water availability and water demand under global change in...

Universität zu Köln

Water availability and water demand under Global Change in Benin, West Africa

GLOWA ConferenceOuagadougou, 25th – 28th August 2008

B. Diekkrüger, M. Diederich, S. Giertz, B. Höllermann, A. Kocher, B. Reichert, and G. Steup

Outline

• From local scale knowledge to regional simulation

• From analysis of the current situation to scenario development and quantification

• From water availability to water demand: Is there water scarcity in Benin?

Why local scale analysis?• to understand the effects of

global change on the hydrological processes

• to be able to develop models which describe the Global Change effects correctly

Approach• local scale gained through

measurements and analysis of processes in the Ara and the Aguima catchments

• transfer of the knowledge to the whole Ouémé basin

Hydrological processes at the local scale

Process studies

Agricultural land use Natural vegetation

Saprolite

Migmatitic basement

Hillwash

e

Saprolite

Hillwash

Plinthite

Lateral processes are important! Processes differ with land use

Giertz et al. HESS 2006

e

Physical-based model on the local scaleSIMULAT- H

Aguima Catchment 16 km²

Modeling water fluxes at the local scale

Giertz & Diekkrüger GEO-ÖKO 2006

0 – 20 cm

30 – 50 cm

measured

simulated

measured

simulated

0

0.5

1

1.5

2

2.5

3

3.5

20.0

6.01

26.0

6.01

02.0

7.01

08.0

7.01

14.0

7.01

20.0

7.01

26.0

7.01

01.0

8.01

07.0

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13.0

8.01

19.0

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31.0

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30.0

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06.1

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30.1

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05.1

1.01

11.1

1.01

17.1

1.01

disc

harg

e [m

m/d

]

measured simulated

water content

• Conceptual, spatially distributed model with an unlimited numberof HRUs, defined by land use and soil types

• Evapotranspiration: optionally: Penman, Priestley-Taylor, Turc• Surface runoff: SCS curve number• Linear storage for root zone, unsaturated zone and groundwater zone• Surface reservoirs• Inland valleys

Model concept UHP-HRU

Capillary rise

Surface runoff

Percolation

Interception

Evapotranspiration

Interflow Infiltration Root zone

Base flowGroundwater zone

Unsaturated zone

Deep groundwater recharge

Catchment withHRUs

Modeling UHP-HRU Ouémé-Bonou: Validation

Save

Cotonou

Bassila

Parakou

Djougou

Natintingou

¹0 25 50 75 10012.5Kilometers

Rivière

Oueme Bonou

Oueme Save

Oueme Zangnanado

Zou Atcherigbe

Validation Ouémé Save

0

200

400

600

800

1000

1200

1400

1600

07.0

1.19

86

07.0

5.19

86

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86

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1.19

87

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5.19

87

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89

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5.19

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07.0

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07.0

9.19

93

m³/s

observedsimulated

Period Surface (km²) R² MEOuémé Save (Cal) 1985-1986 49285 0.9 0.69Ouémé Save (Val) 1996-2003 49285 0.84 0.8Ouémé Zangnanado (Val) 1986-1994 23491 0.64 0.55Zou Atcheribé (Val) 1980-1993 7035 0.84 0.83

Conclusion: from local to regional scale • Knowledge on local scale processes is most important

for inland valley studies, small reservoirs studies as well as agricultural production.

• Local scale knowledge is considered in the Spatial Decision Support Systems

BenIvis Pedro

• Hydrological simulation models for the local and the regional scale have been developed and validated

• These models can be applied for scenario quantification and for Decision Support

Outline




Hydrologisches ModellUHP

SIMULAT-H

climateland use/land cover

hydrologic modelUHP-HRU

soilDEM

surface water resources

Station Parakou - rainfall distribution 1960-2000

0%

10%

20%

30%

40%

50%

<1 mm 1-5 mm 5-10 mm 10-20 mm 20-50 mm 50-100mm

>100 mm

Rainfall amount per day

Frac

tion

of to

tal r

ainf

al

simulated_mean (REMO 6 runs)measured

From climate modeling to hydrological scenarios

100

120

140

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180

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220

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260

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300

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

REMO901 REMO902 REMO903 measured

[mm

]

• Scale of climate models often do not match the scale of the hydrological models

• For linking mesoscale climate model output to a hydrological model a probability matching concerning amount and frequency distribution is required

• After post-processing the climate model output an one-way coupling of climate and hydrological model possible

Mean Potential Evapotranspiration for Parakou(1979-1993) calculated using the Penman-Monteithequation with simulated REMO-Data and measured data

Simulated climate scenariosOuémé Bonou

0

50

100

150

200

250

1985-1995 1995-2004 2005-2015 2015-2025 2025-2035 2035-2045

[mm

/a]

Simulated usingmeasurements

A1B B1

Renewable water resources


Comparison of renewable water resourcesperiod 1995-2004 and scenario A1B 2035-2045

Save

Cotonou

Bassila

Parakou

Djougou

Natintingou

¹0 25 50 75 10012.5Kilometers

Renewable water ressourcesMean 2035-2045 [mm/y]

