Document Type

Article

Author ORCID Identifier

Roxana Peña-Amaro  https://orcid.org/0009-0009-9788-5821  

José Huanuqueño-Murillo  https://orcid.org/0009-0003-8511-4524  

Lia Ramos-Fernández  https://orcid.org/0000-0003-3946-7188  

Lena Cruz-Villacorta  https://orcid.org/0000-0003-2493-533X  

Elizabeth Heros-Aguilar  https://orcid.org/0000-0002-0179-3124  

Edwin Pino-Vargas  https://orcid.org/0000-0001-7432-4364  

Alfonso Torres-Rua  https://orcid.org/0000-0002-2238-9550  

Journal/Book Title/Conference

Remote Sensing

Volume

18

Issue

6

Publisher

MDPI AG

Publication Date

3-10-2026

Journal Article Version

Version of Record

First Page

1

Last Page

29

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Abstract

Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily ET and its components under continuous flooding on the arid Peruvian coast during the 2024–2025 season. A network of 24 drainage lysimeters provided an independent observational benchmark (ETlys); to represent the treatment-level response, lysimeter observations were aggregated as the mean across the 24 units for each UAV campaign. Thirteen UAV surveys supplied radiometric surface temperature and biophysical inputs (e.g., NDVI and fractional cover) to derive spatially explicit ET, while AquaCrop provided continuous daily simulations between flight dates. Direct lysimeter-based validation indicated high agreement for AquaCrop (R2 = 0.85; RMSE = 0.26 mm d−1; MBE = 0.01 mm d−1) and moderate agreement for UAV–TSEB (R2 = 0.66; RMSE = 0.81 mm d−1; MBE = 1.01 mm d−1). Model intercomparison further showed consistent temporal dynamics of ET (R2 = 0.70; RMSE = 1.35 mm d−1) and robust partitioning of crop transpiration (R2 = 0.79; RMSE = 0.99 mm d−1) and soil evaporation (R2 = 0.76; RMSE = 1.03 mm d−1) while revealing a systematic divergence under near-complete canopy cover: AquaCrop tended to suppress evaporation, whereas UAV–TSEB detected residual evaporation from the flooded surface. Overall, the results highlight the complementarity of both approaches—UAV–TSEB as a spatial diagnostic tool and AquaCrop as a temporally continuous simulator—providing a robust framework for ET monitoring, flux partitioning, and water-use-efficiency assessment in water-scarce rice systems.

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