Tuesday, 7 October 2008
George R. Brown Convention Center, Exhibit Hall E
Land application of livestock wastewater as a surrogate for chemical fertilizer has raised public concern regarding the potential for environmental transmission of manure-borne microorganisms. Runoff samples were collected over time and analyzed for microbial indicators (total coliform, Escherichia coli, entercocci) and water quality parameters (erosion, sediment concentration, air temperature, relative humidity, solar radiation, pH, EC, and turbidity) from a manured cropland site near Lincoln, Nebraska, USA. The transport mechanism of microorganisms associated with eroded agricultural soils from farmlands was investigated using Artificial Neural Network (ANN). The ANN-based approach is able to predict microbial runoff concentrations, allowing a real-time assessment of wastewater’s quality and quantity during runoff events from manured cropland. The use of principal component analysis strained out redundant input data and reduced the data requirements for computation. This study found that each microbial indicator has a highly positive relationship with the analyzed water quality parameters (R=0.934~0.942). A major benefit of this study is to provide crucial knowledge on how both eroded soil and water quality factors affect the transport of microorganisms. In addition, highly nonlinear but closely related features enable a rapid and simple way to evaluate microbial contamination associated with the studied manure management practice. The use of continuous water quality monitors would provide real-time estimation of microbial concentrations, and this information would enable the development of guidelines for the environmentally safe management of livestock manure.