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Amie M. G. Brady

Publications and source records attributed to Amie M. G. Brady.

17 recordsLinked to original sources
USGS2013

Comparing rapid and culture indicator bacteria methods at inland lake beaches

A rapid method, quantitative polymerase chain reaction (qPCR), for quantifying indicator bacteria in recreational waters is desirable for public health protection. We report that replacing current Escherichia coli standards with new US Environmental Protection Agency beach action values (BAVs) for enterococci by culture or qPCR may result in more advisories being posted at inland recreational lakes. In this study, concentrations of E. coli and enterococci by culture methods were compared to concentrations of Enterococcus spp. by qPCR at 3 inland lake beaches in Ohio. The E. coli and enterococci culture results were significantly related at all beaches; however, the relations between culture results and Enterococcus spp. qPCR results were not always significant and differed among beaches. All the qPCR results exceeded the new BAV for Enterococcus spp. by qPCR, whereas only 23.7% of culture results for E. coli and 79% of culture results for enterococci exceeded the current standard for E. coli or BAV for enterococci.

Lake and Reservoir Management↗
USGS2013

Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection

Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the E. coli standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day's E. coli concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. Cryptosporidium , adenovirus, eaeA ( E. coli ), ipaH ( Shigella ), and spvC ( Salmonella ) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to E. coli concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.

Ohio↗
USGS2013

Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples

Bacterial indicators are used to indicate increased health risk from pathogens and to make beach closure and advisory decisions; however, beaches are seldom monitored for the pathogens themselves. Studies of sources and types of pathogens at beaches are needed to improve estimates of swimming-associated health risks. It would be advantageous and cost-effective, especially for studies conducted on a regional scale, to use a method that can simultaneously filter and concentrate all classes of pathogens from the large volumes of water needed to detect pathogens. In seven recovery experiments, stock cultures of viruses and protozoa were seeded into 10-liter lake water samples, and concentrations of naturally occurring bacterial indicators were used to determine recoveries. For the five filtration methods tested, the highest median recoveries were as follows: glass wool for adenovirus (4.7%); NanoCeram for enterovirus (14.5%) and MS2 coliphage (84%); continuous-flow centrifugation (CFC) plus Virocap (CFC+ViroCap) for Escherichia coli (68.3%) and Cryptosporidium (54%); automatic ultrafiltration (UF) for norovirus GII (2.4%); and dead-end UF for Enterococcus faecalis (80.5%), avian influenza virus (0.02%), and Giardia (57%). In evaluating filter performance in terms of both recovery and variability, the automatic UF resulted in the highest recovery while maintaining low variability for all nine microorganisms. The automatic UF was used to demonstrate that filtration can be scaled up to field deployment and the collection of 200-liter lake water samples.

Michigan, New York, Ohio, Wisconsin↗
USGS2013

Microbial source tracking as a tool for TMDL development, Little Blue River in Independence, Missouri

The Little Blue River in Jackson County, Missouri has been listed by the Missouri Department of Natural Resources as impaired by bacteria for the protection of aquatic life and contact recreation from urban point and nonpoint sources. The Clean Water Act requires that a total maximum daily load (TMDL) for Escherichia coli (E. coli) be developed. Over a 5-year period, 108 base-flow, 87 stormflow, 48 fecal source, and 12 sewage influent samples were collected and analyzed for E. coli and Bacteroides general and host-associated microbial source tracking (MST) genetic markers. Less than half of the main-stem base-flow samples exceeded the E. coli state standard, whereas, all of the stormflow samples exceeded the standard during the recreation season (April through October). Both E. coli and MST markers were detected more frequently and at higher concentrations in stormflow samples. Only 14 percent of samples with E. coli detections greater than the Missouri state standard of 206 colonies per 100 milliliters had the human-associated Bacteroides marker as the only identified marker; therefore, Little Blue River TMDL development may require a broader scope beyond the municipal separate storm sewer system if bacteria sources are to be identified and addressed. Fecal samples showed a greater specificity with the human-associated marker than the dog- or ruminant-associated Bacteroides markers; however, false positives were at least one order of magnitude lower than true positives. MST data may be a useful tool for identifying probable sources of contamination and directing TMDL strategies.

