Nile Basin Focal Project

19/09/2009, ChaingmaiSupported by: CPWF

IWMI

NBI

ENTRO

ILRI

WORLD FISH CENTER


Outline

1. Background

2. WP1 Poverty analysis

3. WP2: Assessment of Water Resources

4. WP3 Assessment of Water productivity

5. WP4 Institutional analysis

6. WP5 Intervention analysis

7. Conclusions


Nile BFP Project Objective:

To identify high potential water To identify high potential water To identify high potential water To identify high potential water management management management management interventions to reduce interventions to reduce interventions to reduce interventions to reduce poverty and increase poverty and increase poverty and increase poverty and increase water productivitywater productivitywater productivitywater productivity

1. Background assessment of the basin

19/09/2009, ChaingmaiSupported by: CPWFThe Basin is highly variable, the river is very important, various interventions

Basin is highly variable


• Access to water is related to poverty, not availability – need to differentiate access and availability

• Water productivity can be a key driver of wealth generation

• Issues are different between Egypt and Northern part of Sudan and the rest of the basin – access to water, productivity, institutions, etc.

• In US Basin countries water access is limited, and water productivity low – key to poverty reduction.

Key ideas:


• These are missed opportunities because agriculture water management for rainfed, wetland, livestock, fisheries, aquaculture tend to fall in a void.

• There are inadequate institutional arrangements to support this.

Project premise:


• There are numerous opportunities to manage water better for agriculture in order to improve productivity, food security and livelihoods.

• While most of the focus is on river water, we start with rainfall to look for opportunities outside of the river.

• Significant gains can be made through improving rainfed production systems through better agricultural water management

• Livestock, fisheries, aquaculture, wetlands provide opportunities, but are generally absent in Nile discourse.

Project premise:


Agricultural Population in the Nile Basin

0

20

40

60

80

100

Burundi

Congo,

DR

Egypt

Eritre

aEth

iopi

aK

enya

Rwan

daSuda

nTan

zani

aU

ganda

Countries

Pe

rce

nta

ge

of

Ag

ric

ult

ura

l P

op

ula

tio

n1979-1981

1989-1991

1999-2001

2003

2004

Baseline Conditions

3451 45

32

285402

936 1050 1012

3618

1

10

100

1000

10000

Bu

run

di

Eg

yp

t

Eri

tre

a

Rw

an

da

Ug

an

da

Ke

ny

a

Eth

iop

ia

Su

da

n

Ta

nz

an

ia

D R

Co

ng

o

Pre

cip

ita

tio

n (

km

3 y

r-1)

0.15

0.28

0.40

0.53

0.65

0.78

0.90

1972 1978 1984 1990 1996 2002 2008

Year

Hum

an d

evelo

pm

ent in

dex

EgyptSudanKenyaUgandaEthiopiaTanzaniaRwandaaverage, all countries

• High poverty and low development

• High Rainfall Poor Water Distribution-high loss upstream

• Drought & flooding

• High rainfall variability

• High agriculture dependency, slow transformation

• Despite potential, low water usage


Nile Delta

Sudd

Cattle Corridor

Lake Victoria: Ugandan Highlands

Ethiopian Highlands

Study Sites

Basin Wide

Sudan Transect

Nile Basin Study Sites:


#Y

#Y

#Y

#Y

#Y#Y

#Y

#Y

#Y

#Y

#Y

#Y

#Y

#Y

#Y

#Y

#Y

%[

%[

%[

%[

%[

%[

%[

%[

%[

%[

Sio

Yala

Victoria N

ile

Ru v

uvu

Kagera

Mara

Sondu

Sim

yu

Asw

a

Nya b

oro

ngo

Albert N ile

Nzoia

Dima

Semiliki

Kafu

K at on ga

Mu zizi

Jinja

K am dini

P akwachPanyango

Mbulam uti

Laropi

Ma sindi Port

Kaseny i

Bweramule

KatweKazing a C hanne lIshango

N gamba

L. Victoria

L. AlbertL. Kyoga

L. Edward

L. Kivu

L. Tangany ika

L. George

%[

#Y

Nama sagali

Murchision Fa lls

Mongalla

Owen Falls D am

Paraa

Bugondo

But iabaBunia

N imule

Kisumu

Musom a

Bukoba

Mwanza

Kamp ala

Entebbe

Fort Po rtal

Kigali

D R C

S U D A �

Rivers

Equator ial Lake Sub- Basins

#Y Discharge Stations

%[ Towns

Falls

Scale 1:4,250,000

Case Study Sites


The Nile Basin

Food or environment?


