Environ. Sci. Technol. 2010, 44, 6731–6737
Coastal Loading and Transport of Escherichia coli at an Embayed Beach in Lake Michigan Z H O N G F U G E , * ,† M E R E D I T H B . N E V E R S , † DAVID J. SCHWAB,‡ AND RICHARD L. WHITMAN† United States Geological Survey, Great Lakes Science Center, Lake Michigan Ecological Research Station, 1100 North Mineral Springs Road, Porter, Indiana 46304, and National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, 4840 S. State Road, Ann Arbor, Michigan 48108
Received March 11, 2010. Revised manuscript received July 14, 2010. Accepted July 16, 2010.
A Chicago beach in southwest Lake Michigan was revisited to determine the influence of nearshore hydrodynamic effects on the variability of Escherichia coli (E. coli) concentration in both knee-deep and offshore waters. Explanatory variables that could be used for identifying potential bacteria loading mechanisms, such as bed shear stress due to a combined wavecurrent boundary layer and wave runup on the beach surface, were derived from an existing wave and current database. The derived hydrodynamic variables, along with the actual observed E. coli concentrations in the submerged and foreshore sands, were expected to reveal bacteria loading through nearshore sediment resuspension and swash on the beachsurface,respectively.Basedontheobservationthatonshore waves tend to result in a more active hydrodynamic system at this embayed beach, multiple linear regression analysis of onshore-wave cases further indicated the significance of sediment resuspension and the interaction of swash with gulldroppings in explaining the variability of E. coli concentration in the knee-deep water. For cases with longshore currents, numerical simulations using the Princeton Ocean Model revealed current circulation patterns inside the embayment, which can effectively entrain bacteria from the swash zone into the central area of the embayed beach water and eventually release them out of the embayment. The embayed circulation patterns are consistent with the statistical results that identified that 1) the submerged sediment was an additional net source of E. coli to the offshore water and 2) variability of E. coli concentration in the knee-deep water contributed adversely to that in the offshore water for longshore-current cases. The embayed beach setting and the statistical and numerical methods used in the present study have wide applicability for analyzing recreational water quality at similar marine and freshwater sites.
Introduction Human health is often threatened by contact with or swimming in contaminated water at recreational beaches. * Corresponding author phone: (219)926-8336 ext. 430; fax: (219)929-5792; e-mail:
[email protected]. † United States Geological Survey. ‡ National Oceanic and Atmospheric Administration. 10.1021/es100797r
2010 American Chemical Society
Published on Web 08/05/2010
Traditional microbiological techniques for detecting fecal indicator bacteria (FIB) levels in beach water, such as those based on bacteria culturing and incubation, usually take 18-24 h, considerably longer than the time scale of variations of FIB concentrations (1). Modeling FIB variability based on observations of hydrometeorological and biological variables using statistical or process-based mathematical models is a promising alternative. Statistical models in the exploratory stage of recreational water quality modeling mostly have been multiple linear regression models constructed using easily observed hydrometeorological variables, including nearshore wave height, wind speed, turbidity, precipitation, water/ air temperature, and dew point (2–4). Although these models have proven to be effective for managing particular beaches, the explanatory variables seldom provide direct evidence for bacteria importation, transport, and fate. Wind speed, for example, is often used to identify wind storms that in turn generate high waves on the ocean/lake surface. It has been established, however, that the propagation direction of windgenerated waves is not necessarily the same as the wind direction (5). Onshore/offshore wind speed, as a useful means for partitioning data sets (3), may not be effective for all beaches (6) as wind speed has only an indirect influence on bacteria transport and fate in the nearshore hydrodynamic system. Similarly, antecedent precipitation sometimes has a loose connection with FIB counts at a recreational beach especially when there is a complex watershed and ecological system or various nonpoint sources of contamination (7). Previous studies attempting to identify the mechanisms that may directly explain the variability of beach FIB concentration have found that foreshore and submerged sands are important bacteria sources (8–10). These studies confirmed