Multi-step ahead streamflow and uncertainty forecasting using a HyMoLAP rainfall-runoff model-based framework integrated with Bayesian neural networks in the Ouémé river basin, Benin

Open Access

Peer-reviewed

Research Article

About the Authors

Sianou Ezéckiel Houénafa

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing – review & editing

Affiliation Department of Mathematics, Pan African University Institute for Basic Sciences, Technology and Innovation, Nairobi, Kenya

Olatunji Johnson

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – review & editing

Affiliation Department of Mathematics, University of Manchester, Manchester, United Kingdom

Erick K. Ronoh

Roles Formal analysis, Investigation, Supervision, Validation, Writing – review & editing

Affiliation Department of Agricultural and Biosystems Engineering, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya

Stephen E. Moore

Roles Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Validation, Writing – review & editing

Affiliations Department of Mathematics, University of Cape Coast, Cape Coast, Ghana, Center for Artificial Intelligence Research, Cape Coast, Ghana

The authors have declared that no competing interests exist.

Forecasting
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Simulation and modeling
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Artificial neural networks
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Deep learning
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Machine learning
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Neural networks
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Rain
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Water resources
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