High-resolution water footprints of major crops in China from cities to grids.

Jingwen Zhao, Linxiu Wu, Xiaomeng Wang, Yajuan Yu, Kai Huang

Abstract read

In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed

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1 · What the graph read from it

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jingwen ZhaoCollege of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China.

Linxiu WuCollege of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China.

Xiaomeng WangCenter for Smart and Connected Health Technologies, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.

Yajuan YuSchool of Materials Science & Engineering, Beijing Key Laboratory of Environmental Science and Engineering, Beijing Institute of Technology, Beijing, 100081, China.

Kai HuangCollege of Environmental Science and Engineering, Beijing Forestry University, Beijing, 100083, China. huangkai@bjfu.edu.cn.

Funding

National Natural Science Foundation of China 52370190

6 · The paper itself

Abstract

Rapid population and economic growth have led to an increased demand for water and food, thereby exacerbating the water scarcity crisis. Therefore, an objective assessment of water usage in crop production is crucial for ensuring national food security and alleviating water scarcity. However, the city-scale crop production water footprint (CWF) in China remains incomplete, while grid-scale CWF data are plagued by the limitations of coarse crop statistics. To fill this knowledge gap, we propose a novel methodology for developing a high-resolution inventory of CWFs. Based on this methodology, we quantified the city-scale water footprint (WF) of three major crops (rice, wheat, and maize) in China and allocated the CWFs of individual cities to 3 km × 3 km grids through a top-down downscaling approach to create a high-resolution CWF inventory. The results show that the average annual CWF of the three crops from 2000 to 2020 was in the order of rice (2.50 × 10

Indexed as

City-scaleCrop productionDownscaleHigh-resolutionWater footprint

Identifiers

PMID41476078

DOI10.1038/s41598-025-08906-2

PMCPMC12764883

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LicenceCC BY-NC-ND

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.