Irrigation Schemes

Country Irrig. Water Requirement, m3/ha/yr

Irrigation Potential, ha

Irrigated Area, ha

Burundi 13,000 80,000 0

DRC 10,000 10,000 0

Egypt 13,000 4,420,000 3,078,000

Eritrea 11,000 150,000 15,124

Ethiopia 9,000 2,220,000 23,160

Kenya 8,500 180,000 0

Rwanda 12,500 150,000 2,000

Sudan 14,000 2,750,000 1,935,200

Tanzania 11,000 30,000 10,000

Uganda 8,000 202,000 9,120


Irrigation Schemes, current & future …


Hydropower Plants,

current & future

Existing Sites

New Planned Sites


Rain = 1745 km3

Rainfed ET – 190 km3

Irrigated ET – 67 km3

Outflow – 10 to 30 km3

Limited options to expand

irrigation – but gets attention

Ample options to upgrade

agriculture on rainfed lands –

gets little attention

A green-blue viewIrrigated

Pastoral

Rainfed

Wetlands



14 Ramsar Sites

All support agriculture

and/or fisheries

All sites listed as

threatened by these

activities

Image of the Sudd

Nile Wetlands

CPWF, IWMI, WorldFish, ILRI, NBI


The Sudd Wetland: Inundation Extent

Image courtesy of JAXA K&C

ALOS PALSAR L-band SARRED: June 2008, GREEN: September 2008, BLUE: December 2008

Image courtesy of JAXA K&C


Jonglei Canal


Jonglei Canal

360 km long

7 5 m wide

4 to 8m deep


Irrigation Schemes

Country Irrig. Water Requirement, m3/ha/yr

Irrigation Potential, ha

Irrigated Area, ha

Burundi 13,000 80,000 0

DRC 10,000 10,000 0

Egypt 13,000 4,420,000 3,078,000

Eritrea 11,000 150,000 15,124

Ethiopia 9,000 2,220,000 23,160

Kenya 8,500 180,000 0

Rwanda 12,500 150,000 2,000

Sudan 14,000 2,750,000 1,935,200

Tanzania 11,000 30,000 10,000

Uganda 8,000 202,000 9,120


Irrigation Schemes, current & future …




2. WP1 Poverty analysis

Objectives:

• To establish a broad understanding of poverty and how it relates to water access in production systems in the Nile

• To create an overview of poverty and vulnerability indicators relevant for the Nile basin

• To test links between water, agriculture and poverty in the Nile basin


Research questions:

• What are the basin characteristics of water and poverty and how are they linked?

• Where are the poor and what are their water related problems?

• What are the water-related risks in crop-livestock systems?


Methods:

• Literature review of the basin

• Mapping hotspots of poverty in agricultural systems– We use food security, poverty level and poverty inequality to map poverty in the rural agricultural production systems of the Nile Basin.

– Poverty in this case is related to household expenditure on food and non-food items.

– Poverty line is drawn from expenditure required to purchase cost of a basket of goods that allows minimum nutrition requirements

• Mapping vulnerability and water related risks

• Case study on mapping poverty indicators and water access - Uganda


Poverty Hotspots:

0 290 580 870 1,160Kilometers

KEY

Rivers

Water bodies

Poverty level (%)

<15

15 - 25

25 - 35

35 - 45

45 - 55

>55

No data

KEY

Poverty hotspots

Production system

Agro-Pastoral

Pastoral

±

0 290 580 870 1,160145Kilometers

±

0 290 580 870 1,160145Kilometers

KEY

Rivers

Poverty hotspots

Water bodies

Mixed rainfed

Cereals

Cereals+

Legumes

Legumes+

Mixed rain 0 260 520 780 1,040130Kilometers

KEY

Rivers

Lakes

Nile Basin bnd

Poverty level > 50%

Treecrops

Rootcrops+

Treecrops+

Rootcrops

Poverty in pastoral

and agropastoral

systems

Poverty in the

basin

Poverty in cereal

and legume

systems

Poverty in tree and

root crop systems

(banana, cassava &

cotton)


Mapping vulnerability and water

related risks

• Vulnerability as exposure to risk, ability to cope with resulting impacts and the capacity to adapt to new conditions

• Mapped several indicators of bio-physical and social risks which results into vulnerability

• The outcomes of these cluster data were combined asseverity indices ranging from 4 to 5 levels depending on the number of variables used

• Vulnerability maps indicate levels of exposure to risk. These risks ranged from very high risk, high risk, moderate risk, low risk and very low risk.


