Fuente: Sustainability - Revista científica (MDPI) Sustainability, Vol. 17, Pages 11265: Spatiotemporal Evolution and Driving Mechanisms of Water–Energy–Food Synergistic Efficiency: A Case Study of Irrigation Districts in the Lower Yellow River
Sustainability doi: 10.3390/su172411265
Authors:
Yuchen Zheng
Chang Liu
Lingqi Li
Enhui Jiang
Genxiang Feng
Bo Qu
Lingang Hao
Jiaqi Li
Jiahe Li

As an integrated framework linking resource use and environmental sustainability, the WEF (Water–Energy–Food) system plays a vital role in achieving sustainable agricultural development. Focusing on the irrigation districts in the lower reaches of the Yellow River, this study constructed and applied a Super-Undesirable-SBM (super-efficiency undesirable slacks-based measure) model and a GTWR (geographically and temporally weighted regression) model from a WEF perspective to systematically analyze the spatiotemporal evolution and driving mechanisms of WEFSE (Water–Energy–Food Synergistic Efficiency) from 2000 to 2020. The overall WEFSE exhibited a continuous upward trend, with the spatial pattern gradually shifting from the southwest to the northeast and regional disparities becoming more pronounced. The efficiency demonstrated a significant positive spatial autocorrelation, indicating a stable clustering pattern of “high–high” and “low–low” efficiency areas. In terms of driving mechanisms, WEFSE evolved from being dominated by socio-economic drivers to a composite system jointly influenced by ecological and structural factors. Among these, PD (population density) and WP (proportion of water area) had increasingly positive effects, whereas PRE (precipitation) and NDVI (normalized difference vegetation index) imposed notable constraints. Meanwhile, PCL (proportion of cultivated land), GP (proportion of grassland), and AT (average temperature) exhibited significant spatial differentiation. This study highlights that the assessment of WEFSE and identification of its driving mechanisms using the Super-Undesirable-SBM and GTWR models can help to uncover the spatiotemporal dynamics of agricultural resource utilization, providing methodological support and decision-making insights for optimizing resource allocation and promoting sustainable development in the Yellow River irrigation districts and other complex agricultural systems.