4.9
12-Aug-93 0:00 3.51 0.07 3.44 5.3 0.1 5.4
13-Aug-93 0:00 5.46 0.11 5.35 7.8 0.1 7.9
14-Aug-93 0:00 6.23 0.12 6.11 9.4 0.1 9.5
15-Aug-93 0:00 5.57 0.11 5.46 9 0.1 9.1
16-Aug-93 0:00 3.75 0.07 3.68 6.7 0.1 6.9
17-Aug-93 0:00 3.38 0.06 3.32 5.7 0.1 5.8
18-Aug-93 0:00 2.3 0.04 2.26 4.2 0.1 4.3
19-Aug-93 0:00 3.47 0.06 3.41 5.1 0.1 5.2
20-Aug-93 0:00 4.04 0.07 3.97 6.1 0.1 6.2
21-Aug-93 0:00 6.96 0.12 6.84 9.8 0.1 9.9
22-Aug-93 0:00 5.97 0.1 5.87 9.7 0.1 9.8
23-Aug-93 0:00 7.73 0.13 7.6 11.6 0.1 11.7
24-Aug-93 0:00 4.42 0.07 4.35 8.3 0.1 8.4
25-Aug-93 0:00 6.85 0.11 6.74 10.2 0.1 10.3
26-Aug-93 0:00 5 0.08 4.92 8.6 0.1 8.7
27-Aug-93 0:00 3.34 0.05 3.29 6.1 0.1 6.2
28-Aug-93 0:00 3.74 0.06 3.68 6 0.1 6.1
29-Aug-93 0:00 1.93 0.03 1.9 3.8 0.1 3.9
30-Aug-93 0:00 1.36 0.02 1.34 2.5 0.1 2.7
31-Aug-93 0:00 1.53 0.02 1.51 2.4 0.1 2.5
1-Sep-93 0:00 5.11 0.08 5.03 6.7 0.1 6.8
2-Sep-93 0:00 4.64 0.07 4.57 7.3 0.1 7.4
3-Sep-93 0:00 5.09 0.08 5.01 7.9 0.1 8
4-Sep-93 0:00 4.77 0.07 4.7 7.7 0.1 7.8
5-Sep-93 0:00 4.41 0.06 4.35 7.2 0.1 7.3
6-Sep-93 0:00 4.2 0.06 4.14 6.8 0.1 6.9
7-Sep-93 0:00 5.87 0.08 5.79 8.7 0.1 8.8
8-Sep-93 0:00 2.92 0.04 2.88 5.7 0.1 5.9
9-Sep-93 0:00 3.97 0.06 3.91 6.1 0.1 6.2
10-Sep-93 0:00 6.36 0.09 6.27 9.1 0.1 9.3

70. 55
11-Sep-93 0:00 5.56 0.08 5.48 9 0.1 9.1
12-Sep-93 0:00 4.54 0.06 4.48 7.7 0.1 7.8
13-Sep-93 0:00 2.44 0.03 2.41 4.9 0.1 5
14-Sep-93 0:00 3.61 0.05 3.56 5.5 0.1 5.6
15-Sep-93 0:00 4.92 0.06 4.86 7.3 0.1 7.4
16-Sep-93 0:00 3.86 0.05 3.81 6.5 0.1 6.6
17-Sep-93 0:00 5.73 0.07 5.66 8.5 0.1 8.6
18-Sep-93 0:00 1.61 0.02 1.59 4.1 0.1 4.3
19-Sep-93 0:00 2.58 0.03 2.55 4 0.1 4.1
20-Sep-93 0:00 3.32 0.04 3.28 5 0.1 5.1
21-Sep-93 0:00 4.17 0.05 4.12 6.3 0.1 6.4
22-Sep-93 0:00 7.57 0.09 7.48 10.6 0.1 10.8
23-Sep-93 0:00 5.84 0.07 5.77 9.8 0.1 9.9
24-Sep-93 0:00 4.48 0.05 4.43 7.8 0.1 7.9
25-Sep-93 0:00 5.9 0.07 5.83 9 0.1 9.1
26-Sep-93 0:00 3.19 0.04 3.15 6.1 0.1 6.2
27-Sep-93 0:00 2.52 0.03 2.49 4.5 0.1 4.6
28-Sep-93 0:00 2.45 0.03 2.42 4 0.1 4.2
29-Sep-93 0:00 2.51 0.03 2.48 4 0.1 4.1
30-Sep-93 0:00 2.1 0.02 2.08 3.5 0.1 3.6
