Garcia-Prats Alberto, Carricondo-Antón Juan Manuel, Ippolito Matteo, De Caro Dario, Jiménez-Bello Miguel Angel, Manzano-Juárez Juan, Pulido-Velazquez Manuel
Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Camino de vera s/n, Valencia 46022, Spain.
Department of Engineering, Università degli Studi di Palermo, Viale delle Scienze 12, Ed. 8, Palermo 90128, Italy.
J Hydrol Reg Stud. 2025 Aug;60:102531. doi: 10.1016/j.ejrh.2025.102531.
Jucar River System (Spain) and Sicily Island (Italy).
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.
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.
胡卡尔河水系(西班牙)和西西里岛(意大利)。
彭曼 - 蒙特斯作物参考蒸散量(PM - ETo)对于灌溉规划和水文建模至关重要。其估算通常需要配备自动气象站的密集农业气象网络。另外,像ERA5 - Land和AgERA5这样的再分析数据集提供了空间上全面的数据,但其分辨率往往不足。因此需要空间插值技术来估算未采样地点的PM - ETo。本研究应用基于动态回归的插值(DRI)算法,使用三种数据源(气象站记录以及ERA5 - Land和AgERA5再分析产品)为两个区域生成高分辨率(100米)的PM - ETo地图。还评估了AgERA5在PM - ETo估算方面的性能。此外,对来自这三种数据源的PM - ETo插值地图进行了比较。
AgERA5是ERA5经偏差校正后的降尺度数据,与原位数据相比,在西西里岛能有效消除偏差,但在胡卡尔河水系则不行。尽管如此,在两个区域的PM - ETo估算方面,AgERA5的表现均优于ERA5 - Land。插值后,生成的地图保留了原始数据集中识别出的相同偏差,并保留了地面真值地图的频率分布。这表明插值方法不会扭曲各站点之间的基础气象场。所提出的方法为从业者和建模人员提供了一个有价值的工具,能够生成高分辨率、准确且实用的PM - ETo地图,以支持灌溉规划和水文应用。