Rethinking water storage for climate change adaptation in Sub-Saharan Africa

GTZ project

Project overview

Objective Guidance on storage options that ensure optimal adaptation to CC-induced impacts on water

availability in SSA

Partners Duration and focus• Arba Minch University (AMU), Ethiopia 2008-2011, Nile and Volta • Ethiopian Economic Association (EEA)• Water Research Institute (WRI), Ghana• Institute of Statistical, Social and Economic Research (ISSER), Ghana • Center for Development Research (ZEF), Germany • Potsdam Institute for Climate Impact Research (PIK), Germany

Research Questions • How can the need for water storage and the effectiveness and suitability of different

storage options be evaluated and compared for different climate scenarios? • How can water resource planning and management processes be modified to better

account for the uncertainties arising from climate change?

Principal outputGuidelines on how to build climate change into decision-making processes for the planning

and management of agricultural water storage in sub-Saharan Africa

Project Rationale

• Water storage is widely advocated as a key mechanism for CC adaptation• Little analysis of how CC affects existing water storage or how to account for CC in the planning and

management of new water storage

Physical Storage Continuum

Project Output

Guidance on:

“ …..storage options that ensure optimal adaptation to CC-induced impacts on water availability in SSA”

Targeted at institutions that evaluate, design and implement water resource development projects and investment programs

• International development agencies • State bodies • Public and private funding agencies

Evaluation framework Metrics to determine: •The need for water storage•The effectiveness of different options •The suitability of different options

Basin scale analysesEvaluation of climate change impacts on storage at basin scale –effectiveness

Site level analysesUnderstanding storage at the local (economic and socio-political aspects) – suitability

Guidance

Approach

Climate - rainfall, temperature, evaporation • Historic climate • CC scenarios (downscaled to the basins)

Hydrological model (SWAT/SWIM)

Results:Flow at key locations (sub-catchments)

Water resource modeling (WEAP)• current water resource development • future water resource development

Results:Water availability for irrigation/hydropower Effectiveness of existing and planned storage

Basin scale analyses (Nile and Volta)

• Current and future storage plus water use in each basin

• Evaluation of climate change impacts on storage at the basin scale

Climate Modeling

• Approaches of downscaling – Dynamical climate models: CCLM and REMO (both for A1B) + bias correction – Statistical climate model: WettReg (for different scenarios and GCMs)

• Resolution: 0.5° (attempt 10 km but not yet complete)• Further regionalization / interpolation to locations of interest

Mean Annual Total Precipitation [mm], 1971 - 2000

Mean annual total precipitation (mm) 1971-2000

CCLM output for the Nile (A1B scenario)

XGP_106_122

X GP_098_128

GP_106_22Mean Temperature (mm)

GP_098_128Annual Rainfall (mm)

X

X

GP_110_047

GP_095_052

CCLM output for the Volta (A1B scenario)

GP_095_052Mean Temperature (oC)

GP_110_047Annual Rainfall (mm)

RCM Scenarios – Rainfall (Nile)2

030

s –

19

90s

209

0s

– 1

99

0s

Hydrological Modeling

• Rainfall-Runoff simulation to determine impacts of CC on flow regimes and groundwater recharge

• Daily simulation to deduce impacts on extremes – floods and droughts

Nile – Models

STREAM Resolution 1km,

SWIM Soil Water Model (root zone and deep soil water)

Modified MWB Three parameter lumped model – gridded 10km

Volta - Models

SWAT Soil and Water Assessment Tool – Hydrological Response Units

Basin characteristics

NDVITopographic WI

MWB: Model calibration and validation

Water Resource Modeling (WEAP)

• Water Evaluation and Planning (WEAP) Model • Water accounting model (mass balance) – optimizes water use

(monthly time-step)

• Data from:

Nile Volta

MoWR Hydrological Services Department

Basin Master Plans Volta River Authority

Irrigation efficiency studies Ghana Water Resources Management Study

New scheme feasibility studies

Scenarios

Development stage

Historic climate

CC scenario A1B CC scenario A2

2030-2040 2090-2100 2030-2040 2090-2100

Natural Nile

Current situation Nile & Volta

Near Future+ Nile

Distant Future* Nile

+ Planned development – feasibility studies conducted * Potential development – identified in Master Plans etc.

Current situation

Devaraj de Condappa et al (2008)

WEAP configuration for the Volta

WEAP configuration for the Nile

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Current situation Near future Distant future

Blue Nile Ethiopia: Existing and Planned schemes

CurrentNear

futureDistant future

Irrigation (ha) 10,000 210,000 451,000

Hydropower (MW) 218 2,194 6,426

Storage (Bm3) 11.5 56.8 ~100

0

5,000

10,000

15,000

20,000

25,000

30,000

Jan-

60

Jul-6

1

Jan-

63

Jul-6

4

Jan-

66

Jul-6

7

Jan-

69

Jul-7

0

Jan-

72

Jul-7

3

Jan-

75

Jul-7

6

Jan-

78

Jul-7

9

Jan-

81

Jul-8

2

Jan-

84

Jul-8

5

Jan-

87

Jul-8

8

Jan-

90

Jul-9

1

Flow

(Mm

3 )

