This analysis uncovers spatiotemporal patterns and influential factors in the water-land-energy-food nexus, highlighting urbanization's role.
Water, land, energy, and food are fundamental resources for human survival and ecological stability, yet they face intensifying pressure from surging demands and spatial mismatches. Integrated governance of their interconnected nexus is pivotal to achieving sustainable development. In this study, we analyze the water-land-energy-food (WLEF) nexus synergies in China’s North China Plain, a vital grain base for China’s food security. We develop a city-level WLEF evaluation framework and employ a coupling coordination model to assess spatiotemporal patterns of the WLEF system from 2010 to 2022. Additionally, we diagnose critical internal and external influencing factors of the WLEF coupling system, using obstacle degree modeling and geographical detectors. The results indicate that during this period, the most critical internal factor was per capita water resource availability. The impact of the external factor—urbanization level—was characterized by fluctuation and a general upward trend, and by 2022, it had become the dominant influencing factor. Results indicated that the overall development of the WLEF system exhibited a fluctuating trend of initial increasing then decreasing during the study period, peaking at 0.426 in 2016. The coupling coordination level of the WLEF system averaged around 0.5, with the highest value (0.526) in 2016, indicating a marginally coordinated state. Regionally, a higher degree of coordination was presented in the southern regions of the North China Plain compared with the northern areas. Anhui province achieved the optimal coordination, while Beijing consistently ranked lowest. The primary difference lies in the abundant water resources in Anhui, in contrast to the water scarcity in Beijing. Internal diagnostic analysis identified per capita water availability as the primary constraint on system coordination. External factors, including urbanization rate, primary industry’s added value, regional population, and rural residents’ disposable income, exhibited growing influence on the system over time. This study provides a theoretical framework for WLEF system coordination and offers decision-making support for optimizing resource allocation and promoting sustainable development in comparable regions.
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Dai et al. (2025) studied this question.
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