Abstract Soil hydraulic properties (SHPs) link soil structure with water dynamics by regulating infiltration, retention, drainage, and root‐zone moisture, and they are strongly shaped by land use and land cover change (LULCC). Field and laboratory methods for estimating SHPs under LULCC are time‐consuming and limited in scalability due to small‐scale heterogeneity. To address these challenges, we tested an alternative approach that integrates the HYDRUS‐1D inverse modeling framework with in situ soil moisture data from the US National Ecological Observatory Network to estimate the impacts of LULCC on SHPs. Inverse modeling demonstrated the capacity to capture land‐use‐driven shifts in SHPs under specific conditions. Cropland exhibited the strongest model fit (mean R 2 = 0.80) but showed homogenized SHPs with tightly clustered retention curves, reflecting tillage‐induced uniformity. Soils under grassland displayed greater heterogeneity, consistent with preserved root systems and organic matter inputs, while soils that were reforested resembled forest conditions after ∼20 years, with only subtle shifts in the slope of the water retention curve (parameter n ). Clay soils under forest showed poor performance (mean R 2 = 0.30), yielding unreliable parameter estimates and highlighting challenges of parameter identifiability in fine‐textured systems. Across all land‐use transitions, α and K s were the most variable parameters, while θ r and θ s remained relatively stable. This approach can be used for assessing LULCC impacts on SHPs, with its reliability depending on data quality and soil texture.
Chiang et al. (Fri,) studied this question.