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
| Autor: | Sara Karam, Stefan Liersch, S. Fournet, Abdolmajid Mohammadian, Martin Kleynhans, E. D. P. Perera, Mominul Haque, Abdouramane Gado Djibo, Ousmane Seidou |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
lcsh:Hydraulic engineering
010504 meteorology & atmospheric sciences Correlation coefficient Geography Planning and Development 0207 environmental engineering Climate change 02 engineering and technology Shuttle Radar Topography Mission Aquatic Science Bayesian inference 01 natural sciences Biochemistry lcsh:Water supply for domestic and industrial purposes data scarcity TELEMAC 2D lcsh:TC1-978 Statistics 020701 environmental engineering Digital elevation model 0105 earth and related environmental sciences Water Science and Technology Inner Niger Delta lcsh:TD201-500 Water resources Variable (computer science) bayesian model averaging Environmental science Satellite |
| Zdroj: | Water, Vol 11, Iss 9, p 1766 (2019) |
| ISSN: | 2073-4441 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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