Runoff from agricultural lands carrying microorganisms from livestock manure can contaminate the food and water supplies of both animals and humans. Planning and design of animal waste best management practices (BMPs) thus becomes more important as livestock populations become more concentrated. A computer model is proposed to predict the effects of animal waste BMPs on the bacteria concentration of runoff from agricultural lands. The model uses Monte Carlo simulation to combine the deterministic relationships resulting from previous modeling efforts with statistical knowledge concerning rainfall events and temperature variation. Model output is in the form of monthly maximum and minimum log bacteria concentrations of runoff resulting from a storm assumed to occur immediately after manure is applied to the land. The effects of implementing such BMPs as waste storage, filter strips, and incorporation of manure into the soil can be compared. Data and information collected from the Owl Run watershed in Fauquier County, Virginia is used to demonstrate the model applicability and potential.
Long-term manure storage is determined to be the most appropriate practice for reducing bacteria concentrations for the study site. Incorporation of manure is as effective as long-term storage, but requires additional labor. Buffer strips significantly reduce bacteria concentrations, but not as effectively as long-term storage or incorporation. Additional efforts are needed to investigate the most influential variables and to make the temperature simulation submodel more computationally efficient. Once BMPs have been implemented on the study site, more data should be collected to test the accuracy of the model. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/53195 |
| Date | January 1988 |
| Creators | Walker, Sharyl E. |
| Contributors | Agricultural Engineering |
| Publisher | Virginia Polytechnic Institute and State University |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | en_US |
| Detected Language | English |
| Type | Thesis, Text |
| Format | xi, 147 leaves, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 19033568 |
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