High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets

Study region: Jucar River System (Spain) and Sicily Island (Italy). Study focus: Penman-Monteith crop reference evapotranspiration (PM-ETo) is critical for irrigation planning and hydrological modeling. Its estimation typically requires dense agricultural weather networks with automated stations. Al...

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Main Authors: Alberto Garcia-Prats, Juan Manuel Carricondo-Antón, Matteo Ippolito, Dario De Caro, Miguel Angel Jiménez-Bello, Juan Manzano-Juárez, Manuel Pulido-Velazquez
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Journal of Hydrology: Regional Studies
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Online Access:http://www.sciencedirect.com/science/article/pii/S2214581825003568
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author Alberto Garcia-Prats
Juan Manuel Carricondo-Antón
Matteo Ippolito
Dario De Caro
Miguel Angel Jiménez-Bello
Juan Manzano-Juárez
Manuel Pulido-Velazquez
author_facet Alberto Garcia-Prats
Juan Manuel Carricondo-Antón
Matteo Ippolito
Dario De Caro
Miguel Angel Jiménez-Bello
Juan Manzano-Juárez
Manuel Pulido-Velazquez
author_sort Alberto Garcia-Prats
collection DOAJ
description Study region: Jucar River System (Spain) and Sicily Island (Italy). Study focus: Penman-Monteith crop reference evapotranspiration (PM-ETo) is critical for irrigation planning and hydrological modeling. Its estimation typically requires dense agricultural weather networks with automated stations. Alternatively, reanalysis datasets like ERA5-Land and AgERA5 offer spatially comprehensive data, but their resolution is often insufficient. Spatial interpolation techniques are thus required to estimate PM-ETo at unsampled locations. This study applied the DRI (Dynamic Regression-Based Interpolation) algorithm to generate high-resolution (100 m) PM-ETo maps for both regions using three data sources: meteorological station records and ERA5-Land and AgERA5 reanalysis products. The performance of AgERA5 for PM-ETo estimation was also assessed. Additionally, PM-ETo interpolated maps from the three sources were compared. New hydrological insights for the region: AgERA5, a bias-corrected downscaling of ERA5, effectively removed bias in Sicily when compared to in situ data, but not in the Jucar system. Nonetheless, AgERA5 outperformed ERA5-Land in both regions for PM-ETo estimation. Following interpolation, the resulting maps retained the same biases identified in the original datasets and preserved the frequency distributions of ground-truth maps. This indicates that the interpolation method does not distort the underlying meteorological fields between stations. The proposed approach offers a valuable tool for practitioners and modelers, enabling the generation of high-resolution, accurate, and practical PM-ETo maps to support irrigation planning and hydrological applications.
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spelling doaj-art-926a5a5e2bae44e5aa09b403393869272025-08-20T03:25:52ZengElsevierJournal of Hydrology: Regional Studies2214-58182025-08-016010253110.1016/j.ejrh.2025.102531High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasetsAlberto Garcia-Prats0Juan Manuel Carricondo-Antón1Matteo Ippolito2Dario De Caro3Miguel Angel Jiménez-Bello4Juan Manzano-Juárez5Manuel Pulido-Velazquez6Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de vera s/n, Valencia 46022, Spain; Correspondig author.Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de vera s/n, Valencia 46022, SpainDepartment of Engineering, Università degli Studi di Palermo, Viale delle Scienze 12, Ed. 8, Palermo 90128, ItalyDepartment of Engineering, Università degli Studi di Palermo, Viale delle Scienze 12, Ed. 8, Palermo 90128, ItalyResearch Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de vera s/n, Valencia 46022, SpainCentro Valenciano de Estudios sobre el Riego (CVER), Universitat Politècnica de València, Camino de vera s/n, Valencia 46022, SpainResearch Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de vera s/n, Valencia 46022, SpainStudy region: Jucar River System (Spain) and Sicily Island (Italy). Study focus: Penman-Monteith crop reference evapotranspiration (PM-ETo) is critical for irrigation planning and hydrological modeling. Its estimation typically requires dense agricultural weather networks with automated stations. Alternatively, reanalysis datasets like ERA5-Land and AgERA5 offer spatially comprehensive data, but their resolution is often insufficient. Spatial interpolation techniques are thus required to estimate PM-ETo at unsampled locations. This study applied the DRI (Dynamic Regression-Based Interpolation) algorithm to generate high-resolution (100 m) PM-ETo maps for both regions using three data sources: meteorological station records and ERA5-Land and AgERA5 reanalysis products. The performance of AgERA5 for PM-ETo estimation was also assessed. Additionally, PM-ETo interpolated maps from the three sources were compared. New hydrological insights for the region: AgERA5, a bias-corrected downscaling of ERA5, effectively removed bias in Sicily when compared to in situ data, but not in the Jucar system. Nonetheless, AgERA5 outperformed ERA5-Land in both regions for PM-ETo estimation. Following interpolation, the resulting maps retained the same biases identified in the original datasets and preserved the frequency distributions of ground-truth maps. This indicates that the interpolation method does not distort the underlying meteorological fields between stations. The proposed approach offers a valuable tool for practitioners and modelers, enabling the generation of high-resolution, accurate, and practical PM-ETo maps to support irrigation planning and hydrological applications.http://www.sciencedirect.com/science/article/pii/S2214581825003568Penman-MonteithCrop reference evapotranspirationERA5L and AgERA5Spatial interpolation
spellingShingle Alberto Garcia-Prats
Juan Manuel Carricondo-Antón
Matteo Ippolito
Dario De Caro
Miguel Angel Jiménez-Bello
Juan Manzano-Juárez
Manuel Pulido-Velazquez
High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets
Journal of Hydrology: Regional Studies
Penman-Monteith
Crop reference evapotranspiration
ERA5L and AgERA5
Spatial interpolation
title High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets
title_full High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets
title_fullStr High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets
title_full_unstemmed High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets
title_short High-resolution spatially interpolated FAO Penman-Monteith crop reference evapotranspiration maps of Sicily Island (Italy) and Jucar River system (Spain) using AgERA5 and ERA5-Land reanalysis datasets
title_sort high resolution spatially interpolated fao penman monteith crop reference evapotranspiration maps of sicily island italy and jucar river system spain using agera5 and era5 land reanalysis datasets
topic Penman-Monteith
Crop reference evapotranspiration
ERA5L and AgERA5
Spatial interpolation
url http://www.sciencedirect.com/science/article/pii/S2214581825003568
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