Ankela et al. (2026) Spatiotemporal assessment of maize evapotranspiration and surface energy fluxes under varying irrigation regimes using UAV based METRIC

Identification

• Journal: Scientific Reports
• Year: 2026
• Authors: Charan Babu Ankela, L Neelima, Chandrasekar K, Nidhi Misra, Avil Kumar K, Aminullah Noorzai
• DOI: 10.1038/s41598-025-33916-5

Research Groups

• Professor Jayashankar Telangana Agricultural University (PJTAU), Hyderabad, India.
• National Remote Sensing Centre (NRSC), ISRO, Hyderabad, India.
• Sayed Jamaluddin Afghani University, Afghanistan.

Short Summary

This study evaluates the effectiveness of the METRIC model adapted for high-resolution UAV imagery to estimate maize evapotranspiration (ET) and surface energy fluxes under different irrigation regimes. The results demonstrate that UAV-based METRIC accurately captures irrigation-induced variability in ET and energy partitioning, showing strong agreement with ground-based validation methods.

Objective

• To investigate the capability of a UAV-based METRIC model (METRIC-UAV) to capture spatiotemporal variations in evapotranspiration and surface energy dynamics of maize under two distinct irrigation levels (20% and 40% depletion of available soil moisture).

Study Configuration

• Spatial Scale: Field-scale experiment conducted at the Maize Research Centre, Hyderabad, India (14.14 ha area), using UAV imagery with resolutions of 0.05 m (multispectral) and 0.33 m (thermal).
• Temporal Scale: Rabi (winter) cropping season 2022–2023 (November to March), with seven UAV flight campaigns coinciding with Landsat-8 overpasses.

Methodology and Data

• Models used: METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) adapted for UAV data; FAO Penman-Monteith (PM) combination equation; Soil Water Balance (SWB) method.
• Data sources:
  • UAV: Trinity F90+ fixed-wing UAV equipped with a MicaSense Altum PT sensor (multispectral and thermal).
  • Satellite: Landsat-8 imagery (used for atmospheric emissivity reference).
  • Ground-based: Eddy Covariance (EC) flux tower (meteorological data), LAI-2200c Plant canopy analyzer, porometer (stomatal resistance), and gypsum blocks (soil moisture monitoring).

Main Results

• Irrigation Impact: The 20% DASM treatment (400 mm irrigation) resulted in a 1.7 °C lower land surface temperature (LST), a 16.5% higher NDVI, and an 11% increase in daily actual evapotranspiration (ETa) compared to the 40% DASM treatment (316 mm).
• Energy Fluxes: Under water stress (40% DASM), net radiation (Rn) decreased while a larger proportion of energy was partitioned into sensible heat (H) and soil heat (G) fluxes. In contrast, latent heat (LE) dominated energy partitioning in the well-watered 20% DASM treatment.
• ETa Quantification: Seasonal ETa was estimated at 333 mm for the 20% DASM treatment and 288 mm for the 40% DASM treatment.
• Model Validation: METRIC-UAV daily ETa estimates showed strong agreement with the Penman-Monteith method (R² = 0.84; RMSE = 0.22 mm day⁻¹; MAPE = 6.1%). Agreement with the soil water balance method was within ± 3%.
• Yield: The 20% DASM treatment achieved a grain yield of 6.3 t ha⁻¹, compared to 5.4 t ha⁻¹ for the 40% DASM treatment.

Contributions

• High-Resolution Mapping: Successfully adapted the METRIC model for sub-decimeter UAV imagery, allowing for the detection of ET variability across individual crop rows, bunds, and weed patches.
• Precision Irrigation Support: Provides a validated framework for using cost-effective UAV platforms to monitor field-scale crop water requirements and energy dynamics, overcoming the spatial and temporal limitations of satellite data.
• Methodological Validation: Demonstrates the internal energy balance consistency of the METRIC-UAV approach compared to Eddy Covariance and traditional empirical methods.

Funding

• National Hydrology Project (NHP).
• National Remote Sensing Centre (NRSC), ISRO, Hyderabad.
• Ministry of Jal Shakti, Government of India.

Citation

@article{Ankela2026Spatiotemporal,
  author = {Ankela, Charan Babu and Neelima, L and K, Chandrasekar and Misra, Nidhi and K, Avil Kumar and Noorzai, Aminullah},
  title = {Spatiotemporal assessment of maize evapotranspiration and surface energy fluxes under varying irrigation regimes using UAV based METRIC},
  journal = {Scientific Reports},
  year = {2026},
  doi = {10.1038/s41598-025-33916-5},
  url = {https://doi.org/10.1038/s41598-025-33916-5}
}

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