Modeling Extreme Floods Susceptibility Using The GeneralizedExtreme Value Distribution: Case Study Of Gonse And Wayen Burkina Faso,
Lien de l'article: DOI: 10.52155/ijpsat.v41.2.5810
Auteur(s): Bontogho Tog-Noma Patricia Emma, Maré Boussa Tockville, Gaba Olayemi Ursula Charlène, BiaoIboukoun Eliézer
Résumé

Abstract – Over recentes decades, Burkina Faso has experienced extremes events such as droughts and floods. In this study, floodfrequency has been ascertained based on Generalized Extreme Value (GEV). To this end, discharge data from Gonse and Wayenstations are collected from the National Center for Water resources. The period of analysis goes from 1980 to 2022. The Kolmogorov-Smirnov test is applied to check the distribution of the time series. Then, the Maximum Likelihood Estimation (MLE) method isimplemented to estimate the location, the scale and the shape parameters of the GEV distribution. The goodness-of-fit between theempirical data and the theorical distribution is then evaluated based on Akaike criterion (AIC) and Bayenan criterion (BIC). Theresults revealed that across Gonse station, the probability that the annual maximun discharge will be less than 30m3/s is 0.7 and the 50-year return period discharge is 37.33 m3/s. In Wayen station, the probability that the annual maximun discharge will be less than200m3/s is 0.5 and the 50-year return period discharge is 226.38m3/s. The AIC is 308.10 and 484.61 respectively for Gonse and Wayenstation. The BIC is 313.65 and 490.16 respectively for Gonse and Wayen station. The findings may provide a scientific base formanaging the risks of floods to advance climate change adaptation over the Nakambe watershed.

Mots-clés

Flood Return Period Return Level Generalized Extreme Value

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