This study assesses changes in meteorological droughts in West Africa under a high greenhouse gas scenario, i.e., a representative concentration pathway 8.5 (RCP8.5), and under a scenario of stratospheric aerosol geoengineering (SAG) deployment. Using simulations from the Geoengineering Large Ensemble (GLENS) project that employed stratospheric sulfate aerosols injection to keep global mean surface temperature, as well as the interhemispheric and equator-to-pole temperature gradients at the 2020 level (present-day climate), we investigated the impact of SAG on meteorological droughts in West Africa. Analysis of the meteorological drought characteristics (number of drought events, drought duration, maximum length of drought events, severity of the greatest drought events and intensity of the greatest drought event) revealed that over the period from 2030–2049 and under GLENS simulations, these drought characteristics decrease in most regions in comparison to the RCP8.5 scenarios. On the contrary, over the period from 2070–2089 and under GLENS simulations, these drought characteristics increase in most regions compared to the results from the RCP8.5 scenarios. Under GLENS, the increase in drought characteristics is due to a decrease in precipitation. The decrease in precipitation is largely driven by weakened monsoon circulation due to the reduce of land–sea thermal contrast in the lower troposphere.

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This work aims to study the uncertainties in the rainfall-runoff process using a stochastic approach derived from the deterministic hydrological model based on the least action principle (ModHyPMA). The stochastic formulation of ModHyPMA allows for consideration of both the dynamics and stochastic nature of the hydrological phenomenon. The main assumption is that uncertainties in the hydrological process are modelled as Gaussian white noise. It is assumed that hydrological systems are nonlinear dynamical systems that can be described by stochastic differential equations (SDE). From this SDE, we deduce the associated Fokker-Planck equation (FPE). The FPE is a partial differential equation that cannot be solved analytically due to its complexity. We therefore investigated a numerical solution to this equation by using the finite differences and finite volumes methods. The results show that the stochastic model improves the simulations of discharges in Ouémé at Savè Basin (NSE = 0.89, R 2 = 0.90, RMSE = 113 and MAE = 76) compared to the deterministic model (NSE = 0.78, R 2 = 0.78, RMSE = 123 and MAE = 51). The plots of the solutions (the density probability of discharges) always coincide when the investigated numerical solutions are compared, except when the number of meshes is very small (100 meshes). The two solutions are convergent. This numerical solution provides information about the distribution of discharges in the Ouémé at Savè Basin.

Abstract:The aim of the study was to test the possible adequacy of an ensemble model to reproduce the observed flows in the Mékrou basin and in what measure this ensemble simulation could be used instead of a unique model. Single model applications showed shortcomings in terms of simulating both high and low flows at the same time. Thereby, the models were calibrated according to two different modes (high and low flows) and they were tested further through the elaboration of three various ensembles. The observed hydrographs were separated in three parts each in order to evaluate with much precision which model or ensemble fits best the hydrographs. On the basis of the Root Mean Squared Error (RMSE), the models and derived ensembles were assessed using discharge data. In this paper, the comparison is made between models, mean and median ensembles. Good results were obtained for all models and ensembles but the best ones were achieved by the mean-based ensemble.