An Automatic Optimization Technique for the Calibration of a Physically Based Hydrological Rainfall-Runoff Model

Models are tools widely used in the prediction of hydrological phenomena. The present study aims to contribute to the implementation of an automatic optimization strategy of parameters for the calibration of a hydrological model based on the least action principle (HyMoLAP). The Downhill Simplex method is also known as the Nelder-Mead algorithm, which is a heuristic research method, is used to optimize the cost function on a given domain. The performance of the model is evaluated by the Nash Stucliffe Efficiency Index (NSE), the Root Mean Square Error (RMSE), the coefficient of determination (R2), the Mean Absolute Error (MAE). A comparative estimation is conducted using the Nash-Sutcliffe Modeling Efficiency Index and the mean relative error to evaluate the performance of the optimization method. It appears that the variation in water balance parameter values is acceptable. The simulated optimization method appears to be the best in terms of lower variability of parameter values during successive tests. The quality of the parameter sets obtained is good enough to impact the performance of the objective functions in a minimum number of iterations. We have analyzed the algorithm from a technical point of view, and we have carried out an experimental comparison between specific factors such as the model structure and the parameter’s values. The results obtained confirm the quality of the model (NSE = 0.90 and 0.75 respectively in calibration and validation) and allow us to evaluate the efficiency of the Nelder-Mead algorithm in the automatic calibration of the HyMoLAP model. The developed hybrid automatic calibration approach is therefore one of the promising ways to reduce computational time in rainfall-runoff modeling.

History and Projection of Hydrological Droughts in the Benin Basin of the Niger River (Benin)

In the context of a changing climate,the Beninese Niger River basin has been the focus of several research studies for the quantification,planning,and modeling of water and related resources for sustainable use.This re­search aims to characterize the historical(1976-2019)and projected(2021-2050)hydrological drought of the Beninese Niger River basin.The study used daily observations of rainfall,maximum and minimum temperatures,runoff rates and simulations of HIRHAM and REMO RCMs from fifteen(15)rainfall stations installed around the basin.It uses standardized stream­flow indices(SDI)at 12-month and 36-month time steps.The results show that the calculated SDI indices show,on average,for all the model scenar­ios used,chronological trends of increase.These increases are not signifi­cant(are of the order of 0.00001 per year).The analysis of the SDI indices shows that,on average,the hydrological droughts in the Beninese basin of the Niger River will increase at 36 months and decrease at 12 months of the SDI.In fact,these small variations of hydrological droughts will be ac­companied by the increase of their duration and the decrease of their mag­nitudes.The droughts detected in the Benin basin of the Niger River during the historical period will continue until 2050 in the same range but with more extended drought lengths.It should be noted that most of the changes observed in the calculated and analyzed indices are not significant.