Stormwater runoff can transport nutrients, sediments, chemicals, and pathogens to surface waterbodies. Managing runoff is crucial to preserving water quality in rapidly developing urban watersheds like those in Northwest Arkansas. A watershed containing the majority of the University of Arkansas campus was designated as the study area because stormwater from it drains into the West Fork of the White River, designated as an impaired waterbody due to siltation. The project objective was to develop methodology to test existing stormwater drainage infrastructure, identify potential areas of improvement, and estimate potentially contaminated runoff by combining two widely used prediction models. The U.S. Department of Agriculture’s Natural Resource Conservation Service’s curve number (CN) method was used to estimate runoff depths and volumes, while a flow-direction model was created that integrated topography, land use, and stormwater drainage infrastructure in a geographic information system. This study combined the CN and flow-direction models in a single geodatabase to develop flow direction/quantity models. Models were developed for 5-, 10-, 25-, 50-, and 100-year floods and varied by the antecedent moisture content. These models predicted flow directions within existing drainage infrastructure and runoff volumes for each flood, and served as a hypothetical flood analysis model. Results showed that between 24,000 m3 (5-year flood) and 60,000 m3 (100-year flood) of runoff would be transported to the West Fork of the White River. The methodology developed and results generated will help stormwater planners visualize localized runoff, and potentially adapt existing drainage networks to accommodate runoff, prevent flooding and erosion, and improve the quality of runoff entering nearby surface waterbodies.
Koehn, Keshia; Scarlat, Christina; and Brye, Kristofor
"Using combined prediction models to quantify and visualize stormwater runoff in an urban watershed,"
Discovery, The Student Journal of Dale Bumpers College of Agricultural, Food and Life Sciences. University of Arkansas System Division of Agriculture. 9:30-42.
Available at: https://scholarworks.uark.edu/discoverymag/vol9/iss1/8