1-Oct-93 0:00 3.63 0.04 3.59 5.2 0.1 5.3
2-Oct-93 0:00 2.02 0.02 2 3.8 0.1 3.9
3-Oct-93 0:00 1.54 0.02 1.52 2.8 0.1 2.9
4-Oct-93 0:00 1.95 0.02 1.93 3 0.1 3.1
5-Oct-93 0:00 3.32 0.04 3.28 4.7 0.1 4.8
6-Oct-93 0:00 4.63 0.05 4.58 6.8 0.1 6.9
7-Oct-93 0:00 2.99 0.03 2.96 5.3 0.1 5.4
8-Oct-93 0:00 2.49 0.03 2.46 4.3 0.1 4.4
9-Oct-93 0:00 1.96 0.02 1.94 3.4 0.1 3.5
10-Oct-93 0:00 3.73 0.04 3.69 5.3 0.1 5.4
11-Oct-93 0:00 3.34 0.04 3.3 5.4 0.1 5.5
12-Oct-93 0:00 2.09 0.02 2.07 3.9 0.1 4
13-Oct-93 0:00 1.67 0.02 1.65 3 0.1 3
14-Oct-93 0:00 0.98 0.01 0.97 1.9 0.1 2
15-Oct-93 0:00 2.39 0.02 2.37 3.3 0.1 3.4
16-Oct-93 0:00 0.75 0.01 0.74 1.8 0.1 1.9
17-Oct-93 0:00 1.32 0.01 1.31 2 0.1 2.1
18-Oct-93 0:00 2.5 0.03 2.47 3.5 0.1 3.6

71. 56
19-Oct-93 0:00 2.58 0.03 2.55 4 0.1 4.1
20-Oct-93 0:00 3.52 0.04 3.48 5.2 0.1 5.3
21-Oct-93 0:00 4.17 0.04 4.13 6.3 0.1 6.4
22-Oct-93 0:00 1.87 0.02 1.85 3.9 0.1 4
23-Oct-93 0:00 0.48 0 0.48 1.5 0.1 1.6
24-Oct-93 0:00 4.08 0.04 4.04 5.2 0.1 5.3
25-Oct-93 0:00 1.19 0.01 1.18 2.8 0.1 2.9
26-Oct-93 0:00 4.28 0.04 4.24 5.8 0.1 5.9
27-Oct-93 0:00 1.05 0.01 1.04 2.8 0.1 2.9
28-Oct-93 0:00 2.37 0.02 2.35 3.5 0.1 3.6
29-Oct-93 0:00 1.46 0.01 1.45 2.7 0.1 2.7
30-Oct-93 0:00 3.98 0.04 3.94 5.4 0.1 5.5
31-Oct-93 0:00 1.44 0.01 1.43 3.2 0.1 3.3
1-Nov-93 0:00 1.74 0.02 1.72 2.8 0.1 2.9
2-Nov-93 0:00 1.33 0.01 1.32 2.3 0.1 2.4
3-Nov-93 0:00 0.27 0 0.27 0.9 0.1 1
4-Nov-93 0:00 0.98 0.01 0.97 1.4 0.1 1.5
5-Nov-93 0:00 2.87 0.03 2.84 3.8 0.1 3.9
6-Nov-93 0:00 0.18 0 0.18 1.2 0.1 1.3
7-Nov-93 0:00 0 0 0 0.3 0.1 0.4
8-Nov-93 0:00 0.06 0 0.06 0.1 0.1 0.2
9-Nov-93 0:00 0.9 0.01 0.89 1.1 0.1 1.2
10-Nov-93 0:00 0.51 0 0.51 0.9 0.1 1
11-Nov-93 0:00 0.59 0.01 0.58 0.9 0.1 1
12-Nov-93 0:00 2.94 0.03 2.91 3.7 0.1 3.9
13-Nov-93 0:00 0.92 0.01 0.91 2.1 0.1 2.2
14-Nov-93 0:00 0.47 0 0.47 1.1 0.1 1.2
15-Nov-93 0:00 2.09 0.02 2.07 2.7 0.1 2.9
16-Nov-93 0:00 1 0.01 0.99 1.9 0.1 2
17-Nov-93 0:00 1.05 0.01 1.04 1.7 0.1 1.8
18-Nov-93 0:00 0.61 0.01 0.6 1.2 0.1 1.3
19-Nov-93 0:00 3.2 0.03 3.17 4.1 0.1 4.2
20-Nov-93 0:00 0.22 0 0.22 1.4 0.1 1.5
