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Spatial Distribution of the Cropping Pattern Exerts Greater Influence on the Water Footprint Compared to Diversification in Intensive Farmland Landscapes

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  • Xiaohui Wang

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    School of Biology and Agriculture, Shaoguan University, Shaoguan 512005, China
    College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China)

  • Hao Jia

    (Department of Agricultural History Research, China Agricultural Museum, Beijing 100026, China)

  • Xiaolong Wang

    (College of Agriculture, South China Agricultural University, Guangzhou 510642, China)

  • Jiaen Zhang

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    Guangdong Provincial Key Laboratory of Eco-Circular Agriculture, South China Agricultural University, Guangzhou 510642, China)

  • Fu Chen

    (College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China)

Abstract

Global imperatives call for reduced water consumption in homogeneous, intensive farming systems, where farmland landscape heterogeneity significantly impacts anthropogenic, ecological, and socioeconomic factors. However, the impact of this heterogeneity on crop water footprint (WF) remains uncertain. To address this, this study assessed the WF at the landscape scale across 616 subplots (1 × 1 km) in a representative county of North China Plain from 2013 to 2019, integrating green (WF green ), blue (WF blue ), and gray (WF gray ) water footprints. Results showed that the winter wheat–summer maize double cropping pattern (WM) exhibited the highest WF green , WF blue , and WF gray . Over six years, most subplots saw significant reductions in WF green , WF blue , WF gray , and WF. At the landscape scale, diversification (compositional heterogeneity), fragmentation, and spatial distribution (configurational heterogeneity) were assessed using Shannon’s diversity index (SHDI), edge density (ED), and effective mesh size (MESH), which exhibited average variations of 0.07, −3.16 m ha −1 , and −5.86 m 2 , respectively. For WM patches, the percentage of landscape (PLAND) and MESH were used to evaluate diversification and spatial distribution, resulting in reductions of 1.14% and 2.32 m 2 , respectively. Regression analysis and structural equation modeling further illuminated the connections between the landscape pattern and WF, emphasizing the significant role of MESH in reducing WF blue and influencing crop diversity ( p < 0.001). Therefore, spatial distribution, whether directly or through the mediation of diversification, demonstrated a more substantial overall impact on WF. Consequently, future research should prioritize investigating how spatial distribution influences crop choice and agronomic management in order to determine the optimal cropping patterns and field size that strike a balance between crop production and the water footprint. This study offers theoretical guidance and a scientific foundation for redesigning farmland landscapes to bolster water sustainability in intensive farming systems.

Suggested Citation

  • Xiaohui Wang & Hao Jia & Xiaolong Wang & Jiaen Zhang & Fu Chen, 2024. "Spatial Distribution of the Cropping Pattern Exerts Greater Influence on the Water Footprint Compared to Diversification in Intensive Farmland Landscapes," Land, MDPI, vol. 13(7), pages 1-17, July.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:7:p:1042-:d:1433390
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    References listed on IDEAS

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    1. David Tilman & Kenneth G. Cassman & Pamela A. Matson & Rosamond Naylor & Stephen Polasky, 2002. "Agricultural sustainability and intensive production practices," Nature, Nature, vol. 418(6898), pages 671-677, August.
    2. Kashyap, Durba & Agarwal, Tripti, 2021. "Carbon footprint and water footprint of rice and wheat production in Punjab, India," Agricultural Systems, Elsevier, vol. 186(C).
    3. Cao, Xinchun & Zeng, Wen & Wu, Mengyang & Guo, Xiangping & Wang, Weiguang, 2020. "Hybrid analytical framework for regional agricultural water resource utilization and efficiency evaluation," Agricultural Water Management, Elsevier, vol. 231(C).
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    1. Qianyu Zhao & Hao Liu & Peng Zhang & Cailong Deng & Yujiao Li, 2025. "Evaluation of Arable Land Intensive Utilization and Diagnosis of Obstacle Factors from the Perspective of Public Emergencies: A Case Study of Sichuan Province in China Based on the Pressure-State-Resp," Land, MDPI, vol. 14(4), pages 1-22, April.

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