U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2013–3070

October 2013

Coastal Processes Influencing Water Quality at Great Lakes 

Beaches

Printed on recycled paper

The overall mission of this work is to provide science-based information and methods that will allow beach managers to more 

accurately make beach closure and advisory decisions, understand the sources and physical processes affecting beach contaminants, 

and understand how science-based information can be used to mitigate and restore beaches and protect the public. 

The U.S. Geological Survey (USGS), in collaboration with many Federal, State, and local agencies and universities, has conducted research on beach health issues in the Great Lakes Region for more than a decade. The work consists of four science elements 

that align with the USGS Beach Health Initiative Mission: real-time assessments of water quality; coastal processes; pathogens and 

source tracking; and data analysis, interpretation, and communication. The ongoing or completed research for coastal processes is 

described in this fact sheet.

Why do Scientists Study Coastal 

Processes?

Processes such as sediment transport, turbulence associated with currents 

and wave action, changes in lake and 

groundwater levels, and surface-water 

inputs can affect water quality at beaches. 

Additionally, beach sands and algae 

(Cladophora) can accumulate, harboring fecal indicator bacteria (FIB) and 

pathogens that can later be reintroduced 

into lake water and consequently impair 

swimming access. USGS scientists are 

working to characterize the transfer of 

FIB and pathogens to nearshore waters 

by way of these processes. 

In a series of studies examining the 

interaction between water movement and 

bacteria concentrations, several contributing processes have been identified: nearshore sediment resuspension, nearshore 

current and wave actions, lakebed shear 

stress, daily fluctuations of bacteria concentrations (caused by sunlight inactivation during the day, followed by recovery 

overnight), and bacteria entrapment 

inside of embayed beaches. 

Recognizing large-scale lake characteristics is essential in assessing beach 

water quality. USGS scientists identified 

simultaneous FIB fluctuations at multiple 

beaches along the coastline, identifying the importance of development of 

regionalized nowcast models for selected 

nonpoint-source beaches. 

Wave Height and Resuspension of 

Sediments in Nearshore

In a study exploring bacteria loading from beach sand and sediments, 

wave action on the sand was identified 

as an important mechanism for washing 

bacteria into the nearshore water (Ge and 

others, 2010). Factors associated with 

the transport of bacteria from sand to 

water (lakebed shear stress and wave 

run-up) were calculated to describe 

the mobilizing mechanism at the beach. 

Resuspension is particularly important 

at embayed beaches, where beach sand 

tends to concentrate Escherichia coli 

(E. coli). It was found that during highwave events, beach water received the 

majority of E. coli loading from foreshore 

sand and submerged sediments (fig. 1). 

However, higher bacteria loading was 

not always retained at the beach area, 

because longshore currents considerably 

facilitated bacteria exchange from outside 

to inside of the embayment. Finally, the 

occurrence of sediment resuspension in 

the beach water coincided with distribution of bacteria at the different depths. 

Collectively, nearshore hydrodynamics 

and E. coli transport involve multiple 

processes interacting with one another, 

which impact microbial water quality at 

swimming areas.

Daily Pattern and FIB Transport in 

Nearshore

A distinct daily pattern has been 

observed for FIB at the swimming areas, 

which encompasses decrease throughout 

daylight hours and rebound after dark. 

Thus, a theoretical model was developed 

to determine that some of the nightly 

increase of E. coli could be attributed to 

wave-induced mass transport (Ge and 

others, 2012a). The combination of this 

transport and nearshore sand resuspension effectively accounts for the increase 

in E. coli concentrations overnight. 

E. coli concentrations tended to increase 

by nearly three times overnight, and then

decreased from the morning to the afternoon, mostly owing to solar inactivation

and transport by currents. The nighttime 

replenishment of E. coli in nearshore 

water owing to wave-induced mass 

transport can be disturbed by lake-current activities. In coastal waters, however, 

Figure 1. Wave action and associated 

sediment resuspension lead to increased 

concentrations of bacteria in nearshore 

water.
current velocity is low; thus, wave action 

is an important mechanism for bacteria 

transport (fig. 2). These findings are of 

particular importance for water-monitoring programs and for protection of public 

health.

