Enhance Great Lakes Beach Recreational Water Quality Decision Making
COMING SOON... A web services tool was developed to integrate GLRI monitoring data with related ancillary data sets. This web services tool was developed to collect spatially processed meteorological, hydrodynamic, and other environmental data. Current available datasets include USGS and NOAA with the intention to add more as they become available. The application allows for spatial visualization of data from multiple sources. The application also provides sorted, processed data in a single, delimited file for use in beach predictive models.
Important questions about beach closures and management remain unanswered in the Great Lakes where over 500 beaches are routinely used along the nearly 11,000 miles of coastline. The economies of coastal areas are dependent on public confidence in the quality of water at the shoreline, and beach managers need reliable science-based information to make beach closure and beach management decisions.
Scientists in USGS Science Centers in the Great Lakes are leading or involved in much of the research on cost effective ways to make beach closure decisions as well as on a more complete understanding of microbiological science relevant to making effective beach management decisions. Each aspect of the work accomplished within this element of the GLRI will draw on a vast amount of U.S. Geological Survey data and expertise in microbiology, hydrology, coastal processes, instrumentation, methods development, and modeling.
The work proposed in this workplan continues over a decade of efforts by USGS scientists and their partners to improve our knowledge of the underlying science of beaches as it relates to human health impacts and provide improved tools and techniques that can be used by the beach health management community.
This workplan builds upon existing and planned work being accomplished through partner supported projects at the federal, state, and local level; will be coordinated with both NOAA and USEPA efforts; and is aligned with the USGS Ocean Research Priorities Plan project entitled, “Improving Great Lakes Coastal Recreation Water-Quality Monitoring and Forecasting.”
There are three major elements for Beach Health in the USGS GLRI—real-time assessments, data management and evaluation, and methods for pathogen detection. These efforts will be coordinated with EPA and NOAA through an existing interagency team formed to coordinate federal agency efforts on beach health issues in the Great Lakes.
For real-time assessments
The overall goal is to expand the use of operational nowcast systems and rapid analytical methods to additional beaches around the Great Lakes and conduct research to improve existing predictive models used in nowcasts. These activities will be done to improve the timeliness and accuracy of beach closures and advisories. USGS investigators will work directly with stakeholders to collect and analyze data for developing predictive models and (or) applying rapid analytical methods at a variety of Great Lakes beaches. This work will draw on and inform ongoing USGS efforts to develop regionalized models, explore methods for pathogen and microbial source tracking (MST) marker detection, and identify physical, biological, and coastal processes that influence the occurrence and abundance of key bacteria and pathogens from point and non-point sources. Specific objectives for 2010 are the following:
- Continue to improve and refine existing predictive models used in nowcasts by incorporating new variables, exploring alternative processing techniques of existing variables, using in-situ real-time measurements, collecting afternoon samples, investigating the use of alternate dependant variables, and testing new statistical techniques.
- Establish relationships with local agencies and begin collecting data to expand the use of operational models at a variety of different beaches around the Great Lakes. (Two years of data collection are generally needed to develop predictive models).
Real time assessments:
Objective 1: The USGS will improve and refine current predictive modeling activities to develop more accurate predictions of water quality and enhance management capabilities. During 2010, this work will be done at 5 beaches with nowcast systems already in place. A USGS modeling workgroup will meet monthly by conference call to review and discuss data collection activities and modeling strategies. As part of existing monitoring programs or with locally-secured GLRI funding, local agencies will collect samples at each beach at least 4 mornings each week during the recreational season, and analyze samples for E. coli (using standard methods) and turbidity, measure wave heights using a graduated rod, and note field observations. Additional work with USGS GLRI funding is listed below.
Ohio. Work will be done at 2 beaches as part of the Ohio Nowcast (http://www.ohionowcast.info)-- Edgewater (Cleveland) and Huntington (Bay Village). Daily data are collected by the Northeast Ohio Regional Sewer District (NEORSD) and Cuyahoga County Board of Health.
- Perform data analysis and develop updated models for 2010.
