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

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Main Authors: Nury, Ahmad Hasan, Joy, Mahfujur Rahman, Afroz, Rounak, Saim, Abu Sadat Md.
Format: Recurso digital
Language:English
Published: Zenodo 2026
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author Nury, Ahmad Hasan
Joy, Mahfujur Rahman
Afroz, Rounak
Saim, Abu Sadat Md.
author_facet Nury, Ahmad Hasan
Joy, Mahfujur Rahman
Afroz, Rounak
Saim, Abu Sadat Md.
contents <p>Supplemental Material for "Climate Change Impacts on Soil Moisture and SERDI-Based Drought Assessment Using the ML-NBC Framework."</p> <p>This supplemental material includes additional datasets, figures, and mathematical formulations that support the findings of the manuscript. The content is organized as follows:</p> <p>- <strong>Supplemental Material A: Predictor Variables and Supporting Data:</strong> Describes the predictor variables used during model training, including data from NCEP/NCAR Reanalysis and CMIP6.<br>- <strong>Supplemental Material</strong><strong> B: Mathematical Formulations: </strong>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.).<br>- <strong>Supplemental Material </strong><strong>C: Supplemental Figures:</strong> Includes correlation heatmaps, time series plots, and classification plots for different stations (e.g., Cumilla, Dinajpur, Ishwardi, etc.).<br>- <strong>Supplemental Material </strong><strong>D: Supplemental Tables:</strong> Contains consistency statistics and validation performance for NBC-corrected soil moisture across all stations.</p> <p>The supplemental material can be accessed at the following link: [10.5281/zenodo.19372111].</p>
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record_format zenodo
spellingShingle Supplemental Material for "Climate Change Impacts on Soil Moisture and SERDI-Based Drought Assessment Using the ML-NBC Framework"
Nury, Ahmad Hasan
Joy, Mahfujur Rahman
Afroz, Rounak
Saim, Abu Sadat Md.
<p>Supplemental Material for "Climate Change Impacts on Soil Moisture and SERDI-Based Drought Assessment Using the ML-NBC Framework."</p> <p>This supplemental material includes additional datasets, figures, and mathematical formulations that support the findings of the manuscript. The content is organized as follows:</p> <p>- <strong>Supplemental Material A: Predictor Variables and Supporting Data:</strong> Describes the predictor variables used during model training, including data from NCEP/NCAR Reanalysis and CMIP6.<br>- <strong>Supplemental Material</strong><strong> B: Mathematical Formulations: </strong>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.).<br>- <strong>Supplemental Material </strong><strong>C: Supplemental Figures:</strong> Includes correlation heatmaps, time series plots, and classification plots for different stations (e.g., Cumilla, Dinajpur, Ishwardi, etc.).<br>- <strong>Supplemental Material </strong><strong>D: Supplemental Tables:</strong> Contains consistency statistics and validation performance for NBC-corrected soil moisture across all stations.</p> <p>The supplemental material can be accessed at the following link: [10.5281/zenodo.19372111].</p>
title Supplemental Material for "Climate Change Impacts on Soil Moisture and SERDI-Based Drought Assessment Using the ML-NBC Framework"
url https://doi.org/10.5281/zenodo.19372111