Microbial modelling of Lake St. Clair: Impact of local tributaries on the shoreline water quality

Mohammad Madani, Rajesh Seth, Luis F. Leon, Reza Valipour and Craig McCrimmon

Ecological Modelling, 2021, vol. 458, issue C

Abstract: Fecal contamination of surface water resource is a major health concern primarily due to the potential for pathogenic organisms to be transmitted to human by contaminated water. In lake-wide modelling of large lakes with many sources of microbial contamination, minor contributions from small tributaries are generally ignored. In this study, we applied a three dimensional high-resolution hydrodynamic and water quality model to assess the impact of eight smaller tributaries located on the southern edge of Lake St. Clair on microbial water quality during the summer of 2016. The impact at two beaches and two drinking water intakes located in the nearshore region of the southern edge of Lake St. Clair was considered. Results reveal that the microbial water quality in the nearshore regions close to these eight small tributaries' confluence are significantly affected by one or more of these tributaries. Although this effect is captured by our model with a time-variable or constant decay rates, the use of time-variable decay may be preferable for dynamic simulations over time. The total flow contribution from the smaller tributaries was estimated in the range of 18-35% while that for E. coli concentration was >80%. Three small tributaries were also predicted to account for >70% of the E. coli concentrations at drinking water intakes. For tributaries that do not significantly affect the hydrodynamics in a lake, a new framework is presented to identify approximate influence zones for microbial pollution that can help determine if a given location is likely to be impacted by the inflowing tributaries.

Keywords: Microbial modelling; E. coli; AEM3D; Lake St. Clair; CAEDYM (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:458:y:2021:i:c:s0304380021002647

DOI: 10.1016/j.ecolmodel.2021.109709

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