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Effect of low energy waves on the accumulation and transport of fecal indicator bacteria in sand and pore water at freshwater beaches Ming Zhi Wu, Denis Michael O'Carroll, Laura Jill Vogel, and Clare E. Robinson Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05985 • Publication Date (Web): 10 Feb 2017 Downloaded from http://pubs.acs.org on February 19, 2017
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Effect of low energy waves on the accumulation and transport of fecal indicator
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bacteria in sand and pore water at freshwater beaches
3 Ming Zhi Wua, Denis M. O’Carrolla,b, Laura J. Vogela, Clare E. Robinsona *
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Department of Civil and Environmental Engineering, Western University, London ON, Canada N6A 5B9
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School of Civil and Environmental Engineering, Connected Water Initiative, University of New South Wales, Manly Vale NSW 2093, Australia
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Submitted to Environmental Science & Technology
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*Corresponding author
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Address for Correspondence:
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Clare Robinson
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Department of Civil and Environmental Engineering, Western University
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London ON, Canada N6A 5B9
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Tel: 519-661-2111; Fax: 519-661-3779
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e-mail:
[email protected] 19
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Abstract Art
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Abstract
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Elevated fecal indicator bacteria (FIB) in beach sand and pore water represent an
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important non-point source of contamination to surface waters. This study examines the
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physical processes governing the accumulation and distribution of FIB in a beach aquifer.
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Field data indicate E. coli and enterococci can be transported 1 and 2 m, respectively, below
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the water table. Data were used to calibrate a numerical model whereby FIB are delivered to
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a beach aquifer by wave-induced infiltration across the beach face. Simulations indicate FIB
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rapidly accumulate in a beach aquifer with FIB primarily associated with sand rather than
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freely residing in the pore water. Simulated transport of E. coli in a beach aquifer is complex
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and does not correlate with conservative tracer transport. Beaches with higher wave-induced
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infiltration rate and vertical infiltration velocity (i.e., beaches with higher beach slope and
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wave height, and lower terrestrial groundwater discharge) had greater E. coli accumulation
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and E. coli was transported deeper below the beach face. For certain beach conditions, the
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amount of FIB accumulated in sand over five to six days was found to be sufficient to trigger
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a beach advisory if eroded to surface water.
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Keywords: Groundwater-surface water interactions, fecal contamination, bacterial transport, colloid transport, waves, Escherichia coli, enterococci
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Introduction
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Fecal contamination diminishes the recreational and economic value of beaches.1,2 It
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is estimated that human exposure to wastewater-polluted coastal waters worldwide results in
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over 120 million cases of gastrointestinal disease and 50 million cases of respiratory disease
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annually.3 Recreational water quality is assessed through routine monitoring of fecal indicator
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bacteria (FIB), i.e., Escherichia coli at freshwater beaches and enterococci at marine beaches,
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which correlate with the risk of water-borne illnesses to beachgoers. When FIB
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concentrations in surface water exceed water quality standards (e.g., 100 colony forming
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units per 100 mL [CFU/100 mL] based on a geometric mean for E. coli in Ontario, Canada4
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and the United States5; 30 CFU/100 mL for enterococci in the United States5), a beach water
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quality advisory may be issued. FIB are known to accumulate in foreshore sand and pore
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water (herein referred to as the foreshore reservoir; Figure 1a), with concentrations
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considered on a bulk volumetric basis often orders of magnitude higher than in adjacent
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surface waters.6-10 Fecal contaminants in the foreshore reservoir pose a human health risk
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through skin contact and ingestion,11,12 as well as being an important non-point source of
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contamination to surface waters.6,13-16 Sources of FIB to the foreshore reservoir include
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stormwater runoff, septic systems, sewer overflows and repeated seeding from bird and
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animal feces.6,17-19 Infiltration of surface water across the beach face (Figure 1a) can also be
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an important source of FIB to the foreshore reservoir.20-22
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Prior research on the exchange of FIB between the foreshore reservoir and surface
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water has largely focused on release of FIB from the reservoir to surface water.7,23,24 Few
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studies have evaluated the delivery of FIB to the foreshore reservoir from surface water
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infiltration. Due to the complexity of the beach environment (e.g., multiple forcing acting at
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different temporal and spatial scales) it is difficult to quantify the exchange of FIB between
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the foreshore reservoir and surface water via field measurements alone.6,24 Gast et al.25 4 ACS Paragon Plus Environment
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showed that plastic microspheres, used as a proxy for enterococci, were rapidly transported
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about 0.5 – 0.8 m vertically and 6 m horizontally into the groundwater and unsaturated zone
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of a beach aquifer in response to tide- and wave-induced surface water infiltration. More
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recently, Brown et al.19 showed that while recirculating surface water may transport FIB from
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bird feces deposited on the beach surface into the foreshore reservoir, subsequent FIB
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transport from the reservoir to surface water (via groundwater flow) may be low due to FIB
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attachment to sand grains. While studies have illustrated the importance of water exchange
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(infiltration/exfiltration) across the beach face on the delivery of FIB to the foreshore
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reservoir, improved understanding of the physical mechanisms controlling the transport of
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FIB from surface water to the reservoir and their subsequent accumulation is needed.
