Spatial-Temporal Coordination of Agricultural Quality and Water Carrying Capacity in Chengdu-Chongqing

Bingchang Li, Xinlan Liang (), Cuihua Bian, Fengxin Sun, Zichen Xia, Binghao Sun and Ying Cao
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Bingchang Li: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China
Xinlan Liang: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China
Cuihua Bian: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China
Fengxin Sun: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China
Zichen Xia: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China
Binghao Sun: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China
Ying Cao: College of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya’an 625014, China

Agriculture, 2025, vol. 15, issue 13, 1-30

Abstract: Amid accelerating urbanization and intensifying climate variability, the Chengdu–Chongqing region faces acute tensions between high-quality agricultural development and water resource sustainability. This study constructs a multidimensional evaluation framework to analyze the spatiotemporal interaction between the Agricultural Quality Index (AQI) and the Water Resource Carrying Capacity Index (WCI) from 2013 to 2022 across 16 municipalities. Employing the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model, obstacle degree analysis, standard deviational ellipse, and grey prediction modeling, the study finds that AQI exhibits a sustained upward trend—doubling in over half of the region’s cities—while WCI shows fluctuating growth, constrained by climatic extremes and uneven water distribution. Spatial analysis reveals persistent heterogeneity: cities such as Ya’an maintain superior WCI due to natural endowments, whereas Ziyang and Zigong lag due to infrastructural and environmental limitations. From 2013–2016, disparities between AQI and WCI widened, with the spatial coefficient of variation (sCoV) peaking due to resource misallocation and industrial imbalance. However, targeted policies since 2016—e.g., integrated water infrastructure, model agricultural zones, and adaptive land-use planning—have significantly improved regional coordination and narrowed these disparities. The study forecasts AQI to reach 2.0 by 2026, with Chongqing potentially exceeding 3.0, driven by technological modernization and resource integration. Policy recommendations include: (1) cross-regional water reallocation; (2) specialty agricultural clusters anchored by core cities; and (3) climate-resilient cropping systems. This research provides a scalable governance framework for reconciling resource constraints and agricultural modernization, offering practical insights for inland economic zones globally.

Keywords: agricultural-water nexus; spatiotemporal evolution; barrier factor analysis; regional coordination; grey prediction model (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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