Nature Water · 2024 · 163 citations · 57 references
Natural SciencesEarth SciencesHydrologyCrop SensingEcohydrologyRemote SensingEvapotranspiration EstimationEvapotranspiration ModelingLand Surface ModelingAccuracyEddy Covariance MeasurementsEvapotranspirationFlux Tower ValidationMean Absolute ErrorRemote Sensing Of EvapotranspirationRemote Sensing-based Evapotranspiration
Abstract Remotely sensed evapotranspiration (ET) data offer strong potential to support data-driven approaches for sustainable water management. However, practitioners require robust and rigorous accuracy assessments of such data. The OpenET system, which includes an ensemble of six remote sensing models, was developed to increase access to field-scale (30 m) ET data for the contiguous United States. Here we compare OpenET outputs against data from 152 in situ stations, primarily eddy covariance flux towers, deployed across the contiguous United States. Mean absolute error at cropland sites for the OpenET ensemble value is 15.8 mm per month (17% of mean observed ET), mean bias error is −5.3 mm per month (6%) and r 2 is 0.9. Results for shrublands and forested sites show higher inter-model variability and lower accuracy relative to croplands. High accuracy and multi-model convergence across croplands demonstrate the utility of a model ensemble approach, and enhance confidence among ET data practitioners, including the agricultural water resource management community.
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Noel Gorelick, M. Hancher, Mike Dixon et al. · Remote Sensing of Environment · 2017 · 14K citations · Full text
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