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Water exchange across the beach face and groundwater flow patterns are complex and
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dynamic. At freshwater (e.g., Great Lakes) and micro-tidal marine beaches, waves are the
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dominant coastal forcing and typically govern water exchange rates and beach groundwater
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flow patterns. Averaged over a wave period, instantaneous waves produce an onshore upward
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tilt of the sea or lake water surface (termed wave setup; Figure 1a). The hydraulic gradient
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associated with wave setup drives groundwater flow recirculation that extends from the wave
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run-up zone to offshore (Figure 1a).26,27 This causes significant quantities of surface water
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and associated constituents, including FIB, to be delivered and transported through the beach
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aquifer.26,28,29 Prior studies have quantified wave-induced water exchange and recirculation
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for both steady and transient wave conditions as well as their impact on conservative and
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reactive solute transport.26,28,30,31 Numerical modelling approaches are often used to identify
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key mechanisms governing the effect of waves on groundwater flow and solute transport due
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to the complexity of the environment.26,30,31
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Understanding the processes governing bacterial transport in a beach aquifer is
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important not only for FIB but also for other bacteria including pathogenic, sulfate-reducing 5 ACS Paragon Plus Environment
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and nitrifying bacteria.32 The transport of bacteria in groundwater is governed by bacteria-
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sediment interactions including attachment to sand grains and straining.33-35 Bacteria also
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experience inactivation and die-off, grazing, and possible replication.36-39 While prior studies
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have examined the environmental factors affecting the persistence of FIB in beach
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sand,10,38,40-42 the physical transport processes are less understood. For instance, we do not
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understand the time scale at which FIB build up in the foreshore reservoir from surface water
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infiltration, the partitioning of FIB between pore water and sand, and the physical factors
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controlling the spatial distribution of FIB in the reservoir.
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The objective of this study is to generate a mechanistic understanding of the effects of
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low energy waves on the delivery, accumulation and distribution of bacteria, specifically FIB,
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in the saturated portion of a beach aquifer. This study focuses on low energy waves which are
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likely to lead to the accumulation of FIB in the beach aquifer, rather than higher energy
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waves which may be erosive and thus associated with the release of FIB from the foreshore
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reservoir to surface waters.43,44 Field data of FIB distributions in the beach aquifer at two
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freshwater beaches with different groundwater flow conditions are first analysed. A
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numerical model that simulates wave-induced groundwater flows combined with bacterial
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transport is then presented with the numerical approach calibrated using the field data.
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Finally, the model is applied to provide key insights into the physical controls on the
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accumulation and distribution of FIB in a foreshore beach aquifer.
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Materials and Methods 2.1
Field Sites
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Field investigations were conducted at Burlington Beach (43°18’47”N, 79°48’02”W;
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Lake Ontario) and Mountain View Beach (44°40’21”N, 79°58’58”W, Lake Huron).
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Groundwater, surface water and sand surface levels were measured three times at each beach
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from May – September 2013 to determine the groundwater hydraulic gradients and beach 6 ACS Paragon Plus Environment
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topography (see Supporting Information Section 1 for field methods). Burlington Beach is a
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fine sand beach (median grain size diameter [d50] = 0.23 mm, uniformity coefficient [Cu] =
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1.7, saturated hydraulic conductivity [Ks] = 19.4 m/d) with an average beach slope (β) of
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approximately 0.05. The beach water table was relatively deep with groundwater flowing
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landward (foreshore hydraulic gradient ranged from -0.005 to -0.01 from May – September).
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Mountain View Beach had a shallower water table with lakeward groundwater flow
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(foreshore hydraulic gradient ranged from 0.008 to 0.016 from May – September) and an
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average beach slope of 0.03. This beach is comprised of fine sand (d50 = 0.23 mm, Cu = 2.3,
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Ks = 17.8 m/d) that overlies a clay layer. Offshore the depth of the clay layer is approximately
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1.5 m below the sediment surface.
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Water and Sand Sampling and FIB Enumeration
2.2
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Depth profiles of FIB concentrations in the pore water were measured at multiple
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locations along a cross-shore transect at each beach (6 August and 9 September 2013 at
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Burlington Beach, and 25 July 2013 at Mountain View Beach). Intact sand cores up to 0.8 m
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deep and extending below the water table were also collected on 4 June 2013 at Mountain
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View Beach. In addition, foreshore pore water and sand samples as well as surface water
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samples were collected every 2 – 4 weeks at three and four cross-shore transects (50 m apart)
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on Mountain View Beach and Burlington Beach, respectively, from May – September 2013.
