THE IMPACT OF SEDIMENT ON RESERVOIR VOLUME …

DSpace Institution

DSpace Repository http://dspace.org

Structural Engineering Thesis

2020-04

THE IMPACT OF SEDIMENT ON

RESERVOIR VOLUME CHANGE, (THE

CASE OF KOGA RESERVOIR, UPPER

BLUE NILE BASIN, ETHIOPIA)

HANIBAL, GENET

http://ir.bdu.edu.et/handle/123456789/12473

Downloaded from DSpace Repository, DSpace Institution's institutional repository

BAHIR DAR UNIVERSITY

BAHIR DAR INSTITUTE OF TECHNOLOGY,

SCHCOOL OF RESEARCH AND GRADUATE STUDIES

FACULTY OF CIVIL AND WATER RESOURCES ENGINEERING

M.SC. THESIS: THE IMPACT OF SEDIMENT ON RESERVOIR

VOLUME CHANGE,

(THE CASE OF KOGA RESERVOIR, UPPER BLUE NILE BASIN,

ETHIOPIA)

BY: HANIBAL GENET

APRIL, 2020

BAHIR DAR, ETHIOPIA

BAHIR DAR UNIVERSITY

BAHIR DAR INSTITUTE OF TECHNOLOGY,

FACULTY OF CIVIL AND WATER RESOURCES

ENGINEERING

THE IMPACT OF SEDIMENT ON RESERVOIR VOLUME

CHANGE

(THE CASE OF KOGA RESERVOIR, UPPER BLUE NILE BASIN,

ETHIOPIA).

BY: HANIBAL GENET

A thesis submitted in partial fulfillment of the requirements for the

Degree of Master of Science in Hydraulic Engineering

Advisor: Bitew Genet (Ass. Prof.)

April, 2020

Bahir Dar, Ethiopia

@2020 Hanibal Genet

iv

Abstract

Ethiopia has long since been an area strongly affected by sedimentation. Sediment

accumulation modeling in the constructed dam is an obstacle by the lack of historic

sediment concentration data in developing countries. Nevertheless, the purpose of dams is

affected by sedimentation. Water balance models then used to simulate sediment

distribution in the reservoir. This often results in the estimation of sediment variability that

is not identically distributed throughout the time. To show the temporal distribution of

sediment in the Koga reservoir water balance model was used. It is likely that the volume

of the Koga reservoir would reduce over time due to reservoir sedimentation. This reservoir

sedimentation could mean a decrease in water supply for the irrigation project in the future.

In addition, the method applies existing and future knowledge of sedimentation and annual

climate variability relative to the Koga reservoir. Data collection of hydrology,

meteorology, and irrigation water supply for the project site have been statistically

compared and arranged as an input data source to fit the model. The volume change was

incorporated into the water balance model. According to the water balance model result a

reservoir volume reduction of 0, 5, 10, and 15Mm3 leads to minimum water storage of 6.7,

4.8, 2.9, and 0 Mm3 respectively in May. Because the minimum result appears just the end

of the winter season as this is the time of year when the reservoir has been in the largest

use. The thesis result shows sediment accumulation increase reservoir storage volume

decrease. From this study, it is possible to be concluded that the dam is capable of providing

enough irrigation water around 2027 E.C.

Keywords: dam, Sediment rate, Koga Reservoir, Useful period, water balance model

v

Acknowledgment

Much appreciation is expressed for my advisors Mr. Bitew Genet. (Ass. Prof.), his smart

and sweet advice put me on the journey of education and assisted me to begin this final

thesis. Again, I would like to express my thanks to the Ministry of Water, Irrigation, and

Energy for the data assistance given me in data collection. Acknowledgment is expressed

to the staff of Amhara Water Works Design and Supervision Enterprise and Amhara Water

resource and Energy bureau. Special thanks are due to my colleagues, family, relatives,

and friends for their cooperation to accomplish this study. Finally, I am also thankful to all

those who are not mentioned here but have helped and supported me in order to achieve

this research work successfully.

vi

List of Abbreviations

BNB Blue Nile Basin

GDP Gross Domestic Product

GIWR Gross Irrigation Water requirement

FAO Food and Agriculture Organization

ICTZ Inter-Tropical Convergence Zone

IPCC Intergovernmental Panel on Climate Change

Kc Crop coefficient

Kms Kilometers

m Meter

masl Mean Above Sea Level

mm Millimeter

Mm3 Million meter cube

M3/s Meter Cube per Second

MoWIE Ministry of Water, Irrigation, and Electricity

NMSA National Meteorological Services Agency

SN Scenarios

SRES Special Report on Emission Scenario

WEAP Water Evaluation and Planning System

WWDSE Water Works Design and Supervision Enterprise

NSR Night Storage Reservoir

vii

Table of Contents

Declaration ......................................................................... Error! Bookmark not defined.

Abstract .............................................................................................................................. iv

Acknowledgment .................................................................................................................v

List of Abbreviations ......................................................................................................... vi

List of Figure.......................................................................................................................x

List of Tables ................................................................................................................... xiii

1. Introd1uction ....................................................................................................................1

1.1. Back ground ..............................................................................................................1

1.3 Statement of the problem ...........................................................................................2

1.4 Scope of the Study......................................................................................................3

1.5 Significant of the Study ..............................................................................................3

1.6 Research questions .....................................................................................................4

1.7 Objectives of the Study ..............................................................................................4

1.7.1 General objective .................................................................................................4

1.7.2 Specific objectives ...............................................................................................4

1.8 Thesis outline .............................................................................................................4

2 Literature review ...............................................................................................................4

2.1 Sedimentation on Koga reservoir volume change......................................................4

2.2 Reservoir lifetime .......................................................................................................5

2.3 Crop Water demand ...................................................................................................5

2.4 Climate Change Impacts on Reservoir .......................................................................7

2.5 Decreasing Sediment Inflow into the Reservoir ........................................................7

2.6 Suggested and real cropping system ..........................................................................8

2.7 Users Bias on cropping system ....................................................................................10

viii

2.8 The Dam and reservoirs ...........................................................................................10

2.9 The project area and the canal ..................................................................................11

3 Materials and Methods ....................................................................................................13

3.1. Description of the Study Area .................................................................................13

3.2 Location ....................................................................................................................13

3.3 The hydrology and geology of Upper Blue Nile Basin ............................................14

3.4 The geology of the UBNB can be divided into three different part:- ......................14

3.5 Climate and rainfall data ..........................................................................................15

3.6 The water balance Model and its components .........................................................16

3.6.1 River discharge Inflow (Qin) .............................................................................18

3.6.2 Rainfall (P) ........................................................................................................19

3.6.3 Evaporation (E) of the Bahir Dar, Merawi, and Koga site ................................20

3.7 Outflow (Qout) ...........................................................................................................23

3.7.1 Release discharge for Maintenance and sediment flushing ...............................23

3.7.2 Environmental compensation flow ....................................................................23

3.7.3 Irrigation water release flow .................................................................................26

3.7.3.1 Crop water demand (CWR) analysis ..............................................................26

3.7.4. Secondary data collection.....................................................................................28

3.7.5 Data analysis techniques .......................................................................................28

3.8 Model scenarios........................................................................................................28

3.8.1 Model Scenario 1 ...............................................................................................29

3.8.2 Model Scenario 2 ...............................................................................................29

3.8.3 Model Scenario 3 ...............................................................................................29

3.8.4 Model Scenario 4 ...............................................................................................29

4 Model scenarios Results and discussion .........................................................................30

4.1 Model scenarios Results ...........................................................................................30

ix

4.1.1 Scenario 1 Reservoir volume under normal states ............................................30

4.1.2 Scenario 2 reservoir volume change by 5Mm3 ..................................................30

4.1.3 Scenario 3 reservoir volume change by 10 Mm3 ...............................................31

4.1.4 Scenario 4 reservoir volume change by 15 Mm3 ...............................................32

4.2 Model scenario Discussion ......................................................................................33

4.2.1 Model scenario 1 Reservoir volume under normal states ..................................33

4.2.2 Model Scenario 2 reservoir volume change by 5Mm3 ......................................34

4.2.3 Model Scenario 3 reservoir volume change by 10Mm3 ....................................35

4.2.4 Scenario 4 reservoir volume change by 15Mm3 ................................................36

4.2.5 Model scenario summary ...................................................................................37

5. Conclusion and recommendation ...................................................................................39

5.1 Conclusion ................................................................................................................39

5.2 Recommendations ....................................................................................................40

6. Reference .......................................................................................................................41

7. Appendix ........................................................................................................................60

Appendix A ....................................................................................................................60

x

List of Figure

Figure 1 Area coverage of dry season cropping system ......................................................9

Figure 2 the percentage and project area for each crop .......................................................9

Figure 3 the current dry season percentage of the project area for each crop. ..................10

Figure 4 the Koga reservoir and irrigation location. ..........................................................13

Figure 5 Merawi meteorological stations Tmax and Tmin. ...............................................15

Figure 6 Merawi meteorological stations rainfall and eto. ................................................16

Figure 7 Reservoir inflows and outflows; parameters for the water balance model .........17

Figure 8 Monthly Qin values used in the water balance model. ........................................19

Figure 9 Monthly Precipitation values used in the water balance model. .........................20

Figure 10 Monthly evaporation values used in the water balance model ..........................21

Figure 11 Comparison of monthly Eto, Ecal, and Koga E of the site. ...............................23

Figure 12 Water released from the reservoir for environmental compensation flow for each

month given in Mm3 (Ministry of Water Resources, 2006). .............................................25

Figure 13 Water released reservoir for partial environmental compensation release flow for

each month given in Mm3 (Ministry of Water Resources, 2006). ....................................25

Figure 14 Comparison of crop irrigation water demand CIWR from the design report

scenarios .............................................................................................................................27

Figure 15 Reservoir volume under normal states ..............................................................30

Figure 16 gives reservoir volume reduction by 5Mm3 for each month as computed in the

water balance model. .........................................................................................................31





Figure 19 Reservoir volume under normal state ................................................................34

xi

Figure 20 Reservoir volume by 5Mm3 reduction ..............................................................35

Figure 21 volume reductions Reservoir by 10 Mm3. ........................................................36

Figure 22 Reservoir volume by 15Mm3 reduction ............................................................37

Figure 23 summary of volume change due sediment accumulation in different year from

scenario 1-4 ........................................................................................................................38

xii

List of Tables

Table A1 suggested cropping plan for the wet and dry season (Ministry of Water

Resources, 2006) ................................................................................................................60