Figure 2. Measurements of current 

velocities using water-quality probes deployed 

in shallow water help scientists track bacteria 

transport in swimming areas.

The Effects of Sunlight on 

Bacterial Densities

The USGS conducted a 24-hour 

field experiment to study bacterial decay 

in the daytime and recovery at night 

at the Ogden Dunes beaches of Lake 

Michigan. USGS scientists simultaneously observed E. coli concentrations in 

the ambient water and in mesocosms in 

darkened and transparent bags, which 

helped separate the effects of bacterial 

death, inactivation owing to sunlight, 

and recovery during overnight hours, 

from the effects of fluid mixing and settling. The decay of E. coli was observed 

throughout the day as the sunlight caused 

inactivation or die-off of bacteria concentrations. The recovery of E. coli concentrations was noted during nighttime, 

as some of the inactivated cells were able 

to recover in the absence of sunlight. 

Secondarily, it was found that sunlight 

inactivation was variable, depending 

on the degree of water contamination; 

higher amount of suspended particles in 

the water diminishes the effect of sunlight. These findings have implications 

for beach managers, as they emphasize 

the importance of E. coli fluctuations 

during the day affecting sampling time 

for beach-monitoring practices. Also, 

although sunlight inactivation of water 

bacteria is widely accepted, this process 

differs depending on the contamination 

level of the nearshore water. 

Embayments as FIB “Traps”

The 63rd Street Beach in Chicago, 

Illinois, is an embayed beach subject to 

high concentrations of E. coli throughout 

the summer. Sand has been identified 

as a significant source of E. coli to the 

beach water at this location (Whitman 

and Nevers, 2003), but the transport 

mechanism for this process has not 

been adequately described. In a study to 

characterize this process mathematically, 

water-quality instruments were deployed 

at the beach to develop wave and current 

profiles. These data were compared to 

E. coli concentrations in the foreshore 

and submerged sediment and in the beach 

water. Additional variables associated 

with the transport of bacteria from sand 

to water (lakebed shear stress and wave 

run-up) also were calculated, confirming the importance of these processes in 

bacteria loading and the concentration of 

E. coli in beach water. These processes 

are particularly important at embayed 

beaches (fig. 3), where beach sand tends 

to concentrate E. coli, and high-wave 

events result in elevated concentrations in 

the monitored swimming water (Ge and 

others, 2012b). Ongoing work is being 

done to explore the circulation patterns 

within these embayed beaches to determine bacteria-transport patterns following resuspension.

Figure 3. Embayed beach reduces 

water exchange and may re-circulate 

contaminated water within the enclosure 

causing impaired water quality.

Coastal Processes Integrated into 

Predictive Modeling

USGS scientists have explored the 

integration of coastal-process models 

(mechanistic models) with managementoriented predictive models (nowcasts) 

to explore the impact of sediment and 

contaminant discharges from rivers or 

river plumes on the dynamics of FIB at 

beaches. In an extensive examination of 

a plume-affected beach on the southern 

coast of Lake Michigan, USGS scientists 

deployed numerous current, wave, and 

water-quality profiling instruments to 

fully characterize the interaction of the 

river plume and beach water (fig. 4). It 

was found that microbial water quality 

at Ogden Dunes beach was significantly 

influenced by plumes coming out of 

Burns Ditch, about 1 mile east of the 

beaches, which tends not to be substantially diluted. Subsequently, refinements 

to Project SAFE (Swimming Advisory 

Forecast Estimate, first introduced in 

2005; Nevers and Whitman, 2005) were 

applied, which improved the accuracy of 

the predictive model, made predictions 

on a real-time basis, and made the data 

available to the public. This integration of 

mechanistic and management-oriented 

predictive models will have an important 

influence on future applications of nowcasts and accurate estimates of human 

health risk. 