Simulated natural and 2025 scenario flow at the border

Simulated natural flow at the border

Simulated 2025 scenario flow at the border

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

1 2 3 4 5 6 7 8 9 10 11 12

Mea

n M

onth

ly F

low

(M

m3 )

Natural flow 2015 flow 2025 flow

Simulated natural MAF = 47.0 Bm3

Simulated current MAF = 46.9 Bm3

Simulated 2015 MAF = 44.8 Bm3

Simulated 2025 MAF = 44.4 Bm3

Current Near future

Distant future

Irrigation Demand (Bm3) 0.20 3.65 5.13

Hydropower (Gwhy-1) 1,383 12,908 31,297

Results (no climate change)

Site Level Analyses

3 locations in each of Nile and Volta

Nile = Koga, Gumera , Guder IdrisVolta = Vea (Yaragatna River), Golinga, Sata

• Evaluation of socio-economic aspects of storage• What benefits accrue and who gets the benefits? • What are the costs and who has to pay?

• Issues availability; economic viability; uptake; access; equity; institutional arrangements; socio-political aspects etc.

Approach

Socio-economic survey – Quantitative – Conducted in all sub-basins – Information on benefits/costs people derive from different water storage options as well as

perceptions of CC

ZEF investigations – Qualitative– Gender aspects and the access to natural resources in a small-scale irrigation scheme (Shina

dam), Gumara watershed.– Watershed and irrigation management in a large-scale irrigation scheme, Koga watershed.– Resettlement, social bonds and attachment to land in a large-scale irrigation scheme, Koga

watershed.– Power relations and control over water resources. The case of Indris irrigation scheme. – Access to land and water management: Indris irrigation scheme. – Socio-economic and political impact of water storage facilities on rural household livelihood.

A study of Gumera watershed, Abay River Basin, Ethiopia

Impacts of small-scale water storage on rural household livelihoods in Gumera

Benefits • 3 crops/year – sufficient food• Increased variety of crops (e.g. rice)• Increased income. Farmers can earn between 3,000 – 5,000 EB per

vegetable garden• Increased size of land holdings. Some farmers can now rent land to

expand their production• Reduced cases of water borne diseases • Stronger relationship with neighbors due to water sharing

Constraints • Cracking of the soil• High material and construction costs• Labor shortage – common with FHHs, old age HHs• Limited skills in management of ponds

Evaluation Framework

Objective of water storage is to reduce climate vulnerability

Present climate vulnerability (pre-adaptation)

Water storage (adaptation strategy)

Future climate vulnerability (post adaptation)

Increased availability and access to water

Increased adaptive capacity

Increased agricultural productivity

Future climate vulnerability < Present climate vulnerability

Increased water security

Steps

Is storage needed now and/or will it be in future?

No (stop evaluation)

Yes

Is it and will it in future be technically effective? Is it and will it in future

be socio-economically suitable?

No (stop evaluation)

Yes

No (stop evaluation)

YesContinue with detailed planning

As far as possible:

• Objective /quantitative• The same for all storage types • Applicable across a range of scales• Applicable now and under climate change scenarios

The need for agricultural water storage

Metrics Indicators

Agricultural vulnerability to climate • Rainfall variability; • Length of growing season

Community (socio-economic) vulnerability • % of population living below the poverty line• % of population whose livelihood depends on agriculture

Exploitation of water resources • % of cultivated area dependent on full irrigation • Proportion of annual river flow abstracted• Proportion of groundwater recharge abstracted

Importance of existing water storage • Volume of storage/household

Technical effectiveness of the water storage system

Metrics Indicators

Reliability • the probability that the system is in a satisfactory state (i.e. can meet demands).

Resilience • the capability of the system to return to a satisfactory state from a state of failure

Vulnerability • the maximum duration and the cumulative maximum extent of system failure

Reliability Resilience Vulnerability

Koga Gomit Koga Gomit Koga Gomit

Historic climate 0.992 0.950 0.037 0.032 37 71

-20% rainfall 0.968 0.874 0.020 0.016 64 88

+20% rainfall 1.000 0.979 1.000 0.055 0 44

RRV for Koga and Gomit dams in the Nile Basin:

Challenge = need to be able to compute these metrics for a number of storage types within a storage system

Gomit

Koga

Suitability of the water storage system

Metrics Indicators

Accessibility • land and water rights • land tenure • equity of access etc.

Social Cost • relocation/compensation• social stratification • social and patronage networks etc.

Social Benefits • relocation/compensation• social stratification • social and patronage networks etc.

Management/Maintenance • leadership • institutional arrangements • knowledge and skills • labour

Options to adapt • change in livelihood portfolio • change in social networks

Most likely metrics through multi-criteria scoring systems rather than numerical data

Capacity Building

Capacity Building:

• 3 MSc’s completed (Arba-Minch)• 12 Masters ongoing:

– Arba Minch – ZEF – University of Accra – Humboldt University

• 1 PhD student University of Berlin

Project website

– http://africastorage-cc.iwmi.org/

Photo Gallery Links to other sitesReports/Power points/Papers

Thankyou

Bias correction

1. For each grid point, long-term (1961-90) observation (corrected) and long-term simulation by CCLM are compared on a monthly basis;

2. The bias per month is calculated for each cell and month;3. The climate projections are corrected by this bias.

Simulated by climate model

Simulated and bias corrected

Observation corrected by measurement error

Observation