A framework for evaluating the risk of water pollution from the application of liquid dairy manure to agricultural fields was developed and applied. The GLEAMS (Groundwater Loading Effects of Agricultural Management Practices) (Ver 2.1) model was used to simulate NO₃-N leaching below the root zone for different land application rates of liquid dairy waste for fields in Georgia and Texas. Probability distributions of yearly-maximum nitrate concentrations were developed for each application rate at each site using the simulated nitrate concentrations. The probability of failure (exceeding 10 mg/L NO₃-N) for each application rate was determined from its corresponding distribution. An appropriate fine for farmers based on probability of failure for different land application rates was determined through economic analysis. The expected risk to farmers in monetary terms was determined for each application rate based on possible fines and the probability of failure. The monetary risk of nitrate leaching to ground water was compared to the social value of ground water. The probability of failure for liquid dairy waste application rates between 200 to 800 kg·N/ha/yr ranged from 0.0022 to 0.74 for Tifton, GA. The probability of failure for liquid dairy waste application rates between 0 and 1000 kg·N/ha/yr ranged from 0.00 to 0.85 for Overton, TX. The maximum application rate that was environmentally acceptable for both Texas and Georgia was 250 kg·N/ha/yr based on the probability of failure. Fines of $1100/ha and $700/ha for the Georgia and Texas sites, respectively, would provide farmers with economic incentives not to exceed an application rate of 250 kg·N/ha/yr. These fines resulted in risks to farmers of $814/ha in Georgia for 800 kg·N/ha/yr application rate and $595/ha in Texas for 1000 kg·N/ha/yr rate. This compares with a social value ranging from $860/ha to $1432/ha of clean ground water. / Master of Science

A model was developed using contemporary wetland theory to predict the fate of nitrogen runoff in a constructed wetland. The model utilizes nitrogen concentrations of influent water as system inputs. The model is three-dimensional, one dimensional in time, and two dimensional in space. The physical domain of the model incorporates a flat emergent marsh and deep pool and includes the water body and underlying sediment. Solutions for concentration of sediment-bound organic nitrogen are obtained for the water body and the sediment-water interface, while solutions for concentration of ammonium and nitrate are obtained for the entire physical domain. Physical conditions are considered along the system boundaries, and a jump condition is modeled for nutrient diffusion through the sediment-water interface. A hyperbolic advection-settling equation models the transport and deposition of sediment-bound organic nitrogen; mineralization of deposited nitrogen is modeled. A parabolic advection-diffusion equation is used to model the movement of dissolved ammonium and nitrate through the wetland water body; the equation is modified for both ammonium and nitrate to model diffusion and transformation in the sediment layer. Spatial variation of sediment layer aerobic and anaerobic regions is considered, as are temperature and pH effects on transformation rates. Numerical solutions are obtained using divided differences. Constructed wetlands for use in NPS pollution control are a new concept; there is no data currently available to use for model validation. The model was shown to be consistent with qualitative theoretical considerations, based on simulations of different scenarios. / Master of Science

Master of Science / Department of Biological & Agricultural Engineering / Stacy L. Hutchinson / Soil erosion is a serious problem resulting in degradation of soil systems and nonpoint source (NPS) pollution of water resources. Concentrated overland flow is the primary transport mechanism for many NPS pollutants including soil, and locating areas where sheet flow transitions into concentrated flow is useful for assessing the potential for soil erosion. The ability to predict areas where overland flow transitions to concentrated flow and soil erosion potential is high assists land managers in implementing best management practices (BMPs) to reduce soil erosion and NPS. An erosion model, called the nLS model, was developed to identify transitional overland flow regions. The model is based on the kinematic wave overland flow theory and uses Manning’s n values, flow length, and slope as inputs to determine where overland flow transitions to sheet flow and soil erosion potential increases. Currently, the model has only been tested and validated for watersheds within Kansas. In order to assess model uncertainties and evaluate the model’s applicability to other regions, a sensitivity analysis on key input parameters was conducted. To assess model operations, several sensitivity analyses were performed on model inputs, including digital elevation models (DEMs) and landuse/landcover data (LULC). The impact of slope was assessed using two methods. First, by modifying the DEMs in a stepwise fashion from flatter to steeper terrains, and second, by modifying the elevation of each DEM cell based on the associated elevation error. To assess difficulties that might arise from the parameterization of surface roughness, LULC classes were assigned Manning’s n values within the suggested range using a Monte Carlo simulation. In addition, the critical threshold value used for locating erosion potential sites was modified, and alternative model calculations were used to assess the potential for improving model accuracy. Finally, the model was run using data from multiple sites, including two study areas in Hawaii and two in Kansas. The outputs for each site were analyzed in an attempt to identify any trends caused by site characteristics. Results from this study showed that the nLS model was sensitive to all of the inputs. Modifying the Manning’s roughness coefficient significantly altered the final nLS values and shifted the critical threshold points, especially in areas of the upper watershed. Changes in the slope value modified the nLS model outputs in a predictable manner, but there was some variability, especially in areas with lower slope values. In addition, discrepancies in the DEM, which may be present due to measurement or processing error, were shown to significantly alter the flow paths of a watershed. These findings suggest that accurate roughness coefficients and LULC data are especially important for regions with a steeper topography, and accurate elevation data is important for regions with lower slope values. The results also suggest that the threshold value for the model plays a vital role in locating potential soil erosion sites, and adjustments to this value could possibly be used as a method for calibrating the nLS model. Finally, the alternative model calculations used in this study did not significantly improve the accuracy of the nLS model, so the existing model is sufficient for obtaining accurate nLS estimates. The information gained from this study can improve the assessment of soil erosion processes due to concentrated overland flow. By successfully implementing a land management program that makes use of the nLS models, it should be possible to improve BMP placement and design, helping to improve water and soil quality.