Missouri↗
USGS2013

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.) . Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Great Lakes↗
USGS2012

Comparative effectiveness of membrane bioreactors, conventional secondary treatment, and chlorine and UV disinfection to remove microorganisms from municipal wastewaters

Log removals of bacterial indicators, coliphage, and enteric viruses were studied in three membrane bioreactor (MBR) activated-sludge and two conventional secondary activated-sludge municipal wastewater treatment plants during three recreational seasons (May-Oct.) when disinfection of effluents is required. In total, 73 regular samples were collected from key locations throughout treatment processes: post-preliminary, post-MBR, post-secondary, post-tertiary, and post-disinfection (UV or chlorine). Out of 19 post-preliminary samples, adenovirus by quantitative polymerase chain reaction (qPCR) was detected in all 19, enterovirus by quantitative reverse transcription polymerase chain reaction (qRT-PCR) was detected in 15, and norovirus GI by qRT-PCR was detected in 11. Norovirus GII and Hepatitis A virus were not detected in any samples, and rotavirus was detected in one sample but could not be quantified. Although culturable viruses were found in 12 out of 19 post-preliminary samples, they were not detected in any post-secondary, post-MBR, post-ultraviolet, or post-chlorine samples. Median log removals for all organisms were higher for MBR secondary treatment (3.02 to >6.73) than for conventional secondary (1.53-4.19) treatment. Ultraviolet disinfection after MBR treatment provided little additional log removal of any organism except for somatic coliphage (>2.18), whereas ultraviolet or chlorine disinfection after conventional secondary treatment provided significant log removals (above the analytical variability) of all bacterial indicators (1.18-3.89) and somatic and F-specific coliphage (0.71 and >2.98). Median log removals of adenovirus across disinfection were low in both MBR and conventional secondary plants (no removal detected and 0.24), and few removals of individual samples were near or above the analytical variability of 1.2 log genomic copies per liter. Based on qualitative examinations of plots showing reductions of organisms throughout treatment processes, somatic coliphage may best represent the removal of viruses across secondary treatment in both MBR and conventional secondary plants. F-specific coliphage and Escherichia coli may best represent the removal of viruses across the disinfection process in MBR facilities, but none of the indicators represented the removal of viruses across disinfection in conventional secondary plants.

Water Research↗
USGS2012

Development and implementation of a regression model for predicting recreational water quality in the Cuyahoga River, Cuyahoga Valley National Park, Ohio 2009-11

The Cuyahoga River within Cuyahoga Valley National Park (CVNP) is at times impaired for recreational use due to elevated concentrations of Escherichia coli (E. coli), a fecal-indicator bacterium. During the recreational seasons of mid-May through September during 2009–11, samples were collected 4 days per week and analyzed for E. coli concentrations at two sites within CVNP. Other water-quality and environ-mental data, including turbidity, rainfall, and streamflow, were measured and (or) tabulated for analysis. Regression models developed to predict recreational water quality in the river were implemented during the recreational seasons of 2009–11 for one site within CVNP–Jaite. For the 2009 and 2010 seasons, the regression models were better at predicting exceedances of Ohio's single-sample standard for primary-contact recreation compared to the traditional method of using the previous day's E. coli concentration. During 2009, the regression model was based on data collected during 2005 through 2008, excluding available 2004 data. The resulting model for 2009 did not perform as well as expected (based on the calibration data set) and tended to overestimate concentrations (correct responses at 69 percent). During 2010, the regression model was based on data collected during 2004 through 2009, including all of the available data. The 2010 model performed well, correctly predicting 89 percent of the samples above or below the single-sample standard, even though the predictions tended to be lower than actual sample concentrations. During 2011, the regression model was based on data collected during 2004 through 2010 and tended to overestimate concentrations. The 2011 model did not perform as well as the traditional method or as expected, based on the calibration dataset (correct responses at 56 percent). At a second site—Lock 29, approximately 5 river miles upstream from Jaite, a regression model based on data collected at the site during the recreational seasons of 2008–10 also did not perform as well as the traditional method or as well as expected (correct responses at 60 percent). Above normal precipitation in the region and a delayed start to the 2011 sampling season (sampling began mid-June) may have affected how well the 2011 models performed. With these new data, however, updated regression models may be better able to predict recreational water quality conditions due to the increased amount of diverse water quality conditions included in the calibration data. Daily recreational water-quality predictions for Jaite were made available on the Ohio Nowcast Web site at www.ohionowcast.info. Other public outreach included signage at trailheads in the park, articles in the park's quarterly-published schedule of events and volunteer newsletters. A U.S. Geological Survey Fact Sheet was also published to bring attention to water-quality issues in the park.