• hotspots of vulnerability in agricultural systems (biophysical risks estimated from cluster data classification of human and livestock population, market access, internal renewable water resources and area of crop suitability)

• population is a key driver of exposure to biophysical vulnerability especially in the intensifying crop livestock systems throughout the highlands and in the central belt of Sudan

AgropastoralRainfed cereals Rainfed tree crops Irrigated

KEY

River Nile

Water bodies

Bio-Physical risks

Very low

Low

Medium

High

Very high

0 290 580 870 1,160145Kilometers

KEY

River Nile

Water bodies

Bio-physical risk

Very low

Low

Medium

High

Very high 0 290 580 870 1,160145Kilometers

KEY

River Nile

Water bodies

Bio-physical risk

Very low

Low

Medium

High

Very high

0 290 580 870 1,160145Kilometers

KEY

River Nile

Water bodies

Bio-physical vulnerability

Very low

Low

Medium

High

Very high0 290 580 870 1,160145

Kilometers

Vulnerability hotspots:


KEY

River_Nile

Water bodies

Social risk

Low

Medium

High 0 290 580 870 1,160145Kilometers

KEY

River Nile

Water bodies

Social risk

Very low

Low

Medium

High

Very high0 290 580 870 1,160145

Kilometers

KEY

River Nile

Water bodies

Social risk

Very low

Low

Medium

High

Very high

KEY

River Nile

Water bodies

Social risks

Very Low

Low

Medium

High0 290 580 870 1,160145

Kilometers

-hotspots of vulnerability in agricultural systems (social risks estimated from cluster data classification of disease prevalence; malaria HIV/AIDS and stunted growth and malnourished children below age 5)

- high vulnerability index in agropastoral areas reflects exposure and low capacity to cope with disease and food insecurity due to high poverty rates

- low vulnerability index in irrigated systems reflects better institutional capacity to cope with the impacts of disease and food insecurity

- exposure to disease and food insecurity is widespread in the rainfed agricultural systems of the basin except along the lower nile and into the delta region

Agropastoral Rainfed cereals Rainfed tree crops Irrigated

Vulnerability:


- hotspots of water related risks in agricultural systems (hazards estimated from cluster data classification of drought index; rainfall variability as CV rain and changes in the length of growing period; LGP)

- high risk index in agropastoral and rainfed areas reflects high variation due to rainfall and changes in the length of growing period

- low risk index in irrigated systems reflects less dependency on rainfall

KEY

River Nile

Water bodies

Risk due to water

Very low

Low

Medium

High


KEY

River Nile

Water bodies

Risk due to water

Low

Medium

High


±

KEY

River Nile

Water bodies

Risk due to water

Ver Low

Low

Medium

High 0 290 580 870 1,160145Kilometers

Agropastoral Rainfed cereals Rainfed tree crops Irrigated

Water related risks:

KEY

River Nile

Water bodies

Risks due to water

Very low

Low

Medium

High



Linking water, agriculture and poverty

Where are the poor?

• in hotspots with high population densities in the mixed rainfed agricultural systems particularly those supporting cereal-legume cropping and banana/cassava systems

• These are concentrated in the highlands of east Africa (Kenya, Uganda, Rwanda, Burundi and Ethiopia)

• In pastoral and agropastoralsystems of the central belt of Sudan, northern Uganda and the lake region of Tanzania

• Low poverty in rice, wheat and cotton systems

What are their water related problems?

• Food insecurity due to high poverty rates and dependency on rainfed agriculture

• high risk of rainfall variation and changes in length of growing season in pastoral and agropastoral systems

• high exposure to disease and malnutrition due to low institutional capacity to cope with the negative impacts

• low risk of rainfall variation and changes in length of growing season in the highlands as well as lake Victoria sub-basin but widespread poverty still unexplained by good market access


Objectives:– Assess Nile water availability (spatio-

temporal distribution)

– Assess water demands and use

– Assess water accessibility

Methodology– Rapid Assessment through literature review

– Identify and fill in gaps of existing knowledge

– Statistical analysis (trends, frequencies)

– Water accounting

3. WP2: Assessment of Water

Availability and Access

Sudan

Egypt

Ethiopia

Uganda

Tanzania

Kenya

Eritrea

Rwanda

Burundi

Congo, DRC


��Flow station��rainfall station

Nile Basin Databases

• Hydrological data base

• Climate (precipitation)

database (+ grid data)

