Tools and Training

Quick Links to Publications

Use the links on this page to access publications and references related to our work with beach pathogen indicators and water quality models, including a list of useful articles and documents [PDF] dealing with statistical modeling of E. coli and other pathogen indicators.

 

Virtual beach software

Virtual Beach is a software package designed to construct site specific multiple–linear regression (MLR) models for predicting pathogen indicator levels at recreational beaches. The MLR analyses outperform persistence models at beaches where conditions, such as weather, hydrology, and human and animal traffic levels change significantly from day to day. Virtual Beach was developed by scientists with the Ecosystems Research Division [exit DNR] of the National Exposure Research Laboratory [exit DNR] at the U.S. Environmental Protection Agency’s Office of Research and Development.

The original version of Virtual Beach –– Virtual Beach–Model Builder 1.0 –– was pilot–tested, revised and finalized in the summer of 2009. Virtual Beach–Model Builder 1.0 is the focus of the training materials posted below. The software can be downloaded from the Integrated Environmental Modeling hub website [exit DNR].

Hands–on training materials

Wisconsin DNR staff conducted two hands–on training workshops for local beach managers in 2009:

Video recording

For beach managers or others interested in building multivariate statistical models to "nowcast" pathogen indicator levels at their beach, we have posted video recordings of the State of Lake Michigan–Great Lakes Beach Association workshop. These videos accompany the learning modules and example data provided below.

Learning modules

We developed the following learning modules for our workshops.

Learning Module I – Model Building [PDF]
In this module you will learn how to:

  • format and import data tables
  • evaluate data using scatter plots
  • transform variables
  • exclude unwanted observations and variables
  • check for multicollinearity (non–independence)
  • convert wind speed and direction into "longshore" and "onshore" and
  • create interaction terms (combined variables)

Learning Module II – Model Evaluation and Nowcasting [PDF]
In this module you will learn how to:

  • fit models
  • identify influential outliers
  • identify best, unbiased models
  • make single–day predictions with 95% confidence intervals
  • make real–time predictions ("nowcasts")

Example Data

The DNR compiled example data to be used with the learning modules. The data are from the 2003, 2004, and 2005 beach seasons for Red Arrow Park Beach in Manitowoc.

Other resources

For additional guidance on building and evaluating models, see:

Important links

Our work with bacteria forecasting models is part of a broader effort by the EPA–led Midwest Spatial Decision–support Systems Partnership [exit DNR] to develop, promote, and disseminate web–based, spatial decision–support tools for watershed management and land–use decision making. Our outreach and technical assistance builds on Wisconsin DNR’s "Computer Tools for Planning, Conservation, and Environmental Protection" project.

Last revised: Friday April 19 2013