that beach water can actively receive FIB from foreshore sands through swash, suspension, or tidal movements (10). Bacteria can also be deposited from water into the foreshore sand, which makes the water-sand interaction bidirectional (9). The significant bacteria sources in foreshore and submerged sands underscore the importance of hydrodynamic mechanisms in the swash and the surf zones. Besides strong point sources and solar radiation (11), nearshore hydrodynamics is possibly another rapid mechanism responsible for bacteria importation, transport, and deposition at a beach. Investigating hydrodynamic phenomena such as sediment suspension and swash, therefore, will offer more direct evidence than meteorological parameters of the mechanism involved in water-sand interaction and bacteria transport in the beach water. The Chicago 63rd Street Beach is a popular recreational resource in southern Lake Michigan. It suffers from high closures each swimming season (9), partly because the Chicago area is one of the regions under the heaviest influence of sediment resuspension throughout Lake Michigan, with, for example, a bed shear stress over 0.1 Pa for 20% of the time during 1994-1995 (12). Extensive studies have been conducted at this beach to understand the causes of FIB contamination. Prediction-oriented regression models determined that the hydrometeorological variables including wind speed/direction, solar insolation, and rainfall could explain a portion of the variation in E. coli concentration (13). Additional research identified the importance of watersand interaction at this beach and its associated ecological and microbiological effects on water quality (9), while groundwater discharging to the lake was eliminated as a significant E. coli source for the beach water (7). In the present study, we focused on bacteria loading and transport in direct response to nearshore hydrodynamic events. The embayment VOL. 44, NO. 17, 2010 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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FIGURE 1. 63rd Street Beach of Chicago. Sampling locations for E. coli concentration in the foreshore sand (open triangle), in the knee-deep water (open circle), in the submerged sediment (open circle), and in the offshore water (filled circle) are marked. Open square: weather station; dark square: water monitoring point; crossed circle: the location where numerically simulated wave and current data are available; directions within 90° and 45° from the exact onshore direction (SW) are defined as onshore and strictly onshore, respectively; exact longshore direction is the NW-SE direction indicated by the wide dashed-line. Box-plot of the distribution of E. coli concentrations (log10 CFU/100 mL) measured in the foreshore sand (ECforesh), in the submerged sand (ECsed), in the knee-deep water (EC), and in the offshore water (ECoffsh) are inserted on the left. setting, with beach water bounded by breakwaters or jetties, is typical in coastal areas. Methods and findings in the present work have widespread significance for other sites with similar infrastructure and environmental conditions.
Materials and Methods Field Observations. Detailed description of the Chicago 63rd Street Beach has been given elsewhere (9, 13). Briefly, the study area is located on the southwest shore of Lake Michigan. The beach area is in an embayment that is open to the northeast and bounded by two breakwaters in the north and south (Figure 1). Five transects were established 100 m apart from one another. Water samples were taken at approximately 07:00 h on three consecutive days per week, usually from Tuesday through Thursday, in 45 cm deep (knee-deep) water at each transect from April to September 2000. At the same locations, sediment samples were collected from submerged sand. Sand samples were simultaneously collected from the foreshore sand about 1 m landward from the farthest extent of wave actions at each transect. Additional water samples were obtained from the offshore extremity of the southern breakwater (water depth approximately 4 m). After sample collection, water and sediment samples were kept at 4 °C and later analyzed for E. coli concentration in the laboratory within 3 h. Water samples were analyzed by membrane filtration onto mTEC agar as outlined in EPA/600/4-85 076 (14). Besides the same analytical methods, sediment samples required additional preparation including the estimation of the total sample volume with the core liner, the dilution of the test sediment, and the shaking of the sample bottles for 5 min at 210 rpm on an Eberbach platform shaker. Results are reported as colony forming units per 100 mL of water (CFU/100 mL). E. coli concentration averaged over the five transects for the foreshore sand, submerged sediment, and 45-cm water, and of offshore water were further log10transformed and are denoted as ECforesh, ECsed, EC, and ECoffsh, respectively. Onsite weather and water monitoring stations were established on the southern breakwater and near transect #1, respectively. Meteorological parameters observed from the onsite weather station included wind speed, direction, gust (denoted as GT), and air temperature (Ta). The number of gulls on the beach (GL) was observed over the entire beach area. The density of gull-droppings (GD) was counted in three randomly placed 1-m2 quadrats 1-6 m from the furthest 6732
