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Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov

The Yellow River Basin in China has the world's most serious soil erosion problem. The Yellow River Basin in Sichuan Province (YRS), as the upper reaches of the Yellow River, and its water conservation (WC) capacity greatly affects the ecological environment of the downstream basin. In recent y...

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Autores principales: Yang, Zhichong, Dai, Xiaoai, Lu, Heng, Liu, Chao, Nie, Ruihua, Zhang, Min, Ma, Lei, Li, Naiwen, Liu, Tiegang, He, Yuxin, Yang, Zhengli, Qu, Ge, Li, Weile, Wang, Youlin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10395299/
https://www.ncbi.nlm.nih.gov/pubmed/37539201
http://dx.doi.org/10.1016/j.heliyon.2023.e17903
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author Yang, Zhichong
Dai, Xiaoai
Lu, Heng
Liu, Chao
Nie, Ruihua
Zhang, Min
Ma, Lei
Li, Naiwen
Liu, Tiegang
He, Yuxin
Yang, Zhengli
Qu, Ge
Li, Weile
Wang, Youlin
author_facet Yang, Zhichong
Dai, Xiaoai
Lu, Heng
Liu, Chao
Nie, Ruihua
Zhang, Min
Ma, Lei
Li, Naiwen
Liu, Tiegang
He, Yuxin
Yang, Zhengli
Qu, Ge
Li, Weile
Wang, Youlin
author_sort Yang, Zhichong
collection PubMed
description The Yellow River Basin in China has the world's most serious soil erosion problem. The Yellow River Basin in Sichuan Province (YRS), as the upper reaches of the Yellow River, and its water conservation (WC) capacity greatly affects the ecological environment of the downstream basin. In recent years, YRS has received more and more attention, and numerous policies have been developed to improve local WC. However, there is a vacancy in the long-term research of WC in the YRS due to the lack of in-situ data. This study quantitatively evaluated the WC of YRS from 2001 to 2020 through Google Earth Engine (GEE) and analyzed the spatio-temporal variations of WC and land cover (LC). CA-Markov predicted the LC and WC in 2025 under three scenarios to assess the contribution of different scenarios to WC. The WC in YRS fluctuated from 1.93 to 6.77 billion m(3). The climate is the dominant factor of WC change, but the effect of LC on WC is also evident. The WC capacity increases with vegetation coverage and height. The WC capacity of forests per km(2) exceeds 600 mm, while that of grasslands is about 250 mm, and barren can cause around 300 mm of WC loss. In 2025, the WC in YRS may exceed 7.5 billion m(3), but the past ecological management mode should be transformed. Improving the quality of land use and converting grasslands to forests is better than reducing cropland to improve WC.
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spelling pubmed-103952992023-08-03 Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov Yang, Zhichong Dai, Xiaoai Lu, Heng Liu, Chao Nie, Ruihua Zhang, Min Ma, Lei Li, Naiwen Liu, Tiegang He, Yuxin Yang, Zhengli Qu, Ge Li, Weile Wang, Youlin Heliyon Research Article The Yellow River Basin in China has the world's most serious soil erosion problem. The Yellow River Basin in Sichuan Province (YRS), as the upper reaches of the Yellow River, and its water conservation (WC) capacity greatly affects the ecological environment of the downstream basin. In recent years, YRS has received more and more attention, and numerous policies have been developed to improve local WC. However, there is a vacancy in the long-term research of WC in the YRS due to the lack of in-situ data. This study quantitatively evaluated the WC of YRS from 2001 to 2020 through Google Earth Engine (GEE) and analyzed the spatio-temporal variations of WC and land cover (LC). CA-Markov predicted the LC and WC in 2025 under three scenarios to assess the contribution of different scenarios to WC. The WC in YRS fluctuated from 1.93 to 6.77 billion m(3). The climate is the dominant factor of WC change, but the effect of LC on WC is also evident. The WC capacity increases with vegetation coverage and height. The WC capacity of forests per km(2) exceeds 600 mm, while that of grasslands is about 250 mm, and barren can cause around 300 mm of WC loss. In 2025, the WC in YRS may exceed 7.5 billion m(3), but the past ecological management mode should be transformed. Improving the quality of land use and converting grasslands to forests is better than reducing cropland to improve WC. Elsevier 2023-07-01 /pmc/articles/PMC10395299/ /pubmed/37539201 http://dx.doi.org/10.1016/j.heliyon.2023.e17903 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Yang, Zhichong
Dai, Xiaoai
Lu, Heng
Liu, Chao
Nie, Ruihua
Zhang, Min
Ma, Lei
Li, Naiwen
Liu, Tiegang
He, Yuxin
Yang, Zhengli
Qu, Ge
Li, Weile
Wang, Youlin
Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov
title Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov
title_full Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov
title_fullStr Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov
title_full_unstemmed Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov
title_short Evaluation and prediction of water conservation of the Yellow river basin in Sichuan Province, China, based on Google Earth Engine and CA-Markov
title_sort evaluation and prediction of water conservation of the yellow river basin in sichuan province, china, based on google earth engine and ca-markov
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10395299/
https://www.ncbi.nlm.nih.gov/pubmed/37539201
http://dx.doi.org/10.1016/j.heliyon.2023.e17903
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