Ohio↗
USGS2011

Quantifying viruses and bacteria in wastewater—Results, interpretation methods, and quality control

Membrane bioreactors (MBR), used for wastewater treatment in Ohio and elsewhere in the United States, have pore sizes small enough to theoretically reduce concentrations of protozoa and bacteria, but not viruses. Sampling for viruses in wastewater is seldom done and not required. Instead, the bacterial indicators Escherichia coli (E. coli) and fecal coliforms are the required microbial measures of effluents for wastewater-discharge permits. Information is needed on the effectiveness of MBRs in removing human enteric viruses from wastewaters, particularly as compared to conventional wastewater treatment before and after disinfection. A total of 73 regular and 28 quality-control (QC) samples were collected at three MBR and two conventional wastewater plants in Ohio during 23 regular and 3 QC sampling trips in 2008-10. Samples were collected at various stages in the treatment processes and analyzed for bacterial indicators E. coli, fecal coliforms, and enterococci by membrane filtration; somatic and F-specific coliphage by the single agar layer (SAL) method; adenovirus, enterovirus, norovirus GI and GII, rotavirus, and hepatitis A virus by molecular methods; and viruses by cell culture. While addressing the main objective of the study-comparing removal of viruses and bacterial indicators in MBR and conventional plants-it was realized that work was needed to identify data analysis and quantification methods for interpreting enteric virus and QC data. Therefore, methods for quantifying viruses, qualifying results, and applying QC data to interpretations are described in this report. During each regular sampling trip, samples were collected (1) before conventional or MBR treatment (post-preliminary), (2) after secondary or MBR treatment (post-secondary or post-MBR), (3) after tertiary treatment (one conventional plant only), and (4) after disinfection (post-disinfection). Glass-wool fiber filtration was used to concentrate enteric viruses from large volumes, and small volume grab samples were collected for direct-plating analyses for bacterial indicators and coliphage. After filtration, the viruses were eluted from the filter and further concentrated. The final concentrated sample volume (FCSV) was used for enteric virus analysis by use of two methods-cell culture and a molecular method, polymerase chain reaction (PCR). Quantitative PCR (qPCR) for DNA viruses and quantitative reverse-transcriptase PCR (qRT-PCR) for RNA viruses were used in this study. To support data interpretations, the assay limit of detection (ALOD) was set for each virus assay and used to determine sample reporting limits (SRLs). For qPCR and qRT-PCR the ALOD was an estimated value because it was not established according to established method detection limit procedures. The SRLs were different for each sample because effective sample volumes (the volume of the original sample that was actually used in each analysis) were different for each sample. Effective sample volumes were much less than the original sample volumes because of reductions from processing steps and (or) from when dilutions were made to minimize the effects from PCR-inhibiting substances. Codes were used to further qualify the virus data and indicate the level of uncertainty associated with each measurement. Quality-control samples were used to support data interpretations. Field and laboratory blanks for bacteria, coliphage, and enteric viruses were all below detection, indicating that it was unlikely that samples were contaminated from equipment or processing procedures. The absolute value log differences (AVLDs) between concurrent replicate pairs were calculated to identify the variability associated with each measurement. For bacterial indicators and coliphage, the AVLD results indicated that concentrations <10 colony-forming units or plaque-forming units per 100 mL can differ between replicates by as much as 1 log, whereas higher concentrations can differ by as much as 0.3 log. The AVLD results for viruses indicated that differences between replicates can be as great as 1.2 log genomic copies per liter, regardless of the concentration of virus. Relatively large differences in molecular results for viruses between replicate pairs were likely due to lack of precision for samples with small effective volumes. Concentrations of E. coli, fecal coliforms, enterococci, and somatic and F-specific coliphage in post-secondary and post-tertiary samples in conventional plants were higher than those in post-MBR samples. In post-MBR and post-secondary samples, concentrations of somatic coliphage were higher than F-specific coliphage. In post-disinfection samples from two MBR plants (the third MBR plant had operational issues) and the ultraviolet conventional plant, concentrations for all bacterial indicators and coliphage were near or below detection; from the chlorine conventional plant, concentrations in post-disinfection samples were in the single or double digits. All of the plants met the National Pollutant Discharge Elimination System required effluent limits established for fecal coliforms. Norovirus GII and hepatitis A virus were not detected in any samples, and rotavirus was detected in one sample but could not be quantified. Adenovirus was found in 100 percent, enterovirus in over one-half, and norovirus GI in about one-half of post-preliminary wastewater samples. Adenovirus and enterovirus were detected throughout the treatment processes, and norovirus GI was detected less often than the other two enteric viruses. Culturable viruses were detected in post-preliminary samples and in only two post-treatment samples from the plant with operational issues.

