Spatiotemporal Evolution and Driving Mechanisms of Water Footprint with Input-Output Paradigm: A Case Study of China

The evaluation and quantification of water consumption based on water footprint (WF) is important for sustainable utilization of water resources and is becoming one of the key bases for formulating water resources management policies. However, there are few systematic assessments of both temporal ch...

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Bibliographic Details
Published in:Water (Basel) 2022-08, Vol.14 (15), p.2373
Main Authors: Hu, Runzhi, Li, Ruiqi, Han, Siqi, Li, Lin, Yin, Tuo, Li, Yunkai, Chen, Xiuzhi
Format: Article
Language:English
Subjects:
Agricultural production
Agriculture
Consumption
Developing countries
Farm structure
Footprint analysis
International trade
LDCs
Supply chains
Sustainable development
Technological change
Water conservation
Water consumption
Water management
Water policy
Water resources
Water resources management
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Summary:The evaluation and quantification of water consumption based on water footprint (WF) is important for sustainable utilization of water resources and is becoming one of the key bases for formulating water resources management policies. However, there are few systematic assessments of both temporal changes and spatial patterns of WF in China, and the driving of water footprint intensity (WFI) is rarely reported. Based on the research background, this paper takes China, the world’s largest developing country, as an example to analyze the spatiotemporal evolution of WF through the input–output model. The total WF in China increased by 11.76% from 2002 to 2017. National WFI decreased from 550 m³/104 yuan (2002) to 152 m³/104 yuan (2017). The regions found to have the highest WF in China include Shandong, Henan, and Hebei, and regions with higher WFI are distributed in East China. From 2002 to 2017, the total WF of each province in China changed significantly. Guangdong, Fujian, and Zhejiang provinces’ total WF decreased markedly during the study period. The results show that the grain output per capita and GDP per capita have a significant driving effect on WFI. By adjusting the agricultural structure and improving the comprehensive ability of scientific and technological innovation, it is possible to reduce the WFI in China.
ISSN:2073-4441
2073-4441
DOI:10.3390/w14152373