Agricultural Water–Land Matching and Functional Zoning in Northern Shaanxi

Water and land resources are fundamental to agricultural production, and their spatiotemporal matching and utilization efficiency have a profound impact on agricultural sustainability and food security. Utilizing data from 25 counties in Northern Shaanxi (NS) from 2010 to 2021, this study applied the Gini coefficient, generalized matching coefficient, spatial correlation analysis, and clustering techniques to analyze the spatiotemporal matching patterns of agricultural water and land resources (AWLRs) and propose a functional zoning scheme. The results revealed significant spatial disparities in AWLR matching. The AWLR matching coefficient in NS was below the provincial average and substantially lower than the national average, indicating a generally poor level of matching. From 2010 to 2021, the Gini coefficient of AWLR decreased, reflecting an improvement from a severe mismatch to a generally balanced state. A significant positive spatial correlation was observed between AWLR matching and agricultural development levels. Counties with high AWLR matching but low agricultural development were mainly concentrated in the north, whereas southern counties exhibited both high AWLR matching and high agricultural development. The coordinated development degrees among agricultural development level, agricultural water use benefit, and cultivated land use benefit in the 25 counties were at low or relatively low levels. Furthermore, the K-Means++-AHC clustering algorithm demonstrated better applicability for functional zoning, dividing NS into four distinct agricultural zones: Zone I (good AWLR match but low agricultural development); Zone II (low utilization efficiency and AWLR match); Zone III (water scarcity and high land reclamation, sustaining high agricultural development despite poor AWLR match); and Zone IV (the core agricultural area with comprehensive advantages). The results clarify the matching degree of AWLRs and their utilization potential in NS and the zoning framework will guide targeted interventions to enhance agricultural efficiency in water-scarce regions.

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Publication Details

Journal
Applied Sciences
Published
2025-10-22
DOI
https://doi.org/10.3390/app152111306
Primary Topic
Remote Sensing and Land Use
Type
article
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article

Agricultural Water–Land Matching and Functional Zoning in Northern Shaanxi

Hongbo Zhang, Yaxin Li, Hui Li, Yingqi Mu
Applied Sciences
Remote Sensing and Land Use
article

Agricultural Water–Land Matching and Functional Zoning in Northern Shaanxi

Hongbo Zhang, Yaxin Li, Hui Li, Yingqi Mu
article en

Abstract

Water and land resources are fundamental to agricultural production, and their spatiotemporal matching and utilization efficiency have a profound impact on agricultural sustainability and food security. Utilizing data from 25 counties in Northern Shaanxi (NS) from 2010 to 2021, this study applied the Gini coefficient, generalized matching coefficient, spatial correlation analysis, and clustering techniques to analyze the spatiotemporal matching patterns of agricultural water and land resources (AWLRs) and propose a functional zoning scheme. The results revealed significant spatial disparities in AWLR matching. The AWLR matching coefficient in NS was below the provincial average and substantially lower than the national average, indicating a generally poor level of matching. From 2010 to 2021, the Gini coefficient of AWLR decreased, reflecting an improvement from a severe mismatch to a generally balanced state. A significant positive spatial correlation was observed between AWLR matching and agricultural development levels. Counties with high AWLR matching but low agricultural development were mainly concentrated in the north, whereas southern counties exhibited both high AWLR matching and high agricultural development. The coordinated development degrees among agricultural development level, agricultural water use benefit, and cultivated land use benefit in the 25 counties were at low or relatively low levels. Furthermore, the K-Means++-AHC clustering algorithm demonstrated better applicability for functional zoning, dividing NS into four distinct agricultural zones: Zone I (good AWLR match but low agricultural development); Zone II (low utilization efficiency and AWLR match); Zone III (water scarcity and high land reclamation, sustaining high agricultural development despite poor AWLR match); and Zone IV (the core agricultural area with comprehensive advantages). The results clarify the matching degree of AWLRs and their utilization potential in NS and the zoning framework will guide targeted interventions to enhance agricultural efficiency in water-scarce regions.

Applied SciencesVol. 15(21)
Xi'an University of Science and Technology (CN), Chang'an University (CN), Ministry of Water Resources of the People's Republic of China (CN)
Openalex Percentile: Top 65%
Remote Sensing and Land Use
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