Table A2 Actual cropping pattern for dry season (Ministry of Water Resources, 2006). .60

Table A3 dry season proposed cropping system (%).........................................................60

Table A4. Reservoir simulation runs. PIA is the potential irrigated area in hectares

(Ministry of Water Resources, 2006) .................................................................................61

Table A5. Command Areas and their Sizes (Ministry of Water Resources, 2006). The

addition of the Tekel Dib extension area is designed for the future. .................................61

Table A6 Comparison of monthly evaporation between Bahir Dar meteorological station,

calculated and the Koga site. .............................................................................................62

Table A7 Data for Koga river inflow given by design reports Nile (Mott MacDonald, 2004)

............................................................................................................................................62

Table A8. Precipitation data for Bahir Dar (Ministry of Water Resources, 2004). ...........62

Table A9 Crop Water Usage Values estimated by Mott MacDonald in the project

report ..................................................................................................................................63

Table A10 these different scenarios modify the variables in the water balance equation to

represent changes in sedimentation. ..................................................................................63

Table A11 these different scenarios modify the variables in the water balance equation to

represent the partial environmental release. .......................................................................64

Table A12. Monthly compensation flows (Ministry of Water Resources, 2006). .............64

Table A13 Data for Crop Water Usage Calculations (Ministry of Water Resources,

2006) ..................................................................................................................................65

Table A14 Scenarios I-IV net irrigable are and. GIWR of the whole irrigated area (Ministry

of Water Resources, 2008). ................................................................................................67

xiii

Table A15 Growing season lengths in months and total irrigation water requirements in

mm for selected crops as estimated by ..............................................................................69

Table 16 Area covered by each crop ..................................................................................69

Table 17 Average monthly crop water requirement of cultivated crops in the project .....70

1

1. Introd1uction

1.1. Back ground

Ethiopia has long since been an area strongly affected by drought. Although there is a

relatively large amount of fresh water present in the country, (110 billion m3 of water are

discharged out of the country each year) variability in rainfall and lack of infrastructure

lead to the result that most of the population is undersupplied with water (Marx, 2011).

The upper Blue Nile Basin, known as the Abay River Basin in Ethiopia, has an estimated

irrigation potential of 760,000 ha yet actual irrigated land use was measured to be a mere

30,000 ha (Moges, 2010). Dam building balances the increased flow depth and decreased

flow velocity of a reservoir reduces the sediment transport capacity and causes

sedimentation. Silts carried into a reservoir may deposit throughout its full volume, thus

rapidly raising the bed elevation and causing addition. The layer of deposition generally

starts with a deltaic formation, mainly contains coarser sediments in the reservoir bed level.

The flow currents may transport finer sediment particles down to the reservoir. Reservoir

sediment accumulation was a complex process that varies with catchment sediment yield,

rate of motion, and form of accumulation. Reservoir silt accumulation depends on the river

morphology, flood occurrence, reservoir dimension and operation, flocculation potential

silt deposition, flow density currents, and possible watershed changes over the life

expectancy of the reservoir (Raghunath, 2006).

Agriculture employs 85% of the workforce in Ethiopia (CIA World Fact Book, 2012)

and is the largest economic activity (as of 2004) at 46.3%, with services being the second

most prominent at 41.2% of a Gross Domestic Product (GDP) per capita of 1000 USD (UN

Ethiopia, 2012). Despite this fact, the productivity of agriculture in Ethiopia is only 1.2

tons per ha, one of the lowest in the world making food security a serious problem for a

country with a fast growing population(Marx, 2011).

Development of irrigation projects is listed as a prime tool to ensure food security at the

household level. The Ministry of Water Resources sees expansion of irrigated agriculture

as a way to provide food security for a fast growing population. The Koga Dam is a key

project for the Ethiopian government, as a step towards achieving food self-sufficiency at

2

both national and regional levels for a country that has a history of draughts and famine

(Ministry of Water Resources, 2004). Population growth in Ethiopia is projected to be 2.5%

per year, while growth of crop yields is only increasing 1.4% per year (1960-2001),

creating a declining food availability per capital from domestic production(Ministry of

Water Resources, 2008).

On the household step, farmers in the Koga region stand to gain a lot of advantage from

this large irrigation system. The average landholding is 1.68 ha with this size of command

area, a family using a rain-fed irrigation system can have a net income of around 6000

Ethiopian birrs. But in the irrigated system, net income increases to 20000-26000 birr,

about four times as much as under the rain-fed system(Marx, 2011). Sedimentation is a

problem for many reservoirs around the world, and especially in this region. The volume

of the Koga reservoir will likely decrease over time due to reservoir sedimentation. An

enhanced variability in sediment is also predicted for the region which could mean years

with below-average rain. Damming of rivers causes major changes concerning water

availability in the watershed, for example, evaporation increases while runoff decreases.

All crops in the Koga site require water for irrigation during the Dry Season (vorosmarty,

1997).

For this site, it is important to know the irrigation water volume of the reservoir in order to

plan what crops to grow and how much land can be irrigated, which depends on the amount

of irrigation water available in the reservoir. This thesis aims to see the way the change in

maximum reservoir volume, in addition to a change in temperature, precipitation, and

evaporation, affected the irrigation water volume of the reservoir. When reservoir volume

reaches zero and is unable to supply any water is of special interest. An annual water

balance assessment of the Koga dam throughout the entire course of a hydrologic year was

done in order to estimate current and future annual changes in the reservoir’s volume.

Water is not only influenced by human activities, but also by natural factors, such as

temperature, precipitation, and evaporation change (IPCC, 2007).

1.3 Statement of the problem

Reservoir sedimentation is a harmful off-site cause of climate change with large

environmental and economic factors. The threat of sedimentation problems and

3

management methods vary widely from time to time. In the case of the Koga reservoir,

there is an inflow of a huge amount of sediment to the reservoir because of agricultural use,

domestic water supply, deforestation, overgrazing, and geological formation. The research

to study reservoir siltation and sediment change of a dam is a huge challenge for a hydraulic

engineer to determine the useful life of a designed structure and to predict the amount of

sediment settle in the reservoir.

1.4 Scope of the Study

This research was carried out at The Koga reservoir which was built on the Koga River,

about 35km south of the city of Bahir Dar and Lake Tana, outside the village of Merawi,

in the West Gojam zone of the Amhara region. The focus of this study was mainly on

computing the decrease of the reservoir volume due to sediment increase and to compare

the supply irrigation water volume of the reservoir with the crop water requiremen in

order to know a critical/minimum / reservoir supply volume for a given month.

1.5 Significant of the Study

Knowing about the effect of sediment change helps to take a lot of measures that protect

sediment yield entering into the Koga reservoir. The thesis was created announcement for

the farmer and the government to know about the role of sediment change on sediment

yield in the reservoir. In addition to that, the research will give warnings to the farmer and

the government to do different watershed protection activities to control the role of

sediment yield in the reservoir for the future. However, sediment variation would further

obliterate the periodic and chronic shortfall of water and result in repeat droughts in some

places in some time maybe a month. Research on sedimentation problems is important for

the user to know the current and future crop cover and supply irrigation water resources.

Promisingly my work would be an input for the responsible persons in the management,

crop pattern, and further building of the suggested new dam. It also had its own significance

towards the local farmer economy by the proper management of the watershed. This work

was intended for the user by Engineers, Scientists, and water Resource Managers to support

in formulating sediment management plans for reservoirs, in order to satisfy the objective

of plan a reservoir sustainable.

4

1.6 Research questions

What are the effects of sediment change on the reservoir volume?

How to estimate reservoir volume by using the the water balance model?

1.7 Objectives of the Study

1.7.1 General objective

The general objective of this study is to investigate and analyse the impact of sediment

accumulation on koga reservoir.

1.7.2 Specific objectives

To determine the temporal distribution of sediment deposition in the reservoir.

To identify the critical water shortage month in the reservoir.

To evaluate impact of sediment change on reservoir

To evaluate capacity of reservoir to support the command area

1.8 Thesis outline

The final thesis composed of eight main titles and each title has a section and sub-section

to describe the contents i.e.:-

Section1: Introduction

Section 2: Literature review: - Insight learning all research review.

Section 3: Methods/methodology (description of the study area, method, and materials).

Section 4: Result and Discussion: - Result obtained by water balance model including

predicting the use full life of the reservoir, sediment yield estimation from the reservoir,

current and future sediment deposited volume and their discussion.

Section 5: Conclusions and recommendations.

Section 6: References and Section 7 appendixes.

2 Literature review

2.1 Sedimentation on Koga reservoir volume change

Sediment travels in the stream as suspended load (fine particles) in the flowing water, and

as bed load (large particles), which moves along the channel bottom. Sometimes, the

5

particles (small particles of sand and gravel) roll by bouncing along the bed, which is

known as ‘saltation’, which is a critical stage between the bed and suspended load. The

particle, which travels as bed load at one section may be in suspension at another section.

At the time sediment-laden water reaches a reservoir, the velocity and turbulence are

greatly minimized. The dense fluid-solid composition along the bottom of the reservoir

travels slowly in the form of a density current or stratified flows, i.e., a diffused colloidal

suspension having a density that slightly varies from that of the main body of reservoir

water, due to dissolved minerals and temperature, and hence does not diffuse readily with

the reservoir water (IPCC, 2007).

Smaller particles may be settled near the base of the reservoir. Some of the density currents

and settled sediments near the base of the reservoir can be flushed out by operating the

sluice gates. The modern multipurpose reservoirs are operated at different water stages,

which is high in the deposition and movement of silt in the reservoir (Raghunath, 2006).

2.2 Reservoir lifetime

The capacity of the reservoir can also be minimized by sediment accumulation. This

happens because the flow velocity reduces when the water passes through the reservoir.

The consequence is reservoir volume minimization, and the maximization of life

expectancy of a reservoir is therefore limited. The design of a dam is based on future time,

important demographic and hydrological parameters, but with the present evidence of

climate change, such design could be a shortage if supply and demand condition varies.

One way of exercising if the reservoir is inadequate is to enlarge the reservoirs, if it is

topographically and hydrologically feasible(Britannica, 2010).

