Improving rainfall–runoff modelling through the control of uncertainties under increasing climate variability in the Ouémé River basin (Benin, West Africa)

Abstract

The objective of this paper is to understand how the natural dynamics of a time-varying catchment, i.e. the rainfall pattern, transforms the random component of rainfall and how this transformation influences the river discharge. To this end, this paper develops a rainfall-runoff modelling approach that aims to capture the multiple sources and types of uncertainty in a single framework. The main assumption is that hydrological systems are nonlinear dynamical systems which can be described by stochastic differential equations (SDE). The dynamics of the system is based on the least action principle (LAP) as derived from Noether's theorem. The inflow process is considered as a sum of deterministic and random components. Using data from the Ouémé River basin (Benin, West Africa), the basic properties for the random component are considered and the triple relationship between the structure of the inflowing rainfall, the corresponding SDE that describes the river basin and the associated Fokker-Planck equations (FPE) is analysed.

Assessing the Impacts of Climate Change on River Discharge Dynamics in Oueme River Basin (Benin, West Africa)

“…It lies in the Guinea savanna zone and exhibits a bimodal rainfall season (from March to July and from August to October) that peaks in June and September. The interannual mean rainfall on the Oueme at Bonou is around 1100 mm, the minimum is 652 mm (in 1983) and the peak is 1536 mm (in 1963) over the period 1961-2010 [22]. The mean annual daily flow of the Oueme River at Bonou for the last 5 decades is around 170 m 3 /s.…”

“…This catchment lies in the Soudanese savanna zone and has a unimodal rainfall season (from mid-March to October) that peaks in August. The interannual mean rainfall on the Oueme at Bétérou is around 1160 mm, the minimum is 743 mm (in 1983) and the peak is 1587 mm (in 1963) over the period 1961-2010 [22]. The river discharge dynamic is characterized by high flow during the rainy season.…”

“…And the simplest way is the one which minimizes the energy expenditure of the nature" [30]. HyMoLAP has been used successfully in rainfall-runoff modelling for the Bétérou, Save and Bonou catchments of the Oueme River [22,24,30,31]. Details of the model can be found therein.…”

Modelling blue and green water availability under climate change in the Beninese Basin of the Niger River Basin, West Africa

“…To account for the stochastic nature of climate variables (Biao, Alamou, & Afouda, 2016) and as a result of limited computer resources, a total of 20 ensemble simulations were generated for each downscaled variable. Ensemble means were used for the comparison of downscaled and observed variables and to derive the statistics (Kebede et al, 2013).…”

Mid-Century Climate Change Impacts on Ouémé River Discharge at Bonou Outlet (Benin)

“…However, climate models hold some biases that need to be corrected before any impact study. Numerous bias correction methods exist and are applied around the world [16][17][18][19][20][21][22], including delta change, linear scaling, distribution mapping, empirical and adjusted quantile mapping [18,23,24]. M'Po et al [18] showed that empirical quantile mapping (EQM) was the best among other bias correction methods over Ouémé catchment.…”