Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools |
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| Authors: | Jan MH Hendrickx Richard G Allen Al Brower Aaron R Byrd Sung‐ho Hong Fred L Ogden Nawa Raj Pradhan Clarence W Robison David Toll Ricardo Trezza Todd G Umstot John L Wilson |
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| Affiliation: | 1. Department of Earth and Environmental Sciences, New Mexico Tech, Socorro, New Mexico;2. Kimberly Research and Extension Center, University of Idaho, Kimberly, Idaho;3. Water and Environmental Resources Division, U.S. Bureau of Reclamation, Denver, Colorado;4. Engineer Research and Development Center, U.S. Army Corps of Engineers, Vicksburg, Mississippi;5. Department of Geosciences, Murray State University, Murray, Kentucky;6. Water Resources/Environmental Science and Engineering, University of Wyoming, Laramie, Wyoming;7. Hydrological Sciences Lab, NASA Goddard Space Flight Center, Greenbelt, Maryland;8. Daniel B. Stephens and Associates, Inc., Albuquerque, New Mexico |
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| Abstract: | Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite. |
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| Keywords: | soil moisture evapotranspiration
GSSHA
SEBAL
METRIC
DPWM
distributed hydrologic modeling optical/thermal satellite imagery Landsat
MODIS
groundwater recharge water management hydrograph |
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