Physio-Géo (Jul 2012)
Approche par modélisation pluie-débit de la connaissance régionale de la ressource en eau : application au haut bassin du fleuve Sénégal
Abstract
Today water resources management is crucial at various scales (local, regional, national and international). This management is encouraged by the extreme hydrological events (droughts or floods) that can have dramatic consequences on human, economic and political aspects. Appropriately managing a resource requires its evaluation. However, over the last years, there was a tremendous decrease in hydrological monitoring capacities in the riverine countries of the Senegal River to produce sufficiently good information to meet end-users requirements on the main river and its tributaries. Thus there are some gaps in the knowledge of water resources and its seasonal variations in the upper Guinean basin due to discontinuous observation series. In this context, the main objective of this thesis was to simulate missing hydrological data using the GR2M model, especially in the upper Guinean basin. To this end, a physiographic and climatic characterization of the upper basin was performed. The pluviometric regime was characterized using a statistical analysis of annual, monthly and daily rainfall, with a spatial analysis of results. The produced maps provide a visualisation and synthesis tool, not only at the local scale but at the scale of the studied zone. Then the GR2M hydrological model was calibrated and validated on a reference period, which served for infilling gaps in monthly flow time series for the Bafing Makana, Dakka Saïdou and Sokotoro catchments over the 1923-2005 period. On average, the model satisfactorily reproduces the shape of the observed hydrographs. Last, we evaluated the potential impacts of climate change on the evolution of water resources on the upper basin using the outputs of four climate models (CSMK3, HADCM3, MPEH5 and NCPCM) from the 2007 IPPC runs based on the A2 SRES scenario. The impacts of climate change on flows differ between catchments due to different sensitivities to the various climatic variables. On the Bafing Makana catchment, an increase of flow is predicted by the year 2030 with then a decrease by the years 2060 and 2090 when using the CSMK3 and HADCM3 models. A continuous decrease is predicted until 2090 when using the MPEF5 model. Only low variations are predicted with the NCPCM model. At the Dakka Saidou station, the four models yield a decrease of flows for the three time horizons (2030, 2060 and 2090). The Sokotoro catchment is different from the two previous ones. On this catchment, an increase of flow is predicted when using the outputs of the CSMK3, HADCM3 and NCPCM models by the years 2030 and 2060. A decrease in predicted flows is obtained only with the MPEH5 model by the year 2060. For this catchment, a decrease of flows is simulated by the year 2090 compared to 2030 and 2060 when using the CSMK5, HADCM3 and MPEH5 models. A comparison of the annual variability of the outputs of the climate models shows that it is similar for the CSMK3, HADCM3 and MPEH5 models on the three catchments. They yield a progressive decrease in flows between 2030 and 2090. The NCPCM model is different and yields a progressive increase of flows between 2030 and 2090 for the three catchments. This model shows the lowest variability but is also the most optimistic in terms of future flows on the upper basin.
Keywords
