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

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