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Performance assessment and uncertainty prediction of a daily time-step HBV-Light rainfall-runoff model for the Upper Benue River Basin, Northern Cameroon

19 juin 2026 par
David Mokoli
| Aucun commentaire pour l'instant

Auteur : Rodric M. Nonki

Co-Auteur : Amoussou, E., Tshimanga, R. M., Koubodana, H. D., Kemgang Ghomsi, F. E., and Lenouo, A

Review : Journal of Hydrology : Regional Studies

Lien : https://www.sciencedirect.com/science/article/pii/S2214581821000781  

Abstract

Here we show how major rivers can efficiently connect to the deep-sea, by analysing the longest runout sediment flows (of any type) yet measured in action on Earth. These seafloor turbidity currents originated from the Congo River-mouth, with one flow travelling >1,130 km whilst accelerating from 5.2 to 8.0 m/s. In one year, these turbidity currents eroded 1,338-2,675 [>535-1,070] Mt of sediment from one submarine canyon, equivalent to 19–37 [>7–15] % of annual suspended sediment flux from present-day rivers. It was known earthquakes trigger canyon-flushing flows. We show river-floods also generate canyon-flushing flows, primed by rapid sediment-accumulation at the river-mouth, and sometimes triggered by spring tides weeks to months post-flood. It is demonstrated that strongly erosional turbidity currents self-accelerate, thereby travelling much further, validating a long-proposed theory. These observations explain highly-efficient organic carbon transfer, and have important implications for hazards to seabed cables, or deep-sea impacts of terrestrial climate change.

Keywords : Conceptual rainfall-runoff models, Sensitivity analysis, Parameter identifiability, Uncertainty prediction, Parameter optimization, Performance evaluation

David Mokoli 19 juin 2026
 

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