Using optical sensors to detect sewage contamination in the Great Lakes

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In the Great Lakes, large volumes of sewage never make it to wastewater treatment plants due to illicit discharges and leaking sewer infrastructure, but contamination can be difficult to detect. This study will define the utility and practicality of using optical sensors to identify the sources and timing of sewage contamination in surface water and storm sewers in real-time field settings.

Image showing an optical sensor system used to test wastewater.

Prospective sensor system for on-site measurement of optical properties of water. Water was delivered directly from the sampling location to the sensors for collection of data.

The problem: Sewage contamination is present in many of the rivers that flow into the Great Lakes

There are more than 1,400 wastewater treatment facilities in the United States and Canada that discharge 4.8 billion gallons of treated effluent into the Great Lakes each day. However, a large volume of sewage never makes it to wastewater treatment plants due to illicit discharges and leaking sewer infrastructure. Contaminants such as nutrients, pharmaceuticals, endocrine disruptors, toxic compounds, pathogenic bacteria, and viruses found in sewage can have substantial adverse effects on the aquatic ecosystems. Contamination due to failing sanitary sewage infrastructure is dispersed throughout urban areas and can be difficult to rapidly detect in water with available methods. Without efficient means to locate the contamination sources, the repair and remediation process is very slow.

At present, tools to confidently and rapidly identify sanitary sewage contamination in surface waters in a time-efficient manner are almost non-existent. We can test for indicators often associated with sanitary sewage, like fecal coliforms, and chemical markers, like ammonia; however, the presence of these indicators is not definitive for sewage detection because there are many other sources of these indicators which can incorrectly identify sewage contamination. In addition, these methods take substantial time and resources for laboratory analyses to be completed.



The primary goal of this study is to define the utility and practicality of using optical sensors to identify the sources and timing of human sewage contamination in surface water and storm sewers in real-time field settings. Our team is measuring the optical properties of water samples while simultaneously measuring genetic markers of human bacteria that indicate the presence and magnitude of sewage contamination. Statistical relations between optical properties and genetic bacteria markers will be used to calibrate field sensors for detection of sewage contamination.

Improved methods of gathering information on contamination sources would be valuable at several levels. First, defining how much contamination is present in any given stream will allow water resource managers to prioritize areas where further investigation is needed. Second, the timing and environmental conditions under which contamination is present can help focus remediation efforts on situations in which contamination is most likely to enter the waterways. Third, a rapid means to determine contamination levels would help to track down the location of contamination sources efficiently.

In an effort to develop field sensors that can help achieve these three levels of information gathering, a team of researchers at the U.S. Geological Survey and the University of Wisconsin-Milwaukee are collaborating with sensor manufacturers to refine current field sensor technology and provide rapid assessments of the presence of sewage contamination. This technology could enable results to be available in real time field settings, throughout varying hydrologic conditions from dry weather to rainfall to snowmelt periods, and in multiple watersheds.

This work is being supported by the Great Lakes Protection Fund, the Milwaukee Metropolitan Sewerage District, the Great Lakes Restoration Initiative, and the U.S. Geological Survey.

Why optical sensors?

Human sewage has distinctive characteristics that can be detected in specific regions of the fluorescence and absorbance spectra (referred to as the “optical properties”) that are different from those typically observed in natural waters. Our approach is to characterize the optical properties in stormwater and surface-water samples using laboratory-based instruments and concurrently analyze for human-specific bacteria to verify sewage presence and magnitude. The results from these analyses can be used to determine the optical signals that best predict sewage contamination for development of field sensors.

Fluorescence signal graphs showing emission versus excitation wavelength plots for generic sewage and stream water samples

Example fluorescence signals from sewage and stream samples measured using a laboratory-based instrument. The difference in response between the two sources can be used to identify spectral regions for potential sensors that could be used to identify the presence of sewage in a water sample. [RU, relative fluorescence units]

Optical sensors have been used for over a decade to measure dissolved organic matter in water and are a common tool in water-quality management. Using information from this study, optical sensors will be calibrated to focus on the wavelengths that are most predictive of wastewater contamination. These sensors could then be used by water resource managers to better understand the temporal and spatial variability of wastewater contamination in streams and to more effectively plan watershed management strategies.