• ET, soil moisture, biomass,

etc., (WaterWatch)

• Storage systems database

(under development)


Sample results: Data collection

Nile Database: Monthly river flow: 1910 to 2000

ASWAN QP BAHIR_DAR QP DONGOLA QP GIRBA QP HASSANAB QP J_AULIA QP JINJA QPKESSIE QP KHARTOUM QP KILO_3 QP MALAKAL QP MANGALA QP ROSEIRES QP SENNAR QPTAMANIAT QP

11-201011-200011-199011-198011-197011-196011-195011-194011-193011-192011-1910

Dis

ch

arg

e P

roce

sse

d [m

3/s

]


How much is the Nile

(Blue) water?

Is it 84.5 billion m3

(data from 1900 to 1950)

Long term mean: source

Sutcliffe and Parks, 1999


Nile trends: water flows

MAIN NILE

Monthly Flows: 1871/72 -2000/01

0.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

1871

-72

1877

-78

1883

-84

1889

-90

1895

-96

1901

-02

1907

-08

1913

-14

1919

-20

1925

-26

1931

-32

1937

-38

1943

-44

1949

-50

1955

-56

1961

-62

1967

-68

1973

-74

1979

-80

1985

-86

1991

-92

1997

-98

Bill

ion

M3

TOTAL

5yr moving mean

Q 1900 to 1950 = 86.3

Q 1900 to 1995 = 80.8

Q 1951 to 1995 = 76.0

What are the recent trends? More

water? ��88km3


>1600

1400 - 1600

1200 -1400

1000 - 1200

200-400

400 - 600

600 - 800

800 - 1000

< 25

25 - 50

50 - 100

100 - 200

Mean PMean ET0


What is the seasonal

variability?


Nile water accounting: Methodology

• Based on water balance principle (inflow =

outflow +∆∆∆∆S)

• Define indictors: supply, consumption,

beneficial (economical, environmental), non-

beneficial

• Boundary conditions (Inputs):

– Water Supply: Rain, River, Groundwater

– Water use: Consumptive (ET), non-

consumptive, beneficial (T), non-beneficial

(E), committed (treaties), etc.

• Scales:

– Spatial: catchment, production system,

sub-basin, basin, country

– Temporal: month, season, annual, long term

mean

• Output

– Water accounting �� water productivity

Source: Molden, 1997


Input: Land and water use classes

MWsaline sinks15

MWmanaged wetland14

NLnatural lakes and rivers13

MWreservoir12

MWirrigated crop11

NLdesert10

MWUrban + industustry9

MLrainfed crops8

NLnatural wetland7

NLsparse savanna6

NLopen savanna5

NLwoody savanna4

NLshrub land3

NLopen forest2

NLclosed forest1

clas

sLand useNo.


Input: Land and water use classes

3,162,26

6Total

02132021324500%313MWSaline sinks15

01704017044500%501MWManaged wetlands14

015550155512503%88,832NLLakes & rivers13

02916029164000%5,991MWReservoir12

14758808949752502%51,493MWIrrigated crop11

3283221536030%941,604NLDesert10

57761051212273500%5,377MW

Urban and

industrial9

136721556848399107%235,526MLRainfed crops8

17447210108812996700%14,077NLNatural wetland7

874110750461268510%315,078NLSparse savannah6

1642918951069978024%764,232NLOpen savannah5

23348220699919109012%373,785NLWoody savannah4

5074651622272908%260,299NLShrub land3

173161776137919001%19,337NLOpen forest2

33818183929111313503%85,821NLClosed forest1

Productio

n

Kg/ha

E

mm

T

mm

ET

mm

Rainfall

mm

Area

%

Area

Km2

landus

e typeLanduse�o.


�atural land cover Managed land use Managed water use

�atural forest P, ET

Savanna P, ET

Desert P, ET

.. P, ET

Forest plantation P, ET

Rainfed crop P, ET

.. P, ET

Irrigation P, ET

Managed wetlands P, ET

Drinking water P, ET

.. P, ET

inflow

Aquifer & reservoirs

Water balance for 2007 in km3

81.4 -57.4

29.0 Outflow

5.0

0.0

0.0

Committed 9.8


Water balance indicators for 2007

water balance components

1745 1716

76.6 57.4 29.0 9.8 19.20

500

1000

1500

2000

wat

er s

uppl

y

cons

umed

Ava

ilabl

e

dive

rted

outfl

ow

Com

mitt

ed

Exc

ess

km

3

Water Balance indicators

0%

25%

50%

75%

100%

Consumed Available Diverted Excess Committed


Water consumption for 2007

water consumption

1458

189 69

1305

716 588411

0

500

1000

1500

2000

natu

ral la

nd c

...m

anage

d la

n...

man

aged

wat..

