Search USGS⌕ Search

Geology topics

Thomas Ott

Publications and source records attributed to Thomas Ott.

3 recordsLinked to original sources

Estimating irrigation consumptive use for the conterminous United States: Coupling satellite-sourced estimates of actual evapotranspiration with a national hydrologic model

Irrigation consumptive use is crucial information for water resource management and this information is generally not available for most regional and national assessments. From 2000 to 2020, daily estimates of consumptive use were produced for the conterminous U.S. at the 12-digit hydrologic unit code watershed level. Using the Simplified Surface Energy Balance model within the OpenET tool on Google Earth Engine, actual evapotranspiration estimates were derived from Landsat land surface temperature data. These estimates were mapped to the National Hydrologic Model (NHM) spatial units for irrigated areas defined by the Landsat Irrigation Dataset (LANID). The NHM allows for simultaneous estimation of consumptive use and effective precipitation. Results were compared to the 2015 USGS water use report, revealing annual maximum difference in consumptive use of 37 cm, with an average absolute difference of 13 cm and a bias of 2.7 %. Comparisons to field resolution irrigation withdrawals reported by growers in 4 major irrigation regions across the nation were made using efficiencies reported in the literature. These comparisons resulted in root mean square errors that ranged between 10 and 18 cm per year and biases of −18.2 to 15.8 %. Significant differences in these different reported estimates represent challenges in accurate data availability and inconsistent methods and definitions used in assessments. Annual consumptive use in the U.S. can vary by 37 % due to droughts, particularly in regions more heavily dependent on precipitation. Significant increases in consumptive use were noted over the 20-year period in western states, especially the Colorado River basin from 2010 to 2020, exacerbating water supply declines.

conterminous United States↗

Assessing the accuracy of OpenET satellite-based evapotranspiration data to support water resource and land management applications

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.

Nature Water↗

OpenET: Filling a critical data gap in water management for the western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

western United States↗