Developing a geospatial model to identify private well contamination risk in Alabama

Keywords: Private well, Groundwater contamination, Socio-economic factors, Environment, Geospatial methods
Abstract Type: Poster Abstract

Abstract

Contamination of groundwater wells continues to be a problem in the United States. Nitrate, pathogenic bacteria, viruses, and parasites are major contaminants associated with health problems including gastrointestinal illnesses, skin infections, and conjunctivitis. Installing treatment systems, replacing wells, or buying bottled water for drinking purposes can be costly, and because private wells are not regulated by federal, state, or local governments, the burden of contaminant testing, and remediation falls on the well owner. As a result, recent research has considered a mix of demographic, environmental, and geographical attributes that may contribute to contaminant exposure due to private well reliance. Findings suggest that low-income, vulnerable populations are more likely to become victims of well contamination in part due to a lack of knowledge and the ability to afford proper water treatment technologies. Moreover, certain climate-induced hazards, such as flooding can also increase contamination risk. Though numerous research tries to identify the social and environmental well contaminant factors separately, few have attempted to integrate both into a model to estimate private well water contamination. In this project, we bring together measures of socioeconomic vulnerability and environmental risk factors to develop a comprehensive geospatial analysis of private well contamination risk. A series of geostatistical and clustering techniques are combined to estimate contamination risk to well-owner communities across Alabama. The results of this work may be used to inform mitigation strategies such as informational workshops and targeted well-sampling campaigns. Further interrogation of each risk factor adds additional insight into the risk model.