Reference evapotranspiration estimation using reanalysis and WaPOR products in dryland Croplands

Area of Science:

• Hydrology and Water Resources Management
• Agricultural Meteorology
• Remote Sensing and Geospatial Analysis

Background:

• Accurate reference evapotranspiration (ET_o) is vital for crop water needs, but ground station data is often limited in dryland croplands.
• Existing meteorological datasets may not accurately represent conditions in agricultural areas, impacting ET_o estimation.
• The scarcity of agrometeorological stations necessitates evaluating alternative data sources for reliable ET_o calculations.

Purpose of the Study:

• To assess the effectiveness of ERA5, ERA5-Land, and Water Productivity Open-access portal (WaPOR) datasets for estimating ET_o in cropland areas.
• To compare the accuracy of these datasets against ground-based ET_o measurements using statistical metrics.
• To identify the most suitable data source for ET_o estimation across different topographical conditions within a basin.

Main Methods:

• Utilized European Space Agency (ESA) land use/land cover (LULC) data to identify cropland sites representative of agrometeorological stations.
• Collected data from 2009 to 2022 and applied the FAO-Penman-Monteith method for daily and monthly ET_o estimation.
• Evaluated dataset performance using normalized root mean squared error (nRMSE) and relative mean bias error (rMBE) against ground truth.

Main Results:

• ERA5 demonstrated superior overall performance in estimating ET_o compared to ERA5-Land and WaPOR.
• WaPOR outperformed ERA5 and ERA5-Land in high-altitude areas with complex topography.
• No single dataset provided consistently accurate ET_o estimates across all evaluated stations, indicating the need for data fusion.

Conclusions:

• Combining the best-performing data sources offers improved ET_o accuracy over using a single dataset, especially in data-scarce regions.
• Findings support enhanced irrigation scheduling and large-scale water resource management, particularly in dryland agricultural environments.
• The study provides valuable insights for optimizing water use efficiency through improved ET_o estimation methodologies.