Geographic locations monitored

To thoroughly investigate the potential of field-level assessments of sewage contamination, study locations were selected to represent three spatial scales within the Great Lakes Basin including: 

  1. Large-watersheds near the mouth of eight major Great Lakes tributaries. These fixed sampling locations were monitored to develop an understanding of geographic transferability of the sensor technology. (236 samples from July 2011 to June 2013)
  2. Eight small- to medium-sized watersheds in Milwaukee. These fixed sampling locations were chosen in one metropolitan area to investigate the feasibility of prioritizing areas within a small geographic region for targeting management efforts. (189 samples from Feb 2011 to July 2014)
  3. 163 very small subwatersheds. These temporary sampling locations were chosen for a detailed investigation to determine the potential for optical sensors to track a contamination signal from stream to source. (591 samples from August 2014 to Jun 2016)

For all three geographic scales, sampling was designed to determine exactly how optical sensors could be used most effectively to detect sewage contamination. Critical questions include:


  • What will be needed to use optical sensors in new field situations?
  • Will watershed-specific calibrations be needed?
  • Will optical signals change with season?
  • Will optical signals change from year to year?



Illustration showing the locations of the watersheds sampled for sewage contamination

179 locations at three different spatial scales were sampled for sewage contamination.


Photos of a USGS mobile water-quality sampling unit

USGS mobile water-quality sampling unit. The mobile sampling system allows for concurrent measurement of field parameters and raw water sample collection, and provides an efficient way to collect samples at many sites during critical runoff periods.

The sampling operation

Different sampling locations and objectives require different sampling techniques and frequencies. For sampling at fixed stream locations, monitoring structures with dedicated sampling equipment were used to collect samples composited over multiple hours to days. 

  • During periods of low streamflow, samples were collected over 24-hr periods to capture daily variability in contamination levels.
  • During periods of rainfall or snowmelt runoff, sample collection was distributed in time to capture variability throughout the different portions of the runoff event hydrograph.
  • For very small subwatershed sampling locations, mobile water-quality units were used to manually collect samples at multiple sampling locations within the watershed during each sampling event.

Sampling was conducted through at least two years to represent inter-annual variability in optical signals and human-associated genetic markers, and was distributed through the course of the year to represent seasonal variability.

Data collected for this study included a suite of parameters to develop methods to for providing real- time estimations of sewage contamination presence and magnitude in surface water, including:

  • Human-associated genetic markers: Human Bacteroides and Lachnospiraceae
  • General fecal indicator genetic markers: E. Coli and enterococci
  • Optical properties of water: fluorescence and absorbance spectra
  • Other field parameters: turbidity, water temperature, specific conductance, and pH


Photo of a USGS fixed-location water-quality monitoring station

USGS fixed-location water-quality monitoring station

Where do we go from here?

As of spring 2018, we are in the process of analyzing our sampling data to determine effectiveness of optical sensors for wastewater detection. Once this process is complete, we will be able to assess the utility of these sensors, including their ability effectively answer the following questions:

Can optical sensors be used to… 

  • Provide information on presence and timing of wastewater contamination in watersheds to understand the magnitude of the problem?
  • Define seasonal and hydrologic variability for diagnostic information as a starting point for tracking contamination sources?
  • Detect differences within watersheds to direct water quality improvement efforts for focusing on the highest priority subwatersheds?
  • Sense relative differences in storm sewers to follow contamination signals upstream to the source?

The research team:

USGS: Steven R. Corsi, Laura A. DeCicco, Angela M. Hansen, Brian A. Bergamaschi, Peter L. Lenaker, Brian A. Pellerin, Joseph W. Duris, Brett A. Hayhurst

University of Wisconsin-Milwaukee, School of Freshwater Sciences, McLellan Lab: Sandra L. McLellan, Deborah K. Dila, Melinda J. Bootsma

Water Environment Federation: Lisa McFadden, Barry Liner