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extent of waves at each transect followed by averaging. Wave and current conditions were obtained from a nearby offshore location (the origin of the coordinate system in Figure 1) based on an existing numerical simulated database and will be described in next section. The definitions of onshore, offshore, and longshore directions are particularly important for isolating cases from the entire data set. According to Figure 1, exact onshore direction is toward the southwest, and hence onshore wind and current velocity components are defined as the projections of wind and current velocity vectors in this direction, denoted as WDon and CTon, respectively. The northwestsoutheast line is the exact longshore direction in which the projection of current velocity is denoted as CTlong. Furthermore, any vector (wind, wave, or current) that is directed from 135° to 315° (a 180° range) clockwise from the due north is defined as “onshore”. A 90° subrange of these angles, from 180° to 270° clockwise from the due north, is defined as “strictly onshore” directions. Similarly, vectors directed no more than 22.5° from the exact longshore direction were considered to be “longshore”. Categorical variables indicating whether wave propagated onshore (1 for onshore and 0 otherwise) and whether current velocity was longshore (1 for longshore and 0 otherwise) were also used in the following analyses and denoted as IfWVon and IfCTlong, respectively. New Hydrodynamic Variables. Bed shear stress (BSS) and total runup height (R) were derived from numerically simulated wave and current data to reflect the potential of sediment resuspension and bacteria input from the foreshore sand, respectively. Bed Shear Stress and Sediment Resuspension. The occurrence of sediment resuspension is determined by bed shear stress as well as other parameters such as the bed form and sediment mobility (15). Bed shear stress can be estimated from the fluid flow that overlies the sea/lake bed, which often is a combined wave-current boundary layer (WCBL) flow (16). The combined WCBL is not a simple addition of wave and current flow fields but a nonlinear superposition of them. A widely used method for estimating bed shear stress caused by a WCBL was outlined in ref 16. Detailed assumptions and equations are given in the Supporting Information. When bed shear stress exceeds a critical value, empirically 0.05-0.1 Pa, sediment suspension is considered to occur (12). While all suspended FIB are not necessarily sedimentattached (17), elevation of bacteria concentration is usually
observed immediately close to the location of sediment disturbance, as seen, for example, in dredging (18). Therefore, it was assumed that, provided bacteria are initially present in the sediment, sediment resuspension closely coincides with bacteria importation into the water column. In the absence of actually observed current and wave data for the Chicago 63rd Street Beach in 2000, numerically simulated current and wave parameters were obtained from the Great Lakes Environmental Research Laboratory of the National Oceanic and Atmospheric Administration (NOAA). Their numerical simulations of current circulation and surface wave parameters in Lake Michigan were based on a three-dimensional Princeton Ocean Model and wave models adapted for the Great Lakes, which have been extensively validated and applied to many advanced studies (19–21). For the present case, the location for both current and wave parameters is close to the midpoint of the opening of the embayment (Figure 1) with a nominal water depth of 5 m. Current and wave data at 06:00 h were used in order to lead water sampling time, 07:00 h, by an hour, allowing for adaptation of beach water to hydrodynamic conditions. The current velocity used for estimating the bed shear stress in the combined WCBL was obtained at the lowest vertical computational cell in the numerical model, namely 0.12 m above the lake bed. Potential Bacteria Input in the Swash Zone. An additional variable that is potentially important for explaining the bacteria loading at the study beach is wave runup on the beach surface. The total wave runup R is defined as the sum of the maximum wave setup and the standard deviation of the fluctuating swash height (22). The total runup on a beach is empirically proportional to the surf similarity parameter ξ0 )
