Chuphal et al. (2026) Development of Gridded Root-Zone Soil Moisture Product for India, 1981–2024

Identification

• Journal: Scientific Data
• Year: 2026
• Date: 2026-02-28
• Authors: Dipesh Singh Chuphal, Abhishek, Anuj Prakash Kushwaha, Gayathri Vangala, Vimal Mishra
• DOI: 10.1038/s41597-026-06940-x

Research Groups

• Department of Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar, Gandhinagar, India
• Department of Earth Science, Indian Institute of Technology (IIT) Gandhinagar, Gandhinagar, India

Short Summary

This study developed a high-resolution (0.05°), long-term (1981–2024) daily root-zone soil moisture dataset for India using a hybrid modeling and machine learning approach, providing a crucial resource for drought monitoring and agricultural planning.

Objective

• To address the limitations of existing satellite soil moisture products (short records, shallow sensing depths, and reduced accuracy under dense vegetation and irrigation) by reconstructing a high-resolution, long-term (1981–2024) daily root-zone soil moisture dataset for India.

Study Configuration

• Spatial Scale: India, 0.05° (approximately 5.5 km) spatial resolution, root-zone depth of 100 cm.
• Temporal Scale: Daily, 1981–2024.

Methodology and Data

• Models used: H08 land surface model, Random Forest regression.
• Data sources:
  • SMAP RZSM observations (for training, 2016–2024)
  • H08-derived soil moisture and evapotranspiration
  • Precipitation data
  • Temperature data
  • In-situ measurements (for validation)
  • Solar-Induced Chlorophyll Fluorescence (for independent validation)

Main Results

• Cross-validation against SMAP RZSM showed strong agreement with R² and NSE values above 0.90 and a Root Mean Square Error (RMSE) of less than 0.03 m³/m³ across most regions.
• Comparison with available in-situ measurements yielded an RMSE of 0.04 m³/m³ and a correlation coefficient of 0.94.
• Independent validation using Solar-Induced Chlorophyll Fluorescence confirmed consistency with vegetation activity, particularly during drought years (2002, 2009).
• The developed dataset provides a robust, high-resolution, and long-term record of root-zone soil moisture for India.

Contributions

• Provides the first high-resolution (0.05°), long-term (1981–2024) daily root-zone soil moisture dataset for India, addressing critical gaps in existing satellite-based products.
• Utilizes a novel hybrid approach combining a calibrated land surface model (H08) with SMAP RZSM observations through Random Forest regression.
• Offers a valuable resource for analyzing drought variability, calibrating hydrological models, and assessing agricultural risks in monsoon-dependent and irrigation-intensive regions like India.

Funding

• Major Research & Development Program (MRDP) by the Department of Science and Technology, India (Grant MRDP4356).

Citation

@article{Chuphal2026Development,
  author = {Chuphal, Dipesh Singh and Abhishek and Kushwaha, Anuj Prakash and Vangala, Gayathri and Mishra, Vimal},
  title = {Development of Gridded Root-Zone Soil Moisture Product for India, 1981–2024},
  journal = {Scientific Data},
  year = {2026},
  doi = {10.1038/s41597-026-06940-x},
  url = {https://doi.org/10.1038/s41597-026-06940-x}
}