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Network flow and flood routing model for water resources optimization
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 operati...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913779/ https://www.ncbi.nlm.nih.gov/pubmed/35273171 http://dx.doi.org/10.1038/s41598-022-06075-0 |
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author | Tahiri, Ayoub Che, Daniel Ladeveze, David Chiron, Pascale Archimède, Bernard |
author_facet | Tahiri, Ayoub Che, Daniel Ladeveze, David Chiron, Pascale Archimède, Bernard |
author_sort | Tahiri, Ayoub |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8913779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89137792022-03-14 Network flow and flood routing model for water resources optimization Tahiri, Ayoub Che, Daniel Ladeveze, David Chiron, Pascale Archimède, Bernard Sci Rep Article 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. Nature Publishing Group UK 2022-03-10 /pmc/articles/PMC8913779/ /pubmed/35273171 http://dx.doi.org/10.1038/s41598-022-06075-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Tahiri, Ayoub Che, Daniel Ladeveze, David Chiron, Pascale Archimède, Bernard Network flow and flood routing model for water resources optimization |
title | Network flow and flood routing model for water resources optimization |
title_full | Network flow and flood routing model for water resources optimization |
title_fullStr | Network flow and flood routing model for water resources optimization |
title_full_unstemmed | Network flow and flood routing model for water resources optimization |
title_short | Network flow and flood routing model for water resources optimization |
title_sort | network flow and flood routing model for water resources optimization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913779/ https://www.ncbi.nlm.nih.gov/pubmed/35273171 http://dx.doi.org/10.1038/s41598-022-06075-0 |
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