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Updated: Mar 2, 2026
08:20
In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
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Development of Gridded Root-Zone Soil Moisture Product for India, 1981-2024
Dipesh Singh Chuphal1, Abhishek1, Anuj Prakash Kushwaha2
1Department of Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar, Gandhinagar, India.
Scientific Data
|March 1, 2026
Summary
A new long-term soil moisture dataset for India (1981-2024) was created using a hybrid model. This crucial data aids drought monitoring and agricultural planning in the region.
Area of Science:
- Earth and Environmental Sciences
- Hydrology
- Remote Sensing
Background:
- Accurate soil moisture data is critical for India's agriculture and drought management.
- Existing satellite data (SMAP, SMOS) have limitations in record length, depth, and accuracy.
Purpose of the Study:
- To develop a high-resolution, long-term root-zone soil moisture (RZSM) dataset for India (1981-2024).
- To provide a robust resource for drought analysis, hydrological modeling, and agricultural risk assessment.
Main Methods:
- A hybrid approach combining the H08 land surface model with SMAP RZSM data using Random Forest regression.
- Model calibration and predictor training using SMAP observations from 2016-2024.
- Validation using cross-validation, in-situ measurements, and Solar-Induced Chlorophyll Fluorescence.
Main Results:
- The reconstructed RZSM dataset (0.05° daily) shows strong agreement with SMAP (R² > 0.90) and in-situ data (R² = 0.94).
- High accuracy achieved with RMSE < 0.03 m³/m³ compared to SMAP and RMSE = 0.04 m³/m³ for in-situ data.
- Dataset validated against vegetation activity during drought years.
Conclusions:
- The developed dataset offers a reliable, long-term RZSM record for India.
- It serves as a valuable tool for understanding drought dynamics and supporting agricultural decision-making.
- Enhances capabilities for hydrological research and risk management in India.
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