2.3 Crop Water demand

The quantity of irrigation water taken from the reservoir each month depends upon the

irrigation water requirements of the crops grown in the irrigable areas, as well as the

irrigation methods used. The way used to irrigate the fields in the Koga project area and

has a predicted efficiency of 50% (USGS, 2000). This means the water supplied for

irrigation will be smooth twice the evapotranspiration of any given crop. The gross

irrigation water demand (GIWR), the total amount of water required for irrigating, is

affected not only by the amount of precipitation available to the crops but also depends

6

upon what type of crop is irrigated how much area is under irrigation, and in what relation

crops are irrigated. All crops had different water demands due to different natural amounts

of evapotranspiration. Crops irrigated in the irrigable areas include wheat, maize, potato,

green pepper, onion, barley, beans, haricot beans, abish, fasolia, cabbage, tomato, carrot,

beatroot, teff, shallots, millet, noug, and garlic. Furrow irrigation is one of the oldest ways

to irrigate, probably the first system used by humans, and is still largely in use today

(USGS, 2000).

It includes transport of water to the field through farmer dug ditches in the case of the Koga

reservoir irrigable area (field observation). The water then travels the field between the

rows of crops and is absorbed by the crops after infiltrating the soil. Furrow irrigation is

less effective than other systems of irrigation such as drip irrigation. It is predicted that

only 50% of the water used in-furrow irrigation feeds the crop. Much amount is loosened

by the runoff, evaporation, and infiltration of uncultivated areas (USGS, 2000). In the Koga

irrigation project area, furrow irrigation is the system used due to the fact that it is relatively

easy and cheap. The efficiency of water use in irrigation is governed by three root zone

processes; macropore formation, fertilizer application systems, and depth of root uptake.

Knowledge of macropores from root decay and wormholes enhances the flow rate through

the soil and channelize the flow, and make the infiltration less uniform as the flow is

channelized. Macro pores called planar voids have also happened from soil expansion and

contraction cycles that affect water motion. The depth at which roots needed the most water

can be quickly controlled by plants in response to irrigation. When the irrigation water is

applied, near the surface roots become most active created that the volume of water

extracted by roots is much near the surface and shows a decreasing trend with depth.

Fertilizer use in the Koga command area is reduced (Clothier, 1993).

In the study on the efficient use of irrigation water done by (Clothier, 1993). It was

concluded that the most efficient system of irrigating plants that depend on the three root

zone processes stated above was to use little amounts of water and irrigate repeatedly. If

flood irrigation is used such as in the Koga watershed, then the soil should be controlled in

a way that micropores are eliminated or decreased before irrigation. Drainage loss from

micro pores controls two problems; both the loss of water from the root zone that could

7

have been used to grown crops and the enhanced pollution of ground- and surface water

sources (Clothier, 1993).

2.4 Climate Change Impacts on Reservoir

Water is communicated in all parameters of the climate system. Findings of the (IPCC,

2001) high suggests that water resource answered to the global warming in ways that

negatively impacted the water availability and water supplies. The decrease in the runoff

volume will lead to the reduction in the inflow to the reservoirs accordingly; a longer period

might be needed to fill the reservoir. As the result of the enhance in temperature, the rate

of evaporation from the reservoir open water surface may maximum and this may occur

the reservoir to fail to supply at least enough amount of water required because of its

shortage in the active storage water stage (Habtom, 2009).

The most acciaccatura climate drivers for water accessibility are rainfall, temperature, and

Evaporative (justified by net radiation at the ground, atmospheric humidity and wind speed,

and temperature). Water evaporated from the surface and transpired from plants called

evapotranspiration rises with air temperature. These make a huge decrease in runoff and

increase water shortages as a result of a combination of increased evaporation and reduced

precipitation. The repeated and severity of droughts could increase in some areas as a result

of a decrease in precipitation, more frequent dry spells, and higher ET (Kenneth, 1997).

2.5 Decreasing Sediment Inflow into the Reservoir

Sediment accumulation in reservoirs cannot be actually controlled but it can be reduced by

exercising some of the following measures:

I. Reservoir area, which are productive sources of sediment should be avoided.

II. Adopting soil-conservation mechanism in the watershed, as the silt originates in the

catchment area.

III. Agronomic soil conservation methods like cover cropping, strip cropping, contour

farming, suitable crop rotations, application of green manure (mulching), proper control

overgraze lands, terracing, and benching on steep hill slopes, etc. retard overland flow,

increase infiltration and decrease erosion.

IV. Contour trenching and afforestation on hill slopes, contour bundling gully plugging by

check dams, and stream bank control by the use of spurs, revetments, vegetation cover, etc.

are the main engineering measures of soil conservation mechanism.

V. vegetation cover on the land decreases the impact force of raindrops and reduce erosion.

8

VI. Sluice gates constructed in the dam at the various stage and reservoir operation, allow

the discharge of fine sediments without giving them time to reach the bottom.

VII. Sediment accumulation in tanks and small reservoirs may be avoided by excavation,

dredging, draining, and flushing either by mechanical or hydraulic methods and sometimes

may have some sales value.

2.6 Suggested and real cropping system

There is two crop period in a year, one classifying under the rain-fed summer season, and

the other classifying under the winter season that is only made possible by using irrigation.

The weather in the Koga command area is controlled by the motion of the ITCZ and like

most tropical regions it adopts a summer season (June-September) and dry season other

than the wet period. The precipitation during the summer season is assumed to be sufficient

to supply all of the crop water requirement, so no additional irrigation from the dam is

planned during the peak of the rain season. The consultants for the Koga irrigation project,

Mott MacDonald, provide that the crops irrigated during the summer season should have

short growing times in order to reduce the amount of irrigation water required at the end

of the wet season when the rainfall reduces below levels that can support rain-fed irrigation

(Ministry of Water Resources, 2004).

The suggested proportion of crops for each growing season in order to maximize profits

and reduce irrigation water requirements differs smoothly from the real cropping pattern

in place due to variation in crop prices and farmers' personal decisions. The suggested

cropping plan for the summer season and real cropping for the dry season is given in Figure

1-3 below. Values are also listed in Appendix A Tables A1, A2, and Table A3 wet and dry

season suggested cropping system and dry real cropping system respectively (Ministry of

Water Resources, 2006).

The proposed cropping pattern for the wet season is comprised of maize, millet, noug, and

teff. Most of the command area during the current dry season was irrigated with potato,

wheat, barley, maize, onion, and garlic. Crop distribution is different over the whole

command area as farmers ultimately choose what they wish to irrigate. There may also be

smooth differences between irrigable areas in soil quality influencing which crop is most

productive. Each irrigable area, therefore, has a different crop composition distribution to

the total ratios of crops throughout the whole command area. The actual amount of area

9

sown was less than the designed amount of the full 7000 hectares as this is the first year

that the project is fully operational and irrigation method efficiency, as well as farmer

competence, were still not perfect (IPCC, 2001).

Figure 2 the percentage and project area for each crop

20%

20%

20%

40%

wet season suggested cropping system(%)

maize

millet

noug

teff

Figure 1 Area coverage of dry season cropping system

16%

47%12%

7%

18%

dry season suggested cropping system(%)

potato

maize

shallote

peppers

10

Figure 3 the current dry season percentage of the project area for each crop.

2.7 Users Bias on cropping system

The Koga irrigation project office in Malawi does a planed what crops to grow each season

based upon market prices and water usage and supplied a list of possible crops to be

irrigated to the users. The users then make the final adjustment of what they will grow by

deciding from this list. A combination of reference from the project office and farmer

education concerning water efficiency would hopefully put a huge emphasis on efficient

water use when adjusting what crops to irrigate in the future. Users choose what crops to

irrigate each season based on many factors, practices with the crop, seed availability, labor

availability, environmental factors such as soil conditions and climate, government

policies, and availability for their consumption. Nevertheless, the huge factor influencing

their decision is relative productivity. For the Koga irrigation project users, the most

sufficient crop in terms of net returns per area is wheat (Ministry of Water Resources,

2008).

2.8 The Dam and reservoirs

The Koga dam is constructed on the Koga River, a tributary of the Upper Blue Nile

releasing into Lake Tana in Northern Ethiopia. The Koga river is the only river that

releasing water into the reservoir, which upon completion, had a volume of 83.1 Mm3 and

a surface area of 1750 ha ( Marx, 2011).

31.37

19.556

3.2310.1740.108

0.011

0.005

41.559

0.55

0.2290.001

0.004

1.215 1.378 0.601

dry season real cropping system(%)

wheat

Barely

Maize

bean

haricot bean

abish

fasolia

11

There are two outlets in the reservoir to give three purposes:- The first is the bottom outlet,

which uses as an emergency and environmental outlet. The maximum discharge from this

outlet is 31m3/s which is used to release the flow during emergencies or for maintenance.

Water may be flow for maintenance purposes in order to do maintenance on the dam

structure or to release out settled sediment. Sediment releasing happens once a year and

operates at maximum discharge for 30 minutes, releasing 55,800 m3 of water. When

maintenance does not happen, this outlet is used for environmental monthly balanced

flows. These flows change depending upon the month in the amount of water discharged.

Nevertheless, the outlet is set at a max discharge rate of 1m/s The reservoir covers a total

command area of 7000 ha (Ministry of Water Resources, 2008).

The second outlet in the dam uses the irrigation canal (Andualem, 2012). According to a

report from United Nations Environment Programm (UNEP, 2000) called “Climate

variability and Dams”, dams have two roles regarding climate change. They can be a source

of greenhouse gases; both carbon dioxide and, if the water at the bottom of the reservoir

becomes anaerobic, they could also emit methane gas. Another aspect of dams is that they

can be used as flood control infrastructures and if precipitation intensity increases due to

climate variability such infrastructure can save lives. A similar report tells that dams

themselves are affected by climate variability. High temperatures create high evaporation

and increased precipitation intensity would enhance the sediment transport to dams. Both

of these impacts decrease the capacity of the dam(UNEP, 2000).

2.9 The project area and the canal

The main canal receives water from the reservoir at a maximum rate of 9.11m3/s. Which

supply a series of 10 secondary canals it then provides water to multiple tertiary canals.

User dug quaternary canals transport water from the tertiary canals to the fields (site

observation). The Koga irrigation command area can be broken into four different units.

Arranging from largest to smallest, these are:- Command areas, Blocks, units, and Fields.

Command/irrigable/ areas are irrigated by a secondary canal dividing on of the main canal.

Then it is made up of blocks and can be anyplace from 220 ha to more than 1000 ha. Blocks

are areas feed by tertiary canals that receive water from the secondary canals. Blocks are

made up of multiple units and their size is different, from>100 ha to between 20 and 65 ha

12

in size. Units are groups of fields and can be the product of 2 or 4. Nevertheless, ideally

made up of 8 fields and ranges from 8 to 16 ha in size. Fields are the smallest unit in the

command area, usually, 2 ha in size, and Fields are irrigated using furrow

irrigation(Ministry of Water Resources, 2008).

