Abstract
Abstract. 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.
Highlights
West Africa is well known for having experienced a severe drought since the end of the 1960s, but over the last two decades the region has been increasingly affected by floods of unprecedented severity
The application of Distributed Hydrology Soil Vegetation Model (DHSVM) to the Ouémé catchment has been motivated by the ALMIP2 project (AMMA Land surface Model Intercomparison Project – Phase 2; Boone et al 2009) which aims to intercompare results from an ensemble of hydrologic and land surface models applied to the catchments of the AMMA-CATCH observatory
In regions like West Africa where in situ rainfall data are scarce, satellite rainfall are attractive alternatives when it comes to obtaining realistic inputs to hydrological models
Summary
West Africa is well known for having experienced a severe drought since the end of the 1960s, but over the last two decades the region has been increasingly affected by floods of unprecedented severity. The Sahel being characterised by a semi-arid climate, the conclusions of Vischel et al (2007) need to be revisited for the more humid regions of West Africa, where the most damaging floods occurred over the past 10 years or so This is achieved here by using the data produced by a very dense rainfall network covering the Ouémé catchment in Benin (14 600 km). This is achieved here by using the data produced by a very dense rainfall network covering the Ouémé catchment in Benin (14 600 km2) This dataset allows production of high space-time resolution rainfields that are aggregated in time and space to study how using coarser resolutions affects the performance of the physically based hydrological model DHSVM (Distributed Hydrology Soil Vegetation Model; Wigmosta et al, 1994).
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the International Association of Hydrological Sciences
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
