Evolution and drivers of water use in Northern China

The 16 provinces in Northern China. This study constructs a segmented linear regression model to identify the stages of water resource utilization and selects 11 indicators affecting changes in industrial, agricultural, and domestic water use. The logarithmic mean Divisia index (LMDI) method is applied to analyze the driving and restraining factors behind the changes in total water use in each province. We identified three distinct stages of water use in Northern China: drought suppression (1997–2003), economic stimulation (2004–2012), and policy restriction (2013–2021). We selected 11 indicators affecting changes in industrial, agricultural, and domestic water use and applied the logarithmic mean Divisia index (LMDI) method to analyze the driving and constraining factors behind total water use and its variations across provinces. The results show that economic factors contributed 14 % to changes in water use, while social factors contributed 6.5 %. Additionally, the study highlights the significant role of climate change during the drought suppression phase, whereas rapid industrialization and economic growth played a dominant role in the economic stimulation phase. In contrast, policy restrictions have led to a gradual decrease in water use in recent years. • Northern China's water use follows three stages. • LMDI method reveals economic factors drive 14 % of water use changes. • Industrial and agricultural shifts are key to total water consumption evolution. • Policy interventions since 2013 effectively changed water usage across sectors.

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Publication Details

Journal
Journal of Hydrology Regional Studies
Published
2025-04-24
DOI
https://doi.org/10.1016/j.ejrh.2025.102419
Citations
2
Primary Topic
Water Resources and Sustainability
Type
article
Field-Weighted Citation Impact
1.63

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article

Evolution and drivers of water use in Northern China

Zheng Xiaokang, Fang Wan, Chao Ma, Hao Wang et al.
2 citations
Journal of Hydrology Regional Studies
Water Resources and Sustainability
1.63
article

Evolution and drivers of water use in Northern China

Zheng Xiaokang, Fang Wan, Chao Ma, Hao Wang, Hong Lv
article en
2 citations

Abstract

The 16 provinces in Northern China. This study constructs a segmented linear regression model to identify the stages of water resource utilization and selects 11 indicators affecting changes in industrial, agricultural, and domestic water use. The logarithmic mean Divisia index (LMDI) method is applied to analyze the driving and restraining factors behind the changes in total water use in each province. We identified three distinct stages of water use in Northern China: drought suppression (1997–2003), economic stimulation (2004–2012), and policy restriction (2013–2021). We selected 11 indicators affecting changes in industrial, agricultural, and domestic water use and applied the logarithmic mean Divisia index (LMDI) method to analyze the driving and constraining factors behind total water use and its variations across provinces. The results show that economic factors contributed 14 % to changes in water use, while social factors contributed 6.5 %. Additionally, the study highlights the significant role of climate change during the drought suppression phase, whereas rapid industrialization and economic growth played a dominant role in the economic stimulation phase. In contrast, policy restrictions have led to a gradual decrease in water use in recent years. • Northern China's water use follows three stages. • LMDI method reveals economic factors drive 14 % of water use changes. • Industrial and agricultural shifts are key to total water consumption evolution. • Policy interventions since 2013 effectively changed water usage across sectors.

Journal of Hydrology Regional StudiesVol. 59
Tianjin University (CN), North China University of Water Resources and Electric Power (CN), Yellow River Institute of Hydraulic Research (CN)
Tianjin University, National Key Research and Development Program of China
Clean water and sanitation
Openalex Percentile: Top 17%
Water Resources and Sustainability
1.63
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