T323 Water Quality and Aqueous Contaminants (Posters)

Wednesday, 28 September 2016
9:00 AM - 6:30 PM
Exhibit Hall E/F

A RUNOFF-BASED VULNERABILITY ANALYSIS TO EXAMINE AND COMMUNICATE THE DYNAMICS OF BACTERIA POLLUTION EVENTS IN THE GULF OF MAINE

Paper number: T323-16
Program: Technical Sessions
Time: 9:00 AM – 6:30 PM

Authors

Abstract

The culture and economy of coastal Maine is closely linked to near shore water quality. Besides its obvious impacts on health, bacterial pollution in estuaries and beaches has major negative impacts on the multi-million dollar tourism and shellfishing industries in the state. Local stakeholder groups recognize the need for a decision support system that would provide better informed regulations for coastal watershed management. The New England Sustainability Consortium (NEST) is an interdisciplinary NSF EPSCoR funded project organized to strengthen the connection between science and decision-making through the practice of sustainability science. Our objectives are to 1) improve contamination event predictions based on quantitative model scenarios, 2) improve lines of communication between stakeholders and researchers, and 3) provide a workable solution on issues of health and lost revenue.

We use a random forest analysis to identify watershed and estuary characteristics that are linked to higher vulnerability. Hydraulic models are used to determine flow patterns from watershed to coast, and an estuary mixing model is used to determine the amount of time necessary to dilute and disperse bacteria-bearing surface runoff. By combining our statistical model results with salinity and fecal coliform count data, we find that the primary trigger for high levels of bacterial contamination are population density, while metrics that describe the delivery and residence time of water have a secondary influence. Results from our hydraulic models suggest that current regional closure regulations can overestimate the time interval of contamination for some watersheds, and new regulations based on quantitative models and local observations would provide greater economic stability without presenting a significant health risk.

Geological Society of America Abstracts with Programs. Vol. 48, No. 7

doi: 10.1130/abs/2016AM-286861

© Copyright 2016 The Geological Society of America (GSA), all rights reserved. Permission is hereby granted to the author(s) of this abstract to reproduce and distribute it freely, for noncommercial purposes. Permission is hereby granted to any individual scientist to download a single copy of this electronic file and reproduce up to 20 paper copies for noncommercial purposes advancing science and education, including classroom use, providing all reproductions include the complete content shown here, including the author information. All other forms of reproduction and/or transmittal are prohibited without written permission from GSA Copyright Permissions.