Modeling the maximum annual flow in South-East Senegal using the GEV distribution

Abstract. Understanding extreme floods is crucial for water resource management and risk prevention in West Africa. However, the statistical modelling of maximum annual flows in south-East Senegal is still largely unexplored. The present study addresses this gap by analyzing and modelling the maximum annual flow using the generalized extreme value (GEV) distribution. Several statistical methods were compared to fit the model, including maximum likelihood estimation (MLE), probability-weighted moments (PWM), elementary percentiles (EP), and quantile least squares (QLS). The comparative performance of these methods is evaluated using the Average Standardized Absolute Error (ASAE) criterion, as well as probability and quantile plots. The results indicate that the probability-weighted moments method provides the best fit. Goodness-of-fit tests confirm that the Gumbel distribution, a special case of the GEV, is more appropriate for representing maximum annual flows in the study area. The 100-year return level of the maximum annual flow is estimated at 1751.242 m3 s−1, indicating that such a flow is likely to occur on average once every 100 years. This study highlights the value of extreme value models for flood analysis in regions with high hydro-climatic variability. The results provide useful insights for understanding hydrological risks in southeastern Senegal and can support future work in hydrological modeling and water resource management planning.