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• W2783930735 abstract "With continued population growth and increasing use of fresh groundwater resources, protection of this valuable resource is critical. A cost effective means to assess risk of groundwater contamination potential will provide a useful tool to protect these resources. Integrating geospatial methods offers a means to quantify the risk of contaminant potential in cost effective and spatially explicit ways. This research was designed to compare the ability of intrinsic (DRASTIC) and specific (Attenuation Factor; AF) vulnerability models to indicate groundwater vulnerability areas by comparing model results to the presence of pesticides from groundwater sample datasets. A logistic regression was used to assess the relationship between the environmental variables and the presence or absence of pesticides within regions of varying vulnerability. According to the DRASTIC model, more than 20% of the study area is very highly vulnerable. Approximately 30% is very highly vulnerable according to the AF model. When groundwater concentrations of individual pesticides were compared to model predictions, the results were mixed. Model predictability improved when concentrations of the group of similar pesticides were compared to model results. Compared to the DRASTIC model, the AF model more accurately predicts the distribution of the number of contaminated wells within each vulnerability class." @default.
• W2783930735 created "2018-01-26" @default.
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• W2783930735 date "2018-01-08" @default.
• W2783930735 modified "2023-09-26" @default.
• W2783930735 title "Assessing intrinsic and specific vulnerability models ability to indicate groundwater vulnerability to groups of similar pesticides: a comparative study" @default.
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• W2783930735 doi "https://doi.org/10.1080/02723646.2017.1406300" @default.
• W2783930735 hasPublicationYear "2018" @default.
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