Improving the Accuracy of Hydrodynamic Simulations in Data Scarce Environments Using Bayesian Model Averaging: A Case Study of the Inner Niger Delta, Mali, West Africa

Md Mominul Haque,Ousmane Seidou,Abdouramane Gado Djibo,Sara Karam,Stefan Liersch,Edangodage Duminda Pradeep Perera,Samuel Fournet,Martin Kleynhans,Abdolmajid Mohammadian

doi:10.3390/w11091766

Abstract

In this paper, the study area was the Inner Niger Delta (IND) in Mali, West Africa. The IND is threatened by climate change, increasing irrigation, and dam operations. 2D hydrodynamic modelling was used to simulate water levels, discharge, and inundation extent in the IND. Three different digital elevation models (DEM) (SRTM, MERIT, and a DEM derived from satellite images were used as a source of elevation data. Six different models were created, with different sources of elevation data and different downstream boundary conditions. Given that the performance of the models varies according to the location in the IND, the variable under consideration and the performance criteria, Bayesian Model Averaging (BMA) was used to assess the relative performance of each of the six models. The BMA weights, along with deterministic performance measures, such as the Nash Sutcliffe coefficient (NS) and the Pearson’s correlation coefficient (r), provide quantitative evidence as to which model is the best when simulating a particular hydraulic variable at a particular location. After the models were combined with BMA, both discharge and water levels could be simulated with reasonable precision (NS > 0.8). The results of this work can contribute to the more efficient management of water resources in the IND.

Highlights

The Inner Niger Delta (IND) is the second-largest wetland in Africa, and its maximum inundated area can exceed 30,000 km2 during wet years [1]
The elevation data came from two global DEMS (SRTM and MERIT), as well as a DEM derived from satellite imagery and water level observations using waterline methods
Given the data scarcity in the area, a considerable amount of input data, such as bathymetry, the river network, friction coefficient, and inundation extent were derived from secondary sources, leading to a high level of uncertainty in the simulations

Summary

Introduction

The Inner Niger Delta (IND) is the second-largest wetland in Africa, and its maximum inundated area can exceed 30,000 km during wet years [1]. Its main water sources are the Niger and Bani Rivers, which enter the study area at Ké-Macina and Sofara, respectively, flowing through the Delta over several hundred kilometers, before both exit at Diré (Figure 1). The maximum inundation area shrinks to around 10,000 km in dry years [2] under the combined impacts of climate variability, irrigation withdrawals, and dam operation. The Delta plays an important role in promoting sustainable development for food security, water management, and the environment. Damming the main course or branches of the Niger River can impact on food security, ecology, and the environment as a whole by altering flow and inundation patterns

Methods

Results

Conclusion