40 - 60

61 - 80

81 - 100

101 - 120

121 - 140

141 - 160

161 - 180

181 - 200

201 - 220

221 - 260

261 - 280

281 - 400

Rivers

Save

Cotonou

Bassila

Parakou

Djougou

Natintingou

¹0 25 50 75 10012.5Kilometers

Renewable water ressourcesMean 1995-2004 [mm/y]

40 - 60

61 - 80

81 - 100

101 - 120

121 - 140

141 - 160

161 - 180

181 - 200

201 - 220

221 - 260

261 - 280

281 - 400

Rivers

Conclusion: hydrological scenarios

• The scenarios reveal a significant decrease of available water resources in the Ouémé basin

• Detailed and distributed information on water availability is provided based on a thorough understanding of the processes

• The model is implemented in the Spatial Decision Support System BenHydro which allows to analyze the effects of climate change, land use change, reservoirs etc. on water availability

• Test the SDSS BenHydro

Outline




Is water a scarce resource in Benin?

• currently 4000 m3/cap/a (critical < 1700 m3/cap/a)but• water scarcity at the local scale is currently observed at

the end of the dry season (although often due to economic reasons)

• poor drinking water quality• increase in population cause a decrease in water

availability per capita (halving every 22 years)• increase in irrigation agriculture and livestock causes an

increase in water demand

Aquifer properties

~10 m

~50 m

Saturated thickness

Watervolume

Specific Yield [-]

0.03

0.0001Jan-05 Jan-06 Jan-07

337

338

339

340

341

342

343

Wat

er ta

ble

elev

atio

n

Fô-Bouré

Seasonal water level fluctuation of 2.5 meters in the weathered zone influence the water storage by about 25 %

300 l/m2

5 l/m2

Average water storage: 305 l/m2

98% in the weathered zone

Balancing water availability and water demandWEAP: Water Evaluation and Planning System

WEAP is able to• use external simulation results concerning water availability

or use integrated simple hydrological modeling • consider surface water reservoirs• compute water demand considering different sectors

– domestic water use– agricultural water use– industrial water use

and to consider access to water • consider water price development• to compute water quality• …

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Com

mun

eTc

haou

rou

Com

mun

eO

uess

e

Sub-basin no. 93

Oue

me

catc

hmen

twith

27

sub-

basi

ns

• 27 sub-basins

• 5 departments

• 34 communes

• 32 river segments

• 28 groundwater aquifers

• 188 demand sites

• 4 reservoirs (Djougou, Parakou, Savalou, Savé)

• monthly time steps

Application of WEAP to the Ouémé basin

Scenario development

Climate scenarios:IPCC A1B oder B1

B1: Economic growth

and consolidation of decentralization

B2: Economic stagnation

and institutional insecurity

B3: Business as

Usual

Scenarios developed for

1. Domestic water use

2. Agricultural water demand (irrigation agriculture, livestock)

3. Industrial water demand

Water demand per sector and scenario in Mm³/a

0

5

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25

30

35

40Ye

ar 2

002

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ar 2

010

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ar 2

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ar 2

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5

Domestic: Rural Domestic: Urban Industry Periurban Irrigation Basfonds Irrigation Large Scale Irrigation Livestock

Scenario B1 Scenario B2 Scenario B3

Scenario

Domestic: Domestic: Industry Periurban Inland Large Livestock Rural Urban Irrigation Valley Scale

Irrigation Irrigation

B1: economic growth B2: economic stagnation B3: business as usual

Total monthly water demand in Mm³mean over 2002 - 2025


0

1

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5

6

7

8

9

10

January

Febru

ary

March

April

May

June July

AugustSep

tember

October

November

Decem

ber

Total unmet demand in Mm³IPCC climate scenario A1B


-

5

10

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2520

02

2003

2004

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2006

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2010

2011

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2024

2025

Unmet demand per sector and scenario in Mm³IMPETUS B1 economic growth with

IPCC climate scenario A1B

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22

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2025

Urban Rural Livestock Periurban Irrigation

Total monthly unmet demand in Mm³IMPETUS B1 economic growth with

IPCC climate scenario A1B

0

0.5

1

1.5

2

2.5

3

January

Febru

ary

March

April

May

June

July

AugustSep

tember

October

November

Decem

ber

Scenario B1 A1B 2015 -2025 Scenario B1 A1B 2002 - 2014

Conclusion: water demand• Scenario calculations reveal an

– increase in water demand due to an increase in domestic water use and irrigation agriculture

– increase in total unmet demand (2015 – 2025)

– increase in length of the water scarcity period up to 8 to 10 months with a peak from December to March

– increasing pressure on reservoirs and surface water

• User relying upon groundwater are less affected although groundwater level decreases (economic scarcity possible)

• Test the Spatial Decision Support System BenEau

BenEAU

Conclusion

• The analysis of water availability and water demand reveals that water is one of the key issues for sustainable development in Benin

• The IMPETUS studies are important for supporting the Integrated Water Resource Management process which is currently developing in Benin

• Based on the interdisciplinary modeling approach a number of Spatial Decision Support Systems have been developed which links knowledge gained at different scale with scenario development

• Please visit the poster session and test our SDSS

Thank you for your attention


water availability and water demand under global change in...

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