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

Author:

Wang Xiaohui123ORCID,Jia Hao4ORCID,Wang Xiaolong5,Zhang Jiaen16ORCID,Chen Fu3

Affiliation:

1. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China

2. School of Biology and Agriculture, Shaoguan University, Shaoguan 512005, China

3. College of Agronomy and Biotechnology, China Agricultural University, Beijing 100193, China

4. Department of Agricultural History Research, China Agricultural Museum, Beijing 100026, China

5. College of Agriculture, South China Agricultural University, Guangzhou 510642, China

6. Guangdong Provincial Key Laboratory of Eco-Circular Agriculture, South China Agricultural University, Guangzhou 510642, 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 (WFgreen), blue (WFblue), and gray (WFgray) water footprints. Results showed that the winter wheat–summer maize double cropping pattern (WM) exhibited the highest WFgreen, WFblue, and WFgray. Over six years, most subplots saw significant reductions in WFgreen, WFblue, WFgray, 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 m2, 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 m2, 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 WFblue 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.

Funder

the National Key Research and Development Program of China

Rural Energy and Environmental Agency, Ministry of Agriculture and Rural Affairs

Publisher

MDPI AG

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