β
√H0 /L0
(1)
where β denotes the beach slope, and H0 and L0 are the deepwater wave height (or significant wave height Hs for random waves) and wavelength, respectively. The empirical proportionality leads to a convenient estimate of total runup on a beach R ) C√HsTp
(2)
where Tp is the peak wave period, and C is a coefficient of proportionality that is at least dependent on the beach slope β and can be calibrated for specific beaches. For many studies, deep-water wave parameters such as Hs and Tp are available from publicly accessible sources. Physically, shear stress on the beach surface during wave runup-backwash cycles is hypothesized to be a direct agent for bacteria input from the foreshore sands to the swash zone. Due to the lack of reliable models for directly estimating swash shear stress (23) and the complexity of the wave-sand interactions (24), we simply assumed that the total runup reflects the potential of bacteria loading from the foreshore sand. In estimating the total runup for the present work, eq 2 was used, but the coefficient C was omitted without affecting any analysis in the following sections. Beach width (Bw), the distance from a fixed inland point to the upper tip of swash lenses, was actually observed during the field study and is (inversely) comparable to the total runup. A summary of explanatory variables used in the following statistical analyses are listed in Table 1. In the Results section, parsimonious models under particular hydrodynamic conditions are identified by a backward elimination process based on the probability of F-to-remove larger than 100. Backward elimination started with 10-14 variables (i.e., the full model) introduced in the present section. The number
TABLE 1. Explanatory Variables Used in Statistical Analysis variable
description
E. coli concentration in the foreshore sand (log10 CFU/100 mL) E. coli concentration in the knee-deep beach EC water (log10 CFU/100 mL) E. coli concentration in the submerged sediment ECsed (log10 CFU/100 mL) E. coli concentration in the offshore deep water ECoffsh (log10 CFU/100 mL) BSS bed shear stress (Pa) Hs significant wave height (m) R estimated total runup (arbitrary unit) Bw beach width (m) CTon onshore component of current velocity (ms-1) CTlong longshore component of current velocity (ms-1) WDon onshore component of wind speed (ms-1) GT gust (ms-1) Ta air temperature (°C) GL number of gulls gull dropping density on the beach GD (number m-2) BwGD product of Bw and GD IfWVon 1 if wave direction is onshore; 0 if otherwise IfCTlong 1 if current velocity is longshore; 0 if othereise 1 if current velocity is longshore and downIfDnCoast coast; 0 if longshore but up-coast ECforesh
of variables included in the full models was limited by the issue of no multicollinearity. No serious multicollinearity was found between E. coli concentrations at different locations. It is important to note that linear regression models used here are not for prediction purposes but for identifying relationships among variables. In practical predictive models, for example, E. coli concentrations in the submerged and foreshore sands are usually unavailable, and more water chemistry variables should be considered.
Results General Results. Distributions of the four E. coli concentration variables, ECforesh, ECsed, EC, and ECoffsh, in the entire study period (N ) 75) are shown in the insert of Figure 1. The foreshore sand had the highest E. coli concentration with a median slightly over 104 CFU/100 mL. The median of E. coli concentration in the submerged sand was approximately 103 CFU/100 mL, while those in the nearshore and offshore waters were about 102 and 10 CFU/100 mL, respectively. There thus was an approximately exponential decay of E. coli concentration from the sand farthest onshore to the water offshore (9). The simulated wave height and current speed as well as their directions are shown in Figure 2, with onshore-wave cases highlighted by symbols. The 75-d study period can be nearly evenly divided into two categories: onshore wave cases (38 d) and offshore-wave cases (37 d). Moreover, a majority of onshore-wave cases, 25 out of 38 d (the filled circles that fall in the horizontal belt bounded by solid lines in Figure 2c), are strictly onshore. Longshore currents were prevailing nearshore outside the embayment. According to the definition given in Figure 1, there were 64 d (out of 75 d) with longshore currents. Figure 3a shows the estimated bed shear stress due to a combined WCBL in the nearshore water. On the days when the wave action was negligible (wave height
