Salinity management of reservoirs by linking hydrodynamic model, surrogate model, and evolutionary optimization

Sedighkia, M., and Datta, B. (2024) Salinity management of reservoirs by linking hydrodynamic model, surrogate model, and evolutionary optimization. International Journal of Environmental Science and Technology, 21. pp. 6235-6248.

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Abstract

This study proposes a combined system for salinity management of reservoirs in which the lake ecosystem simulation is integrated with the reservoir operation optimization. A finite volume-based depth-averaged model is applied for simulating salinity in the reservoir for a long-term period. Then, a surrogate model is developed by applying outputs of the fluid dynamic model using adaptive neuro-fuzzy inference system. The surrogate model is used in the structure of the optimization model to estimate the average salinity concentration in the reservoir. Two objectives are defined in the reservoir operation optimization including minimizing water supply loss and mitigating salinity impacts on the aquatic habitats in the lake ecosystem. According to case study results, the fluid dynamic model is reliable for simulating salinity distribution in the reservoir, which means it is recommendable for simulating salinity distribution of reservoirs. Moreover, The Nash–Sutcliff coefficient of surrogate model is 0.79, which implies it is reliable for applying in the optimization model as a surrogate model of salinity. Based on the environmental considerations, 0.55 ppt was defined as the average threshold of habitat suitability. Average optimal salinity during the simulated period is 0.52 ppt, which implies the optimization model is able to reduce salinity impacts properly. We recommend using the proposed method for the case studies in which increasing salinity is an environmental challenge for the aquatic species those living in the artificial lakes of large dams.

Item ID: 82087
Item Type: Article (Research - C1)
ISSN: 1735-2630
Keywords: Adaptive neuro-fuzzy inference system, Environmental reservoir operation, Fluid dynamic model, Optimization, Salinity
Copyright Information: This 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/.
Date Deposited: 08 May 2024 00:09
FoR Codes: 40 ENGINEERING > 4005 Civil engineering > 400513 Water resources engineering @ 100%
SEO Codes: 18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180301 Assessment and management of freshwater ecosystems @ 100%
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