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E. coli and enterococci in water and sand samples were enumerated using standard
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membrance filtration methods45 with bacteria extracted from sand using methods
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recommended by Boehm et al.46 The sampling and FIB enumeration methods are further
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described in Supporting Information Section 1. E. coli and enterococci concentrations are
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expressed as log CFU/100mL for water samples and log CFU/g of dry sand (based on sand
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moisture content). The log transformed FIB concentrations were used for the statistical
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2.3
Numerical Model
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Groundwater flows and bacterial fate and transport in a beach aquifer exposed to
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steady low energy waves was simulated in the finite-element solver COMSOL Multiphysics
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(version 4.4).47 Variably saturated groundwater flow in a beach aquifer was simulated using
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the Richards equation.48 Bacterial fate and transport in the beach aquifer included die-off and
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attachment of bacteria to sand grains simulated using colloid filtration theory (CFT).49 Given
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parameter values are better defined for E. coli compared to other FIB, the transport of E. coli
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was simulated with enterococci transport simulated for select cases. Key model parameter
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values are shown in Table 1 with details of the mathematical model and additional parameter
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values provided in Supporting Information Section 2. Note, some field results are described
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in this section as they are important for explaining the model set-up.
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Two-dimensional models were set up to simulate the beach aquifers at Burlington
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Beach and Mountain View Beach (Figure 1b,c). The model simulates the delivery of FIB to
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the beach aquifer by surface water infiltration driven by low energy waves. Once delivered to
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the aquifer, FIB may be transported by the flowing groundwater, accumulate in the sand, die-
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off or exfiltrate to surface water. The effect of waves was simulated by considering the phase-
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averaged effect of waves as described by wave setup (eq S8 in the Supporting Information),
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rather than simulating instantaneous wave action. Submerged nodes along the boundary BCD
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(Figure 1b) were assigned a hydrostatic pressure corresponding to the wave setup profile.
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Nodes landward of the wave setup point along BCD were unsaturated and represented as a
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no-flow boundary. As there was no infiltration landward of the wave setup point, the majority
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of FIB was transported in fully saturated pores in our domain.
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The simulated lake E. coli concentration was determined as part of the model
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calibration with a constant concentration applied for nodes along boundary BCD with
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infiltration into the aquifer as determined by the steady state flow model (Figure 1b). A zero 8 ACS Paragon Plus Environment
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concentration gradient was applied for nodes with exfiltration. The first-order die-off rate
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coefficient µdec for FIB was estimated based on an average value determined from microcosm
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experiments conducted using foreshore sand from Burlington Beach.50 Given die-off rates for
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both FIB in water and sediment often have similar ranges [O(0.01-1) 1/d],51-55 the same µdec
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was assumed for FIB in the aqueous phase and those attached to sand. The FIB concentration
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in the terrestrial groundwater (Qt) was zero based on negligible FIB detected in the landward
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groundwater at each site (Figure S2). The initial FIB concentration in the beach aquifer was
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set to zero. This assumes that all FIB in the beach aquifer were released to surface water by a
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preceding period of high erosive wave conditions.44 Details of the model domain and the flow
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boundary conditions including wave setup are described in Supporting Information Section 2.
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A simulation time of 5 days was adopted. This corresponds to the average time between
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periods of higher wave activity on Lake Huron.
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The bacterial attachment efficiency (αtot) and lake E. coli concentration were
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determined by fitting model simulations (after 5 days simulation time) to the observed E. coli
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vertical travel distance (Figure S2) and the observed mean E. coli saturated sand
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concentrations at the two beaches (Figures S3 and S4). The possible range of αtot for E. coli
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was based on literature values (Table S3). The lake E. coli concentration was varied within
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the range of concentrations measured in ankle-depth surface water from May – September
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2013 (0.48-2.61 log CFU/100 mL at Burlington Beach; 0.30-2.38 log CFU/100 mL at
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Mountain View Beach). Simulation results were consistent with the field results using αtot =
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0.05 and a lake E. coli concentration of 1.81 log CFU/100 mL. Following calibration, a
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sensitivity analysis was conducted to determine the physical controls on the accumulation and
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distribution of FIB in the beach aquifer.
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Results and Discussion 3.1
Comparison Between Field and Simulated FIB Distribution
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Consistent with prior studies,6,16,21,24 the highest concentrations of E. coli and
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enterococci at Mountain View Beach and Burlington Beach from May – September 2013
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were observed in the foreshore pore water, followed by surface water at ankle-depth, then at
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waist-depth (Table 2; Figures S3 and S4). FIB concentrations were highly variable over the
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sampling season at both beaches. E. coli and enterococci concentrations at ankle-depth and
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waist-depth were generally similar between Mountain View Beach and Burlington Beach,
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particularly in July through September (Figures S3c,d and S4c,d). The pore water and
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saturated sand concentrations between the two beaches were not statistically different (pore
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water: p = 0.34 for E. coli and p = 0.31 for enterococci; saturated sand: p = 0.11 for E. coli
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and p = 0.15 for enterococci; Mann Whitney test). This may in part be due to the high spatial
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heterogeneity in pore water and sand concentrations, coupled with the limited number of
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sampling events at each beach (5 and 8 sampling events at Mountain View Beach and
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Burlington Beach, respectively). Although the concentrations were not statistically different,
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distinct trends are observed for saturated sand E. coli and enterococci concentrations between
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Mountain View Beach and Burlington Beach, with concentrations typically larger at
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Burlington Beach. At both beaches E. coli and enterococci pore water concentrations were
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consistently higher than Ontario4 and U.S. EPA5 surface water guidelines (
