Supplemental Material for "Climate Change Impacts on Soil Moisture and SERDI-Based Drought Assessment Using the ML-NBC Framework"

Supplemental Material for "Climate Change Impacts on Soil Moisture and SERDI-Based Drought Assessment Using the ML-NBC Framework." This supplemental material includes additional datasets, figures, and mathematical formulations that support the findings of the manuscript. The content is organized as follows: - Supplemental Material A: Predictor Variables and Supporting Data: Describes the predictor variables used during model training, including data from NCEP/NCAR Reanalysis and CMIP6.- Supplemental Material B: Mathematical Formulations: Details the mathematical formulations of machine-learning models (Linear Regression, Random Forest, and Support Vector Regression) as well as the evaluation metrics (R², RMSE, KGE, etc.).- Supplemental Material C: Supplemental Figures: Includes correlation heatmaps, time series plots, and classification plots for different stations (e.g., Cumilla, Dinajpur, Ishwardi, etc.).- Supplemental Material D: Supplemental Tables: Contains consistency statistics and validation performance for NBC-corrected soil moisture across all stations. The supplemental material can be accessed at the following link: [10.5281/zenodo.19372111].