All of the fields within a unit would be irrigated on a periodic cycle during which each

field is irrigated once every 8 days. If a unit is smaller than 8 fields, irrigation water coming

into the unit would be blocked off after all fields have been irrigated and the additional

water has used another place in the block until it is time for the periodic to begin again. At

max crop supply, fields operate on a schedule of 12 hours of irrigation from the irrigation

stream (Ministry of Water Resources, 2004).

Night Storage Reservoirs (NSR) are another design feature found in the command area and

control how much water is usable in the secondary canals, effectively doubling the amount

of water used from the main canal (Ministry of Water Resources, 2004). The discharge

from the NSR provides 50% of the maximum required to discharge for the fields. The

additional 50% comes directly from the main canal (Lema, 2012).

Table A3 in Appendix A lists the different command areas and their sizes. In addition to

these two outlets, there is a spillway in the place, if the dam volume should reach more

than its full volume of 83.1 million cubic meters (Mm3), excess water would be flushing,

thus keeping the reservoir volume from filling overcapacity. The Ministry of Water

Resources in Ethiopia has predicted in its Cost Recovery Study for the Koga Irrigation

Project that the irrigation demand of this area of 7000 ha can be fully met if the volume of

the reservoir is in 80 Mm3 and the rest is dead storage for aquatic life i.e 3.1 Mm3. Table

4 in Appendix A, gives values for 10 different model runs done by the Koga engineers

showing the potential irrigation area in ha for the reservoir with 80% reliability. Averaging

all these runs gives a value of 6665.4 ha for the amount of area that could potentially be

irrigated. This is less than the original value of 7000 ha. If these estimations are correct

then the reservoir could be at risk if the volume were to decrease The design volume of the

reservoir is over this recommended value (Ministry of Water Resources, 2006).

13

3 Materials and Methods

3.1. Description of the Study Area

3.2 Location

The Koga catchment lies within the UBNB, in the headwaters of the Upper Blue Nile

Basin. Monthly flow throughout the year varies with the precipitation system and thus the

minimum flow turnaround is during April and the maximum flow turnaround is during

August. The Koga reservoir was built on the Koga River in the Koga watershed, about

35km south of the city of Bahir Dar and Lake Tana, outside the village of Merawi, in the

West Gojam zone of the Amhara region. The dam was built as part of a project to enhance

food security in the country which is poorly low at the moment due to change in sediment,

rainfall, and dependence upon rain-fed agriculture by nearly 90% of the 600,000 people

living in the catchment. It was the first large scale project to be built in the UBNB since

1987 and the first in a series of planned projects (Eguavoen, 2011) and an effective pilot

project as the effectiveness of the Koga project may influence future projects still at the

planning level The wet(rainy) season (July-September) generates about 70% of the runoff

contributing the Koga River (Mott MacDonald, 2004).

Figure 4 the Koga reservoir and irrigation location.

Command

area Koga reservoir

14

3.3 The hydrology and geology of Upper Blue Nile Basin

The precipitation in the UBNB was guided by the Inter-Tropical Convergence Zone’s

migration over the region, which receives moisture from the Indian and Atlantic oceans.

Rainfall ranges between 800 and 2200 mm annually. Most of this Rainfall falls during the

wet season, which takes place from (June – September). The dry season lasts from

(December – May) which receives the smallest amounts of precipitation. This water

collected in the watershed produces an outlet flow of 49.4 G m3 yr-1 at the Sudanese border

(Gebrehiwot, 2010). At the time it reaches the Aswan Dam in Egypt, the Blue Nile accounts

for 62 percent of the flow at that point (Ministry of Water Resources., 1998)

3.4 The geology of the UBNB can be divided into three different part:-

√ Exposed crystalline basement rock covers 32% of the basin,

√ Sedimentary formations compose 11% and volcanic,

√ Formations make up the remaining 52 percent of the catchment.

The major soil type is clay vertisol, which covers around 15% of the region (Gebrehiwot,

2010). Vertisol can be defined as the main type of shrinking and expanding clay. This

movement in the clay can cause cracks to form when it dries and is very susceptible to

erosion (Gebrehiwot, 2010) The geology in the project site are mainly alisols type soils,

with light to medium composition. They are leaky, with a relatively high infiltration rate.

The soils had a fixed irrigation size of (2-4l/s) (Ministry of Water Resources, 2008).

The majority of the soils are very fine (silt-clay) category. Usable water in the root region

was found to be 187mm per meter of soil and the adopted management allowed depletion

level is 30-60% of the important moisture in the effective root zone, depending on the type

of irrigated land. 87% of the irrigation area has been categorized as silty clay soils best for

irrigation. Infiltration is available for irrigation, the soils are low in some nutrients needed

for plant growth, particularly phosphorus, and are acidic and high in sodium this can be

detrimental to cropland. Fertilizers are used in small quantities when available to counteract

this (Ministry of Water Resources, 2008). poor land management throughout the history

of the basin has caused erosion and exposed some bedrock (UNESCO, 2004).

15

3.5 Climate and rainfall data

The climate in the project land is mainly guided by the movement of the ITCZ (Gebrehiwot,

2010). It has two seasons a wet (kiremt) season and a dry (bega) season. The bega season,

called the dry season, takes from December - May while the wet time of year, or rainy

period, called kiremt takes from June - July to September - October(Marx,2011). High river

discharge occurs during the kiremt season as a result of rainfall and runoff, which can be

difficult as it promotes high rates of erosion (Ministry of Water Resources., 1998). The

temperature, rainfall, and evapotranspiration data for the Koga irrigation project area can

be seen in the Figure below. The temperature and precipitation and evapotranspiration

figures were made using data from Merawi meteorological stations. The Penman-Monteith

equation was used for evapotranspiration (ETo) computation.

Figure 5 Merawi meteorological stations Tmax and Tmin.

0

5

10

15

20

25

30

35

jan feb mar apr may jun july aug sep oct nov dec

tem

pra

ture

(ºc

)

Months

max temp deg)

min temp(deg)

16

Figure 6 Merawi meteorological stations rainfall and eto.

3.6 The water balance Model and its components

The water balance model is a science and engineering rule such as applicable for protecting

the environmental role or improving the environmental benefits of a number of water

projects including irrigation, municipal water supply, and wastewater systems. The water

balance model, which calculates reservoir inputs and outputs, is another way of knowing

the hydrologic cycle and the feasibility of the reservoir cycle, as well as comparing the

supply volume of reservoir sustainability of sedimentation and climate change (Dingman,

2002). The water balance equation generally describes equating the balance between the

flowing input and output flow of any hydrological cycle. Due to the high degree of

complexity of our water process, they are always classified into independent components.

preparing a monthly water balance for the reservoir makes it possible to predict the supply

volume of the reservoir on a monthly basis. The water balance is designed to compare the

supply irrigation water volume of the reservoir with the crop water requirement in order

to estimate a final reservoir supply volume for a given month.

0

50

100

150

200

250

300

350

400

450

500

jan feb mar apr may jun july aug sep oct nov dec

rain

fal

l an

d e

to

month

rainfall and evapotranspiration

rain fall(mm/month)

eto(mm/month)

17

The model and equations used for calculating different parts of the water balance parameter

are described below. The water would be presented, along with a description of all of the

parameters and equations used to compute them. The parameters used in the reservoir

volume water balance model was computed in this section.

Vm= Vm-1 + p+ Qin) - (E + Qout). Equation 1

Equation 1 was taken For the Koga Reservoir because the water balance equation is used

for large reservoirs (with a volume of more than 50 Mm3). Put in a monthly time step as

much of the climate data used to calculate the parameter is given in monthly value. So my

project site is 83.1Mm3 which is greater than 50 Mm3 in a semiarid tropical region used by

(Guntner, 2004). Where Vm is the specific storage volume of the reservoir at the specific

month m,

P is precipitation,

Qin is the discharge from the Koga River into the reservoir,

E is evaporation and

Qout is the discharge out of the main irrigation canal and bottom outlet.

All parameters were given in millions of cubic meters (Mm3). The model computes the

volume of the reservoir for each month based on the volume of the last month add inputs

and subtract outputs of the month. Parameters in the model are the discharge from the Koga

River, precipitation, and runoff. Water losses from the reservoir were included evaporation

from the reservoir area, the water discharged into the primary irrigation canal, and water

flows through the bottom outlet for monthly environmental balanced flows and sediment

release. The change in reservoir volume from one month to the other is therefore equal to

Figure 7 Reservoir inflows and outflows; parameters for the water balance

model

18

the precipitation plus the discharge from the river subtract evaporation from the reservoir

area and discharge from the reservoir outlets. The water balance model take September as

the first month since Ethiopia is located to the south of the equator is which is the line of

the eastern hemisphere (east of Greenwich meridian) this is the beginning of the hydrologic

cycle for the Northern Hemisphere as given by the United States Geological Survey

(USGS, 2008).

Koga reservoir volumes beginnings in September and endings in August. The volume is

expressed in Mm3 for each value. The beginning volume in the model (Vm-1) is the volume

for September, taking October as the beginning computed volume. The model area was

chosen to be a maximum volume of 83.1 Mm3 and a minimum volume of dead storage

which is 3.9 Mm3. The increased reservoir volume is the point at which the water stage in

the reservoir higher than the height of the spillway, as given in the design reports( Mott

MacDonald, 2004).

The main parameter important for the equation was taken from the design reports done by

Mott MacDonald. Monthly values for precipitation (P) were given in mm. Estimated river

discharge (Qin) was also given in Mm3. Three parameters of Qout, environmental balanced

flows, and maintenance flow were given in Mm3 per month. Other parameters had taken

from the design reports were monthly climate data for crop water requirement and

evaporation (E) computation and a list of reservoir surface areas at particular reservoir

volumes curve used for making a volume to surface conversion equation to compute

evaporation from the reservoir.

3.6.1 River discharge Inflow (Qin)

The Koga River discharge is the only river entering into the reservoir. Direct discharge

value is not assessable for the inflow at the reservoir, but a gauging station is put on a

tributary of the river just side the reservoir that can be used. Monthly gauging discharge

values were listed in the design reports (Mott MacDonald, 2004). And are given in Fig 8

and the values are in appendix table A5.

19

Figure 8 Monthly Qin values used in the water balance model.

Assumptions

The river flow (Qin) was suggested to include all runoff from the watershed. The gauging

site from which the data obtained is only an estimate of the actual amount of discharge

flowing into the reservoir. As a result, the flow at the gauging site may vary from discharge

at the reservoir inlet. The river discharge values used in the water balance model are an

estimation of the best available information.

