Extreme rainfall in West Africa: A regional modeling

Abstract

[1] In a world of increasing exposure of populations to natural hazards, the mapping of extreme rainfall remains a key subject of study. Such maps are required for both flood risk management and civil engineering structure design, the challenge being to take into account the local information provided by point rainfall series as well as the necessity of some regional coherency. Two approaches based on the extreme value theory are compared here, with an application to extreme rainfall mapping in West Africa. The first approach is a local fit and interpolation (LFI) consisting of a spatial interpolation of the generalized extreme value (GEV) distribution parameters estimated independently at each station. The second approach is a spatial maximum likelihood estimation (SMLE); it directly estimates the GEV distribution over the entire region by a single maximum likelihood fit using jointly all measurements combined with spatial covariates. Five LFI and three SMLE methods are considered, using the information provided by 126 daily rainfall series covering the period . The methods are first evaluated in calibration. Then the predictive skills and the robustness are assessed through a cross validation and an independent network validation process. The SMLE approach, especially when using the mean annual rainfall as covariate, appears to perform better for most of the scores computed. Using the Niamey 104 year time series, it is also shown that the SMLE approach has the capacity to deal more efficiently with the effect of local outliers by using the spatial information provided by nearby stations.

Climate or Land Use?—Attribution of Changes in River Flooding in the Sahel Zone

“…We assume that this effect is based on changes in the frequency of precipitation in the climatic forcing. The findings of Panthou et al [61,62] of increasing convective precipitation supports this theory that heavy precipitation leads to an increase of the run-off coefficient, and finally to an increase in discharge. This effect is also shown by means of measurements in Amogu et al [22].…”

“…Therefore, we assume that changes in the rainfall patterns, most likely an increase in the frequency of heavy precipitation, contribute to the trend. This is supported by state-of-the-art analysis of climatic changes in the Sahel, for example by Panthou et al [61,62].…”

From pointwise testing to a regional vision: An integrated statistical approach to detect nonstationarity in extreme daily rainfall. Application to the Sahelian region

“…[9] Among the most recent advances in the modeling of extreme events, original developments have been proposed to model the extreme events at regional scale by taking into account the spatial heterogeneities of the distributions by incorporating spatial covariates [see, e.g., Blanchet and Lehning, 2010;Panthou et al, 2012]. Panthou et al [2012] show that pooling individual point series in order to fit directly a regional model using a spatial covariate reduces significantly the impact of temporal sampling effects.…”

Time Series Analysis of Floods across the Niger River Basin

“…Okpara et al [10] analyzed general rainfall discharge relations, however without considering data after 2002. The studies of Panthou et al [11,12] analyzed changes in rainfall and heavy rainfall, concluding that there has been a recent increase in heavy precipitation. Due to the increase in heavy precipitation and flooding in the recent past, Casse et al [13] analyzed satellite rainfall products in order to predict flood events of the Niger at Niamey.…”