Variations in Water Stress and Its Driving Factors in the Yellow River Basin
As one of the most sensitive areas to climate change in China, the Yellow River Basin faces a significant water resource shortage, which severely restricts sustainable economic development in the region and has become the most prominent issue in the basin. In response to the national strategy of eco...
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2024-12-01
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| author | Haodong Lyu Jianmin Qiao Gonghuan Fang Wenting Liang Zidong Tang Furong Lv Qin Zhang Zewei Qiu Gengning Huang |
| author_facet | Haodong Lyu Jianmin Qiao Gonghuan Fang Wenting Liang Zidong Tang Furong Lv Qin Zhang Zewei Qiu Gengning Huang |
| author_sort | Haodong Lyu |
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| description | As one of the most sensitive areas to climate change in China, the Yellow River Basin faces a significant water resource shortage, which severely restricts sustainable economic development in the region and has become the most prominent issue in the basin. In response to the national strategy of ecological protection and high-quality development of the Yellow River Basin, as well as Sustainable Development Goal 6.4 (SDG 6.4), we applied the water stress index (WSI) to measure water stress in the basin. This analysis utilized land use datasets, socio-economic datasets, irrigation datasets, water withdrawal/consumption datasets, and runoff datasets from 2000 to 2020. We also identified the driving factors of the WSI using a partial least squares regression (PLSR) and assessed spatial clustering with global and local Moran’s indices. The results indicate that water stress in the Yellow River Basin has been alleviated, as indicated by the decreasing WSI due to increased precipitation. However, rising domestic water withdrawals have led to an overall increase in total water withdrawal, with agricultural water use accounting for the largest proportion of total water consumption. Precipitation is the most significant factor influencing water stress, affecting 46.25% of the basin area, followed by air temperature, which affects 12.64% of the area. Other factors account for less than 10% each. Furthermore, the global Moran’s index values for 2000, 2005, 2010, 2015, and 2020 were 0.172, 0.280, 0.284, 0.305, and 0.302, respectively, indicating a strong positive spatial autocorrelation within the basin. The local Moran’s index revealed that the WSI of 446 catchments was predominantly characterized by high–high and low–low clusters, suggesting a strong positive correlation in the WSI among these catchments. This study provides a reference framework for developing a water resources assessment index system in the Yellow River Basin and supports regional water resources management and industrial structure planning. |
| format | Article |
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| institution | Kabale University |
| issn | 2073-445X |
| language | English |
| publishDate | 2024-12-01 |
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| series | Land |
| spelling | doaj-art-f4b0d82770974a3bbf7bf2de8eca92aa2025-01-24T13:37:42ZengMDPI AGLand2073-445X2024-12-011415310.3390/land14010053Variations in Water Stress and Its Driving Factors in the Yellow River BasinHaodong Lyu0Jianmin Qiao1Gonghuan Fang2Wenting Liang3Zidong Tang4Furong Lv5Qin Zhang6Zewei Qiu7Gengning Huang8State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, ChinaCollege of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaState Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, ChinaState Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, ChinaCollege of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaSchool of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaSchool of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, ChinaCollege of Geography and Environment, Shandong Normal University, Jinan 250358, ChinaAs one of the most sensitive areas to climate change in China, the Yellow River Basin faces a significant water resource shortage, which severely restricts sustainable economic development in the region and has become the most prominent issue in the basin. In response to the national strategy of ecological protection and high-quality development of the Yellow River Basin, as well as Sustainable Development Goal 6.4 (SDG 6.4), we applied the water stress index (WSI) to measure water stress in the basin. This analysis utilized land use datasets, socio-economic datasets, irrigation datasets, water withdrawal/consumption datasets, and runoff datasets from 2000 to 2020. We also identified the driving factors of the WSI using a partial least squares regression (PLSR) and assessed spatial clustering with global and local Moran’s indices. The results indicate that water stress in the Yellow River Basin has been alleviated, as indicated by the decreasing WSI due to increased precipitation. However, rising domestic water withdrawals have led to an overall increase in total water withdrawal, with agricultural water use accounting for the largest proportion of total water consumption. Precipitation is the most significant factor influencing water stress, affecting 46.25% of the basin area, followed by air temperature, which affects 12.64% of the area. Other factors account for less than 10% each. Furthermore, the global Moran’s index values for 2000, 2005, 2010, 2015, and 2020 were 0.172, 0.280, 0.284, 0.305, and 0.302, respectively, indicating a strong positive spatial autocorrelation within the basin. The local Moran’s index revealed that the WSI of 446 catchments was predominantly characterized by high–high and low–low clusters, suggesting a strong positive correlation in the WSI among these catchments. This study provides a reference framework for developing a water resources assessment index system in the Yellow River Basin and supports regional water resources management and industrial structure planning.https://www.mdpi.com/2073-445X/14/1/53water resourceswater stress index (WSI)Yellow River Basinspatial autocorrelationMoran’s index |
| spellingShingle | Haodong Lyu Jianmin Qiao Gonghuan Fang Wenting Liang Zidong Tang Furong Lv Qin Zhang Zewei Qiu Gengning Huang Variations in Water Stress and Its Driving Factors in the Yellow River Basin Land water resources water stress index (WSI) Yellow River Basin spatial autocorrelation Moran’s index |
| title | Variations in Water Stress and Its Driving Factors in the Yellow River Basin |
| title_full | Variations in Water Stress and Its Driving Factors in the Yellow River Basin |
| title_fullStr | Variations in Water Stress and Its Driving Factors in the Yellow River Basin |
| title_full_unstemmed | Variations in Water Stress and Its Driving Factors in the Yellow River Basin |
| title_short | Variations in Water Stress and Its Driving Factors in the Yellow River Basin |
| title_sort | variations in water stress and its driving factors in the yellow river basin |
| topic | water resources water stress index (WSI) Yellow River Basin spatial autocorrelation Moran’s index |
| url | https://www.mdpi.com/2073-445X/14/1/53 |
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