Veysi Shadman, Nouri Milad, Jabbari Anahita
Soil and Water Research Institute (SWRI), Agriculture Research Extension Education Organization (AREEO), Alborz, Karaj, Iran.
Agriculture Research Extension Education Organization (AREEO), West Azerbaijan, Urmia, Iran.
Heliyon. 2024 Feb 19;10(4):e26531. doi: 10.1016/j.heliyon.2024.e26531. eCollection 2024 Feb 29.
Accurate estimation of the reference evapotranspiration (ET) 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 ET 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 ET 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 ET. The accuracy and reliability of ET estimates with the three datasets were evaluated by comparing them with ET 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 ET. 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 ET 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.
准确估算参考蒸散量（ET）对于确定作物需水量至关重要。然而，缺乏代表农田的合适气象站，尤其是在旱地，可能会对ET估算的准确性产生不利影响。为克服这一问题，一种有前景的方法是利用农田地区的气象站收集代表实际情况的气象数据。然而，这些地区的农业气象站数量有限。因此，本研究旨在评估三个数据集，包括ERA5和ERA5-Land以及WaPOR（水生产率开放获取门户），在流域尺度上估算农田地区ET的有效性。利用欧洲航天局（ESA）的土地利用/土地覆盖（LULC）来识别类似农业气象站的地点。收集了2009年至2022年的数据，并采用FAO-彭曼-蒙特斯方法估算每日和每月的ET。通过将三个数据集估算的ET与地面测量估算的ET进行比较，评估了ET估算的准确性和可靠性。使用统计分析指标、归一化均方根误差（nRMSE）和相对平均偏差误差（rMBE）来评估数据集的性能。本研究强调，在估算ET方面，ERA5与其他数据集相比表现出卓越的整体性能。然而，在地形不均匀的高海拔站点，WaPOR的表现优于欧洲中期天气预报中心的再分析数据（即ERA5和ERA5-L）。因此，没有一个数据集能够为流域内的所有站点提供准确的ET估算。因此，应用表现最佳的数据源比使用单个数据集能产生更好的结果。这些发现对于大规模改进灌溉调度和水资源管理实践具有重要价值，特别是在面临数据稀缺挑战的数据稀缺地区。
