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System dynamics modeling of lake water management under climate change

Lake Urmia, the twentieth largest lake in the world, is the most valuable aquatic ecosystem in Iran. The lake water level has decreased in recent years due to human activities and climate change. Several studies have highlighted the significant roles of climatic and anthropogenic factors on the shri...

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Autores principales: Bozorg-Haddad, Omid, Dehghan, Paniz, Zolghadr-Asli, Babak, Singh, Vijay P., Chu, Xuefeng, Loáiciga, Hugo A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8986815/
https://www.ncbi.nlm.nih.gov/pubmed/35388036
http://dx.doi.org/10.1038/s41598-022-09212-x
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author Bozorg-Haddad, Omid
Dehghan, Paniz
Zolghadr-Asli, Babak
Singh, Vijay P.
Chu, Xuefeng
Loáiciga, Hugo A.
author_facet Bozorg-Haddad, Omid
Dehghan, Paniz
Zolghadr-Asli, Babak
Singh, Vijay P.
Chu, Xuefeng
Loáiciga, Hugo A.
author_sort Bozorg-Haddad, Omid
collection PubMed
description Lake Urmia, the twentieth largest lake in the world, is the most valuable aquatic ecosystem in Iran. The lake water level has decreased in recent years due to human activities and climate change. Several studies have highlighted the significant roles of climatic and anthropogenic factors on the shrinkage of the lake. Management policies for water resources harvesting must be adopted to adapt to climate change and avoid the consequent problems stemming from the drought affecting Lake Urmia, and rationing must be applied to the upstream water demands. This study analyzes strategies and evaluates their effectiveness in overcoming the Urmia Lake crisis. Specifically, system dynamics analysis was performed for simulating the water volume of Lake Urmia, and the Hadley Centre coupled model was applied to project surface temperature and precipitation for two future periods: 2021–2050 and 2051–2080. Six management scenarios were considered for decreasing the allocation of agricultural water demand corresponding to two options: (1) one-reservoir option (Bukan reservoir only), and (2) six-reservoir option. The net inflow of Urmia Lake was simulated for the two future periods with the IHACRES model and with artificial neural network models under the six management scenarios. The annual average volumes of Lake Urmia would be 30 × 10(9) and 12 × 10(9) m(3) over the first and second future periods, respectively, without considering the management scenarios. The lake volumes would rise by about 50% and 75% for the first and second periods, respectively under the management scenarios that involve strict protective measures and elimination of the effect of all dams and their reservoirs. Implementing strict measures would increase the annual average lake volume to 21 × 10(9) m(3) in the second period; yet, this volume would be less than the long-term average and strategic volume. The human water use would be completely eliminated under Scenario 6. Nevertheless, Lake Urmia would experience a considerable loss of storage because of drought.
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spelling pubmed-89868152022-04-08 System dynamics modeling of lake water management under climate change Bozorg-Haddad, Omid Dehghan, Paniz Zolghadr-Asli, Babak Singh, Vijay P. Chu, Xuefeng Loáiciga, Hugo A. Sci Rep Article Lake Urmia, the twentieth largest lake in the world, is the most valuable aquatic ecosystem in Iran. The lake water level has decreased in recent years due to human activities and climate change. Several studies have highlighted the significant roles of climatic and anthropogenic factors on the shrinkage of the lake. Management policies for water resources harvesting must be adopted to adapt to climate change and avoid the consequent problems stemming from the drought affecting Lake Urmia, and rationing must be applied to the upstream water demands. This study analyzes strategies and evaluates their effectiveness in overcoming the Urmia Lake crisis. Specifically, system dynamics analysis was performed for simulating the water volume of Lake Urmia, and the Hadley Centre coupled model was applied to project surface temperature and precipitation for two future periods: 2021–2050 and 2051–2080. Six management scenarios were considered for decreasing the allocation of agricultural water demand corresponding to two options: (1) one-reservoir option (Bukan reservoir only), and (2) six-reservoir option. The net inflow of Urmia Lake was simulated for the two future periods with the IHACRES model and with artificial neural network models under the six management scenarios. The annual average volumes of Lake Urmia would be 30 × 10(9) and 12 × 10(9) m(3) over the first and second future periods, respectively, without considering the management scenarios. The lake volumes would rise by about 50% and 75% for the first and second periods, respectively under the management scenarios that involve strict protective measures and elimination of the effect of all dams and their reservoirs. Implementing strict measures would increase the annual average lake volume to 21 × 10(9) m(3) in the second period; yet, this volume would be less than the long-term average and strategic volume. The human water use would be completely eliminated under Scenario 6. Nevertheless, Lake Urmia would experience a considerable loss of storage because of drought. Nature Publishing Group UK 2022-04-06 /pmc/articles/PMC8986815/ /pubmed/35388036 http://dx.doi.org/10.1038/s41598-022-09212-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access 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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Bozorg-Haddad, Omid
Dehghan, Paniz
Zolghadr-Asli, Babak
Singh, Vijay P.
Chu, Xuefeng
Loáiciga, Hugo A.
System dynamics modeling of lake water management under climate change
title System dynamics modeling of lake water management under climate change
title_full System dynamics modeling of lake water management under climate change
title_fullStr System dynamics modeling of lake water management under climate change
title_full_unstemmed System dynamics modeling of lake water management under climate change
title_short System dynamics modeling of lake water management under climate change
title_sort system dynamics modeling of lake water management under climate change
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8986815/
https://www.ncbi.nlm.nih.gov/pubmed/35388036
http://dx.doi.org/10.1038/s41598-022-09212-x
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