21-Nov-93 0:00 1.58 0.01 1.57 2.2 0.1 2.3
22-Nov-93 0:00 2.12 0.02 2.1 3.1 0.1 3.2

72. 57
23-Nov-93 0:00 1.55 0.01 1.54 2.7 0.1 2.8
24-Nov-93 0:00 2.22 0.02 2.2 3.3 0.1 3.4
25-Nov-93 0:00 1.21 0.01 1.2 2.3 0.1 2.4
26-Nov-93 0:00 1.26 0.01 1.25 2.1 0.1 2.2
27-Nov-93 0:00 1.19 0.01 1.18 1.9 0.1 2.1
28-Nov-93 0:00 0.65 0.01 0.64 1.3 0.1 1.4
29-Nov-93 0:00 0 0 0 0.3 0.1 0.4
30-Nov-93 0:00 1.01 0.01 1 1.3 0.1 1.4
1-Dec-93 0:00 1.44 0.01 1.43 2.1 0.1 2.2
2-Dec-93 0:00 0.43 0 0.43 1.1 0.1 1.2
3-Dec-93 0:00 0.09 0 0.09 0.4 0.1 0.5
4-Dec-93 0:00 0.12 0 0.12 0.2 0.1 0.3
5-Dec-93 0:00 1.28 0.01 1.27 1.6 0.1 1.7
6-Dec-93 0:00 0.43 0 0.43 0.9 0.1 1.1
7-Dec-93 0:00 0.22 0 0.22 0.5 0.1 0.6
8-Dec-93 0:00 0.96 0.01 0.95 1.3 0.1 1.4
9-Dec-93 0:00 0.43 0 0.43 0.9 0.1 1
10-Dec-93 0:00 0.33 0 0.33 0.6 0.1 0.7
11-Dec-93 0:00 0 0 0 0.2 0.1 0.3
12-Dec-93 0:00 0.16 0 0.16 0.2 0.1 0.3
13-Dec-93 0:00 0.64 0.01 0.63 0.8 0.1 0.9
14-Dec-93 0:00 0.76 0.01 0.75 1.1 0.1 1.2
15-Dec-93 0:00 0.14 0 0.14 0.5 0.1 0.6
16-Dec-93 0:00 0 0 0 0.1 0.1 0.2
17-Dec-93 0:00 0 0 0 0 0.1 0.1
18-Dec-93 0:00 0.02 0 0.02 0 0.1 0.1
19-Dec-93 0:00 0.23 0 0.23 0.3 0.1 0.4
20-Dec-93 0:00 0 0 0 0.1 0.1 0.2
21-Dec-93 0:00 0.01 0 0.01 0 0.1 0.1
22-Dec-93 0:00 0.28 0 0.28 0.3 0.1 0.5
23-Dec-93 0:00 0.98 0.01 0.97 1.3 0.1 1.4
24-Dec-93 0:00 0.36 0 0.36 0.8 0.1 0.9
25-Dec-93 0:00 1.01 0.01 1 1.4 0.1 1.5
26-Dec-93 0:00 0.11 0 0.11 0.5 0.1 0.6
27-Dec-93 0:00 0.42 0 0.42 0.6 0.1 0.7
28-Dec-93 0:00 0.16 0 0.16 0.4 0.1 0.5
29-Dec-93 0:00 0.04 0 0.04 0.1 0.1 0.2
30-Dec-93 0:00 0 0 0 0 0.1 0.1
31-Dec-93 0:00 0.46 0 0.46 0.6 0.1 0.7

73. 58
Appendix Table 1 Soil suitability for lowland maize and Sorghum
S1 S2 N
highly suitable
moderately to
marginally
suitable
not suitable
0-400
1400-1800 over 1800
20.0-22.5 below 20.0
30.0-32.5 over 32.5
2 GROWINGPERIOD
Length of growing
period
day 120-150 90-120 below 90
400-600 below 400
900-1200 over 1200
I VP-P
SE E
Soil unit FAO unit JGRTHBLAN Q IEVZYXO
LS-SL S
SiC-C(rd) C(bl)
Stones and rock
outcrops
% 0-3 15-Mar over 15
Slope angle % 0-8 30-Aug over 30
LS-SL S
SiC-C(rd) C(bl)
5.0-5.5 below 5.0
