Rigorous assessment measures accuracy of OpenET’s evapotranspiration data

Jan. 23, 2024
A new study offers a large-scale assessment of the accuracy of OpenET’s satellite-based evapotranspiration measurements.

A new study , published Jan. 15 in Nature Water, scientists assess the accuracy of OpenET data to address regional water sustainability, according to a press release by the Desert Research Institute.

Sustainable water management is an increasing concern in arid regions around the world, and scientists and regulators are turning to remote sensing tools like OpenET to help track and manage water resources. OpenET uses publicly available data produced by NASA and USGS Landsat and other satellite systems to calculate evapotranspiration (ET), or the amount of water lost to the atmosphere through soil evaporation and plant transpiration, at the level of individual fields.

The new study provides a thorough analysis of the accuracy of OpenET data for various crops and natural land cover types. A large team of researchers compared OpenET data to evapotranspiration data produced by 152 ground-based micrometeorological stations known as eddy covariance flux towers.

The researchers found that OpenET data has high accuracy for assessing evapotranspiration in agricultural settings, particularly for annual crops like wheat, corn, soy and rice. OpenET results for these crops were particularly reliable in arid regions like California and the Southwest, supporting the use of this tool to address an ongoing regional water sustainability crisis.

“One of the biggest questions for users of OpenET data is how accurate it is, given the magnitude and implications of the use of the data for water resource management,” said John Volk lead author of the study. “A lot of groups want to know what the expected rates of error are in agricultural lands, so that’s the major question that we wanted to address for this paper.”

The eddy covariance stations consist of instruments and techniques for calculating the flux of trace gases, like water vapor, coming off the land surface. They provided the researchers the opportunity to compare the ground-based observations with those provided by satellites. Each station’s data was compared to the OpenET model ensemble, which combines six different Landsat-based models to produce an average, as well as data from each individual model. Then, the stations were grouped by land cover type and climate zone to assess how the accuracy of OpenET data changes across these variables.

For annual crops, OpenET data for monthly, growing season, and annual evapotranspiration had an average error rate of approximately 10-20%, which is within the targeted range set by OpenET partners such as farmers and water management agencies.

For annual crops growing in Mediterranean climates, monthly error rates were consistently below 10% during peak growing season. Accuracy for orchards was more variable (17%), which could be related to the way that shadows impact satellite data for taller vegetation, the authors say.

OpenET data can also be used for monitoring evapotranspiration in natural ecosystems and error rates for most natural land cover types was less than 1 mm per day at monthly to annual timesteps. However, ET rates are generally lower for these ecosystems, resulting in relative error rates that are higher in these environments than in croplands, and range from 35% for forests to 50% for shrublands.

“Evapotranspiration is one of the hardest hydrologic fluxes to measure, and to think we are quantifying this flux from space with comparable or better accuracy to ground-based weather stations and meter data for agricultural lands is really remarkable,” said study co-author Justin Huntington. “The combined use of the Landsat-satellite archive with new Google Earth Engine cloud computing resources has been key, as has our collaboration across different research groups and use of multiple models to better understand model strengths and weaknesses and identify areas for improvement.”

Future research will focus on natural ecosystems and how OpenET models compare under different agricultural demand management and conservation actions, such as those being explored in the Colorado River Basin.

The study notes that although all OpenET models have room for improvement, the results show the progress achieved in developing fully automated remote sensing techniques for mapping evapotranspiration at large spatial scales and at the resolution of individual fields based on petabytes of Landsat satellite data and new cloud computing resources.

“Farmers and water managers increasingly need accurate, field-level data on water use,” said Maurice Hall, OpenET directo6. “This study helps confirm the vital role OpenET plays in providing a more granular, dynamic picture of water use that can meaningfully inform real-time water decision-making. We look forward to continuing to refine and expand the implementation of OpenET to ensure farmers, ranchers and communities can thrive in a world of highly stressed and variable water supplies.”

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