Expanding the performance curve of different weather data sources for hydrologic modeling in central Texas: a comparison of ground observations and the Climate Forecast System Reanalysis as watershed model inputs

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Daniel R Fuka1, Amy Collick2, Daniel Auerbach3, Peter J A Kleinman4, Moges Berbero Wagena5, Andrew Sommerlot5, Daren Harmel2, Zachary M Easton1 and Easton Hydrology and Water Quality Simulation Lab, (1)Virginia Polytechnic Institute and State University, Blacksburg, VA, United States, (2)USDA ARS, Pendleton, OR, United States, (3)EPA, DC, United States, (4)USDA-ARS Pasture Systems and Watershed Management Research Unit, University Park, PA, United States, (5)Virginia Tech, Blacksburg, VA, United States
Obtaining location specific representative meteorological data can be difficult and time consuming, even though correctly representing the weather is critical to hydrological modeling and watershed management planning. The Climate Forecast System Reanalysis (CFSR) dataset provides continuous, globally-available records that offer a consistent baseline for assessments of candidate weather data, have produced satisfactory hydrological model performance in some temperate and monsoonal locations, as well as have been demonstrated as a solution for ungaged tropical and semi-tropical montane basins. Taking advantage of exceptionally high rainfall data density in USDA-ARS’s Reisel experimental watershed. We compared model performance under alternative weather inputs: Climate Forecast System Reanalysis (CFSR) records, a standard public weather station dataset available from the Global Historical Climate Network (GHCN), and a the high density research quality dataset available from the USDA-ARS. Results show that utilizing the CFSR precipitation and temperature data to force a watershed model provides stream discharge simulations that are as good as or better than models forced using traditional weather gauging stations available from GHCN, especially when stations are more than 10-km from the watershed. These results further demonstrate that adding CFSR data to the suite of watershed modelling tools provides new opportunities for meeting the challenges of modelling ungauged watersheds and advancing real-time hydrological modelling.