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Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China
Global warming and anthropogenic changes can result in the heterogeneity of water availability in the spatiotemporal scale, which will further affect the allocation of water resources. A lot of researches have been devoted to examining the responses of water availability to global warming while negl...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041889/ https://www.ncbi.nlm.nih.gov/pubmed/33846438 http://dx.doi.org/10.1038/s41598-021-86961-1 |
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author | Tian, Jing Guo, Shenglian Deng, Lele Yin, Jiabo Pan, Zhengke He, Shaokun Li, Qianxun |
author_facet | Tian, Jing Guo, Shenglian Deng, Lele Yin, Jiabo Pan, Zhengke He, Shaokun Li, Qianxun |
author_sort | Tian, Jing |
collection | PubMed |
description | Global warming and anthropogenic changes can result in the heterogeneity of water availability in the spatiotemporal scale, which will further affect the allocation of water resources. A lot of researches have been devoted to examining the responses of water availability to global warming while neglected future anthropogenic changes. What’s more, only a few studies have investigated the response of optimal allocation of water resources to the projected climate and anthropogenic changes. In this study, a cascade model chain is developed to evaluate the impacts of projected climate change and human activities on optimal allocation of water resources. Firstly, a large set of global climate models (GCMs) associated with the Daily Bias Correction (DBC) method are employed to project future climate scenarios, while the Cellular Automaton–Markov (CA–Markov) model is used to project future Land Use/Cover Change (LUCC) scenarios. Then the runoff simulation is based on the Soil and Water Assessment Tool (SWAT) hydrological model with necessary inputs under the future conditions. Finally, the optimal water resources allocation model is established based on the evaluation of water supply and water demand. The Han River basin in China was selected as a case study. The results show that: (1) the annual runoff indicates an increasing trend in the future in contrast with the base period, while the ascending rate of the basin under RCP 4.5 is 4.47%; (2) a nonlinear relationship has been identified between the optimal allocation of water resources and water availability, while a linear association exists between the former and water demand; (3) increased water supply are needed in the water donor area, the middle and lower reaches should be supplemented with 4.495 billion m(3) water in 2030. This study provides an example of a management template for guiding the allocation of water resources, and improves understandings of the assessments of water availability and demand at a regional or national scale. |
format | Online Article Text |
id | pubmed-8041889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80418892021-04-13 Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China Tian, Jing Guo, Shenglian Deng, Lele Yin, Jiabo Pan, Zhengke He, Shaokun Li, Qianxun Sci Rep Article Global warming and anthropogenic changes can result in the heterogeneity of water availability in the spatiotemporal scale, which will further affect the allocation of water resources. A lot of researches have been devoted to examining the responses of water availability to global warming while neglected future anthropogenic changes. What’s more, only a few studies have investigated the response of optimal allocation of water resources to the projected climate and anthropogenic changes. In this study, a cascade model chain is developed to evaluate the impacts of projected climate change and human activities on optimal allocation of water resources. Firstly, a large set of global climate models (GCMs) associated with the Daily Bias Correction (DBC) method are employed to project future climate scenarios, while the Cellular Automaton–Markov (CA–Markov) model is used to project future Land Use/Cover Change (LUCC) scenarios. Then the runoff simulation is based on the Soil and Water Assessment Tool (SWAT) hydrological model with necessary inputs under the future conditions. Finally, the optimal water resources allocation model is established based on the evaluation of water supply and water demand. The Han River basin in China was selected as a case study. The results show that: (1) the annual runoff indicates an increasing trend in the future in contrast with the base period, while the ascending rate of the basin under RCP 4.5 is 4.47%; (2) a nonlinear relationship has been identified between the optimal allocation of water resources and water availability, while a linear association exists between the former and water demand; (3) increased water supply are needed in the water donor area, the middle and lower reaches should be supplemented with 4.495 billion m(3) water in 2030. This study provides an example of a management template for guiding the allocation of water resources, and improves understandings of the assessments of water availability and demand at a regional or national scale. Nature Publishing Group UK 2021-04-12 /pmc/articles/PMC8041889/ /pubmed/33846438 http://dx.doi.org/10.1038/s41598-021-86961-1 Text en © The Author(s) 2021 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 Tian, Jing Guo, Shenglian Deng, Lele Yin, Jiabo Pan, Zhengke He, Shaokun Li, Qianxun Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China |
title | Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China |
title_full | Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China |
title_fullStr | Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China |
title_full_unstemmed | Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China |
title_short | Adaptive optimal allocation of water resources response to future water availability and water demand in the Han River basin, China |
title_sort | adaptive optimal allocation of water resources response to future water availability and water demand in the han river basin, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8041889/ https://www.ncbi.nlm.nih.gov/pubmed/33846438 http://dx.doi.org/10.1038/s41598-021-86961-1 |
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