- Work with USEPA to compare models developed by use of Virtual Beach to those developed using existing modeling procedures.
- Include the use of new statistical techniques, new predictor variables and alternative processing of variables as described, combining collinear variables, and using an onshore/ offshore/ alongshore wind variable.
- Update the Ohio Nowcast web site with current information
- Continue real-time data collection from the wave buoy, radiation sensor, and turbidity probe at Huntington and the wave buoy, rain gage, and piezometer at Edgewater.
- Continue afternoon sampling at Huntington (cooperator in-kind services)
- Add the analyses of morning samples for enterococci.
- Investigate the use of variables for antecedent sand moisture and scouring (the use of scour ropes to estimate sand gain or loss to the lake) (cooperator in-kind services) and for sheer stress.
Wisconsin. At Upper Lake Park Beach (Port Washington), models have been developed and are used for beach advisories by the Ozaukee County Health Department and Wisconsin DNR.
- Perform data analysis and develop models for 2010. Compile available historical data and conduct data analysis.
- Develop modeling options using multiple statistical techniques, new predictor variables, decomposition of directional vector variables into orthogonal components, alternative processing of variables, and combining collinear variables.
New York. At Ontario and Durand beaches (Rochester), models have been developed and are used for beach advisories and closings by the Monroe County Health Department.
- Perform data analysis and develop updated models for 2010. Include the use of new statistical techniques and new predictor variables.
Objective 2: USGS will expand modeling activities to additional beaches and begin to develop regional models for extended shorelines, where applicable. To do this, the USGS will work with local agencies in 10 areas selected to provide good geographic coverage of Great Lakes beaches and based on the willingness of local agencies to participate. Areas are also selected if they include beaches that are good candidates for modeling; that is, beaches that exceed recreational water-quality standards 8-30% of the time with large swimmer populations. From these areas, beaches will be selected to include a range of different types of beaches and sources of fecal contamination.
1st and 2nd quarters 2010. The USGS will contact potential cooperators to determine their level of interest and encourage them to apply for GLRI funding to expand their local monitoring programs. We will visit any areas and gather information on beaches to make the final selection, if needed. A list of potential areas, with beach and cooperator information include, but are not limited to, the following:
- Illinois, Chicago area, Lake Michigan. A number of beaches in Cook County are good candidates for predictive modeling. Contact will be made to establish relationships with municipalities in this area.
- Michigan, southwest, Lake Michigan. Berrien County has 21 Lake Michigan beaches, including Silver Beach (where sand was implicated as a health hazard), beaches in natural areas, and beaches impacted by agricultural sources. The Berrien County Health department has expressed interest in developing predictive models.
- Michigan, southeast, Lake St. Clair. The USGS developed predictive models for two Lake St. Clair beaches, but the models are not operational. Macomb and Oakland counties have extremely willing cooperators, and collaborations with NOAA at some sites are possible.
- Michigan, northwest, Grand Traverse Bay. The USGS previously studied beaches in Grand Traverse Bay. The Grand Traverse Health Department is eager to develop predictive models.
- Michigan, east central, Saginaw Bay. Work has been done by the USGS and other researchers to identify sources of fecal contamination and pathogens at beaches and in the watershed. The Michigan Beach Coordinator identified Caseville County Park as a good candidate for predictive modeling. Two local health departments have expressed interest in developing predictive models.
- New York, Lake Erie. The NY Beach Coordinator identified Woodlawn Beach as a good candidate for predictive modeling; other beaches in Erie County may also be suitable. Contact will be made to establish relationships with the Erie County Health Department.
- Ohio, northwest, Lake Erie. At Maumee Bay State Park (Oregon), the USGS has been working with the University of Toledo (UT) to collect data, develop predictive models, and add Maumee Bay to the Ohio Nowcast. The UT has agreed to apply for GLRI funds and work with the USGS to analyze data from 2008-09, develop predictive models, and validate the models.
