A new rigorous assessment of remote sensing tool accuracy to support satellite-based water management

Sustainable water management is a growing 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 transpiration of plants, at the level of individual fields.

This tool has the potential to revolutionize water management, enabling operational monitoring of water use at a field scale, and a new study provides an in-depth analysis of the accuracy of OpenET data for various crops and types of natural land cover.

In the study, published in Natural waterDRI scientists led a large team of researchers in a comparison of OpenET data with evapotranspiration data produced by 152 ground-based micrometeorological stations known as eddy covariance flux towers.

The researchers found that OpenET data is very accurate for assessing evapotranspiration in agricultural settings, particularly for annual crops like wheat, corn, soybeans and rice. OpenET’s results for these crops were particularly robust 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 scale and implications of using the data for water resources management,” said John Volk , Ph.D., lead author of the study and assistant. researcher and software engineer at DRI. “Many groups want to know what error rates are expected on agricultural land, so that’s the main question we wanted to address in this article.”

Eddy covariance stations consist of instruments and techniques to calculate the flux of trace gases, such as water vapor, from the ground surface. They offer one of the best methods for quantifying ground-based evapotranspiration, Volk says, which allowed researchers to compare ground-based observations with those provided by satellites.

Data from each station was compared to the OpenET model ensemble, which combines six different Landsat-based models to produce an average, as well as to data from each individual model. Next, stations were grouped by land cover type and climate zone to assess how OpenET data accuracy changed based on these variables.

“I was impressed with the level of performance of the OpenET system,” Volk said. “It’s quite surprising how well the models worked and how well they adapted to each other at agricultural sites, especially during the peak growing season when water demand is highest. “

For annual crops, OpenET data for months, growing season and annual evapotranspiration had an average error rate of around 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 the peak growing season, highlighting the usefulness of these data. Accuracy for orchards was more variable (17%), which could be related to how shadows affect satellite data for taller vegetation, the authors say.

OpenET data can also be used to monitor evapotranspiration in natural ecosystems and error rates for most natural land cover types were less than 1 mm per day at monthly or annual time steps. However, ET rates are generally lower for these ecosystems, resulting in higher relative error rates in these environments than in croplands, and vary from 35% for forests to 50% for shrublands. . Although relative errors are higher for natural ecosystems, ET data remain useful as indicators of the impacts of drought, vegetation water stress, and water availability.

“Evapotranspiration is one of the most difficult hydrological fluxes to measure, and to think that we are quantifying this flux from space with comparable or better accuracy to ground weather stations and meter data for agricultural land is truly remarkable,” said Justin, co-author of the study. Huntington, Ph.D., research professor at DRI.

“The combined use of the Landsat satellite archive with the new cloud computing resources of Google Earth Engine has been essential, as has our collaboration between different research groups and the use of multiple models to better understand the strengths and weaknesses of the models 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 explored in the Colorado River Basin.

The study notes that while all OpenET models can be improved, the results show the remarkable progress made 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, on-the-ground data on water use,” said Maurice Hall, OpenET Director and Senior Advisor, Resilient Water Systems to climate, Environmental Defense Fund. “This study helps confirm the critical role OpenET plays in providing a more granular and dynamic picture of water use, which can significantly 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 where water supplies are highly stressed and variable. »