Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province

Abstract Water security is not only an ecological environmental issue but also a bearing on national security and development. The study of water resources carrying capacity is the basis for future socioeconomic development and is the driving force for social progress. Therefore, it is important to...

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Main Authors: Lyu Yan, Dong Jiao, Zhan Yongshi
Format: Article
Language:English
Published: Nature Portfolio 2023-08-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-40487-w
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author Lyu Yan
Dong Jiao
Zhan Yongshi
author_facet Lyu Yan
Dong Jiao
Zhan Yongshi
author_sort Lyu Yan
collection DOAJ
description Abstract Water security is not only an ecological environmental issue but also a bearing on national security and development. The study of water resources carrying capacity is the basis for future socioeconomic development and is the driving force for social progress. Therefore, it is important to investigate the influence factors of regional and national water resources carrying capacity (WRCC) and predict the future trend development. In view of the regional water resources data of the past 10 years in Anhui province, China, the Driving force Pressure State Impact Response Management (DPSIRM) model framework is constructed and the entropy weight method and variable weight theory can be used to make a comprehensive evaluation of the WRCC. Based on the comprehensive evaluation value, a modified Grey-Markov combination forecast can be introduced to predict the local WRCC in the coming years. The study on account of the Anhui Statistical Yearbook, the Water Resources Bulletin, and the water resources data of the Forestry Bureau for the past 10 years shows that the WRCC of Anhui Province is weak from 2010 to 2013 and gradually strengthens from 2014 to 2019; the WRCC of Anhui Province is mainly correlated with the impact subsystem, the management subsystem, and the state subsystem. The combined projections reflect that the future WRCC of Anhui Province is in good condition. It is recommended that the Anhui provincial government should strengthen water security and management, improve water resources utilization techniques, and construct complete and effective management tools and measures to fundamentally safeguard the province's water resources security and improve the WRCC.
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spelling doaj.art-041df2b1c66a4cb3a5b151c4f66c2d772023-11-20T09:19:45ZengNature PortfolioScientific Reports2045-23222023-08-0113111710.1038/s41598-023-40487-wEvaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui provinceLyu Yan0Dong Jiao1Zhan Yongshi2School of Humanities and Social Sciences, Anhui University of Science & TechnologySchool of Humanities and Social Sciences, Anhui University of Science & TechnologySchool of Humanities and Social Sciences, Anhui University of Science & TechnologyAbstract Water security is not only an ecological environmental issue but also a bearing on national security and development. The study of water resources carrying capacity is the basis for future socioeconomic development and is the driving force for social progress. Therefore, it is important to investigate the influence factors of regional and national water resources carrying capacity (WRCC) and predict the future trend development. In view of the regional water resources data of the past 10 years in Anhui province, China, the Driving force Pressure State Impact Response Management (DPSIRM) model framework is constructed and the entropy weight method and variable weight theory can be used to make a comprehensive evaluation of the WRCC. Based on the comprehensive evaluation value, a modified Grey-Markov combination forecast can be introduced to predict the local WRCC in the coming years. The study on account of the Anhui Statistical Yearbook, the Water Resources Bulletin, and the water resources data of the Forestry Bureau for the past 10 years shows that the WRCC of Anhui Province is weak from 2010 to 2013 and gradually strengthens from 2014 to 2019; the WRCC of Anhui Province is mainly correlated with the impact subsystem, the management subsystem, and the state subsystem. The combined projections reflect that the future WRCC of Anhui Province is in good condition. It is recommended that the Anhui provincial government should strengthen water security and management, improve water resources utilization techniques, and construct complete and effective management tools and measures to fundamentally safeguard the province's water resources security and improve the WRCC.https://doi.org/10.1038/s41598-023-40487-w
spellingShingle Lyu Yan
Dong Jiao
Zhan Yongshi
Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province
Scientific Reports
title Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province
title_full Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province
title_fullStr Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province
title_full_unstemmed Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province
title_short Evaluation of regional water resources carrying capacity in China based on variable weight model and grey-markov model: a case study of Anhui province
title_sort evaluation of regional water resources carrying capacity in china based on variable weight model and grey markov model a case study of anhui province
url https://doi.org/10.1038/s41598-023-40487-w
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AT zhanyongshi evaluationofregionalwaterresourcescarryingcapacityinchinabasedonvariableweightmodelandgreymarkovmodelacasestudyofanhuiprovince