3.6.2 Rainfall (P)

Rainfall data were assessable for each month in Merawi meteorological station in mm. In

order to calculate the volume in cubic meters, the Rainfall was multiplied by the surface

area of the reservoir at max level. All Rainfall falling outside of this area is count as runoff,

which is added to river flow (Qin). When the reservoir is not at a full level due to

evaporation or water use, the surface area would be reduced. In spite of this, the area of the

reservoir at the full level is still used to determine the direct Rainfall falling on the reservoir.

This means the area used for computing the Rainfall input will be larger than the surface

area of the lake. As a result when the maximum volume, the Rainfall surface is equal to

the reservoir surface area plus the exposed land that would be included by the reservoir at

maximum level. This covered area would be incorporated into the runoff, although in order

to clear things the surface area is kept constant when calculating Rainfall. Monthly Rainfall

(P) values used in the water balance model are given in Figure 9 appendix A table A6.

0

5

10

15

20

25

30

35

40

Jan Feb Mar April May June July Aug Sep Oct Nov Dec

Qin

(Mm

3)

Months

20

Figure 9 Monthly Precipitation values used in the water balance model.

Assumptions

In computing the Rainfall input (P) it is suggested that all of the Rainfall falling on the

included area of the reservoir would make it into the reservoir as runoff. It is also suggested

that all runoff generated from Rainfall falling outside of the surface area of the reservoir at

a maximum level such as in the upstream watershed, is included in Qin.

3.6.3 Evaporation (E) of the Bahir Dar, Merawi, and Koga site

To compute the evaporation from the Koga project, the evaporation (Eo) from the

simplified Penman equation was multiplied by the surface area of the reservoir in

maximum capacity in order to get Mm3 evaporated.

Eo = (0.015 + 0.00042T + 10-6h) (0.8Rs-40 + 2.5F*u (T-Td) Equation 2

Where T is weighted air temperature in degrees Celsius, h is altitude in m, Rs is solar

radiation in w/m2, Td is the dew point temperature, F* is approximated as 1-8.7*10-5h, and

u is the wind speed in m/s. Weighted air temperature is used to estimate temperature from

the maximum (Tmax) and minimum (Tmin) temperature values. The equation for computing

weighted temperature is taken from Linacre (1993) and is given as:

T= (0.6Tmax+0.4Tmin) Equation 3

0

1

2

3

4

5

6

7

8

9


P(M

m3)

Months

21

Dew point temperature would be calculated from relative humidity and air temperature

using the August-Roche-Magnus approximation (Equation 4)

Td = bG/a-G

Where G = (aT/b+T) + ln(RH/100) Equation 4

Where a is 17.271, b is 237.7 degrees Celsius, and RH is the relative humidity in %. The

output for the evaporation from the Koga project for each month in Mm3 is given in Figure

10. These are the result used in the water balance model when there has been a normal state

of the initial volume. New conversion curves were created and used to calculate new

monthly evaporation values for the scenarios suggesting a change in initial sediment.

Values for the evaporation in mm and Mm3 are given in Table A7 in Appendix A.

Figure 10 Monthly evaporation values used in the water balance model

Assumptions

The evaporation computation suggests a constant in the Koga reservoir’s area classification

throughout the time. Nevertheless, in actual the behavior of the reservoir concerning

evaporation would change as the depth in the reservoir changes. Therefore, It should be

0

0.5

1

1.5

2

2.5

3

3.5


E (

Mm

3)

Months

Koga Reservoir

22

considered that these evaporation computations are predicted subject to huge margins of

error even though they are based on the best data and last research available. The computed

evaporation equation in mm (Ec) shows good results with the evapotranspiration (ET) data

from the Bahir Dar meteorological site.

3.6.3.1 Evaporation model scenario analysis

Comparing the computed evaporation for the Koga project, with the evapotranspiration

from Bahir Dar and merawi meteorological station, it can be seen that the output are similar

and follow the same monthly curve. This was true as Bahir Dar has a similar climate, found

just 35 km away from the Koga reservoir. The equation used to calculate evaporation

output is known as an assumption but the comparison did fit well, indicating the

calculations are consistent with observed values in the nearby Bahir Dar meteorological

station. To check the perfection of the computed evaporation for the Koga site, the values

were compared with data from the Bahir Dar meteorological station. The annual

evaporation in mm was calculated to be 1715.7, an equivalent of 24.4 Mm3. As a

comparison, the rainfall was predicted in the design report to be 1588.9mm yearly. The

month with the lowest evaporation in Mm3 is July and August, with a value of 1.7Mm3.

April is the month with the highest evaporation at 3.1 Mm3. These real evaporation values

for the reservoir depend not only on the evaporation rate but also on the shape of the

reservoir. Evaporation at the Koga reservoir and evapotranspiration in Bahir Dar

meteorological station, are compared in Figure 11. Monthly evapotranspiration values for

Bahir Dar meteorological site in mm, which is taken from the design report, are also

presented in Appendix A in Table A4.

23

Figure 11 Comparison of monthly Eto, Ecal, and Koga E of the site.

3.7 Outflow (Qout)

Discharge from the reservoir (Qout) can be classified into three different units; monthly

environmental compensation flows, maintenance flow, and irrigation flow. Monthly data

is assessed in the design report for environmental flow and maintenance flow, which occurs

only once annually. Climate data from the Merawi and Bahir Dar meteorological site and

the cropping patterns had given in the design reports were used for computing the irrigation

release.

3.7.1 Release discharge for Maintenance and sediment flushing

Maintenance flow occurs only once a year for sediment releasing taking 30 minutes, and

flushing 0.0558 Mm3 of water. This is a little significant compared with the other unit of

Qout. The maintenance flow is ordered for the month of June in the water balance model,

this means when the water level in the reservoir is low. Water can also be flushing for

maintenance than sediment releasing.

3.7.2 Environmental compensation flow

To see the possibility that in order to provide the irrigation water needed to supply the

whole command area the Koga project engineers were willing to neglect the environmental

compensation flow to compute sedimentation.

0

20

40

60

80

100

120

140

160

180

200

E(m

m)

month

koga E(mm)

KogaEcalc(mm)

BDR E(mm)

24

First, the reservoir volume was examined with decreasing volumes and under the

assumption that environmental release flows were only be shut off during the months where

the reservoir volume reaches a minimum.

Second, the reservoir volume is examined with change initial volumes and no

environmental flows released at the entire course of the year. Prioritizing the irrigation flow

over the environmentally balanced flows would advantage the farmers in the Koga

irrigation project area but would be respected by the downstream communities and

ecosystems as the water supply would be cut off. Stopping the environmental release is not

named in the design reports and is not likely to happen as a management activity in the

future for an ethical and legal case. However, the opportunity was examined for

theoretical/ideal/ purposes.

There is an actual amount of water that needs has to be flown into the downstream of the

Koga irrigation project area each month in order to respect natural flows in the Koga River

as they were before the Koga irrigation dam was built. In this way, it can be assured that

the downstream community will not be missing out on their water rights and the

downstream ecosystems can be protected. Turning off the environmental balanced release

during the months when the reservoir would run dry/ does not save enough water/ to irrigate

the whole project area using the current and future cropping pattern. Eliminating the

environmental balanced also becomes unable to supply sufficient water for irrigation after

the reservoir is forced to start operating at 78% maximum volume (Ministry of Water

Resources, 2006). The monthly Environmental compensation release was given in Figure

12 below

25

Figure 12 Water released from the reservoir for environmental compensation flow

for each month given in Mm3 (Ministry of Water Resources, 2006).

Figure 13 Water released reservoir for partial environmental compensation release

flow for each month given in Mm3 (Ministry of Water Resources, 2006).

As shown in Figure 12 and Figure 13 without affecting the downstream right I can redesign

the environmental compensation release flow and prolong the use full period of the

reservoir. As a result, shown above the redesign neither affecting the downstream nor the

reservoir.

0

0.5

1

1.5

2

2.5

3

month oct nov dec jan feb mar apr may

wat

er r

elea

se (

Mm

3)

Months

0

20

40

60

80

Sep Oct Nov Dec Jan Feb Mar April May June July Aug

wat

er r

elea

se (

Mm

3)

Months

26

3.7.3 Irrigation water release flow

3.7.3.1 Crop water demand (CWR) analysis

Nevertheless, this was not the final result used for the irrigation water flow parameters of

Qout, as there is no irrigation during the months of June-August. In order to check that the

policy of not irrigating during the peak of the wet season was realistic, I compared the

rainfall with the crop water demand for the three months in question. The wet season crop

pattern of 40% teff, 20% maize, 20% noug, and 20% millet give combined

evapotranspiration of about 27.95 Mm3 for the entire 7000 hectares of command area. For

the months of June-August, when there is no pattern irrigation, the combined evaporation

is 22.87 Mm3. Values for each month are given in Appendix A in Table A7. The rainfall

(Merawi extended rainfall values) falling on the command area’s 7000 ha during the rainy

season is 28.99 Mm3, for the combined months of June, July, and August. The precipitation

is therefore slightly larger than the total evapotranspiration during this season. If there is

no pattern irrigation during this period then the precipitation amount must fulfill the crop

water demand. The precipitation will meet crop water requirements if the efficiency of the

rain-fed irrigation is 79% (22.87Mm3/28.99Mm3) this shows the combined evaporation is

lower than the combined precipitation. It should be possible to operate using rain-fed

irrigation during June-August, nevertheless, if the whole project area is cropped during this

time, irrigation may not be needed to ensure crop survival.

The GIWR would vary based on the cropping patterns and irrigation schedule. Mott

MacDonald, therefore, estimated four different scenarios based on different climate data

and crop growing season lengths in order to generate different examples of possible gross

irrigation water demand. Total hectares of area irrigated each month vary between the

scenarios which affect the final yearly gross water requirement (GIWR).

Scenario I is dependent upon a short growing season and revised original climate data from

the working papers done by Mott MacDonald and has a predicted yearly GIWR of 60Mm3

(Ministry of Water Resources, 2006).

Scenario II uses the same data in conjunction with scenario I a longer growing season,

which has an estimated yearly GIWR of 76Mm3/yr.

