Master of Science / Department of Biological & Agricultural Engineering / Stacy L. Hutchinson / A field study was conducted at Fort Riley, Kansas from late spring to early winter of 2007 to investigate the ability of vegetated filter strips (VFS) to attenuate pollutants resulting from military activities, the impact of different management practices (i.e. burning and mowing) on VFS performance, and the effects of vegetation on hydrological components of VFS, especially infiltration and runoff. Two native tallgrass VFS sites, each comprising three plots, located in the military training area of Fort Riley were used for this study. Fifteen rainfall events were simulated on each site along with overland application of water containing nitrogen (N), phosphorous (P) and sediment. At the end of the season both VFS were managed by mowing or burning and a final rainfall simulation was done. Variables including rainfall, infiltration, runon, runoff, above ground biomass density, pollutant concentrations of runon and runoff, and soil moisture were measured and used in the data analysis. Hydrograph development, water balance, and mass balance calculations were carried out in order to calculate the pollutant trapping efficiencies (PTE) of the VFS. Statistical analysis was done by fitting several regression models. Mean comparisons were also done for variables and variance was decomposed into time, plot and site effects at an alpha = 0.05. Results showed that on average the VFS attenuated 84 % of total nitrogen, 24 % of total phosphorous and 95 % of sediments. Regression models showed that infiltration percentage and biomass density have a positive correlation with PTE. Runoff volume and PTE were negatively correlated. Soil moisture was negatively correlated with infiltration and time to runoff. With increasing biomass density, percentage of water infiltrating and time of concentration increased. Management practices, especially burning, tended to reduce PTE. Also, both management practices reduced infiltration percentage and time of concentration. PTE reduced with intensifying rainfall and increased when rainfall faded off. Phosphorous was the most sensitive pollutant for intense storm conditions followed by nitrogen, while sediment was comparatively insensitive.

In 2011, the Deep River Portage-Burns Waterway Watershed was identified as a priority in the Northwest Indiana watershed management framework by the Northwester Indiana Regional Planning Committee. 319 grant cost-share programs were initiated in effort of maintaining and restoring the health of Deep River Portage-Burns Waterway Watershed. A watershed management plans have been developed for this watershed which proposed the implementation of vegetated filter strips (VFS) as an option. In this thesis work, the effectiveness of VFS as a best management practice (BMP) for the Deep River system was evaluated using a hydrological model scheme. <div><br></div><div>In this research, a Nonpoint Source Pollution and Erosion Comparison Tool (NSPECT) model and a Soil Water Assessment Tool (SWAT) model were constructed with required watershed characteristic data and climate data. The initial hydrologic and nutrient parameters of the SWAT model were further calibrated using SWAT Calibration and Uncertainty Programs (SWAT_CUP) with historical flow and nutrient data in a two-stage calibration process. The calibrated parameters were validated to accurately simulate the field condition and preserved in SWAT model for effectiveness analysis of BMP implementations. </div><div><br></div><div>To evaluate the effectiveness of VFS as a BMP, four different scenarios of VFS implementations along the Turkey Creek was simulated with the calibrated SWAT model. With the implementation of VFS in the tributary subbasin of Turkey Creek, the annual total phosphorus (TP) of the VFS implemented subbasin was reduced by 1.60% to 78.95% and the annual TP of downstream subbasins were reduced by 0.09% to 55.42%. Daily percentage of TP reductions ranged from 0% to 90.3% on the VFS implemented subbasin. Annual TP reductions of the four scenarios ranged from 28.11 kg to 465.01 kg.<br></div>