Figure 4. Instruments that collect 

continuous measurements of current and 

wave activities, helping scientists build 

more precise predictive models.
Tracking River Flow Into Lake 

Michigan and Onto Adjacent 

Beaches

In 2008, USGS scientists, along with 

Michigan State University researchers, 

performed a dye study at Burns Ditch 

(fig. 5) to track the movement of contaminants that could affect the adjacent 

beaches (Thupaki and others, 2010). 

Studies like this help answer the following questions: (1) What is the relative 

importance of various physical and biological processes influencing the fate and 

transport of E. coli? (2) How much contamination from the river plume is diluted 

as it enters Lake Michigan? (3) How does 

the river plume affect the total E. coli

budget in the nearshore? Using numerical models, scientists found that currents 

in the nearshore are characterized by 

a strong alongshore component and a 

relatively weak cross-shore component; 

thus, contaminant plumes in southern 

Lake Michigan often lengthen along 

multiple beaches (fig. 6). Further, vertical 

turbulent mixing in the water column 

and cross-shore exchanges are significant 

in overall E. coli transport. The results 

have important implications for modeling 

E. coli at recreational beaches affected by 

river outfalls.

E. coli Fluctuations along Illinois 

and Indiana Coastline

USGS scientists have determined 

that there is a persistent background 

concentration of E. coli in the nearshore 

waters of Lake Michigan affecting 

multiple beaches (Nevers and Whitman, 2008; Whitman and Nevers, 2008) 

(fig. 7). The background E. coli concentration interacts with local sources of 

E. coli at specific beaches, and these local 

and background sources influence overall 

E. coli concentrations and therefore 

beach-monitoring results. Simultaneous 

fluctuations of other FIB and markers 

of various types of contamination with 

E. coli concentrations are being explored, 

so that immediate and persistent sources 

can potentially be eliminated. Further 

research will expand into regional detection of different genetic and fecal markers 

present in beach samples, so that the 

influence of large-scale lake processes on 

beach water quality can be determined.

Figure 5. Dye released into Burns Ditch 

helped track the movement of contaminants 

into Lake Michigan.

Escherichia coli

(Colony forming units per 100 milliliters)

350

200

150

100

50

Figure 6. Numerical models simulate the 

fate of the river plume and potential effects 

on nearshore water quality.

Five-year mean log Escherichia coli 

from far north Chicago to 

Michigan City, Indiana

Figure 7. Regional sources may influence 

water quality resulting in similar Escherichia 

coli concentrations at multiple neighboring 

beaches.

Twenty-Three Chicago Beaches 

USGS scientists have explored 

E. coli data collected over 5 years from 

23 Chicago beaches and found patterns 

linking beaches on a regional scale. 

Temporal fluctuations were evident by 

comparing highs and lows in bacteria 

concentrations throughout the summer 

seasons. Spatially, beaches located closer 

together had higher correlations in E. coli

levels. Variables identified for use in a 

regional predictive model were day of the 

year, wave height, and barometric pressure. The model explained up to 40 percent of the variation, which is comparable 

to individual, site-specific models. The 

study by Whitman and Nevers (2008) 

concluded that the regional modeling 

approach helps understand large-scale 

processes affecting fluctuations of E. coli

concentrations. 

Twelve Indiana Beaches 

USGS scientists simultaneously 

examined E. coli fluctuations at 12 

beaches along 35 kilometers of Indiana’s Lake Michigan coastline and built 

an empirical model, which included 2 

variables: wave height and an interactive 

term comprised of wind direction and 

creek turbidity (Nevers and Whitman, 

2008). Regional modeling results were 

similar to previously obtained models 

for individual beaches. The advantage 

of extending the coastline distance for 

modeling purposes is to see broader-scale 

changes in bacteria concentrations over 

time and space (fig. 8).

