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Article Dans Une Revue Scientific Reports Année : 2022

Network flow and flood routing model for water resources optimization

Résumé

Real-time management of hydraulic systems composed of multi-reservoir involves conflicting objectives. Its representation requires complex variables to consider all the systems dynamics. Interfacing simulation model with optimization algorithm permits to integrate flow routing into reservoir operation decisions and consists in solving separately hydraulic and operational constraints, but it requires that the water resource management model is based on an evolutionary algorithm. Considering channel routing in optimization algorithm can be done using conceptual models such as the Muskingum model. However, the structure of algorithms based on a network flow approach, inhibits the integration of the Muskingum model in the approach formulation. In this work, a flood routing model, corresponding to a singular form of the Muskingum model, constructed as a network flow is proposed and integrated into the water management optimization. A genetic algorithm is involved for the calibration of the model. The proposed flood routing model was applied on the standard Wilson test and on a 40 km reach of the Arrats river (southwest of France). The results were compared with the results of the Muskingum model. Finally, operational results for a water resource management system including this model are illustrated on a rainfall event.
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Dates et versions

hal-03956137 , version 1 (11-04-2023)

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Ayoub Tahiri, Daniel Che, David Ladeveze, Pascale Chiron, Bernard Archimède. Network flow and flood routing model for water resources optimization. Scientific Reports, 2022, 12 (1), pp.3937. ⟨10.1038/s41598-022-06075-0⟩. ⟨hal-03956137⟩
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