- Ohio, northeast, Lake Erie. The USGS will identify a second area and will initiate work with local agencies to collect data and develop predictive models. Candidate areas include Ashtabula County, Lake County, and Lorain County, where contacts with local agencies have already been made.
- Pennsylvania, Lake Erie. The USGS worked with local agencies in 2004-06 to develop predictive models, but because of funding issues, the work ceased in 2007. There are 10 beaches at Presque Isle State Park (Erie), and some may be suitable for regional models. The Erie County Health Department would like to continue working with the USGS.
- Wisconsin, Lake Superior. Several beaches in Douglas County are good candidates for predictive modeling. Contact will be made to establish relationships with the local monitoring agency.
- Wisconsin, southeast, Lake Michigan. Many beaches along the coastline in this area are good candidates for predictive modeling, and some have models already being used by local agencies. Contact will be made to establish relationships with Kenosha, Manitowoc, and Sheboygan County agencies.
After finalizing the list of areas and beaches, the USGS will write sampling plans and protocols, QA/QC requirements, provide lists of equipment and supplies, and design field/lab forms and data spreadsheets. The USGS will work with local agencies to complete a sanitary survey at each beach and will provide training for any project activity, if needed.
3rd and 4th quarters 2010. Cooperators will monitor the beaches during the recreational season for E. coli and enterococci at least 4 days/week and collect and compile environmental and water-quality data for predictive models. The USGS will work with local agencies to ensure high quality data sets are collected. This will include the following USGS activities:
- Review sanitary surveys to help identify model variables.
- Help cooperators to measure or identify sources of data for explanatory variables for predictive models, including rainfall, stream flow, wind speed/direction, current direction, solar radiation, turbidity, etc.
- Regularly check cooperator data spreadshseets for proper data entry and accuracy.
- Conduct several QA/QC field and lab visits, as needed.
- Provide QA/QC samples, monitor performance, and take any corrective actions.
- Provide any technical guidance needed throughout the sampling period.
- Establish sites and cooperator codes for data entry into NWIS QWDATA.
- Install and maintain any equipment to measure real-time variables, as needed, and provide these data in real-time on NWIS Web.
Data Management and Evaluation:
Objective 1 - Data Compilation and Integration: USGS staff from the Center for Integrated Data Analytics (CIDA) in Middleton, WI have been the primary database managers for WI beach data since prior to the US Beach Act of 2000. In their data management capacity they have developed data assembly methods, maintained databases, designed and maintained the State’s Beach Health web page, and developed protocols for transferring data in the correct form to the USEPA STORET database on behalf of beach managers. WI beach managers collect and record information beyond that required by the USEPA for STORET. These ancillary data include water quality and environmental variables. These ancillary data are available for public access at the WI Beach Health web page, via CIDA. Recently CIDA has been developing a digital form for recording sanitary survey data at WI beaches. Therefore, CIDA is already intimately familiar with WI beach data.
However, as for other beaches in the Great Lakes, beach monitoring data and ancillary data from WI beaches is not integrated with other data, such as meterological data from NOAA, that would be useful for developing predictive models or evaluating conditions that influence bacteria concentrations at beaches. The goal of this objective is to compile and integrate all such data. Under this objective, CIDA will use Extraction, Transformation, and Loading (ETL) technology to process fields to a common data standard to facilitate integration of the data sets, and will use web services to output integrated data.
Products: One product will be example digital templates for data entry that might lead to a common data standard for Great Lakes beaches. The effort will show how field data collected at the beach can be entered and managed efficiently and integrated with public data, for specific purposes. A second product will be demonstration of integrated data access and assembly via web services.
Objective 2 - Develop an Integrated Beach Data Access (IBDA) Pilot: MI WSC will develop a GIS coverage in the GIS Beach Analysis Tool that will demonstrate how the integrated data set can be accessed through this example web-based portal. CIDA will provide support to Michigan in accessing the integrated data, and Michigan will develop the appropriate coverage layer such that selection of a beach point leads to the integrated data set.