Benef

icial

Benef

icial-E

con

Benef

icial -

EnvNon-

bene

ficia

lE

T,

km

3

Water consumption indicators

0%

20%

40%

60%

80%

100%

Nat

ural

LU

Man

aged

LU

Man

aged

WU

Benef

icial

ET

Ben_E

con.

ET

Ben_E

nv. E

T


Water production for 2007

Biomass production in 109kg

0

500

1000

1500

Clo

se

dfo

res

t

Op

en

fore

st

Sh

rub

lan

d

Wo

od

ys

av

an

na

h

Op

en

sa

va

nn

ah

Sp

ars

es

av

an

na

h

Na

tura

lw

etla

nd

Ra

infe

dc

rop

s

Urb

an

an

din

du

str

ial

De

se

rt

Irri

ga

ted

cro

p

Re

se

rvo

ir

La

ke

s &

riv

ers

Ma

na

ge

dw

etla

nd

s

Sa

line

sin

ks

land and water use

an

nu

al

bio

ma

ss

in

10

^9

kg

Biomass

Food

Feed

wood

Env.


Basin PS: Low to High Resolution

4. WP3: Production Systems &

Productivity


Water productivity mapping:

METHODOLOGY


• Production data:- Countries statistic departments - FAO database in 2005

• Market prices of agricultural products

• RS images and secondary GIS data

- Waterwatch 2007 ETa and Ta maps

- Land use/land cover (LULC); GLC 2008/ Africover

- Admin and basin boundaries, road network, ecological zones

Data sources


Standardized gross value of production

SGVP: is an index which helps to compare the economical

value of different crops regardless in which country or

region they are.

∑=

×

×=

i

i

cropbaseicrop

cropbase

icrop

crops pricenalInternatioproductionpricelocal

pricelocalSGVP

1

Wheat is the major crop in the basin and it is taken

as base crop.


Rainfall and Water stress


SGVP

SGVP/ha is highly variable

across the basin.

Egypt has the highest SGVP/ha, 1830 US$/ha

Sudan has the lowest SGVP/ha, which goes down to about 20 US$/ha in Northern Darfur


WP – SGVP/ETa & SGVP/Ta


Conclusions

- More than half of the basin area is under high water stress

- SGVP and Water productivity are highly variable across

the Nile basin

- While Egypt has the highest SGVP and WP, Sudan has the

lowest

- Except Gezira and northern provinces of Sudan in which

irrigated farming is common practice, WP is very low in

other parts of the country where rainfed farming is

predominant.


Livestock Productivity: Where are the animals?

Nile BasinTropical

Livestock

Units per Km2

<1

1-10

10-20

20-30

>30


Water productivity calculations for livestock for the Nile Basin.


Water Productivity of Aquaculture

http://girlsoloinarabia.typepad.com/photos/egypt/water_wheel.jpg

Objective• to estimate quantities of water used

per unit biomass of fish produced in ponds in the Nile Delta

• to prepare water budgets for earthen pond aquaculture to help guide future water allocation policies

• to assess the water productivity benefits of different aquaculture technologies and incorporating aquaculture with agriculture

– production and incomes

– poverty


Site 2

Site 1

� Estimate net water use in pond

aquaculture throughout production

season at two sites in the Nile Delta

(WorldFish Center pond farm,

Abbassa, and at a commercial fish

farm, Kafr El-Sheikh)

� Estimate water losses through

different routes (seepage,

evaporation, drainage etcL)

� Determine the amount of fish

produced

� Estimate water consumption rates

(m3) per kg fish production

Experimental plans


Estimating water use

waterfeed + inflow = outflow + ∆S + waterfish

modified from Nath & Bolte (1998)

excluding rain, surface runoff, waterfeed, and

infiltration, inflow can be regarded as water added

excluding overflow and waterfish outflow can be regarded

as change in pond storage plus seepage and evaporation

i.e.

water consumption per kg fish production = kg fish pond-1/Ii – (E + S + Q ± ∆S)

water consumption per pond = Ii – (E + S + Q ± ∆S)


