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In West Africa, the concomitant occurrence of extreme droughts and damaging floods points to the urgent need for linking the climate variability at various time scales (daily to decadal) to its impact in terms of water related risks. While hydrological models are key tools to do so, their use in this part of the world is strongly limited by the scarcity of rainfall data. Satellite precipitation products can be used as rainfall input to models in order to make up for this shortage of appropriate surface data. However, these satellite products have their own weaknesses, both in terms of accuracy and resolution. While the accuracy of satellite rainfall estimates has already received a fair amount of attention, little published work deals with the resolution issue. The study presented here is motivated by this lack of attention to the resolution issue. It makes use of the data produced by a very dense rainfall network covering the Ouémé catchment in Benin (14 600 km²), to study the impact of varying the space-time resolution of input rainfields on the output produced by DHSVM (Distributed Hydrology Soils and Vegetation Model), thus mimicking the resolution-induced errors associated with using satellite rainfall input for such physically-based models. The major result of this sensitivity analysis is that the model output is much more sensitive to the time resolution than to the space resolution, at least for this region and for the range of resolutions tested

Influence of rainfall space-time variability over the Ouémé basin in Benin