Estimation of critical soil moisture based on surface energy partitioning characterizing land aridity in China

作者：J. Lu, Ruixin Li, Xuan Zhao · 发表于：Geo-spatial Information Science · 年份：2026 · DOI：10.1080/10095020.2026.2631950 · 研究领域：Soil Moisture and Remote Sensing、Plant Water Relations and Carbon Dynamics、Soil and Unsaturated Flow

Understanding the mechanisms of surface energy partitioning is essential for diagnosing land-atmosphere interactions and regional drought risk. In this study, we aim to improve the large-scale estimation of critical soil moisture (CSM), an emerging property that marks a shift between water- and energy-limited evapotranspiration regimes, by leveraging remote sensing data and surface energy partitioning patterns across China. First, we employed a generalized additive model to quantify the relative contributions of five environmental drivers to variations in the evaporative fraction (EF), confirming the dominant roles of soil moisture (SM) and air temperature (Tair) in shaping EF variability. To identify hydro-climatic constraints, we introduce a correlation difference index (∆Corr), defined as the difference between the Spearman correlation coefficients of EF with Tair and with SM. This metric is then used to delineate energy- and water-limited regimes and assess their spatial and temporal trends from 2002 to 2018. Compared with traditional drought indices such as the aridity index, ∆Corr exhibits stronger spatial heterogeneity and higher sensitivity to short-term variability in water and energy availability. Furthermore, large-scale CSM was determined at 0.16 m3 m−3 for China. A series of local CSMs representing specific grid cells had median and mean values of 0.17 m3 m−3 and 0.19 m3 m−3, respectively. Variations in CSM across precipitation gradients, vegetation types, and co...