27

Scenario III take a short growing season and wind speed data for evapotranspiration

computation from Bahir Dar, 30 km north of the site with a GIWR of 58Mm3/yr and

Scenario IV uses the same data in conjunction with scenario III but with a long growing

period, has an estimated yearly GIWR of 74Mm3/yr. These scenarios were estimated for

designing the dam and irrigation canals but none of them are being applied exactly in

practice today. Monthly values for each scenario as well as other details about the scenarios

are given in Table A14 in Appendix A. This comparison shows a tolerable difference

between the requirement (CIWR) design report result. So it is possible to use these data

enterchangebly for my thesis.

Figure 14 Comparison of crop irrigation water demand CIWR from the design

report scenarios

Assumption

The crop water demand computation is based on a few suggestions. These assumptions are

that the whole crops are planted at the same time, at the start of the respective planting day.

This is done in order to get the simplified result that well fits the water balance model on a

monthly respective time. In actual the crops are not all planted on the same day, they are

planted in different places on different days, always in rotations. For example, maize could

be planted on 4 different dates during the planting month, once at the starting of each week.

This prediction of water demand is therefore not perfect, but rather a monthly prediction

of water is needed. The computed crop water demand also assumes an irrigation efficiency

0

10

20

30

40

50

60

70

80

90

Oct Nov Dec Jan Feb Mar April May June July Aug Sep

CIW

R

month

Scenario IV(CIWR)

Scenario III(CIWR)

Scenario II(CIWR)

Scenario I(CIWR)

28

of 50% and are correspondingly computed as double the sum of the evapotranspiration for

each month.

3.7.4. Secondary data collection

Secondary data used for the study were collected as much as possible from responsible

bodies and officials. These data include discharge of the Koga River, climatic data, and

existed irrigation water requirements for the command area for the project. Discharge data

collected from the Ministry of Water Resources enclosed different stations on the Upper

Blue Nile basin.

3.7.5 Data analysis techniques

Data collected using different models, equations and techniques were analyzed and

interpreted as specific stated research objectives and study questions. A water balance

model that involves predictive sediment yield was used to analyze, interpret, and discussed.

Analysis and interpretation, preparatory works that involve data editing has been employed

in order to minimize irregularities and maximize accuracy by using medley software. To

this effect, physical data editing has been performed in order to see problems that made an

error, and data concentrated effort was the second task that I had employed as data collected

are subject to a series of check-ups in order to clean them from invalid formats, unusable

values and check the reasonableness of the distribution. The other preparatory task is data

Grammarly correction, where collected information is translated into values appropriate

for further data analysis, and types of variables representing the factors to be studied have

been identified, and given values/levels. To do this thesis I were used mendely softwear

for citation and bibliography, and grammarly checher.

3.8 Model scenarios

The Koga reservoir volume could reduce in the future mainly due to sedimentation and

climate change. I hope Sedimentation is occurred in the reservoir and knows about being a

harsh condition of the country. Draughts, minimum rainfall, and intense storms are capable

of reducing the reservoir’s volume, either by reducing the water demand from precipitation

and river runoff or by increasing sediment load and evaporation, this results an increase of

sedimentation in the reservoir.

If the sediment accumulation rates of reservoir 5 Mm3 every 7 years estimated in the design

reports by Mott MacDonald hold correct, this could mean the dam runs dry for at least one

29

or two months of the year ( Benjamin, 2013). In order to get an idea of how the reservoir

volume may change throughout a year under changed climate and sedimentation predicted

for the future, I created 4 scenarios

The reservoir volume decreases by 0 5, 10, and 15, Mm3 of sediment accumulation were

selected. These in turn correspond to new Vm-1 values of 83.1, 78.1, 73.1, and 68.1, Mm3.

The parameters in the water balance equation that were simplified in this scenario were the

extra several new Vm-1 equations were created. Monthly values for all of the model

component are presented in Appendix A in Tables A10.

3.8.1 Model Scenario 1

Computation from water balance equation, under 0 sediment acommulation. Figure 15

gives the normal state volume of the reservoir for a month as computed in the water balance

model or the volume reduction of the reservoir before 7 year as computed in the water

balance model. .


Computation from water balance equation, under 5 Mm3 sediment acommulation. Figure

16 gives the volume reduction of the reservoir after 7 year as computed in the water balance

model.



17 gives the volume reduction of the reservoir after 14 year as computed in the water

balance model.



18 gives the volume reduction of the reservoir after 21 year as computed in the water

balance model.

The results from scenarios 1, 2, 3 , and 4, simulating possible upcoming reservoir volumes

change are presented below in figures 15-18.

30

4 Model scenarios Results and discussion

4.1 Model scenarios Results

In this part, the variability in volume of the reservoir throughout the period of a

hydrological year has resulted for each model scenario. The possible role of changes in

sedimentation on reservoir volume is discussed.

This volume decreases of reservoir by 0, 5, 10, and 15Mm3 due Sediment increase is in the

year of 2006, 2013, 2020, and 2027, respectively. These in turn correspond to new Vm-1

values of 83.1 78.1, 73.1, and 68.1Mm3.

4.1.1 Scenario 1 Reservoir volume under normal states

From Computation of water balance equation before 7 year sediment accumulation results

a minimum reservoir volume of 6.7Mm3 in may in 2006 E.C. The results from scenarios 1

simulating possible upcoming reservoir volumes are mentioned in figures 15.

4.1.2 Scenario 2 reservoir volume change by 5Mm3

Computation from water balance equation, under a 5Mm3 sediment accumulation or after

7 year sediment increase results a minimum reservoir volume of 4.8Mm3 in may in 2013

E.C. The results from scenarios 2 simulating possible upcoming reservoir volumes are

mentioned in figures 16.

0

20

40

60

80

100


Volu

me(

Mm

3

Months

Before 7 years sediment accumulation

Figure 15 Reservoir volume under normal states

31

Figure 16 gives reservoir volume reduction by 5Mm3 for each month as computed

in the water balance model.

4.1.3 Scenario 3 reservoir volume change by 10 Mm3

From water balance equation Computation, under a 10Mm3 sediment accumulation or after

14 year sediment increase results a minimum reservoir volume of 2.9 Mm3 in may in 2020

E.C. The results from scenarios 3 simulating possible upcoming reservoir volumes are


Figure 17 gives reservoir volume reduction by 10Mm3 for each month as

computed in the water balance model.

0

20

40

60

80

100


Volu

me(

Mm

3)

Months

After 7 Years sediment accumulation

0

20

40

60

80

100

Sep Oct Nov Dec Jan Feb Mar April May June July AugVolu

me(

Mm

3

Months

After 14 years sediment accumulation

32

4.1.4 Scenario 4 reservoir volume change by 15 Mm3

Computation from water balance equation, under a 15Mm3 sediment accumulation or after

21 year sediment increase results a minimum reservoir volume of 0 in may in 2027 E.C.

The results from scenarios 4 simulating possible upcoming reservoir volumes are


Figure 18 gives reservoir volume reduction by 15Mm3 for each month as

computed in the water balance model.

0

10

20

30

40

50

60

70

80


Volu

me(

Mm

3

Months

After 21 years sediment accumulation

33

4.2 Model scenario Discussion

In this section:-

The results obtained in the last part are presented. The current and the future nature of the

Koga reservoir for the irrigation project is discussed,

The Koga reservoir volume could reduce in the future mainly due to sedimentation and

slight climate change. I hope Sedimentation is occurred in the reservoir and knows about

being a harsh area of the country. Water balance modeling to estimate an increase in

sedimentation direct to more water loss due to reservoir volume reduction and causing

more droughts and famine as well as minimum rainfall. Draughts, minimum rainfall, and

intense storms are capable of reducing the reservoir’s volume, either by reducing the water

demand from precipitation and river runoff or by increasing sediment load and evaporation,

resulting from an increase in dam sedimentation. The water balance model, not the only

model that the reservoir volume as it would behave under current climate conditions with

no reduction in maximum volume from sedimentation but also the future climate condition.

If the prediction of sedimentation yield of five Mm3 every seven years were true, the

reservoir would be depleted for at least part of the month in 2027 E.C. This tells us

decreases in the reservoir's maximum volume could create a huge problem for the reservoir

in the 21 years.

4.2.1 Model scenario 1 Reservoir volume under normal states

using current and future sedimentation results and unchanged in initial reservoir volume,

the reservoir should be able to feed sufficient water for irrigation and environmental

balance discharge throughout the month. The reservoir decreases a minimum volume of

6.7Mm3 in May. At this minimum volume, the reservoir is not in the problem of being

irrigating the entire command area and has sufficient flow to supply additional irrigation

area. The minimum result appears just the end of the winter season as this is the time of

year when the reservoir has been in the largest use. As the wet season starts, the reservoir

is no longer used for irrigating and starting instead it overfill. The reservoir is able to

overfill to a huge volume than the beginning volume. The entire course of the hydrological

year, the reservoir volume enhances 13.1Mm3 in size, make full to its maximum volume.

34

Even though, it has the capacity of irrigating the entire command areas. However, it might

not always be able to irrigate this in the future as sedimentation and changes in climate

become increase. Scenarios 1-4 give susceptible outcomes for Koga reservoir volumes in

the future and remedial measures/mitigation action/.

A 0 sediment accumulation in reservoir volume directs to the Koga reservoir just sufficient

to supply already in May and after a reservoir becomes 13.1Mm3 in June.

The graph shows the reservoir is longer able to feed sufficient water for the year, in May,

becoming close to the reservoir. The reservoir is still able to feed water year over

nevertheless, it reaches a minimum volume of 6.7 Mm3 it seems to good to irrigate.

4.2.2 Model Scenario 2 reservoir volume change by 5Mm3

In 5Mm3 reservoir volume reduction, by using future sedimentation result with the 2013

E.C year reduction in initial reservoir volume. Nevertheless, the reservoir should be able

to give sufficient water for the whole command area and possible to release environmental

compensation flow the entire year. The reservoir decreases a minimum volume of 4.8Mm3

in May. At this minimum volume, the reservoir is not in the problem of being irrigating the

entire command area and has sufficient flow tosupply additional irrigation area. The

reservoir is able to overfill to a huge volume than the beginning volume. During the entire

course of the hydrological year, the reservoir volume enhances 8.1Mm3 in size, make full

0

10

20

30

40

50

60

70

80

90


Vo

lum

e( M

m3)

Months

Figure 19 Reservoir volume under normal state

35

to its maximum volume. Even though, it has the capacity of irrigating the entire command

areas. However, it might not always be able to irrigate this in the future as sedimentation

and changes in climate become increase. Scenarios 2-4 give susceptible outcomes for Koga

reservoir volumes in the future and remedial measures/mitigation action/.

