Evapotranspiration (ET), and in particular Reference Evapotranspiration (ET0), is essential for agricultural planning, irrigation management, and water resource allocation—especially in regions facing water scarcity and limited observational data. While ground-based ET0 is typically estimated using the FAO Penman-Monteith method, satellite-derived products such as MOD16 offer broader spatial coverage, although with conceptual and methodological differences. MOD16 provides Potential Evapotranspiration (PET) estimates, which, unlike ET0, depend on local biome characteristics and are not standardized to a reference surface. This study investigates whether the PET data from the MOD16A2GF product (version 6.1) can be adapted for ET0 estimation in Piemonte (NW Italy), a region characterized by diverse climates and topographies. We compared PET data from 2010 to 2022 with ground-based ET0 and applied a bias-correction method using linear regression models calibrated on local meteorological time series. The corrected dataset (ET0) shows significantly improved agreement with ground-based ET0, reducing the Mean Absolute Error from 10.06 mm/8 d to 2.48 mm/8 d, a 75% improvement. This correction proved robust across the region and particularly effective during the summer, when accurate ET0 estimation is critical for crop irrigation. Our results suggest that, with appropriate local calibration, MOD16A2GF PET data can serve as a practical surrogate for ET0 in data-scarce environments. Future research should focus on exploring the impact of additional factors, such as altitude and land cover variability, to further refine the accuracy of satellite-derived ET0 estimates and improve their applicability in diverse climatic and topographical conditions.

Aligning Evapotranspiration from MOD16A2.061 Product to Ground Estimates in Piemonte (NW Italy): an analysis of temporal and spatial biases

Ronco, Edoardo;Borgogno Mondino, Enrico Corrado
2025-01-01

Abstract

Evapotranspiration (ET), and in particular Reference Evapotranspiration (ET0), is essential for agricultural planning, irrigation management, and water resource allocation—especially in regions facing water scarcity and limited observational data. While ground-based ET0 is typically estimated using the FAO Penman-Monteith method, satellite-derived products such as MOD16 offer broader spatial coverage, although with conceptual and methodological differences. MOD16 provides Potential Evapotranspiration (PET) estimates, which, unlike ET0, depend on local biome characteristics and are not standardized to a reference surface. This study investigates whether the PET data from the MOD16A2GF product (version 6.1) can be adapted for ET0 estimation in Piemonte (NW Italy), a region characterized by diverse climates and topographies. We compared PET data from 2010 to 2022 with ground-based ET0 and applied a bias-correction method using linear regression models calibrated on local meteorological time series. The corrected dataset (ET0) shows significantly improved agreement with ground-based ET0, reducing the Mean Absolute Error from 10.06 mm/8 d to 2.48 mm/8 d, a 75% improvement. This correction proved robust across the region and particularly effective during the summer, when accurate ET0 estimation is critical for crop irrigation. Our results suggest that, with appropriate local calibration, MOD16A2GF PET data can serve as a practical surrogate for ET0 in data-scarce environments. Future research should focus on exploring the impact of additional factors, such as altitude and land cover variability, to further refine the accuracy of satellite-derived ET0 estimates and improve their applicability in diverse climatic and topographical conditions.
2025
44th EARSeL Symposium
cze
2025
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
International Society for Photogrammetry and Remote Sensing
XLVIII-M-7-2025
M-7-2025
201
206
Italy; MOD16A2GF; Penman-Monteith; Piemonte; Reference evapotranspiration
Ronco, Edoardo; Borgogno Mondino, Enrico Corrado
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/2139310
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