An interdisciplinary scenario analysis to assess the water availability and water consumption in the Upper Oueme catchment in Benin

Type Journal Article - Advances in Geosciences
Title An interdisciplinary scenario analysis to assess the water availability and water consumption in the Upper Oueme catchment in Benin
Author(s)
Volume 9
Issue 9
Publication (Day/Month/Year) 2006
Page numbers 3-13
URL http://www.adv-geosci.net/9/3/2006/adgeo-9-3-2006.pdf
Abstract
Abstract. This paper presents an interdisciplinary scenario analysis to assess the influence of global and regional change on future water availability and water consumption in the Up- per Oue ´me ´ catchment in central Benin. For the region three development scenarios were evolved. These scenarios are combined with climate change scenarios based on the IPCC (Intergovernmental Panel on Climate Change). In the mo- delling approach the quantification of the land use/land cover change is performed by the cellular automata model CLUE- S. The future climate scenarios are computed with the re- gional climate model REMO driven by the global ECHAM model. Using this data different land use and climate change scenarios can be calculated with the conceptual hydrological model UHP-HRU to assess the effects of global changes on the future water availability in Benin.
To analyse the future water availability also the water con- sumption has to be taken into account. Due to high popula- tion growth an increase in water need in the future is expected for the region. To calculate the future household water con- sumption data from a regional survey and demographic pro- jections are used. Development of the water need for animal husbandry is also considered.
The first test run of the modelling approach was performed for the development scenario ‘business as usual’ combined with the IPCC scenario B2 for the year 2025. This test demonstrates the applicability of the approach for an inter- disciplinary scenario analysis. A continuous run from 2000– 2025 will be simulated for different scenarios as soon as the input data concerning land use/land cover and climate are available.

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