Evolution and Driving Factors of Water Footprints for Major Grain Crops: Evidence from China’s Main Grain-Producing Regions

The water footprint of grain crop production is a key indicator for assessing agricultural water stress and resource-use efficiency. This study analyzes the dynamic evolution, convergence characteristics, and driving forces of water footprints for major grain crops in China’s primary producing regions from 2011 to 2022. The results show the following: (1) Total water footprints are mainly driven by blue and green water components, while grey water contributes relatively little, and the total footprint follows a fluctuating pattern of “decline–increase–decline–increase–decline.” Rice exhibits the highest water footprint, with an average annual value of 59.8251 million m3, whereas beans and tubers show much lower levels, each with an average annual footprint below 20 million m3. Grey water footprints for all grain crops have declined significantly since 2018, with reductions exceeding 10% by 2022. (2) Significant absolute convergence is observed across provinces, with the absolute convergence rate ultimately approaching 0.1, indicating that inter-provincial differences in water footprints are narrowing and that high-footprint regions are improving more rapidly toward lower-footprint regions. (3) Conditional convergence is also confirmed, with the conditional convergence rate approaching 0.2, suggesting that provinces converge toward their own steady-state levels, though convergence speeds are influenced by heterogeneous factors such as economic development, technological progress, and population size. (4) Generalised Divisia Index Method (GDIM) decomposition reveals that per capita agricultural GDP and mechanization intensity are the core drivers of changes in water footprints, and their synergistic effects produce an amplification impact, with cumulative contributions exceeding 100%. The findings provide important policy implications for optimizing water resource management and promoting sustainable agricultural development in China’s major grain-producing areas.

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Publication Details

Journal
Water
Published
2025-12-19
DOI
https://doi.org/10.3390/w18010009
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
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article

Evolution and Driving Factors of Water Footprints for Major Grain Crops: Evidence from China’s Main Grain-Producing Regions

Hailiang Ma, Yifan Guo, H. M. Yun
Water
Environmental Impact and Sustainability
article

Evolution and Driving Factors of Water Footprints for Major Grain Crops: Evidence from China’s Main Grain-Producing Regions

Hailiang Ma, Yifan Guo, H. M. Yun
article en

Abstract

The water footprint of grain crop production is a key indicator for assessing agricultural water stress and resource-use efficiency. This study analyzes the dynamic evolution, convergence characteristics, and driving forces of water footprints for major grain crops in China’s primary producing regions from 2011 to 2022. The results show the following: (1) Total water footprints are mainly driven by blue and green water components, while grey water contributes relatively little, and the total footprint follows a fluctuating pattern of “decline–increase–decline–increase–decline.” Rice exhibits the highest water footprint, with an average annual value of 59.8251 million m3, whereas beans and tubers show much lower levels, each with an average annual footprint below 20 million m3. Grey water footprints for all grain crops have declined significantly since 2018, with reductions exceeding 10% by 2022. (2) Significant absolute convergence is observed across provinces, with the absolute convergence rate ultimately approaching 0.1, indicating that inter-provincial differences in water footprints are narrowing and that high-footprint regions are improving more rapidly toward lower-footprint regions. (3) Conditional convergence is also confirmed, with the conditional convergence rate approaching 0.2, suggesting that provinces converge toward their own steady-state levels, though convergence speeds are influenced by heterogeneous factors such as economic development, technological progress, and population size. (4) Generalised Divisia Index Method (GDIM) decomposition reveals that per capita agricultural GDP and mechanization intensity are the core drivers of changes in water footprints, and their synergistic effects produce an amplification impact, with cumulative contributions exceeding 100%. The findings provide important policy implications for optimizing water resource management and promoting sustainable agricultural development in China’s major grain-producing areas.

WaterVol. 18(1)
Hohai University (CN)
Openalex Percentile: Top 60%
Environmental Impact and Sustainability
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