Abstract

A comprehensive understanding of the spatiotemporal evolution of water use efficiency (WUE) and its driving mechanisms is essential for sustainable water resource management in the Huang–Huai–Hai Plain (HHHP), a critical agricultural production base in northern China. Based on multi-source remote sensing datasets from 2001 to 2024, this study adopted the Sen-MK trend test and optimized XGBoost-SHAP framework to characterize the spatiotemporal variations in WUE and quantify corresponding driving forces: (1) WUE exhibited a predominantly rising trend across 78.53% of the study area, with significant increases concentrated in the southwestern Shandong hilly region; high WUE values (1.68–1.74 g C·m−2·mm−1) occurred in the eastern Shandong hills and southwestern North China Plain, while low values (1.50–1.56 g C·m−2·mm−1) were found in the northern North China Plain and southeastern Bohai Bay area. (2) Among vegetation types, shrubland showed the highest multi-year mean WUE (1.75 g C·m−2·mm−1) and wetland the lowest (1.34 g C·m−2·mm−1); cropland displayed the most rapid increasing trend (0.0045 g C·m−2·mm−1·a−1), while wetland showed a decreasing trend. (3) The HHHP showed low interannual volatility and strong persistence of WUE, with stable interannual WUE and historical persistence suggesting that the increasing trend may continue in most areas. (4) Spatial variation in WUE is primarily driven by NDVI and temperature, with NDVI having the greatest influence, accounting for approximately 40.36% of the vegetated area, while temperature accounts for 26.43%, ranking second; precipitation and the aridity index exerted secondary regulatory effects, with positive effects mainly in the Huang–Huai Plain and negative effects in the North China Plain. This study elucidates the evolutionary mechanisms of WUE under coupled climate–vegetation influences, providing critical scientific evidence for optimizing regional water resource allocation and management and promoting sustainable agricultural practices in this water-limited region.

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