Scientific Investigations Report↗
USGS2010

Occurrence of Escherichia coli in the Cuyahoga River in the Cuyahoga Valley National Park, Ohio

There are several measures of the 'cleanliness' of a natural body of water, including concentrations of indicator bacteria, anthropogenic chemicals (chemicals derived from human activities), and nutrients, such as nitrogen and phosphorous. Escherichia coli (E. coli) is a bacterium that lives in the intestinal tract of warm-blooded animals, such as humans, deer, cows, and dogs. Most strains of E. coli are not harmful and are in fact beneficial to humans by aiding in the digestive process. A few strains, such as the O157 strain, produce toxins that can cause gastrointestinal illness, but occurrence of toxic strains in the environment is not common. E. coli is considered a good indicator bacterium because its occurrence in the environment indicates the presence of fecal contamination and therefore the possible presence of pathogenic organisms associated with feces. The U.S. Environmental Protection Agency (USEPA) recommends using measurements of E. coli to monitor freshwaters and set criteria for the concentration of bacteria that can be present in the water with minimal adverse human-health effects. Typically, a State's waters are assigned a recreational-use designation, such as bathing, primary-contact, or secondary contact waters, which is used to set the State's water-quality standards based on the USEPA criteria. The Cuyahoga River in the Cuyahoga Valley National Park is designated for primary-contact recreation; therefore, when concentrations of E. coli exceed 298 CFU/100mL, the river would be considered potentially unsafe for recreation.

Fact Sheet↗
USGS2009

Relations between environmental and water-quality variables and Escherichia coli in the Cuyahoga River with emphasis on turbidity as a predictor of recreational water quality, Cuyahoga Valley National Park, Ohio, 2008

During the recreational season of 2008 (May through August), a regression model relating turbidity to concentrations of Escherichia coli (E. coli) was used to predict recreational water quality in the Cuyahoga River at the historical community of Jaite, within the present city of Brecksville, Ohio, a site centrally located within Cuyahoga Valley National Park. Samples were collected three days per week at Jaite and at three other sites on the river. Concentrations of E. coli were determined and compared to environmental and water-quality measures and to concentrations predicted with a regression model. Linear relations between E. coli concentrations and turbidity, gage height, and rainfall were statistically significant for Jaite. Relations between E. col i concentrations and turbidity were statistically significant for the three additional sites, and relations between E. col i concentrations and gage height were significant at the two sites where gage-height data were available. The turbidity model correctly predicted concentrations of E. coli above or below Ohio’s single-sample standard for primary-contact recreation for 77 percent of samples collected at Jaite.