Figure 8. Water-quality signs inform 

swimmers in Indiana about potential risk 

associated with swimming at the beach.
Glossary

background concentration of 

E. coli Ambient concentration of E. coli

bacteria in the environment from unspecified sources.

E. coli budget Quantitative expression 

of E. coli input and removal. 

embayed beach Usually curved shape 

beach with breakwalls present that limit 

water exchange.

lakebed shear stress The force applied 

to parallel area of lake bottom.

mechanistic models Mathematical 

models which use the laws of physics 

and an understanding of the behavior of 

a system’s components to predict particle 

movement. 

mesocosms Controlled studies set up to 

mimic natural conditions. 

microbial water quality Water-quality 

assessment based on microbial organisms.

nowcast models Mathematical models 

that use quickly obtained measurements 

to predict E. coli concentrations in real 

time.

resuspension of sediments Stirring up 

settled particles from the lake bottom into 

the water column.

solar inactivation Bacterial decay 

during the day caused by ultraviolet solar 

activity.

turbidity A measure of light scattering in the water caused by suspended 

particles.

wave-induced mass transport The 

movement of bacteria from intermediate 

water depths to shallow depths as a result 

of wave motion.

wave run-up Maximum vertical extent 

of waves on a beach shore. 

References

Ge, Zhongfu, Nevers, M.B., Schwab, 

D.J., and Whitman, R.L., 2010, Coastal 

loading and transport of Escherichia 

coli at an embayed beach in Lake 

Michigan: Environmental Science & 

Technology, v. 44, no. 17, p. 6731–

6737.

Ge, Zhongfu, Whitman, R.L., Nevers, 

M.B., and Phanikumar, M.S., 2012a, 

Wave-induced mass transport affects 

daily Escherichia coli fluctuations 

in nearshore water: Environmental 

Science & Technology, v. 46, no. 4, 

p. 2204–2211.

Ge, Zhongfu, Whitman, R.L., Nevers, 

M.B., Phanikumar, M.S., and Byappanahalli, M.N., 2012b, Evaluating the 

role of an embayed beach as a reservoir and a net source of fecal contamination: Limnology and Oceanography, 

v. 57, no. 1, p. 362–381.

Nevers, M.B., and Whitman, R.L., 2005, 

Nowcast modeling of Escherichia 

coli concentrations at multiple urban 

beaches of southern Lake Michigan: 

Water Research, v. 39, no. 20, p. 5250–

5260.

Nevers, M.B., and Whitman, R.L., 2008, 

Coastal strategies to predict Escherichia coli concentrations for beaches 

along a 35 km stretch of southern Lake 

Michigan: Environmental Science & 

Technology, v. 42, no. 12, p. 4454–

4460.

Thupaki, Pramod, Phanikumar, M.S., 

Beletsky, Dmitry, Schwab, D.J., Nevers, M.B., and Whitman, R.L., 2010, 

Budget analysis of Escherichia coli at 

a southern Lake Michigan beach based 

on three-dimensional transport modeling: Environmental Science & Technology, v. 44, no. 3, p. 1010–1016. 

Whitman, R.L., and Nevers, M.B., 2003, 

Foreshore sand as a source of Escherichia coli in nearshore water of a 

Lake Michigan beach: Applied and 

Environmental Microbiology, v. 69, no. 

9, p. 5555–5562.

Whitman, R.L., and Nevers, M.B., 2008, 

Summer E. coli patterns and responses 

along 23 Chicago beaches: Environmental Science & Technology, v. 42, 

no. 24, p. 9217–9224.

Program Information

Funding for USGS beach projects 

and research in the Great Lakes comes 

from a variety of sources including the 

Ocean Research Priorities Plan, the 

USGS, the Great Lakes Restoration 

Initiative, the EPA, the NOAA Center 

for Great Lakes and Human Health, and 

many State and local partner agencies 

and organizations throughout the region.

Contact

James R. Morris, Director

USGS Michigan and Ohio 

 Water Science Centers

614-430-7700

http://greatlakesbeaches.usgs.gov/