Accurate estimation of the reference evapotranspiration (ETo) is crucial for determining crop water requirements. However, the lack of appropriate weather stations representing croplands, particularly in drylands, may adversely influence the accuracy of ETo estimates. To overcome this issue, a promising approach is to use meteorological stations in cropland areas to collect weather data that are representative of actual conditions. However, the number of agrometeorological stations in these areas is limited. Therefore, this study aims to assess the effectiveness of three datasets, including ERA5 and ERA5-Land, and WaPOR (Water Productivity Open-access portal), for estimating ETo in cropland areas on a basin scale. The land use/land cover (LULC) of the European Space Agency (ESA) was used to identify the sites resembling agrometeorological stations. Data were collected from 2009 to 2022, and the FAO-Penman-Monteith method was used to estimate daily and monthly ETo. The accuracy and reliability of ETo estimates with the three datasets were evaluated by comparing them with ETo estimated by ground measurements. Statistical analysis metrics, normalized root mean squared error (nRMSE), and relative mean bias error (rMBE) were used to assess the performance of the datasets. This study highlights that ERA5 exhibited superior overall performance compared to other datasets in estimating ETo. However, WaPOR performed better at high-altitude stations with inhomogeneous topography than ECMWF reanalysis (i.e., ERA5 and ERA5-L). Thus, none of the datasets could provide accurate ETo estimates for all the stations within the basin. Therefore, applying the best-performing data source yielded better results than using a single dataset. These findings are valuable for improving irrigation scheduling and water management practices on a large scale, particularly in regions facing data scarcity challenges.
Keywords: Agrometeorological station; Gridded dataset; Land use/land cover; Top-performing dataset.
© 2024 The Authors.