Figure 20 Reservoir volume by 5Mm3 reduction


becoming close to the reservoir. But the reservoir is still able to supply water year over

nevertheless, it reaches a minimum volume of 4.8 Mm3 again it seems to good to irrigate

A 5Mm3 decrease in maximum volume directs to the Koga reservoir just becoming

minimum already in May and after the reservoir becomes 8.1Mm3 in June.

4.2.3 Model Scenario 3 reservoir volume change by 10Mm3


becoming close to the reservoir. The reservoir is still able to supply water year over

nevertheless, it reaches a minimum volume of 2.9 Mm3 again it seems to good to irrigate.

In 10Mm3 reservoir volume reduction, by using future sedimentation result with the

2020E.C year reduction in initial reservoir volume. Nevertheless, the reservoir should be

able to give sufficient water for the whole command area and possible to release

environmental compensation flow the entire year. The reservoir decreases a minimum

volume of 2.9Mm3 in May. At this minimum volume, the reservoir is not in the problem

0

10

20

30

40

50

60

70

80

90


Vo

lum

e( M

m3)

Months

36

of being irrigating the entire command area and has sufficient flow to supply additional

irrigation area. The reservoir is able to overfill to a huge volume than the beginning volume

by10.3Mm3in June. Even though, it has the capacity of irrigating the entire command areas.

However, it might not always be able to irrigate this in the future as sedimentation and

changes in climate become increase. Scenarios 3-4 give susceptible outcomes for Koga

reservoir volumes in the future and remedial measures/mitigation action/.

A 10Mm3 decrease in maximum volume directs to the Koga reservoir just becoming

minimum already in May and after that, the reservoir becomes 10.3Mm3 in June.

Figure 21 volume reductions Reservoir by 10 Mm3.

4.2.4 Scenario 4 reservoir volume change by 15Mm3

In 15Mm3 reservoir volume reduction, by using future sedimentation result with the 2027

E.C year reduction in initial reservoir volume. Nevertheless, the reservoir should not be

able to give sufficient water for the whole command area, and impossible to release full

environmental compensation flow the entire year. At this minimum volume, the reservoir

is in the problem of being irrigating the entire command area and has an insufficient flow

to supply additional irrigation area. The reservoir is able to overfill to a huge volume than

the beginning volume by 7.5Mm3 in June. Therefore, it has not the capacity of irrigating

0

10

20

30

40

50

60

70

80

90


Vo

lum

e( M

m3

Months

37

the entire command areas. Scenarios 4-4 give susceptible outcomes for Koga reservoir

volumes in the future. A 15Mm3 decrease in maximum volume directs to the Koga reservoir

just becoming empty already in May and after that, the reservoir becomes 7.5Mm3 in June.

4.2.5 Model scenario summary

When I summarise ize the four different scenarios for reservoir volume change discussed

in the calculation result obtained and described in the previous section, the calculated

reservoir volume change is roughly varied due to the number of reduction terms of volume

and greatly varied From year to year. This can be shown in Figure 23.

Figure 23 Scenario 1-4: shows Changes in reservoir volume with decreases in the

maximum volume due to sedimentation. Different decreases in the maximum volume are

given, ranging from no decrease to a 15Mm3 decrease in the initial reservoir volume.

Figure 24 displays the volumes calculated for each month in scenarios 1-4, using reduced

initial reservoir volumes to simulate sedimentation. The dam volume reaches zero in the

model runs with reductions in initial reservoir volume of 15Mm3 and greater than this. This

tells Sediment increase reservoir volume decrease

0

10

20

30

40

50

60

70

80


Vo

lum

e( M

m3)

Months

Figure 22 Reservoir volume by 15Mm3 reduction

38

Figure 23 summary of volume change due sediment accumulation in different year

from scenario 1-4

0

10

20

30

40

50

60

70

80

90


volu

me(

Mm

3 )

month

summary

2006 E.C

2013 E.C

2020 E.C

2027 E.C

39

5. Conclusion and recommendation

5.1 Conclusion

The following conclusions were listed after computing the change in reservoir

sedimentation based on the water balance model. The thesis first analyzed the sediment

variability, volume capacity loss, useful lifetime, and amount of deposited sediment over

its useful time in the Koga irrigation project. The water balance model requires several

parameters, such as Koga River inflow (Qin) the precipitation, evaporation, and the outflow

(Qout) of the reservoir.

In this study, the investigation of the change reservoir sedimentation was done through the

method of water balance equation. The main problem during my thesis was to know the

reservoir size every year to calculate precipitation and evaporation due to this difficulty I

did the reservoir size constant which could lead to huge errors. Therefore, in the future, the

Koga irrigation project engineer should consider the change in reservoir size.

According to the water balance model, the Koga reservoir should be able to feed sufficient

water for irrigating the whole project area up to 10Mm3 sedimentation deposition. The

reservoir is able to come up to maximum volume at the end of the hydrologic month in

four scenarios but scenario four did not do like others. Due to this, the future of the project

is threatened by the problem of sedimentation. The model result tells that after a 15 Mm3

reduction in initial volume the reservoir becomes dry for at least one month of the year.

The Koga irrigation project office aims to increase the number of command areas in the

future. If sedimentation happens, the reservoir supply volume will most likely be reduced

below the volume required to irrigate 7000 ha. If the reservoir fails to supply the required

volume for the project design, the dam could be considered a failure and might affect the

farmer’s interest. Not only farmers in the irrigable land affected, but also for the rest of

Ethiopia.

However, sedimentation increase had the greatest effect on reservoir volume this causes

large decreases in reservoir volume throughout the year and the model showed the dam

running empty.

40

Generally, the results of the model could use as an important origin to support the design

and implementation of sediment protection policy in the catchment area and deposition in

the Koga reservoir.

5.2 Recommendations

Based on the water balance studies and result the following recommendations were

suggested. Nevertheless, comparing the result of sediment rate and useful life/design period

of the reservoir with the design document was not formulated. There are so many active

gullies on the catchment area as observed in the study shows. These gullies have much

depth and width eroded simply by the flood. Therefore, it is very useful to treat these gullies

to decrease the inflow sediment and expand the life span of the dam. Irrigational farmland

near the reservoir is plowed around to the reservoir area on both sides of the reservoir.

Therefore, this practice maximizes the sediment deposition to the reservoir, then decrease

the incoming sediment and expand the life span of the reservoir. Engineers, Designers,

managers, and decision-makers should give attention to installing adequate bottom outlets

for sediment discharge/flushing deposited sediments /or sluice get by considering the

amount of sediment releasing from the reservoir on catchment designing in order to

maximize the useful life of the reservoir.

Generally, this study work in the Koga irrigation project has been performed by water

balance model and can provide some methodological benefit for other catchment studies

in the area. Koga irrigation scheme suffers from economic water scarcity that makes its

water utilization difficult. A detailed understanding of the hydrological processes is

important for balancing crop irrigation water requirement and the reservoir volume. And

this type of study has to be adopted and accomplished on some other irrigation projects in

the country. Hydrologic analysis, the 80% dependable flow of Koga River indefinite dry

years did not meet the Crop Water Requirement. For that reason, to take care of the

uncertainties, mechanisms such as increasing storage in the catchment in a form of a pond

and small dams, reduction of command area when demand is greater than the available

discharge in the river, adopting time management for irrigation means irrigating crops at

night, morning and evening is best and also the provision of night storage is important.

41

6. Reference

Alemaw, D., Ayana, E. K., Legesse, E. S., Michael, M., Tilahun, S. A., & Moges, M.

A. (2016). Estimating reservoir sedimentation using bathymetric differencing and

hydrologic modeling in data-scarce Koga watershed, Upper Blue Nile, Ethiopia.

110(2), 413–427. https://doi.org/10.12895/jaeid.20162.519

Britannica. (2010). Britannica Online Encyclopedia, available

Benjamin. (2013). Variability and change in Koga reservoir volume, Blue Nile, Ethiopia

CIAWorld Fact Book ( (2012). Available at: https://www.cia.gov/library/publications/the-

world-factbook/geos/et.html, Accessed 2012. 31(2), 3245.

Clothier. (1993). B. E., Green, S. R. Rootzone Processes and the efficient use of irrigation

water, Environment Group, Hort Research, Private Bag 11-030, Palmerston North,

New Zealand.

Dingman. (2002). Physical Hydrology. 2nd ed. New Jersey: Prentice-Hall.

Eguavoen. (2011). I., Weyni T. Rebuilding livelihoods after dam-induced relocation in

Koga, Blue Nile basin, Ethiopia, ZEF Working Paper 83. Bonn. August.

https://doi.org/10.21276/ijee.2017.10.0305

Guntner. (2004). Krol, M. S., De Araujo, J. C., Bronstert, A., Simple water balance

modeling of surface reservoir systems in a large data-scarce semiarid region,

Hydrological Sciences– Journal–des Sciences Hydrologiques, 49.

H.M.Raghunath. (2006). Hydrology, New Age International (P) Limited, Publisher New

Delhi.

Habtom. (2009). Evaluation of Climate Change Impact on Upper Blue Nile Basin

Reservoir. 9(8).

IPCC. (2001). The scientific basis technical summary of the working group I report.

Cambridge university press, New York, 94pp.

IPCC. (2007). Technical paper VI Climate change and Water.

Kenneth. (1997). Frederick, Senior, F. Water Resources and Climate Change, Washington,

DC. January. https://doi.org/10.1017/S0014479710000955

Marx. (2011). Large-Scale Irrigation in the Blue Nile Basin: Changes and Obstacles in

Implementing Farmers’ Self-Management a Case Study of the Koga Irrigation and

Watershed Management Project in Amhara Region, Ethiopia, Research report for the

project.

Ministry of Water Resources. (1998). Abbay river basin integrated development master

plan project. In: Phase 2: data collection- site investigation survey and analysis.

BECOM (French Engineering Consultants) in association with BRGM and ISL

Consulting Engineer, Addis Ababa, Ethiopia.

Ministry of Water Resources. (2004a). Koga Irrigation Project Working Paper Nr. 1-10,

Available as a hardcopy at Koga Irrigation Project Office in Merawi. February.

Ministry of Water Resources. (2004b). Koga Irrigation Project Working Paper Nr. 1-10,

42

Available as a hardcopy at Koga Irrigation Project Office in Merawi.

