Jeanine Chura McCloskey
Master's Student, School of Public Health
The University of Michigan

EPA's Beach Watch

• requiring states with coastal waters to implement standards (new or revised) for pathogens and their indicators by April 10, 2004, 
• requiring the EPA to conduct studies and publish new water quality guidance for pathogens effecting human health by 2005, and 
• allowing the EPA to award grants to states in order for them to implement beach and risk communication programs regarding recreational water quality (2).

Causes of Beach Closures

• Rainfall: sewer overflows, storm water runoff, septic systems
• Boating wastes
• Location:  land-use, sewers
• Number of users
• Animal wastes

Oakland County samples approximately 60 of their 286 beaches yearly; others are on a five-year rotation schedule.  Beaches sampled each year include government owned properties, camps, and commercial beaches (or “pay to enter”) properties.  In addition, any beach that has a history of high bacterial levels, is also sampled each year.  Three 100ml samples of beach water, at waist level, are taken at each assigned beach each week.  The samples are then analyzed for the presence of E-coli.  Initially, if any one of the samples is greater than 300 E-Coli per 100ml the beach must be closed.  After one month of sampling, a rolling geometric mean is calculated and the limit is 130 E-Coli per 100ml.  The testing method is done on-site in the County’s laboratory and results are obtained after 18 hours.  Last summer I had the privilege of interning with the County and worked on the beach program as one of several other responsibilities.  The interns were responsible for sampling their assigned beaches for the amount of E-coli per 100ml at least once per week and determining whether or not the beach should remain open from the results of the tests.  I had noticed throughout the summer that almost every time it rained it seemed as if many  beaches would close the next day. 

Rainfall, indeed, has been shown to be a beach closure predictor for some beaches although its importance in terms of a determinant have been debated.  In a study done in the UK, researchers claim that rainfall is only a minimal component stating that sunshine, wind, and catchment sources were much stronger predictors (Crowther et al. 4029).  Other studies, however, claim that rainfall is a major component.  Studies done in Australia indicated a “linear relationship between visual indicators and bacterial density . . . and rainfall alone as a predictor is equivalent to or better than visual assessment” (Armstrong et al. 249).  Many beaches in Australia use rainfall determined from gauge stations throughout the country to prepare daily beach reports/closures (249).

In this study I compare rainfall and beach closings in Oakland County, for 1998 and 2001, using GIS as the main investigative tool.  Correlations between the two variables is investigated in order to see if this simplified analysis could be utilized for beach closure decision making:  GIS might prove to be an invaluable resource in terms of presenting the spatial relationships between rainfall and rain gauge sites in relation to beach locations.  Results may aid in predictive modeling for E-coli in recreational waters since the present testing methods require at least 18 hours in order to obtain results.  If rainfall alone can be used as a predictor of beach closure in the county then there is the potential to save money spent on beach programs and sampling, to protect individuals from health threats due to "dirty" water, and to avoid time delays waiting for results.

The initial portion of the study determines the “beach closure days” for June and July of 1998 and 2001.  To these, "beaches closed" are then added to a database table.  The rain gauge locations had are geocoded as U.S. street addresses using the Oakland County street layers from the Map Library at UM as a reference theme.  Eighteen rain gauge stations locations are mapped from the twenty-one present (three locations not precise).  The rain gauge locations are saved as a new theme or .shp file.  With gauge stations defined, the rainfall at each station is then incorporated into the database tables for a portion of the month of June (when sampling began) through the end of July in 1998 and 2001.  The appropriate Excel tables are transferred to ArcView 3.2 as .dbf files.  ArcView 3.2 spatial analysis extension is used to determine the rainfall at each closed beach.  The rainfall at the closed beaches on the day of the closure is determined and incorporated into the tables in Excel.  Layouts are produced for each day (June-July) showing the spatial analyst interpolated rainfall distribution for the County and the closed beaches.  Graphs using Excel are made to show the rainfall amounts in hundredths of inches and bacteria levels in #E-coli per 100ml. 

Hardware:  Windows based machine.

Software:  ArcView 3.2 was used to analyze the rainfall and beach closure data.  Microsoft Excel was used to create the data tables of the rainfall and beach closing information.  Adobe photoshop was used to format all layouts for web use.  Gamani Moviegear was used to create the animations. 

2001:  In 2001 there were a total of 29 beaches closed.  Twelve beaches were closed in June with 4 closure days occurring on zero inch rainfall days.  July had 17 closures with 10 closure days occurring on days with zero inches of rain.  The total average rainfall for June and July was 2.6 inches and .90 inches, respectively.

Graphs showing E-Coli/100 ml. versus rainfall (1/100 in.) for the 1998 and 2001 closed beaches suggest that there is not a direct correlation between rainfall and beach closures.  In fact, the graphs suggest that shorter amounts of rainfall may be more indicative of beach closures.  This might be because during short rain storms bacteria get washed into the beach concentrating near the shore, whereas during long storms the bacteria has a chance to disperse further into the lake and not concentrate near the shore and the beach (causing the E.Coli beach levels to diminish).

Most beaches were closed on days that it had rained.  Thirty-two of the 49 beaches closed in 1998 and 15 of the 29 beaches closed in 2001 were on "rainy" days.  Also, if it had not rained on the beach closure day, most beaches recorded rain measurements on the day prior to the closure.  For example, out of the 49 beaches closed in 1998, 10 of these were closed on days recording 0 inches of rain on both the day prior to the closure and the beach closure day itself.  In 2001 there were 5 beaches out of 29 closed that did not receive rain on both the day prior and the day of the closure.  This time factor might make a difference because no data was available on the time the beach was sampled or on the time of the rain gauge measurement.  It must be stressed that this study only took into account rainfall and many other factors including beach location, proximity to sewers and storm drains, amount of use, and animal activity also have the potential to effect bacterial levels and beach closure.

 Future Goals