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    Opportunities for Standardization in Monitoring of Best Management Practices in the Southeastern United States

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    Date
    2005-01-24
    Author
    Yonce, Mary Elizabeth
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    Abstract
    Silvicultural activities, particularly forest harvesting operations, have the potential to negatively impact water quality. In order to lessen the probability that water quality degradation will occur, a suite of best management practices has been developed and adopted by southeastern states. The Clean Water Act exempts silvicultural activities from the permitting process of Section 404 as long as federally accepted best management practices are implemented to control nonpoint source pollutants. To demonstrate that these practices are being implemented, states are now inspecting and reporting on best management practice usage on a state wide basis. The Environmental Protection Agency is responsible for executing the Clean Water Act and would like to use the information provided by the individual states to guide water quality protection programs at a regional scale since states have developed their own unique methods or reporting. Currently there it is difficult to compare the information provided by states, and this impedes further development of water quality protection programs. To address this issue, a state of the art review of current inspection and monitoring methods in the southeast was conducted. Forestry professionals were then surveyed to identify opportunities for standardization in the inspection and reporting methodologies employed by states. Using the information resulting from the review and survey, recommendations for standardization were made in the following areas: site selection criteria, field execution method, form design, best management practices evaluated and water quality threat assessment. A standardized form was also developed and tested across three physiographic regions. This information is helpful for future planning and modifications that state agencies can use to standardize their BMP implementation monitoring methods.
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    http://hdl.handle.net/10919/31162
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    • Masters Theses [22188]

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