6.7-8.0 over 8.0
Organic matter % over 3 3-Jan 0-1
Effective soil depth cm over 100 50-100 0-50
Stones and rock
outcrops
% 0-3 15-Mar over 15
LS-SL S
SiC-C(rd) C(bl)
ACr,Agr,FBl, CPr,CCo,MPl,
MBl,FPr,FCo CPl,Mas,Inc
Electrical conductivity mmhos/cm 0-4 6-Apr over 6
ESP % 0-15 15-25 over 25
CaCO3% 0-15 15-30 over 30
Slope angle % 0-8 30-Aug over 30
Stones and rock
outcrops
% 0-3 15-Mar over 30
LS-SL S
SiC-C(rd) C(bl)
CBl,MPr,MCo,
FPl
8 TOXICITES
Other limiting toxicities
9
MANAGEMENT,LAN
D PREPARATION
AND
MECHANIZATION
POTENTIAL Soil texture class L-SC
7
ROOTING
CONDITION AND
WORKABILITY
Soil texture class L-SC
Soil structure class
Soil texture class L-SC
6
NUTRIENT STATUS
AND RETENTION
Soil texture CLASS L-SC
Soil reaction pH 5.5-6.7
4 DRAINAGE Soil drainage class MW-W
Mean temperature for
growing period
o
C 22.5-30.0
3
MOISTURE
AVAILABILITY
Rainfall during growing
period
mm 600-900
1
TEMPERATURE
REGIME
Altitude m 400-1400
No LAND QUALITY
LAND
CHARACTERSTICS
UNIT
RANGES OF SUITABILITY

74. 59
Appendix Table 2Land Use/Land Cover
LUC Area KM2
suitability
Cultivated Land 633 S1
Dense Bush Shrub Land 36 S2
Dense Shrub Land 331 S2
Exposed Rock Surface with scattered shrubs 1 N
Irrigated Agriculture 7 N
Open Shrub Grass Land 1 S1
Open Shrub Land 26 S1
Settlements 7 N

75. 60
Appendix Table 3 Evapotranspiration
lat 8.9 elve 1300
GIVEN 0.082
0.155335
S.No- Year
Tmax,
oC Tmin, oC Tave (T) Elev. (Z) Jth
dr delta ωs(rad) Ra(mm/day)ETo(mm/day)
1 1/1/1993 28.01 10.97 19.49 1300.00 1.00 1.03 -0.40 1.50 13.01 4.61
2 1/2/1993 28.31 10.35 19.33 1300.00 2.00 1.03 -0.40 1.50 13.02 4.71
3 1/3/1993 29.01 10.16 19.59 1300.00 3.00 1.03 -0.40 1.50 13.04 4.87
4 1/4/1993 28.19 9.84 19.02 1300.00 4.00 1.03 -0.40 1.51 13.05 4.73
5 1/5/1993 28.08 10.59 19.34 1300.00 5.00 1.03 -0.39 1.51 13.07 4.67
6 1/6/1993 27.94 10.52 19.23 1300.00 6.00 1.03 -0.39 1.51 13.09 4.65
7 1/7/1993 28.12 10.04 19.08 1300.00 7.00 1.03 -0.39 1.51 13.10 4.73
8 1/8/1993 27.67 10.12 18.89 1300.00 8.00 1.03 -0.39 1.51 13.12 4.64
9 1/9/1993 28.03 8.75 18.39 1300.00 9.00 1.03 -0.39 1.51 13.14 4.80