Product: The IBDA Pilot will demonstrate for selected WI beaches how beach data can be assembled and accessed for a specific purpose, and how such data can be accessed via a web-based portal. The IBDA Pilot will also demonstrate how public data (e,g. Federal agency data) can be accessed and simplified for the beach manager.
Objective 3 - Data Assessment and Evaluation of Options for Common Beach Data Access and Integration: The primary goal of this objective is to evaluate options for data collection and integration for other beaches in the Great Lakes. This objective is slightly more challenging than for WI beach data because 1) each state (and in some states, each local management agency) collects and records data in different ways; and 2) ancillary data collected also varies by management agency. The first step in this objective is to conduct a data assessment for up to six selected beaches across the Great Lakes. MI WSC has already developed some understanding of which States or localities collect ancillary beach data, through prior year ORPP efforts. Beaches will be selected based on prior information about ancillary datasets available, as well as communication with State beach managers. This objective will require participation by Great Lakes data managers to supply information about their available data, and willingness to share such data sets. Therefore, such willingness will also guide beach selection for this objective. The types of data needed for Great Lakes beaches include: the data owner, how the data is accessed, data dictionary information (data field types, length, domains, etc.), geographical coverage, temporal coverage, completeness, quality of the data (if it can be determined), and known dataset issues. Once the types and formats of beach data are known, example data templates and protocols that would allow data access and integration for e.g., predictive modeling purposes, can be determined.
Product: Given the many unknowns regarding the data access and integration issues for beaches in states other than WI, a reasonable product for FY2010 is a summary of the issues and challenges. This product could be a presentation at various stakeholder meetings, including the Great Lakes Beach Association meeting in FY2011. At this time (October 2009) we acknowledge that other data access and integration efforts under GLOS and GLRI, and within USEPA specifically for the purposes of their Virtual beach predictive modeling tool, are beginning to develop. This proposal seeks to foster and maintain discussions with these other efforts, and these discussions will likely guide further product development.
A secondary goal of this objective is to explore a common means to assemble and serve data for ORPP science. It is likely that at least one selected beach will be an ORPP focus beach, at which a variety of environmental variables are measured. This step will include integration with the Real-Time Assessments Proposal FY2010 (Francy and others). Data collected by ORPP scientists at beaches are similar to those determined by beach managers but there are some differences: 1) data collection is of greater duration or intensity; 2) some data collection may be automated (e.g., buoy data); and 3) and the scientific or reporting needs for this data are different than those of typical beach managers. Nevertheless, with advancement of Great Lakes Observing Systems efforts and sensor technologies, there will be a need for integration of such data. This effort will explore how such data can be entered, assembled, and integrated for research as well as public information needs.
Product: The primary product will be an internal database for ORPP research at the selected beach.
Stakeholder Participation: A variety of stakeholders have been identified in the Introduction and Objectives. Specific stakeholders include the other Federal agencies maintaining beach-relevant public databases (USEPA and NOAA); State, Federal and local beach managers; stakeholders with an interest in beach data assembly, integration and access (e.g., developers of Virtual Beach, GLOS, GLC, data managers at the state or local level, university scientists). Stakeholder engagement will take place via attendance at meetings and conferences, and specific discussions fostered by ORPP and/or GLRI, GLOS or other regional efforts.
Objective 4 - GIS Beach Analysis Tool and Evaluation of Factors Influencing Beach Monitoring Data: Facilitation of assembly of data and the potential role of the GIS Beach Analysis Tool as the portal for accessing beach data (ORPP Data Analysis and Interpretation long-term Goals C, D and E2) is described in a different proposal (submitted by Emmanuelli, Haack, Corsi, Jodoin). The goals of scientific evaluation and interpretation of beach water quality, and of enhancing beach water quality communication inform this proposal. The specific objectives for FY2010 (highlighted in italics below) are aligned completely with the long-term Goals A, B, E and F of the ORPP Data Analysis and Integration theme, as taken directly from the ORPP Five-year Science Plan:
- Compile in a GIS geographic coverages likely to be related to beach water
- -Initial coverages related to factors already identified as influencing beach water quality (completed).
