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

Haque, Md Mominul, Seidou, Ousmane, Mohammadian, Abdolmajid, Gado Djibo, Abdouramane, Liersch, Stefan, Fournet, Samuel, Karam, Sarah, Perera, Duminda and Kleynhans, Martin, (2019). 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. Water, 11(9), n/a-n/a

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  • Sub-type Journal article
    Author Haque, Md Mominul
    Seidou, Ousmane
    Mohammadian, Abdolmajid
    Gado Djibo, Abdouramane
    Liersch, Stefan
    Fournet, Samuel
    Karam, Sarah
    Perera, Duminda
    Kleynhans, Martin
    Title 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
    Appearing in Water
    Volume 11
    Issue No. 9
    Publication Date 2019-08-24
    Place of Publication Basel
    Publisher MDPI
    Start page n/a
    End page n/a
    Language eng
    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.
    Copyright Holder The Authors
    Copyright Year 2019
    Copyright type Creative commons
    DOI doi.org/10.3390/w11091766
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    Created: Sat, 29 Jan 2022, 07:12:40 JST by Anderson, Kelsey on behalf of UNU INWEH