EMPACT Beach Water Quality Study

Transcription

1 EMPACT Beach Water Quality Study Madison Department of Public Health Wisconsin State Laboratory of Hygiene U.S. Geological Survey

2 US EPA EMPACT PROGRAM Environmental Monitoring for Public Access and Community Tracking EMPACT grants are no longer available - ended in 2001 Our project was the in the last round of grants awarded An emphasis on getting environmental data to the public

3 Background City had done weekly microbiological testing for about 50 yrs Beach closure decisions were based on these micro results and also observations of physical conditions at beach Closures were communicated via signs at the beaches and press releases

4 Background Problems with existing system Micro results take too long ~ 24 hrs Micro results may not reflect the occurrence of pathogens Often people only discover closures when they showed up at the beach Major differences between beach bacteria levels for no apparent reason

5 Background We looked at the existing system and thought times have changed : analytical methods water quality monitors www Can these changes be used to improve the system?

6 Study Goals Collect environmental, microbial indicator and pathogen data Determine if beach closure decisions can be based on more appropriate and timely data Get the data to the public more rapidly efficiently

7 Study Goals Determine correlations between 1) microbial indicators 2) meteorological, physical and water quality data 3) pathogen occurrence Produce a predictive microbial water quality model Communication to the public of beach water quality Construct a water quality database with dynamic query capability Use F+ coliphage genotyping to evaluate sources

8 Study Beaches - Olbrich

9 Study Beaches - Spring Harbor

10 Study Beaches - Vilas

11 Data Collection 3 types of monitoring: Continuous 15 min data Scheduled collect when the schedule says Event based based on environmental trigger

12 Continuous monitoring Water-quality sondes turbidity, water temp, conductance, dissolved oxygen, chlorophyll

13 Continuous monitoring Met stations rain, wind, air temp

14 Continuous monitoring Pressure transducer for wave data & water level Datalogger & Modem to remotely retrieve the data and control the equipment

15 Continuous monitoring Also got solar radiation data from UW atmospheric sciences and wind and rain data from National Weather Service

16 Scheduled Monitoring Manual samples were collected for indicator organisms: fecal coliform (5X/week) E. coli (5X/week) enterococci (5X/week) F+ coliphage (3X/week) and for pathogens : Salmonella (1X/week) Cryptosporidium (1X/week) Giardia (1X/week) E. coli 0157 (3X/week)

17 Event-based monitoring When certain environmental conditions were met we would collect samples more frequently using autosamplers. Conditions like: Rainfall High turbidity Waves/wind Vilas wave height

18 Event-based monitoring Automatic water quality sampler Datalogger controlled sampling

19 Number of Indicators Collected Number of scheduled and event indicator samples collected Fecal coli. E. coli Enterococci F + coliphage Beach S E S E S E S E Olbrich Spring Harbor Vilas Total S = scheduled sample & E = event sample

20 Number of Pathogens Collected Number of scheduled and event pathogen samples collected E.Coli O157 Giardia Cryptosporidium Salmonella Beach S E S E S E S E Olbrich Spring Harbor Vilas Total S = scheduled sample & E = event sample

21 Results Indicator concentrations were greater in event samples than scheduled samples M edian concentration of indicator microorganisms in event and scheduled samples Scheduled samples Event samples Fecal coliform (CFU/100 ml) E. coli (MPN/100 ml) Enterococci (MPN/100mL)

22 Results Pathogens were found in a higher percentage of event samples than scheduled samples. Percent of event and scheduled samples where pathogens were detected when pathogens were analyzed 60% 50% 40% Scheduled samples Event samples 30% 20% 10% 0% Giardia Cryptosporidium Salmonella aggregated pathogens

23 Results Pathogens were detected in 37% of samples analyzed for pathogens (40 of 108 analyses) Giardia was present most often followed by Cryptosporidium and then Salmonella The initial reaction is that this is a high percentage - but that should be tempered by:

24 Results The levels detected might have been very low so large volumes of water would need to be ingested to cause illness No viability testing was done There were no unusual reports of illness associated with beach activities

25 Results Pathogen detections did not correlate with high indicator levels. Number of pathogen positive samples Number of pathogen positive samples in E. coli concentration ranges at three Madison beaches 108 pathogen samples were analyzed and 40 had positive results (37%) 73% of pathogen positive results were in samples that had E. coli concentraions less than 235/100 ml 90% of pathogen positive results were in samples that had E. coli concentrations less than 1000/100 ml y E. coli concentration range (MPN/100ml)

26 Results F+ coliphage F+ coliphage analysis found both DNA and RNA plaques throughout the study period. All four types of RNA plaques, I through IV, were present at some time during the study period, implying that both human and nonhuman sources influence these beaches.

27 Modeling Results Phase 1: Prediction of exceedance of E. coli standards Used logistic and least squares regression to predict E. coli levels above 1000 and 235 MPN/100ml from environmental conditions. For E. coli above 1000 MPN/100ml The best combined beaches model included specific conductance, wave height and rainfall as predictive variables. For E. coli above 235 MPN/100ml The best combined beaches model included specific conductance, wave height, water temperature and wind speed as predictive variables.

28 Modeling Results Phase 2: Prediction of pathogen presence Models using indicator organisms were not useful Models using environmental variables were not useful

29 Public communication

30 Public communication

31 Public communication On-site information kiosk Public outreach activities by Friends of Lake Wingra Telephone hotline Regular postings to newspapers, TV and radio stations

32 Take home points 1. During event periods, microbial indicator concentrations were higher and microbial pathogens were more likely to be present M edian concentration of indicator microorganisms in event and scheduled samples Scheduled samples Event samples Fecal coliform (CFU/100 ml) E. coli (MPN/100 ml) Enterococci (MPN/100mL)

33 Take home points 2. Pathogen occurrence did not relate to microbial indicator levels Number of pathogen positive samples in E. coli concentration ranges at three Madison beaches Number of pathogen positive samples pathogen samples were analyzed and 40 had positive results (37%) 73% of pathogen positive results were in samples that had E. coli concentraions less than 235/100 ml 90% of pathogen positive results were in samples that had E. coli concentrations less than 1000/100 ml y E. coli concentration range (MPN/100ml)

34 Take home points 3. We COULD use real-time environmental data to predict microbial indicator levels C e coli = Cond Ht AP 3 4. We COULD NOT use real-time environmental data nor microbial indicators to predict microbial pathogen occurrence

35 Thanks Jon Standridge,, WSLH Marty Collins, WSLH Lyle Kleppe,, MDPH Kirsti Sorsa,, MDPH Tommye Schneider, MDPH Lary Larson, Madison IS Steve Corsi,, USGS John Walker, USGS Jim Lorman,, FOLW