Huanuqueño-Murillo et al. (2025) Comparative Analysis of Evapotranspiration from METRIC (Landsat 8/9), AquaCrop, and FAO-56 in a Hyper-Arid Olive Orchard, Southern Peru

Identification

• Journal: Agriculture
• Year: 2025
• Date: 2025-11-25
• Authors: José Huanuqueño-Murillo, David Quispe-Tito, Javier Quille-Mamani, Germán Huayna, Carolina Cruz-Rodríguez, Bertha Silvana Vera Barrios, Lía Ramos-Fernández, Edwin Pino-Vargas
• DOI: 10.3390/agriculture15232423

Research Groups

• Departament of Water Resources, National Agrarian University La Molina, Lima, Peru
• Geo-Environmental Cartography and Remote Sensing Group (CGAT), Universitat Politècnica de València, Valencia, Spain
• Departament of Civil Engineering, Jorge Basadre Grohmann National University, Tacna, Peru
• Doctoral Program in Water Resources, Jorge Basadre Grohmann National University, Tacna, Peru
• Faculty of Mining Engineering, National University of Moquegua, Moquegua, Peru
• Doctoral Program in Water Resources, Graduate School, National Agrarian University La Molina, Lima, Peru

Short Summary

This study compared evapotranspiration (ET) estimates from METRIC (Landsat 8/9), AquaCrop, and FAO-56 in a hyper-arid olive orchard in southern Peru over two contrasting seasons, finding that the integrated METRIC-AquaCrop framework provides robust, spatially explicit, and temporally continuous ET data crucial for precision irrigation management.

Objective

• To analyze and compare three evapotranspiration modeling approaches (METRIC, AquaCrop, FAO-56) in a hyper-arid olive orchard in Tacna, Peru.
• To test the hypothesis that combining satellite-based energy-balance modeling (METRIC) with process-based soil-water balance simulations (AquaCrop) yields a more physically consistent and operationally relevant characterization of ET dynamics than either model alone, thereby strengthening the scientific basis for precision irrigation, water-use optimization, and sustainable orchard management in hyper-arid environments.

Study Configuration

• Spatial Scale: Experimental olive orchard covering 8 hectares; METRIC ET maps at 30 meter resolution; PlanetScope canopy cover at 3 meter spatial resolution.
• Temporal Scale: Two contrasting agricultural campaigns (2021–2022 high-yield and 2023–2024 water-limited); 16 cloud-free Landsat 8/9 scenes; meteorological data recorded at 30 minute intervals and aggregated daily/monthly.

Methodology and Data

• Models used: METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) energy-balance model; AquaCrop (FAO Crop Water Productivity Model) process-based model; FAO-56 Penman–Monteith equation.
• Data sources:
  • Satellite: Landsat 8 OLI/TIRS and Landsat 9 OLI-2/TIRS-2 imagery (Collection 2, Level 2) for surface reflectance, albedo, emissivity, land surface temperature (LST), NDVI, SAVI, and LAI.
  • Satellite: PlanetScope scenes (3 meter spatial resolution) for canopy cover (CC) estimation.
  • Observation (in situ): Davis Vantage Pro2 automatic weather station for air temperature, relative humidity, solar radiation, and wind speed.
  • Observation (field): Soil characterization (texture, bulk density, field capacity, permanent wilting point), phenological observations, canopy cover (CC) estimation, irrigation volume monitoring, and yield assessment.
  • Platform: Google Earth Engine (GEE) for METRIC implementation and preprocessing.

Main Results

• METRIC detected intra-parcel ET heterogeneity and seasonal dynamics, with local peaks of approximately 6–7 mm d⁻¹ in dense central blocks and orchard-mean values up to 4.25 ± 1.76 mm d⁻¹.
• During the high-yield 2021–2022 season, ET METRIC and ET AQUACROP showed excellent agreement (R² = 0.94; RMSE = 0.21 mm d⁻¹; bias μ = 0.11 mm d⁻¹).
• During the high-yield 2021–2022 season, FAO-56 consistently underestimated ET compared to METRIC (R² = 0.88; RMSE = 0.82 mm d⁻¹; bias μ = 0.81 mm d⁻¹).
• Under water-limited 2023–2024 conditions, model correspondence remained strong but attenuated (ET METRIC –ET AQUACROP: R² = 0.75; RMSE = 0.64 mm d⁻¹; ET METRIC –ET FAO-56: R² = 0.95; RMSE = 0.59 mm d⁻¹).
• METRIC exhibited a persistent positive bias (μ = 0.43–0.56 mm d⁻¹) under water-limited conditions, attributed to localized soil evaporation and micro-advection.
• AquaCrop calibration against observed green canopy cover showed high agreement (r = 0.82 and 0.78; RMSE = 10.5 and 9.8 percentage points; NSE = 0.47 and 0.81).

Contributions

• Developed an integrated framework combining satellite-based energy-balance modeling (METRIC) with process-based soil-water balance simulations (AquaCrop) for robust ET estimation in hyper-arid perennial systems.
• Provided high-resolution spatial diagnostics of canopy stress (METRIC) and daily continuity with explicit evaporation/transpiration (E/Tr) partitioning (AquaCrop), enabling a coherent multiscale assessment of ET.
• Demonstrated the operational relevance of the integrated framework for monitoring water use and supporting deficit-irrigation optimization in hyper-arid olive systems.
• Quantified the limitations of the empirical FAO-56 method in capturing ET dynamics under hyper-arid orchard conditions, especially compared to physically-based models.

Funding

• Vice-Rectorate for Research of the Jorge Basadre Grohmann National University (UNJBG) through the canon and mining royalties funds.
• Project: “Use of remote sensors to improve irrigation management in olive trees (Olea europaea L.) and confront climate change in arid zones” (Rectoral Resolution No. 11174-2023-UNJBG).
• Water Research Group (H2O-UNJBG).

Citation

@article{HuanuqueñoMurillo2025Comparative,
  author = {Huanuqueño-Murillo, José and Quispe-Tito, David and Quille-Mamani, Javier and Huayna, Germán and Cruz-Rodríguez, Carolina and Barrios, Bertha Silvana Vera and Ramos-Fernández, Lía and Pino-Vargas, Edwin},
  title = {Comparative Analysis of Evapotranspiration from METRIC (Landsat 8/9), AquaCrop, and FAO-56 in a Hyper-Arid Olive Orchard, Southern Peru},
  journal = {Agriculture},
  year = {2025},
  doi = {10.3390/agriculture15232423},
  url = {https://doi.org/10.3390/agriculture15232423}
}