An investigation of microbial groundwater contamination seasonality and extreme weather event interruptions using “big data”, time-series analyses, and unsupervised machine learning

Temporal studies of groundwater potability have historically focused on E. coli detection rates, with non-E. coli coliforms (NEC) and microbial concentrations remaining understudied by comparison. Additionally, "big data" (i.e., large, diverse datasets that grow over time) have yet to be employed for assessing the effects of high return-period extreme weather events on groundwater quality. The current investigation employed ≈1.1 million …