Ohio↗
USGS2009

Performance of Traditional and Molecular Methods for Detecting Biological Agents in Drinking Water

To reduce the impact from a possible bioterrorist attack on drinking-water supplies, analytical methods are needed to rapidly detect the presence of biological agents in water. To this end, 13 drinking-water samples were collected at 9 water-treatment plants in Ohio to assess the performance of a molecular method in comparison to traditional analytical methods that take longer to perform. Two 100-liter samples were collected at each site during each sampling event; one was seeded in the laboratory with six biological agents - Bacillus anthracis (B. anthracis), Burkholderia cepacia (as a surrogate for Bu. pseudomallei), Francisella tularensis (F. tularensis), Salmonella Typhi (S. Typhi), Vibrio cholerae (V. cholerae), and Cryptospordium parvum (C. parvum). The seeded and unseeded samples were processed by ultrafiltration and analyzed by use of quantiative polymerase chain reaction (qPCR), a molecular method, and culture methods for bacterial agents or the immunomagnetic separation/fluorescent antibody (IMS/FA) method for C. parvum as traditional methods. Six replicate seeded samples were also processed and analyzed. For traditional methods, recoveries were highly variable between samples and even between some replicate samples, ranging from below detection to greater than 100 percent. Recoveries were significantly related to water pH, specific conductance, and dissolved organic carbon (DOC) for all bacteria combined by culture methods, but none of the water-quality characteristics tested were related to recoveries of C. parvum by IMS/FA. Recoveries were not determined by qPCR because of problems in quantifying organisms by qPCR in the composite seed. Instead, qPCR results were reported as detected, not detected (no qPCR signal), or +/- detected (Cycle Threshold or 'Ct' values were greater than 40). Several sample results by qPCR were omitted from the dataset because of possible problems with qPCR reagents, primers, and probes. For the remaining 14 qPCR results (including some replicate samples), F. tularensis and V. cholerae were detected in all samples after ultrafiltration, B. anthracis was detected in 13 and +/- detected in 1 sample, and C. parvum was detected in 9 and +/- detected in 4 samples. Bu. cepacia was detected in nine samples, +/- detected in two samples, and not detected in three samples (for two out of three samples not detected, a different strain was used). The qPCR assay for V. cholerae provided two false positive - but late - signals in one unseeded sample. Numbers found by qPCR after ultrafiltration were significantly or nearly significantly related to those found by traditional methods for B. anthracis, F. tularensis, and V. cholerae but not for Bu. cepacia and C. parvum. A qPCR assay for S. Typhi was not available. The qPCR method can be used to rapidly detect B. anthracis, F. tularensis, and V. cholerae with some certainty in drinking-water samples, but additional work would be needed to optimize and test qPCR for Bu. cepacia and C. parvum and establish relations to traditional methods. The specificity for the V. cholerae assay needs to be further investigated. Evidence is provided that ultrafiltration and qPCR are promising methods to rapidly detect biological agents in the Nation's drinking-water supplies and thus reduce the impact and consequences from intentional bioterrorist events. To our knowledge, this is the first study to compare the use of traditional and qPCR methods to detect biological agents in large-volume drinking-water samples.

Scientific Investigations Report↗
USGS2009

Predicting recreational water quality using turbidity in the Cuyahoga River, Cuyahoga Valley National Park, Ohio, 2004-7

The Cuyahoga River within Cuyahoga Valley National Park (CVNP) in Ohio is often impaired for recreational use because of elevated concentrations of bacteria, which are indicators of fecal contamination. During the recreational seasons (May through August) of 2004 through 2007, samples were collected at two river sites, one upstream of and one centrally-located within CVNP. Bacterial concentrations and turbidity were determined, and streamflow at time of sampling and rainfall amounts over the previous 24 hours prior to sampling were ascertained. Statistical models to predict Escherichia coli (E. coli) concentrations were developed for each site (with data from 2004 through 2006) and tested during an independent year (2007). At Jaite, a sampling site near the center of CVNP, the predictive model performed better than the traditional method of determining the current day's water quality using the previous day's E. coli concentration. During 2007, the Jaite model, based on turbidity, produced more correct responses (81 percent) and fewer false negatives (3.2 percent) than the traditional method (68 and 26 percent, respectively). At Old Portage, a sampling site just upstream from CVNP, a predictive model with turbidity and rainfall as explanatory variables did not perform as well as the traditional method. The Jaite model was used to estimate water quality at three other sites in the park; although it did not perform as well as the traditional method, it performed well - yielding between 68 and 91 percent correct responses. Further research would be necessary to determine whether using the Jaite model to predict recreational water quality elsewhere on the river would provide accurate results.