Abbassa ponds

• 5 ponds, stocked 1 June 2008


Routine measurements

• pond water levels determined weekly using fixed graduated tubes at three locations per pond

• water levels determined before and after water was added to compensate for losses

• fish sampled monthly to determine growth

• fortnightly water samples taken to determine DO, pH, Secchi disc depth, N and P

• monthly analysis of phytoplankton

tube to measure pond

water column height


Fish growth in earthen ponds

over a five-month growing period

0

50

100

150

200

250

Start

mon

th 1

mon

th 2

mon

th 3

mon

th 4

mon

th 5

Groth period (month)

Avera

ge f

is w

eig

ht

(gm

)

Pond 1

Pond 5

Pond 10

Pond 13

Pond 16


Water use – preliminary results

(Abbassa Site)

tube to measure pond water column height


Seasonal variation in losses of

water


Research questions

• What are the water related institutions and policies that shape agricultural outcomes in the Nile Basin?

• Do existing institutional and policy environment support beneficial use of water for poverty alleviation?

• Are basin wide priorities and nation wide institutions and policies compatible?

• What are the agriculture related outcomes in the basin?

5. WP4: Institutional Analysis of

the Nile Basin


Research methods

• Understanding institutions and policies at multiple scales

– Basin wide analysis: (Institutional analysis of the NBI and CFA)

– Country analysis: Review of institutions and policies in selected countries (Egypt, Sudan and Ethiopia)

– Micro level analysis at hotspots: Lake Victoria, Ethiopian Highlands, Gezira scheme and Sudd wetlands

• Mixed methods: Literature review and primary data collection


Institutional analysis of NBI

• What worked?

– Promoted the culture

of dialogue between

riparian states

– Attracted large donor

funding

– Basin wide

perspective

– Shared Vision and

Subsidiary Action

Program produced

important outputs


Institutional analysis of NBI

• What did not work as expected?– Not much evidence that power

balance between upstream and downstream riparians have indeed changed

– Absence of a clear regulatory framework even after 10 long years of negotiation

• Conclusion– The future of cooperation in the

Nile Basin is not ‘black or white’: the choice is not between, on the one hand, fully-fledged cooperation and non-cooperation on the other. On the contrary, there exists a large and diverse grey-scale and the different emerging scenarios involve their own complexities.


Results from micro-level

institutional studies

• Insights on collective action for watershed management in Ethiopian

Highlands

–Compared successful watershed intervention with a not so successful one

–The inherent strength of local institutions & support given by implementing

agency (GTZ in this case) are the two crucial factors in success.

• Impact of institutional and policy change on productivity of Gezira

–Change in institutional regime from joint account to individual account to

economic liberalisation

–Production, productivity and cropping pattern changed with every change in

policy and institutions

–Area under cotton fell and gave away to wheat and other food crops.


Results from micro-level

institutional studies

• Institutional mechanisms in Lake Victoria

Multiplicity of institutions and overlap of authority and responsibilities;

–Fisheries management is the best coordinated activity among the 3

eastern Nile country

–Centrality of income from fisheries leads to such cooperation

–Provides employment to 3 million people

–Generates USD 400 million worth of income of which USD 250 is export

earning


6. WP5 Intervention Analysis

Objectives:• To understand interventions that can have greater

impacts in the Nile Basin

• Specific objectives are to:– Inventory and characterize existing interventions in

production systems

– document success and failures of interventions and map intervention types

– detail performance analysis of existing interventions and impacts

– undertake tradeoff analysis, ranking and modeling to select and evaluate high impact interventions and implementation strategy

– Develop problem tree & impact pathways through interventions


Key Research Questions

• What are the existing water related interventions in the basin under various production systems?

• Which interventions have succeeded and which ones failed?

• What are the technical, economic, institutional setups for successful or failed interventions under various systems?

• Which future interventions are required to bring high impact on poverty, water availability, access and productivity for various target groups?