- -Adapt coverages as new information reveals additional factors
- Develop a public-accessible, web-based, interactive GIS that allows
visualization of Great-Lakes- wide data and selected features associated with
beaches (Great Lakes Beach GIS) (initial version completed).
- -Subsequent development based on stakeholder feedback
- Use the GIS and database to support and expand ORPP science
- -Conduct Great-Lakes-basin-wide analyses of patterns of beach water quality data.
- -Examine E. coli data for spatial patterns
- -Conduct analysis using GIS to evaluate spatial patterns with respect to landscape variables
- -Explore integration of the time-variable central database with the Great Lakes recreational water quality GIS database.
- -Conduct Great-Lakes-basin-wide analyses of patterns of beach water quality data.
Methods of Pathogen Detection:
Objective 1: The USGS will work with cooperators in 6 areas to enable technology transfer of the IMS/ATP method and collect data to compare IMS/ATP, QPCR, and culture results at a variety of different beaches. These include beaches in Erie County (Ohio), along the western shore of Lake Erie (Toledo, Ohio), beaches in northeast Ohio (NEORSD), Macomb County (Michigan), City of Racine (Wisconsin), and City of Chicago (University of Illinois-Chicago). As part of existing monitoring projects or with locally-secured GLRI funding, local agencies will collect samples 3 mornings each week for 8 weeks and analyze samples for E. coli (using a standard method and IMS/ATP) and turbidity, measure wave heights using a graduated rod, note field observations, and freeze filters for QPCR analyses. USGS activities include the following:
- Continue to work with the Erie County Health Department, Northeast Ohio Regional Sewer District, and City of Chicago and initiate work with the City of Toledo, Macomb County Health Department, and City of Racine to provide technology transfer of the IMS/ATP method and test the QPCR method. Provide training for analysis of samples by IMS/ATP and freezing of filters for subsequent analysis by QPCR. Provide supplies and equipment to local agencies, as needed.
- The Ohio Water Microbiology Laboratory will analyze samples by QPCR from 2009 from one Erie County beach and from 2010 from all six beaches for E. coli and enterococci. The data will be used to determine the relations between IMS/ATP or QPCR and standard method results. Funds will be used to purchase a new thermalcyler for QPCR analysis recommended by USEPA for beach monitoring. The new system is less expensive, faster, and more versatile than older units.
- The USGS will augment existing work on pathogen detection at beaches by developing and testing new molecular pathogen detection techniques and expanding work to additional beaches around the Great Lakes.
Objective 2: The USGS will work with a non-federal partner to develop a hands-on training workshop for rapid analytical methods. Activities include preparing a workshop announcement, organizing registration/logistics, preparing an agenda and presentations, organizing a lab practical, and compiling an equipment/supply list. The training will be given in all 8 Great Lakes states, beginning with 4 states in 2010. The USGS will also consult with local and state agencies that are working on developing the capability to run QPCR; this includes providing hands-on training and troubleshooting, as needed, and answering questions through email or phone calls.
Objective 3: The USGS will work with a non-federal partner to develop a hands-on training workshop for rapid analytical methods. Activities include preparing a workshop an
Real time assessments:
Future efforts would be directed at continuing to expand and improve predictive modeling activities by increasing the number of beaches with models and integrating additional model improvements. Support would also continue for offering technical assistance to beach managers.
After two years of data-collection in the areas described above, the USGS will work with local agencies to develop models and initiate an operational nowcast system. This will include applying the use of USEPA’s Virtual Beach program, whenever feasible. This effort will involve coordination with NOAA to improve the integration of data for model development (including, but not limited to, statistical and hydrodynamic data) and identification of opportunities for design of alternative models.
We will begin to incorporate research for development of “next generation" models that include processes that may be beach- or region- specific. Some models will incorporate new parameters based on ongoing USGS research including variables that quantify swash/wave dynamics, solar radiation, and microbial life cycle processes and models with pathogens as dependent variables.
