Rapid changes in spring water quality in karst areas due to rapid recharge of bacterially contaminated water are a major concern for drinking water suppliers and users. The main objective of this study was to use field experiments with fecal indicators to verify the vulnerability of a karst spring to pathogens, as determined by using a numerical modeling approach. The groundwater modeling was based on linear storage models that can be used to simulate karst water flow. The vulnerability of the karst groundwater is estimated using such models to calculate criteria that influence the likelihood of spring water being affected by microbial contamination. Specifically, the temporal variation in the vulnerability, depending on rainfall events and overall recharge conditions, can be assessed and quantified using the dynamic vulnerability index (DVI). DVI corresponds to the ratio of conduit to diffuse flow contributions to spring discharge. To evaluate model performance with respect to predicted vulnerability, samples from a spring were analyzed for Escherichia coli, enterococci, Clostridium perfringens, and heterotrophic plate count bacteria during and after several rainfall events. DVI was shown to be an indication of the risk of fecal contamination of spring water with sufficient accuracy to be used in drinking water management. We conclude that numerical models are a useful tool for evaluating the vulnerability of karst systems to pathogens under varying recharge conditions.
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