Ministry of Water Resources. (2006). Koga Dam and Irrigation Project Design Report,

available as a hardcopy at Koga Irrigation Project Office in Merawi. 10(4), 269–280.

https://doi.org/10.5897/AJAR2014.8703

Ministry of Water Resources. (2008). Large-Scale Irrigation in the Blue Nile Basin:

Changes and Obstacles in Implementing Farmers’ Self-Management a Case Study of

the Koga Irrigation and Watershed Management Project in Amhara Region, Ethiopia,

Research report for the project. 127–155.

moges. (2010). Moges, Semu, Helmut Kloos, Stuart McFeeters and Worku Legesse (2010),

The Water Resources of Ethiopia and Large-scale Hydropower and Irrigation

Development, in Kloos, H. et al. (eds.) Water Resources Management in Ethiopia.

Mott MacDonald. (2004). Koga Dam and Irrigation Project Contract KDIP 3: Koga

Irrigation and Drainage System, Hydrology Factual Report. Available as a hardcopy

at Koga Irrigation Project Office in Merawi.

UNEP. (2000). Climate Change and Dams: An Analysis of the Linkages between the

UNFCCC Legal Regime and Dams, available

at:1www.dams.org/docs/kbase/contrib/env253.pdf, Accessed 15-08-2015. 6(1), 1–11.

UNESCO. (2004). United Nations Educational, Scientific, and Cultural Organization

World Water Assessment Program. 153–162.

USGS. (2000). Irrigation Techniques, Available at

http://ga.water.usgs.gov/edu/irmethods.html, Accessed 2012.

USGS. (2008). Explanations for the Natural Water Conditions, Available at

http://water.usgs.gov/nwc/explain_data.html.

vorosmarty. (1997). The storage and aging of continental runoff in large reservoir systems

of the world.

Wahaj. (2007). Policy Research Working Paper 4288: Actual Crop Water Use in Project

Countries: A Synthesis at the Regional Level, The World Bank Development Research

Group Sustainable Rural and Urban Development Team.

60

7. Appendix

Appendix A

Table A1 suggested cropping plan for the wet and dry season (Ministry of Water Resources, 2006)

Crop potato maize shallots peppers wheat millet noug teff sum

Dry season

(%)

16 47 12 7 18 100

Wet

season (%)

20 20 20 20 100

Table A2 Actual cropping pattern for dry season (Ministry of Water Resources, 2006).

Crop whe

at

barel

y

mai

ze

bea

n

Haricotbe

en

abis

h

fasol

ia

potat

o

cabba

ge

toma

to

carr

ot

beatro

ot

garl

ic

onio

n

preenpep

per

dry(

%)

31.4 19.6 3.23 0.2 0.10

8

0.0

1

0.00

5

41.6 0.55 0.229 0.00

1

0.00

4

1.22 1.38 0.60

1

Table A3 dry season proposed cropping system (%)

potato maize shallote peppers wheat

16 46 12 7 18

61

Table A4. Reservoir simulation runs. PIA is the potential irrigated area in hectares (Ministry of Water Resources, 2006)

Exp No. PIA (ha)

1 5833

2 5879

3 6104

4 6332

5 7588

6 7331

7 6143

8 6481

9 7645

10 7318

Table A5. Command Areas and their Sizes (Ministry of Water Resources, 2006). The addition of the Tekel Dib

extension area is designed for the future.

62

Table A6 Comparison of monthly evaporation between Bahir Dar meteorological station, calculated and the Koga site.

Month Jan Feb Mar April May June July Aug Sep Oct Nov Dec

BDR Eto(mm) 124 126.6 160.27 164.4 150.36 123 102.6 100.8 111.6 125.55 117.3 114.1

KogaEcalc(mm) 136 141.8 169.54 175.75 158.12 125.19 99.35 92.49 112.72 135.36 127.2 128.7

kaga E(mm) 138 141.4 173.86 178.23 156.58 123.86 98.04 95.38 114.27 137.41 131.5 129.2

koga E(Mm3) 2.41 2.47 3.04 3.11 2.74 2.16 1.71 1.67 2 2.4 2.3 2.26

Table A7 Data for Koga river inflow given by design reports Nile (Mott MacDonald, 2004)


Qin(Mm3) 2.71 2.13 2.15 2.12 2.61 5.09 24.93 35.74 22.58 9.79 4.95 3.52

Table A8. Precipitation data for Bahir Dar (Ministry of Water Resources, 2004).


p(mm) 3.2 1.7 10.1 30.6 102.7 227.8 445.3 406.7 219.7 102.2 23 5.3

63

p(Mm3) 0.06 0.03 0.17 0.53 1.79 3.98 7.79 7.11 3.84 1.78 0.43 0.09

Table A9 Crop Water Usage Values estimated by Mott MacDonald in the project report


CIWR(Mm3) 9.95 6.72 3.44 0 3.89 7.08 10.3 6.07 1.61 0 4.14 7.72

CIWR*50% 19.9 13.43 6.88 0 7.79 14.2 20.05 12.14 3.21 0 8.29 15.45

Table A10 these different scenarios modify the variables in the water balance equation to represent changes in

sedimentation.

Month Sep Oct Nov Dec Jan Feb Mar April May June July Aug

V@0(Mm3) 83.1 79.4 80.9 53.7 32.5 21.8 11.3 11.1 6.7 13.1 55.3 80.1

V@5(Mm3) 78.1 76.9 69.4 56.3 29.7 17.5 8.9 8.8 4.8 8.1 44.3 72.7

V@10(Mm3) 73.1 72.3 64.5 49.7 27.1 15.4 6.2 6.1 2.9 10.3 45.3 70.1

V@15(Mm3) 68.1 67.6 61.9 48.3 29.1 26.4 3.1 3 0 7.5 46.1 69.8

64

Table A11 these different scenarios modify the variables in the water balance equation to represent the partial

environmental release.

month Sep Oct Nov Dec Jan Feb Mar April May June July Aug

V0.5

(Mm3)

73.1 67.6 61.9 48.3 29.1 26.4 3.1 3 0.5 7.5 46.1 69.8

Table A12. Monthly compensation flows (Ministry of Water Resources, 2006).

Month volume(Mm3)

Oct 2.68

Nov 1.56

Dec 0.8

Jan 1.07

Feb 0.97

mar 0.8

Apr 0.67

may 0.8

65

Table A13 Data for Crop Water Usage Calculations (Ministry of Water Resources, 2006)

crop crowing season length (days) ET(kc*Eto)(mm/day) ET(mm/season) dry area wet area

initial development mid end initial mid end % ha % ha

tomato 30 40 40 25 2.5 5 3.75 506.66 0.23 16.02 0

maize 25 40 45 35 1.3 5 2.5 469.13 3.23 226.2 20 1400

onion 5 25 40 30 2.9 4 4.17 395.11 1.38 96.46 0

garlic 5 25 40 30 2.9 4 2.92 357.58 1.22 85.06 0

potato 30 40 50 30 2.1 5 3.13 533.76 41.56 2909.1 0

Greenpeper 25 35 40 20 2.5 4 3.75 433.16 0.6 42.07 0

wheat 20 30 50 30 1.3 5 1.67 405.53 31.37 2195.9 0

barley 20 30 50 30 1.3 5 1.04 386.77 19.57 1369.6 0

beans 15 25 25 10 1.7 5 1.46 240.3 0.17 12.21 0

Haricotbeens 15 25 25 20 1.7 5 2.29 271.57 0.11 7.54 0

abish 15 25 25 20 1.7 5 2.29 271.57 0.01 0.74 0

fasilia 15 60 25 20 1.7 5 2.29 271.57 0 0.34 0

cabbage 40 30 50 15 2.9 4 3.96 614.03 0.55 38.53 0

carrot 20 30 40 20 2.9 4 3.96 422.21 0 0.08 0

beatroot 25 30 25 10 2.1 4 3.96 298.16 0 0.26 0

teff 20 30 45 25 1.3 5 1.67 373.22 0 40 2800

shallots 5 25 40 30 2.9 4 3.96 399.8 0 0

noug 25 40 50 30 1.5 5 1.46 445.15 0 20 1400

millet 20 30 55 40 1.3 4 1.25 385.73 20 1400

67

Table A14 Scenarios I-IV net irrigable are and. GIWR of the whole irrigated area (Ministry of Water Resources, 2008).

The scenario I; Revised climate data and cropping pattern with short period growing

varieties

month Jan Feb Mar April May June July Aug Sep Oct Nov Dec total

Net irrigable area 5897 7000 6988 4874 2380 5261 6930 7000 6988 4736 1246 4615

GIWR(Mm3) 12.38 12.4 19.27 7.6 0.87 0 0 0 1.15 2.91 0.36 2.58 60

Scenario II; Revised climate data and cropping pattern with long period growing

varieties


GIWR(Mm3) 8.17 11.52 20.15 13.94 1.42 0 0 0 2.85 11.76 4.1 1.19 76

Scenario III; Revised climate data and cropping pattern with short period growing varieties using Bahir Dar wind speed

data


GIWR(Mm3) 11.96 11.95 18.6 7.36 0.84 0 0 0 1.08 2.85 0.36 2.5 58

Scenario IV; Revised climate data and cropping pattern with long period growing varieties using Bahir Dar wind speed

data


GIWR(Mm3) 9.08 11.41 19.44 13.51 1.36 0 0 0 2.76 11.56 4.01 1.15 74

69

Table A15 Growing season lengths in months and total irrigation water

requirements in mm for selected crops as estimated by

crop water needed(mm) growing

season(month)

wheat 450-650 4 to 5

teff 400-600 3 to 4

maize 600-1200 4 to 5

barley 400=800 4 to 6

noug 80-1100 4 to 5

sweet

potato

500-1000 4 to 5

peppert 600-900 3 to 5

tomato 400-600 3 to 5

Table 16 Area covered by each crop

Crop type Barley Beans Maize Peppers Vegetab

le

Wheat Total

Area

covered

(ha)

157.5 9.9 538.7 53.4 2196 2750 5705

70

Table 17 Average monthly crop water requirement of cultivated crops in the

project

CWR(m3/s) Average Monthly

Total

Month Barley beans

Maize Pepper Vegetable Wheat Average

Jan 0.077 0.005 0.20 0.034 1.70 0.87 2.89

Feb 0.20 0.012 0.59 0.050 2.50

2.40 5.75

Mar 0.23 0.014 0.81 0.070 2.88 3.96 7.97

Apr 0.15 0.007 0.65 0.073 0.94 3.52 5.34

May 0.00 0.000 0.10 0.022 0.00 0.54 0.66

Total 0.66 0.038 2.35 0.250 8.00 11.29 22.58

THE IMPACT OF SEDIMENT ON RESERVOIR VOLUME …

Documents

Transcript of THE IMPACT OF SEDIMENT ON RESERVOIR VOLUME …