Abstract
Sediment transport in basins disturbs the ecological systems of the water bodies and leads to reservoir siltation. Its evaluation is crucial for managing water resources. The practical application of the process-based model can confront some limitations noticed in the lower accuracy during the validation process due to the lack of reliable physical datasets. In this study, we attempt to apply machine-learning-based modeling (ML) to predict the suspended sediment load, using hydro-climatic data as input variables in the semi-arid Bouregreg basin, Morocco. To that end, data for the years 2016 to 2020 were used for the training process, and the validation was performed with 2021 data. The results showed that most ML models have good accuracy, with a Nash–Schiff efficiency (NSE) ranging from 0.47 to 0.80 during the validation phase, which indicates satisfactory performances in predicting the SSL. Furthermore, the models were ranked against their generalization ability (GA), which revealed that the developed models are good to excellent in terms of GA. Overall, the present study provides new insight into predicting the SSL in a semi-arid environment, such as the Bouregreg basin.
Highlights
IntroductionSediment transport in hydrodynamic systems is still not a well-understood phenomenon and, it is a crucial topic in hydrological studies
We focused on the hydro-climatic variables in order to predict the suspended sediment load (SSL), namely: rainfall in the basins and discharges both upstream and downstream
These results demonstrate the importance of the input variables
Summary
Sediment transport in hydrodynamic systems is still not a well-understood phenomenon and, it is a crucial topic in hydrological studies. Its exceedance existence in streams can significantly impact the river flows by changing the rheological proprieties of the water, which can impact the design capacity of the channel culverts and increase the damages associated with flash floods [1–4]. The siltation of sediments in dam reservoirs reduces their storage capacity, leading to freshwater scarcity, especially in arid and semi-arid regions [5]. Sediments can pose a threat to the water bodies’ quality and lead to ecological damages by disturbing aquatic systems [6,7]. The understanding of the sediment transport mechanism and its quantification at the basin scale are challenging problems in water resources planning and management, in dynamic basins under high climatic variability
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