10 1/10/1993 27.98 9.29 18.63 1300.00 10.00 1.03 -0.38 1.51 13.16 4.77
11 1/11/1993 28.47 10.45 19.46 1300.00 11.00 1.03 -0.38 1.51 13.19 4.80
12 1/12/1993 28.40 10.68 19.54 1300.00 12.00 1.03 -0.38 1.51 13.21 4.78
13 1/13/1993 27.88 10.07 18.98 1300.00 13.00 1.03 -0.38 1.51 13.23 4.72
14 1/14/1993 27.81 10.37 19.09 1300.00 14.00 1.03 -0.37 1.51 13.26 4.70
15 1/15/1993 28.16 11.10 19.63 1300.00 15.00 1.03 -0.37 1.51 13.28 4.72
16 1/16/1993 28.69 10.68 19.69 1300.00 16.00 1.03 -0.37 1.51 13.31 4.87
17 1/17/1993 28.76 10.93 19.84 1300.00 17.00 1.03 -0.36 1.51 13.33 4.87
18 1/18/1993 28.86 11.53 20.19 1300.00 18.00 1.03 -0.36 1.51 13.36 4.86
19 1/19/1993 28.79 11.03 19.91 1300.00 19.00 1.03 -0.36 1.51 13.39 4.89
20 1/20/1993 28.73 10.70 19.72 1300.00 20.00 1.03 -0.35 1.51 13.42 4.92
21 1/21/1993 28.39 12.28 20.33 1300.00 21.00 1.03 -0.35 1.51 13.45 4.73
22 1/22/1993 28.33 12.73 20.53 1300.00 22.00 1.03 -0.35 1.51 13.48 4.69
23 1/23/1993 29.18 11.19 20.19 1300.00 23.00 1.03 -0.34 1.51 13.51 5.01
24 1/24/1993 28.85 11.96 20.41 1300.00 24.00 1.03 -0.34 1.52 13.54 4.89
25 1/25/1993 29.28 11.65 20.47 1300.00 25.00 1.03 -0.34 1.52 13.57 5.01
26 1/26/1993 29.44 10.08 19.76 1300.00 26.00 1.03 -0.33 1.52 13.60 5.17
27 1/27/1993 29.53 10.57 20.05 1300.00 27.00 1.03 -0.33 1.52 13.63 5.17
28 1/28/1993 29.33 10.55 19.94 1300.00 28.00 1.03 -0.32 1.52 13.67 5.14
29 1/29/1993 29.53 10.00 19.76 1300.00 29.00 1.03 -0.32 1.52 13.70 5.23
30 1/30/1993 29.06 9.61 19.33 1300.00 30.00 1.03 -0.31 1.52 13.74 5.17
31 1/31/1993 27.16 7.86 17.51 1300.00 31.00 1.03 -0.31 1.52 13.77 4.91
32 2/1/1993 29.22 9.04 19.13 1300.00 32.00 1.03 -0.30 1.52 13.80 5.27
33 2/2/1993 29.02 8.65 18.84 1300.00 33.00 1.03 -0.30 1.52 13.84 5.26
34 2/3/1993 29.82 9.39 19.61 1300.00 34.00 1.03 -0.29 1.52 13.87 5.40
35 2/4/1993 29.35 9.80 19.57 1300.00 35.00 1.03 -0.29 1.52 13.91 5.29
36 2/5/1993 29.60 9.27 19.44 1300.00 36.00 1.03 -0.28 1.52 13.95 5.38
37 2/6/1993 29.69 9.88 19.79 1300.00 37.00 1.03 -0.28 1.53 13.98 5.38
38 2/7/1993 29.71 9.61 19.66 1300.00 38.00 1.03 -0.27 1.53 14.02 5.42
GIVEN
HARGREAVES