• Note: All questions may not be answered and some will lead to future work


Interventions Category/ Types

- Production/Farming system based• Crop Based: Field Crops, Horticulture, Forestry/ agro-ForestryQ

• Animal based: Livestock, Fisheries/Aquaculture

• Rain fed, irrigation, mixed crop-livestock, etc

– Physical based• Infrastructural interventions

• Water and land based interventions: eg watershed management

– Socio-economic based• Ag trade, virtual water

• Hydropower-generation, power trade, interconnection

• Industrial – value addition

– Institutional and policy based• Institutional innovations, basin, sub-basin institutions

• Benefit/water-sharing


Interventions Category

Regions/zones

– 5 specific detail case study sites• Ethiopian Highlands

• Victoria Nile

• The Sudd

• Gezirra

• Delta

– One integrated basin wide analysis


Example 1: Ethiopian Highlands Agricultural Interventions

(Agriculture - main source of livelihood)

Challenges• Extreme biophysical variations

– Elevation, soil, climate

• Population pressure and land

degradation

⇒Shortage of land

⇒Encroachment to marginal lands

⇒Exacerbating deforestation and erosion

⇒Reduced land and water productivity

• Poor infrastructural development

• Limited use of modern technologies

– Lack of site specific technologies

– Lack of integrated approach

Incr

ea

sed

po

ve

rty

, fo

od

in

secu

rity

&

Vu

lne

rab

ilit

y t

o c

lim

ate

ch

an

ge

Majo

r chale

ng

es t

o a

gricu

lture

Required: Identification +Disseminate of Site specific Technologies

Pre-requisite: identify “Homogeneous Units”


77

Methodology

• “Homogenous” units of farming systems (FS) have been

mapped based on:

– Agro-ecology (Elevation, Soil, LGP) (BMPS, Woody

Biomass) data

– Major crops grown (BMPS, CSA reports)

• Current crop and livestock productivity of the FS examined

(BMPS,CSA reports)

• Major productivity limiting constraints identified

• Promising technologies identified (secondary data)

• Productivity & Poverty impacts analyzed (HH consumption

data)


78

Results- The FS

10 F

Ss

iden

tified

Single cropping

FS the largest of

cereals

Single cropping

FS the largest of

cereals

Livestock density changes with

small cereals

Livestock density changes with

small cereals

Cereal based

system

dominate


79

Results- the FS: Distribution and

Productivity

• Crop productivity too low

regardless of the FS

• Average grain yield < 1 T/ha

• Maize and sorghum are high

yielding

- much less than the potential &

national average

Some reasons:• Low Soil Quality

• Lack of improved technologies

• AWM (SWC, irrigation, drainage)

• Soil fertility management

• Improved Crop varieties


Characterization


The way-out: Multi-faceted

Interventions

– Agricultural water management

• Conservation, Irrigation, Drainage

– Soil and Water Conservation

• Biological + mechanical

– Soil fertility management

• Fertilizers +Liming

– Improved crop varieties

– Crop protection

• Pre +Post harvest tech.

81

Technological

Integrate

Technologies:

– S+S+W

– IWSM


82

0

0.5

1

1.5

2

2.5

3

3.5

Traditional Tied ridge Traditional Tied ridge Traditional Tied ridge

Sorghum Mungbean Maize

Yield (t ha-1)

Location Variety Management practices Increment (%)

Traditional Improved

Jimma local 28.4 37.3 32

UCB 25.9 46.1 78

Beletech 26.3 39.8 51

BH_140 26.4 45.9 74

BH-660 25.8 57.6 124

kuleni 26.5 46.2 75

Adet BH-540 29.3 48.96 67

kuleni 50.6 81.8 61

Pawe BH-530 41.7 81.7 96

BH-140 41.7 76.7 84

Bako BH-140 29 34.2 18

Beletech 29 38.2 32

Cro

p v

eri

tie

s a

nd

Mg

t

Some examples of Interventions


Inventory for AWM

In-situEx-situ

Improved planting pits

DiversionStone bunds

Trash lines

Spate irrigation

Well+motorised pump

Well + Treadle

pump + Drip kit

Micro dam + canal + furrow

Large irrigation


List of promising AWM technologies

Dams6.

TerracesTankers 5.

SpatePondPonds 4.

PondWellsWells 3.

River diversionMicro damsMicro dam 2.

WellsRiver diversionRiver Diversion 1.

OromiaAmharaTigrayRank


Poverty, HFS, Institutions & Impacts

• Poverty– 22% less poverty incidence for users

of AWMT

– Treatment led to an increase in HH income - ca.ETB 670/ household

– deep wells, river diversions and micro dams have led to 50, 32 and 25 %reduction in poverty levels compared to the reference, i.e. rain fed system.

∴∴∴∴The impacts of ponds and shallow wells are relatively modest compared to deep wells, diversions and small dams.

• HH food security has significantly improved

• Institutional: – Traditional irrigators higher efficiency

– Modern irrigators have higher production frontiers

– Institutional stabilities considerably affecting performance, L.