Ohio↗
USGS2009

Comparison of the Immunomagnetic Separation/Adenosine Triphosphate Rapid Method and the Modified mTEC Membrane-Filtration Method for Enumeration of Escherichia coli

Water quality at beaches is monitored for fecal indicator bacteria by traditional, culture-based methods that can take 18 to 24 hours to obtain results. A rapid detection method that provides estimated concentrations of fecal indicator bacteria within 1 hour from the start of sample processing would allow beach managers to post advisories or close the beach when the conditions are actually considered unsafe instead of a day later, when conditions may have changed. A rapid method that couples immunomagnetic separation with adenosine triphosphate detection (IMS/ATP rapid method) was evaluated through monitoring of Escherichia coli (E. coli) at three Lake Erie beaches in Ohio (Edgewater and Villa Angela in Cleveland and Huntington in Bay Village). Beach water samples were collected between 4 and 5 days per week during the recreational seasons (May through September) of 2006 and 2007. Composite samples were created in the lab from two point samples collected at each beach and were shown to be comparable substitutes for analysis of two individual samples. E. coli concentrations in composite samples, as determined by the culture-based method, ranged from 4 to 24,000 colony-forming units per 100 milliliters during this study across all beaches. Turbidity also was measured for each sample and ranged from 0.8 to 260 neophelometric turbidity ratio units. Environmental variables were noted at the time of sampling, including number of birds at the beach and wave height. Rainfall amounts were measured at National Weather Service stations at local airports. Turbidity, rainfall, and wave height were significantly related to the culture-based method results each year and for both years combined at each beach. The number of birds at the beach was significantly related to the culture-based method results only at Edgewater during 2006 and during both years combined. Results of the IMS/ATP method were compared to results of the culture-based method for samples by year for each beach. The IMS/ATP method underwent several changes and refinements during the first year, including changes in reagents and antibodies and alterations to the method protocol. Because of the changes in the method, results from the two years of study could not be combined. Kendall's tau correlation coefficients for relations between the IMS/ATP and culture-based methods were significant except for samples collected during 2006 at Edgewater and for samples collected during 2007 at Villa Angela. Further, relations were stronger for samples collected in 2006 than for those collected in 2007, except at Edgewater where the reverse was observed. The 2007 dataset was examined to identify possible reasons for the observed difference in significance of relations by year. By dividing the 2007 data set into groups as a function of sampling date, relations (Kendall's tau) between methods were observed to be stronger for samples collected earlier in the season than for those collected later in the season. At Edgewater and Villa Angela, there were more birds at the beach at time of sampling later in the season compared to earlier in the season. (The number of birds was not examined at Huntington.) Also, more wet days (when rainfall during the 24 hours prior to sampling was greater than 0.05 inch) were sampled later in the season compared to earlier in the season. Differences in the dominant fecal source may explain the change in the relations between the culture-based and IMS/ATP methods.

Scientific Investigations Report↗
USGS2007

Escherichia coli Concentrations in the Mill Creek Watershed, Cleveland, Ohio, 2001-2004

