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United States Department of Agriculture

Agricultural Research Service

Research Project: AGRICULTURAL LAND MANAGEMENT TO OPTIMIZE PRODUCTIVITY AND NATURAL RESOURCE CONSERVATION AT FARM AND WATERSHED SCALES

Location: Great Plains Agroclimate and Natural Resources Research Unit

Title: Integration of energy balance ET and SWATmf models

Authors
item Guzman, Jorge
item Gowda, Prasanna
item Moriasi, Daniel
item Steiner, Jean
item Starks, Patrick

Submitted to: Transactions of the ASABE
Publication Type: Abstract Only
Publication Acceptance Date: March 11, 2013
Publication Date: N/A

Interpretive Summary: Abstract only

Technical Abstract: Hydrologic response at the watershed scale results from coupled processes occurring at local and global scales in the earth’s atmosphere, surface and subsurface domains. In agricultural watersheds, evapotranspiration (ET) may account for a major portion of the hydrologic water budget. Therefore, accurate estimation of ET is required to improve estimations of surface and subsurface water fluxes. However, in most watershed modeling studies limited or no verification of predicted ET accuracy is reported. Recent advances in energy balance based ET (EB_ET) algorithms made it possible to estimate ET at field to global scales with improved accuracy. This provides us with an opportunity to use remote sensing derived ET as a model input to decrease the uncertainty associated in hydrologic simulation of distributed water fluxes at the watershed scale. This paper presents an integration of five EB_ET algorithms and the recently coupled SWAT-MODFLOW (SWATmf) model to better estimate hydrologic budget and distributed aquifer recharge at a daily time step. Data from the Fort Cobb Reservoir Experimental Watershed (FCREW), located in southwest Oklahoma, was used to build the models. Measured groundwater levels from the underlying Rush Spring aquifer and flow data at daily time-step from five USGS stream gauge stations within the FCREW were used to evaluate the integrated models. Distributed recharge for the period 2010-2012 estimated using the Penman-Monteith and EB_ET models were compared. Results from this study will be presented and discussed.

Last Modified: 8/27/2014
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