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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Analysis of Oregon's Domestic Well Testing Act data for use in a sentinel surveillance system for private well contaminants

Hoppe, Brenda O. 01 May 2012 (has links)
The Safe Drinking Water Act ensures that public systems provide water that meets health standards. However, no such protection exists for millions of Americans who obtain water from private wells. Concern for safety is warranted as most wells draw from underground aquifers, and studies demonstrate that groundwater is affected by a range of contaminants, most often nitrate. Oregon's Domestic Well Testing Act (DWTA) links well testing to property sales, enabling continuous data collection by the State. This research addresses a need for identifying datasets for characterizing exposure to private well contaminants by evaluating DWTA data for use in a sentinel surveillance system. Validation of DWTA data was accomplished by developing a land use regression (LUR) model based on agricultural nitrogen inputs and soil leachability to predict nitrate concentrations in well water. Geographic information systems (GIS) were used to advance methods for high resolution spatial modeling of fertilizer and manure nitrogen with statewide coverage. Hazard mapping with these datasets suggests that nearly half of recently drilled wells are susceptible to nitrate contamination. Spearman's rank correlation demonstrated a significant correlation between LUR-predicted nitrate levels and levels reported in the DWTA dataset. These results suggest that DWTA data is valid for use in a sentinel surveillance system, such that evidence of nitrate contamination in a single well may indicate an area-wide health hazard. However, a low fraction of variance explained by the LUR model highlighted the need for specific improvements to datasets crucial for understanding nitrate contamination in well water, including the DWTA. / Graduation date: 2012

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