Variables Incidence (α=0)

Depth (α=1)

Severity

(α=2)

Access to irrigation

Irrigators 0.585 0.322 0.226

Non-irrigators 0.771 0.425 0.283

0

5

10

15

20

25

30

35

40

45

50

Sales of

Cattle

Sales of Small

Animals

Off-farm

Employment

Consumption

Credit

Food shortage copping strategy

% o

f sa

mple

farm

ers

report

ing

Irrigators

Non-Irrigators


Example 2: Integrated Basin

Analysis

Integrated basin-wide modeling

to: •Assess the current and future

large-scale intervention scenarios

•Evaluate the impacts of these

scenarios on water availability,

access and productivity

•Generate biophysical indicators

of interventions for socio-

economic and environmental

assessments


Integrated Basin Analysis

Infrastructural Interventions

• Control and

Management of

Natural Lakes (2)

• Large

Dams/Reservoirs

and Diversions (15)

• Small dams

• Ground Water

Storage and

Recharge

• Non-Conventional

Water Sources

Technologies


• Large-scale interventions considered:

– Water control and storage infrastructures (single or multi-purpose)

– Irrigation schemes

– Hydropower plants

– Environment and wetlands

• Simulation Scenarios:

– Current large-scale developments (Baseline)

– Medium-term intervention plans (2015)

– Long-term intervention plans (2025)

Large-scale Interventions and

Scenarios


Modeling Framework

• WEAP water resources simulation model applied at monthly time-step

• Monthly river flows are extended from rainfall and ET using monthly water balance model

• Annual irrigation demands are disaggregated according to ET

• Wetland consumptions are treated as sinks (environmental flow requirements)

• Storage release rules are represented as stream flow requirements {Q = f(storagehead)}


Integrated Analysis:River Schematization and Flows

Lake Tana

3,8093,920

Bosheilo

2,072Welaka

4,798Jemma

4,389

North Gojam

2,440Muger

2,187

Guder

1,719

Finchaa

5,012

South Gojam

2,355Anger

5,673

Didessa

3,874

Wonbera

Flow gauging station

Reservoir

6,246

Dabus

4,345

Beles

2,797 Dinder

1,102 Rahad

Khartoum

Border

Roseires

Sennar

Kessie

Outlet Lake Tana

Giwasi

Hawata

SUDAN

ETHIOPIA

4,345Mean annual discharge (Mm3)


All plans:

-Country specific

-SAP projects


Preliminary Results – Lake Victoria

$

#

(ð


Preliminary Results – Wetlands


• The topology of the basin is configured for WEAP simulation model

• Reliable information and data relevant to the integrated modeling are almost collated

• Basin-wide simulations of large-scale intervention scenarios are being conducted

• Finally, the integrated modeling experiment shall generate biophysical indicators for impact assessment and identification of potential interventions

Aggregated Basin Conclusions

and Outlook


WP5 Example: Capacity Building

• Tewdros : Water Resources Allocation of the Nile River Basin: A cooperative Game Theoretic Approach– Integrated economic-hydrologic-institutional modeling at the River Basin

Scale

• George: Developing Optimal Economic Incentives for Managing Transboundary Water Externalities in the Blue Nile River Basin – Application of economic instruments to review the past and present legal

documents on the Blue Nile and treaties governing the entire Nile River Basin

– Modeling optimal allocation of water for maximizing use benefits among the countries established

• Binyam: Equitable Distribution of Benefits in TransboundaryWaters– Irrigation and Hydropower Benefits Sharing

– From Water Allocation and Cost Sharing to Benefit-Sharing: Implications

for Transboundary Rivers in the Nile Basin

• M.Sc. students


7. Conclusions

• Poverty is prevalent in high population, rainfed, pastoral and agropstoral areas and less in irrigated systems and with access to AWM

• Temporal and spatial variability of rainfall and runoff are highand not sufficient mechanisms for improving water access

• Water productivity and productivity/ha are higher in managed water system part of the basins and significant opportunities to improve rainfed productivity

• Regional bodies such as NBI and water institutions give low focus to rainfed production systems, livestock and fisheries. Establishing relevance is important

• NBI Institutional Arrangement is progressing but the outcome is uncertain

• Multiple interventions exist to improve rain fed productivity, reduce poverty and enhance negotiations and economic integration


Thank You

Nile Basin Focal Project

Technology

cpwf river

river water

y alak

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agriculture water management

basin access

low water usageyear10000

assessment of water