openet_ensemble
The OpenET project aims to make satellite-based estimates of the total amount of water that is transferred from the land surface to the atmosphere through the process of evapotranspiration (ET) available for improved water management (1, 2). OpenET datasets include ET estimates from six different satellite-driven ET models as well as an ensemble product, which is calculated as the mean of the ensemble after filtering and removing outliers using the median absolute deviation approach. All models currently use 30-meter Landsat data to produce ET estimates, and the monthly ET dataset provides data on total ET by month as an equivalent depth of water in millimeters.
Our openet_ensemble evaluation dataset is derived from the OpenET monthly
total ensemble product in Earth Engine. This dataset is designed not to measure
performance on ET estimation directly. Rather, it characterizes performance on
proxying the OpenET model ensemble, given that ensemble approaches are
inherently computationally intensive and challenging to scale and have therefore
historically limited OpenET ensemble coverage. Thus accurate proxy models could
be a more viable means of scaling ensemble results over larger extents.
We construct our openet_ensemble evaluation by first tiling CONUS in 35km grid
cells in the Albers conic projection with EPSG code 5070. For each grid cell, we
select a random month from all possible months mapped in the source OpenET
ensemble product, and sample 2 locations for each of 10 equally spaced 20mm bins
between 0mm and 200mm. Locations with ET values > 200mm were assigned to the
highest bin. We ignore locations where less than 5 models in the ensemble ran,
or the disagreement between the minimum and maximum model estimates exceeded
10mm. To each sample we assigned a valid period of the entire month from which
it was drawn, and a support period ending with the end of the valid period, and
extending 1 year prior: this was chosen to emulate the realistic scenario where
evapotranspiration estimates are desired at the conclusion of a given calendar
month. We selected 300 train points per bin, and allocated the remainder to
test. Our final openet_ensemble evaluation dataset has a total of 3,000
training points and 32,683 test points after pre-processing and spatial
proximity filtering.
License
OpenET Ensemble Monthly Evapotranspiration v2.0 from OpenET, Inc. is licensed under the Creative Commons Attribution 4.0 International License (CC-BY). You may obtain a copy of the CC-BY license at: https://creativecommons.org/licenses/by/4.0/legalcode. You can obtain a copy of the dataset at https://developers.google.com/earth-engine/datasets/catalog/OpenET_ENSEMBLE_CONUS_GRIDMET_MONTHLY_v2_0#description. This version of the dataset is modified as described above.
For the dataset citation, please see (1) in the “References” section below.
References
- F. S. Melton, J. Huntington, R. Grimm, J. Herring, M. Hall, D. Rollison, T. Erickson, R. Allen, M. Anderson, J. B. Fisher, A. Kilic, G. B. Senay, J. Volk, C. Hain, L. Johnson, A. Ruhoff, P. Blankenau, M. Bromley, W. Carrara, B. Daudert, C. Doherty, C. Dunkerly, M. Friedrichs, A. Guzman, G. Halverson, J. Hansen, J. Harding, Y. Kang, D. Ketchum, B. Minor, C. Morton, S. Ortega-Salazar, T. Ott, M. Ozdogan, P. M. ReVelle, M. Schull, C. Wang, Y. Yang, R. G. Anderson, OpenET: Filling a critical data gap in water management for the western United States. J. Am. Water Resour. Assoc. 58, 971–994 (2022).
- J. M. Volk, J. L. Huntington, F. S. Melton, R. Allen, M. Anderson, J. B. Fisher, A. Kilic, A. Ruhoff, G. B. Senay, B. Minor, C. Morton, T. Ott, L. Johnson, B. Comini de Andrade, W. Carrara, C. T. Doherty, C. Dunkerly, M. Friedrichs, A. Guzman, C. Hain, G. Halverson, Y. Kang, K. Knipper, L. Laipelt, S. Ortega-Salazar, C. Pearson, G. E. L. Parrish, A. Purdy, P. ReVelle, T. Wang, Y. Yang, Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications. Nat Water 2, 193–205 (2024).