Development of High-Resolution Soil Moisture Product for India, 1981-2024

Reliable soil moisture records are vital for drought assessment and agricultural planning in monsoon-driven and irrigation-intensive regions such as India. Existing satellite products like SMAP and SMOS have advanced global monitoring but remain constrained by short data spans, shallow penetration depth, and reduced accuracy in vegetated or irrigated areas. To address these gaps, we developed a high-resolution (0.05°) daily root-zone soil moisture (RZSM) dataset for 1981–2024. The dataset was generated using a hybrid framework that combines simulations from the calibrated H08 land surface model with SMAP RZSM through grid-wise Random Forest regression. By merging physical modeling with satellite observations, this dataset provides improved spatial detail, extended temporal coverage, and enhanced reliability, supporting applications in drought monitoring, hydrological modeling, and agricultural risk assessment.可靠的土壤湿度记录对于季风驱动且灌溉密集型地区（如印度）的干旱评估与农业规划至关重要。现有SMAP、SMOS等卫星产品虽推动了全球土壤湿度监测，但仍存在数据周期较短、穿透深度较浅，且在植被覆盖或灌溉区域精度下降等局限。为填补这些研究空白，我们构建了一套1981–2024年的高分辨率（0.05°）逐日根区土壤湿度（root-zone soil moisture, RZSM）数据集。该数据集采用混合框架构建：将经过校准的H08陆面模型的模拟结果，通过逐网格随机森林回归与SMAP RZSM数据进行融合。通过融合物理模拟与卫星观测数据，该数据集具备更精细的空间细节、更长的时间覆盖范围与更高的可靠性，可为干旱监测、水文模拟及农业风险评估等应用提供支撑。