Rajesh et al. (2025) Satellite-based estimation of potential evapotranspiration using the Thornthwaite–Mather model for sub-regional water resource assessment

Identification

• Journal: International Journal of Environmental Science and Technology
• Year: 2025
• Date: 2025-12-04
• Authors: G. M. Rajesh, S. Prasad, Dinesh Kumar Vishwakarma, Rohitashw Kumar, Sudhir Kumar Singh, Ahmed Z. Dewidar, Mohamed I. A. Othman, Mohamed A. Mattar
• DOI: 10.1007/s13762-025-06914-3

Research Groups

• Department of Soil and Water Conservation Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Kerala Agricultural University, Tavanur, Malappuram, Kerala, India
• Department of Soil and Water Engineering, College of Agricultural Engineering, Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, India
• Department of Irrigation and Drainage Engineering, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Udham Singh Nagar, Uttarakhand, India
• College of Agricultural Engineering and Technology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Shalimar, Srinagar, Jammu and Kashmir, India
• K. Banerjee Centre of Atmospheric and Ocean Studies, Institute of Interdisciplinary Studies, University of Allahabad, Prayagraj, Uttar Pradesh, India
• Prince Sultan Bin Abdulaziz International Prize for Water Chair, Prince Sultan Institute for Environmental, Water and Desert Research, King Saud University, Riyadh, Saudi Arabia
• Department of Agricultural Engineering, College of Food and Agriculture Sciences, King Saud University, Riyadh, Saudi Arabia

Short Summary

This study estimates potential evapotranspiration (PET) using satellite-derived land surface temperature (LST) and the Thornthwaite–Mather model for Samastipur district, Bihar, India, finding that bias-corrected LST significantly improves PET estimation accuracy and reveals stable long-term PET trends despite seasonal temperature shifts.

Objective

• To derive Land Surface Temperature (LST) from the GLDAS-2.1 product with a spatial resolution of 0.25° × 0.25°.
• To estimate Potential Evapotranspiration (PET) using the Thornthwaite–Mather model.
• To validate the PET estimates using ground-based pan evaporation data from the Meteorological Station (MS), Pusa.
• To apply statistical validation techniques (Root Mean Square Error, Mean Error, Pearson Correlation Coefficient, and Bias) to assess and adjust biases in satellite-derived PET estimates.

Study Configuration

• Spatial Scale: Samastipur district, Bihar, India (approximately 2,904 km²), divided into 67 grid cells (8 km × 8 km). GLDAS-2.1 Noah LST product at 0.25° × 0.25° spatial resolution.
• Temporal Scale: 21 years (2000–2020), monthly timescale.

Methodology and Data

• Models used:
  • Thornthwaite–Mather model (for PET estimation)
  • Linear scaling technique (for bias correction)
  • Inverse Distance Weighting (IDW) interpolation (for spatial distribution)
  • Mann–Kendall test and Sen’s slope estimator (for trend analysis)
• Data sources:
  • Satellite: Global Land Data Assimilation System (GLDAS-2.1) Noah Land Surface Model L4 product (Land Surface Temperature, LST) from NASA Earth Data portal.
  • Observation: Ground-based meteorological data (maximum and minimum temperatures, pan evaporation, sunshine hours) from the Meteorological Station (MS) of Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa.

Main Results

• Bias-adjusted GLDAS-derived LST showed improved agreement with observed ground temperature, increasing the R² value from 0.89 to 0.96.
• Estimated PET values at 67 grid points showed a strong correlation (R² = 0.90) with reference evapotranspiration (ET₀) recorded at MS, Pusa.
• The mean monthly PET ranged from a minimum of 5.5 mm in January to a maximum of 139.1 mm in May and 120.7 mm in June.
• Trend analysis using the Mann–Kendall test and Sen’s slope estimator revealed no statistically significant monthly, seasonal, or annual changes in PET over 21 years at MS Pusa, indicating overall stability despite minor non-significant fluctuations.
• Monthly mean temperature trends at MS Pusa showed a significant decreasing trend in January (Z = −2.0232, p = 0.0431, slope = –0.0663 °C/year) and significant warming trends in September (Z = 2.0836, p = 0.0372, slope = 0.0951 °C/year) and November (Z = 3.1707, p = 0.0015, slope = 0.0720 °C/year).

Contributions

• Provides an efficient and scalable framework for long-term PET estimation in data-scarce agricultural regions by integrating satellite-derived LST with the Thornthwaite–Mather model.
• Enhances the reliability of remote sensing-based agro-hydrological assessments through rigorous validation and bias correction of satellite data.
• Offers valuable inputs for agricultural decision-making, optimizing irrigation scheduling, crop calendars, and water-use efficiency, particularly at the policy-relevant district level in India.
• Contributes to the development of resilient and sustainable agricultural planning frameworks in data-scarce regions.

Funding

• Deanship of Scientific Research, King Saud University (through the Vice Deanship of Scientific Research Chairs; Research Chair of Prince Sultan Bin Abdulaziz International Prize for Water).
• Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur, Bihar, India.

Citation

@article{Rajesh2025Satellitebased,
  author = {Rajesh, G. M. and Prasad, S. and Vishwakarma, Dinesh Kumar and Kumar, Rohitashw and Singh, Sudhir Kumar and Dewidar, Ahmed Z. and Othman, Mohamed I. A. and Mattar, Mohamed A.},
  title = {Satellite-based estimation of potential evapotranspiration using the Thornthwaite–Mather model for sub-regional water resource assessment},
  journal = {International Journal of Environmental Science and Technology},
  year = {2025},
  doi = {10.1007/s13762-025-06914-3},
  url = {https://doi.org/10.1007/s13762-025-06914-3}
}