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PLoS One ; 16(8): e0256606, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-34432827

RESUMEN

Threats to public health and environmental quality from septic systems are more prevalent in areas with poorly draining soils, high water tables, or frequent flooding. Significant research gaps exist in assessing these systems' vulnerability and evaluating factors associated with higher rates of septic systems replacement and repair. We developed a novel GIS-based framework for assessing septic system vulnerability using a database of known septic system specifications and a modified Soil Topographic Index (STI) that incorporates seasonal high groundwater elevation to assess risks posed to septic systems in coastal Georgia. We tested the hypothesis that both the modified STI and septic system specifications such as tank capacity per bedroom and drainfield type would explain most of the variance in septic system repair and replacement using classification inference tree and generalized logistic regression models. Our modeling results indicate that drainfield type (level vs. mounded) is the most significant variable (p-value < 0.001) in predicting septic systems functionality followed by septic tank capacity per bedroom (p-value < 0.01). These show the importance of septic system design regulations such as a minimum requirement for horizontal separation distance between the bottom of trenches and seasonal water table, and adequate tank capacity design. However, for septic systems with a mounded drainfield and a larger tank capacity per bedroom, the modified STI representing hydrological characteristics of septic system location is a significant predictor of a high septic system repair and replacement rate. The methodology developed in this study can have important implications for managing existing septic systems and planning for future development in coastal areas, especially in an environment of rapid climatic change.


Asunto(s)
Modelos Teóricos , Eliminación de Residuos Líquidos , Administración de Residuos , Área Bajo la Curva , Geografía , Georgia , Modelos Logísticos , Curva ROC , Reproducibilidad de los Resultados , Suelo
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