Study and application of the profile-attenuation-based standardized soil moisture index

Abstract

Cold-region spring crops are highly sensitive to water stress during the seedling stage, making spring agricultural drought a major constraint on crop productivity in semi-arid regions. Conventional drought monitoring often relies on the Standardized Soil Moisture Index (SSMI), which does not account for vertical root distribution and can produce “pseudo-wet” signals in deep soil layers due to permafrost thawing. To address these limitations, we developed a Profile-Attenuation-based Standardized Soil Moisture Index (PASSMI). By incorporating a root-driven weight attenuation function, PASSMI amplifies shallow moisture signals while suppressing deep-layer interference, thereby better aligning soil moisture profiles with crop physiological demands. Compared to SSMI, PASSMI is more sensitive in identifying drought events and better captures spring drought evolution.Using the semi-arid region of western Heilongjiang as a study area, we integrated in-situ observations with CMA-RA reanalysis data to reconstruct high-resolution vertical soil moisture profiles (1980–2020) through a hybrid framework combining K-Nearest Neighbor Inverse Distance Weighting (KNN-IDW) with Light Gradient Boosting Machine–Gaussian Process Regression (LightGBM-GPR). Comparative analysis shows that PASSMI improves sensitivity in identifying extreme drought events(e.g., 2003 and 2009)—by 54.2% over SSMI. Spring droughts in the study area exhibit a distinct “wet in the east, dry in the west” spatial pattern.Temporally, the drought cycle followed four stages: quiescence, intensification, peak, and recovery, with a 70.3% occurrence frequency dominated by mild to severe events. This study provides a more accurate tool for agricultural drought monitoring in cold regions and offers scientific support for water resource management and irrigation optimization in similar semi-arid environments.