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United States Department of Agriculture

Agricultural Research Service

Research Project: USING REMOTE SENSING & MODELING FOR EVALUATING HYDROLOGIC FLUXES, STATES, & CONSTITUENT TRANSPORT PROCESSES WITHIN AGRICULTURAL LANDSCAPES Title: Examining issues with water quality model configuration

Authors
item Sexton, Aisha -
item Sadeghi, Ali
item McCarty, Gregory
item Lang, Megan -
item Hively, W -
item Shirmohammadi, Adel -

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: March 14, 2011
Publication Date: April 27, 2011
Citation: Sexton, A., Sadeghi, A.M., McCarty, G.W., Lang, M., Hively, W.D., Shirmohammadi, A. 2011. Examining issues with water quality model configuration [abstract]. Abs. 45, BARC Poster Day.

Technical Abstract: Complex watershed–scale, water quality models require a considerable amount of data in order to be properly configured, especially in view of the scarcity of data in many regions due to temporal and economic constraints. In this study, we examined two different input issues incurred while building and calibrating a model of the German Branch watershed using the Soil and Water Assessment Tool (SWAT). The German Branch is a sub-watershed of the Choptank, a benchmark basin of USDA’s Conservation Effects Assessment Project (CEAP). One set-up scenario addressed the issue of accounting for copious drainage ditches within the study area by comparing stream flow estimates derived using a conventional DEM versus a DEM, hand-edited to include drainage ditches in the topography. The second set-up scenario examined the issue of estimating measured sediment loads for time-periods lacking data using sediment rating curves. Results indicated a slight improvement in model performance (a 4% increase in NSE value) to estimate flow during the calibration period and a significant decrease in model performance (15% in NSE value) during the validation period. Sediment rating curves provided good estimates of monthly sediment loads during model calibration period (NSE = 0.62), but strongly underestimated sediment loads during the validation period (NSE = -1.27).

Last Modified: 10/22/2014
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