Assessment of current and future trends in water resources in the Gambia River Basin in a context of climate change

Abstract

The accurate assessment of water resources at the catchment level is crucial for effective integrated river basin management. While semi-distributed/distributed models require complex structures and large amounts of input data, conceptual models have gained attention as an alternative for watershed modeling. In paper, the performances of the GR4J conceptual model for the runoff simulation in the Gambia catchment at the Simenti station are analyzed over the calibration (1981-1990) and validation (1991-2000 and 2001-2010) period. The primary inputs for conceptual models like GR4J are daily precipitation data and potential evapotranspiration (PET) measured from the same catchment or a nearby location. Calibration of these models is typically carried out using the Nash-Sutcliffe daily efficiency with bias penalty as the objective function. In this case, the GR4J model is calibrated using four optimization parameters. To assess the effectiveness of the model's runoff predictions, various statistical measures such as the Nash-Sutcliffe efficiency, coefficient of determination, bias, and linear correlation coefficient are calculated. The results obtained in the Gambia watershed at the Simenti station indicate satisfactory performance of the GR4J model in defined of prediction accuracy and computational efficiency. However, this study is significant to observe that the investigation shows an extensive dispose of changes in all measurements across the watershed sample under different scenarios, specifically the SSP 245 and SSP 585 scenarios. These changes recomamnde a decreasing trend in flows, which would pose significant challenges for water management. Consequently, it is clear that sustainable water management would require substantial adaptation measures to cope with these changes.