Mill Creek in Cleveland, Ohio, receives discharges from combined-sewer overflows (CSOs) and other sanitary-sewage inputs. These discharges affect the water quality of the creek and that of its receiving stream, the Cuyahoga River. In an effort to mitigate this problem, the Northeast Ohio Regional Sewer District implemented a project to eliminate or control (by reducing the number of overflows) all of the CSOs in the Mill Creek watershed. This study focused on monitoring the microbiological water quality of the creek before and during sewage-collection system modifications. Routine samples were collected semimonthly from August 2001 through September 2004 at a site near a U.S. Geological Survey stream gage near the mouth of Mill Creek. In addition, event samples were collected September 19 and 22, 2003, when rainfall accumulations were 0.5 inches (in.) or greater. Concentrations of Escherichia coli (E. coli) were determined and instantaneous discharges were calculated. Streamflow and water-quality characteristics were measured at the time of sampling, and precipitation data measured at a nearby precipitation gage were obtained from the National Oceanic and Atmospheric Administration. Concentrations of E. coli were greater than Ohio's single-sample maximum for primary-contact recreation (298 colony-forming units per 100 milliliters (CFU/100 mL)) in 84 percent of the routine samples collected. In all but one routine sample E. coli concentrations in samples collected when instantaneous streamflows were greater than 20 cubic feet per second (ft3/s) were greater than Ohio's single-sample maximum. When precipitation occurred in the 24-hour period before routine sample collection, concentrations were greater than the maximum in 89 percent of the samples as compared to 73 percent when rainfall was absent during the 24 hours prior to routine sample collection. Before modifications to the sewage-collection system in the watershed began, E. coli concentrations in Mill Creek ranged from 220 to 29,000 CFU/100 mL. After major modifications, E. coli concentrations ranged from 110 to 80,000 CFU/100 mL. The percentage of sample E. coli concentrations in the former group greater than Ohio's single-sample maximum was 88 percent, whereas 85 percent of sample concentrations was greater than the maximum after major modifications occurred. Instantaneous discharges of E. coli were calculated for each of the modification periods. No statistically significant difference was observed between the median instantaneous discharges of E. coli for the premodification and minor-modification periods (5.1 ? 106 and 3.6 ? 106 CFU per second, respectively). During rainfall events in September 2003, samples were collected every 15 to 30 minutes. E. coli concentrations in all of these samples (n = 34) were greater than Ohio's single-sample maximum for primary-contact recreation. On September 19, total accumulated rainfall was 1.7 in., and streamflow reached a peak of 1,040 ft3/s. Sample collection started after 0.8 in. of precipitation had fallen and continued throughout the remainder of the storm. For these samples, E. coli concentrations ranged from 32,000 to 140,000 CFU/100 mL. On September 22, total accumulated rainfall was 0.5 in., and streamflow reached a peak of 497 ft3/s. Sample collection began before the start of the rain and continued throughout the storm. E. coli concentrations ranged from 450 to 260,000 CFU/100 mL.

Open-File Report↗
USGS2007

Rapid Method for Escherichia coli in the Cuyahoga River

This study is a continuation of a previous U.S. Geological Survey (USGS) project in cooperation with the National Park Service at Cuyahoga Valley National Park in Brecksville, Ohio. A rapid (1-hour) method for detecting Escherichia coli (E. coli) in water was tested and compared to the standard (24-hour) method for determining E. coli concentrations. Environmental data were collected to determine turbidity, rainfall, and streamflow at the time of sampling. In the previous study (2004-5), data collected were used to develop predictive models to determine recreational water quality in the river at two sites within the park. Data collected during this continued study (2006) were used to test these models. At Jaite, a centrally located site within the park, the model correctly predicted exceedances or nonexceedances of the Ohio Environmental Protection Agency maximum for recreational water quality in 80 percent of samples. At Old Portage, a site near the upstream boundary of the park, the model correctly predicted recreational water quality in 58 percent of samples. All of the data collected in 2004-6 will be used to develop more accurate models for use in future studies. Analysis and discussion of model results are scheduled to be included in an upcoming USGS Scientific Investigations Report.

Open-File Report↗
USGS2007

Escherichia coli and Suspended Sediment in Berger Ditch at Maumee Bay State Park, Oregon, Ohio, 2006

Berger Ditch discharges to the marina at Maumee Bay State Park (MBSP), just east of the MBSP bathing beach. Recent studies by U.S. Geological Survey (USGS) and University of Toledo researchers have identified the ditch as a source of Escherichia coli (E. coli), an indicator bacterium that is used to assess recreational water quality. An automatic sampler was installed at a USGS streamgage on Berger Ditch. Samples were collected as a function of streamflow, including negative flow conditions. Instantaneous discharges of E. coli and suspended sediment from Berger Ditch were calculated. When samples were collected, streamflow ranged from -21 to 227 cubic feet per second (ft3/s) and over the entire time period, streamflow ranged from -23 to 243 ft3/s. Discharges of E. coli ranged from 2.5 ? 108 to greater than 2.6 ? 1010 colony-forming units per second (cfu/s), and suspended-sediment discharges ranged from 0.01 to 2.2 kilograms per second (kg/s). One sample was collected during negative flow conditions, and discharges of E. coli and suspended sediment in this sample were -4.3 ? 108 cfu/s and -0.015 kg/s, respectively.

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