Beyond elevation: Unravelling land cover–elevation interactions in governing soil moisture variability in the lower Himalayas

Understanding the spatiotemporal variability of soil moisture (SM) in topographically complex and data-scarce regions, such as the Himalayas, remains a major challenge due to the interactive influence of elevation, land cover heterogeneity, and anthropogenic activities. This study presents an extensive 57-week soil moisture monitoring campaign conducted at 104 systematically gridded locations in the Suketi watershed, Himachal Pradesh, India. Soil moisture samples were classified into three land cover types: agricultural lands, forests, and grasslands, and further stratified into five elevation zones (739–2914 m) using a quantile-based classification method to accurately capture altitudinal variability. Statistical methods, including Student’s t-distribution, Spearman rank correlation, analysis of variance, Tukey’s post-hoc test, and partial dependence plots, were employed to quantify the interactive controls of SM variability. The findings underscore that elevation alone inadequately explains SM variability, however, land cover-specific attributes such as vegetation cover, soil texture, and anthropogenic practices exert significant influence. Grasslands consistently exhibited higher moisture retention (∼18.05 %) and lower spatial variability across elevations, making them ideal buffer zones for hydrological planning. Forests exhibited moderate SM levels (∼16.69 %) and greater temporal stability, while agricultural areas showed pronounced variability (standard deviation ∼5.20 %) and significant sensitivity to elevation (ρ = –0.36, p < 0.01), indicating the need for denser sampling strategies in such landscapes. The study also introduces a statistically robust framework for determining optimal sampling locations under varying precision thresholds, offering valuable guidance for sensor network optimization. The findings provide critical insights for enhancing hydrological modeling, satellite SM product validation, and precision water resource management in mountainous environments. • 57-week monitoring yields high-resolution soil moisture data in mountain watershed. • Elevation alone inadequate as elevation–landform interactions govern soil moisture. • At 1 % error, forests needed 88 % sampling, agriculture 63 %, grasslands 40 %, highlighting lean-season variability. • Grasslands with higher, stable soil moisture are ideal buffer zones in hilly areas. • Findings aid hydrological modelling and satellite soil moisture product validation.