Data Management and Evaluation:
Continue to maintain and update the data assessment as a tool for beach managers to find data and inform others about their available datasets. Build a web interface for dataset managers to contribute and update the information about their datasets (mybeach.gov?) that provides information to beach data managers on best practices for creating and serving datasets that can be integrated. Based on information gathered during the pilot, or in subsequent data evaluations, recommend a standard for reporting beach-related data. Relate data tiers (levels of data collections and recording) to applications/services that can be used with that tier of data, via a GIS coverage. Example: “Data Tier X -- beach can use Virtual Beach for predictive modeling.” Expand the pilot to all Great Lakes beaches that fall within certain data tiers and, eventually, all Great Lakes beaches. Work closely with stakeholders to identify specific USGS database roles and products.
As FY2010 unfolds, a variety of beach and nearshore investigations, funded by ORPP and/or GLRI will take place. In addition, there is great interest among stakeholders, from USEPA down to local beach mangers, in better communication of beach-related data. There will be need among ORPP researchers, and among stakeholders, for beach or nearshore-related GIS, and for tools that enhance communication of beach data. Therefore, the plan for FY2011 and beyond is to remain flexible in supporting these needs, and to work closely with stakeholders to identify the best information tools, and the best platforms for providing complex environmental data such as beach monitoring and ancillary data (regardless of which agency ultimately takes over the “service” portion of this work). We also plan to advance the science of beach monitoring by demonstrating, through the GIS, the Beach Analysis Tool, and through journal articles, the influence of environmental setting and scale on beach water quality data.
Methods of pathogen detection:
Technology transfer and testing of the IMS/ATP method will be complete at the Erie County Health Department by 2011 and at the City of Toledo and Macomb County Health Department by 2012. We hope to expand the use of IMS/ATP to other agencies within the Great Lakes in 2011 and beyond.
The data and information collected by sanitary surveys could be very useful in providing a rich data set of Great Lakes beach information that could be used by researchers to develop a wide range of tools and information useful to beach mangers.
Beach closure and advisory information based on predictive models will be provided through internet-based nowcast systems by more agencies around the Great Lakes.
A template fact sheet for the general public on why and how predictive models are used for beach closure or advisory decisions that can be tailored to include local information on beaches and associated local issues.
Potential Manuscripts/Reports include:
- The status of the use of rapid assessments throughout the Great Lakes—5 years of progress.
- The development and testing of predictive models at selected Great Lakes beaches including the incorporation of new model variables and statistical techniques, utilization of real-time sensors, and application of alternative dependent variables.
- Perspectives on beach-specific versus regional modeling at different scales and on factors that influence bacterial-indicator models at different categories of beaches.
- Applying the use of rapid analytical methods (IMS/ATP and QPCR) and comparison to standard methods for bacterial indicators at Great Lakes beaches.
- Pathogen detection methods suitable for beach monitoring studies.
Report on USGS/NOAA/USEPA Great Lakes Beach Health Research Needs Workshop of November 4, 2005
Francy, D.S., 2009, Use of predictive models and rapid methods to nowcast bacteria levels at coastal beaches, Aquatic Ecosytem Health & Management, v. 12, no. 2, p. 177-182.
SOLEC Report. 2008. 11th Biennial Report. Desired Outcomes: Swimmability. http://www.ijc.org/php/publications/html/11br/english/report/chapter1/outcomes_swim.html
US EPA. 1999. Action plan for beaches and recreational waters. EPA/600/R-98/079, US Environmental Protection Agency, Washington, DC.
Water Environment Research Foundation. 2009. Experts Scientific Workshop on Critical Research and Science Needs for the Development of Recreational Water Quality Criteria in Inland Waters. 18-20 February 2009, Dallas/Ft. Worth, TX.
Whitman, R. L. and M. B. Nevers. 2009. Policies and Practices of Beach Monitoring in the Great Lakes: A Report to the International Joint Commission. US Geological Survey, Porter, Indiana.
Point of Contact: