Geology topics

Donna S. Francy

Publications and source records attributed to Donna S. Francy.

At least 19 recordsLinked to original sources

USGS2024

Isolation and identification of microcystin-degrading bacteria in Lake Erie source waters and drinking-water plant sand filters

The increasing prevalence of cyanobacterial harmful algal blooms and the toxins they produce is a global water-quality issue. In the Western Basin of Lake Erie, high microcystin concentrations have led to water-quality advisories, process adjustments for treating drinking water, and increased water-quality monitoring. Biodegradation is an environmentally friendly and cost-effective way to reduce concentrations of microcystins in drinking water; however, few studies have been done to determine biodegradation potential of bacteria indigenous to the Lake Erie watershed. As part of a cooperative program between the U.S. Geological Survey and the U.S. Environmental Protection Agency, this study aimed to identify naturally occurring microcystin-degrading bacteria in source waters and in the sand filters of drinking-water treatment plants in the Western Basin of Lake Erie. Biodegradation of microcystin-LR was found to occur in microcosms developed with three different Lake Erie-area sources—Lake Erie water, water from storage reservoirs supplied by inland streams, and water or solid medium from sand/anthracite filters at drinking-water plants. In microplates with microcystin-LR as the sole carbon source, 10 isolates exhibited cellular respiration and were, therefore, identified as promising microcystin biodegraders; 4 of those isolates subsequently were found to have potential to form biofilms. The 10 promising isolates along with 14 additional isolates from the microcosms were identified by 16S ribosomal RNA sequencing: 15 isolates were γ-proteobacteria, 6 isolates were β-proteobacteria, 1 isolate was an α-proteobacterium, 1 isolate was a flavobacterium in the phylum Bacteroidetes , and 1 isolate was in the phylum Actinobacteria . Isolates were screened for possession of the mlrA gene (found to encode for the protein responsible for cleaving the cyclic structure of microcystin), and results indicate that, for Lake Erie source waters and elsewhere, more work would be required to identify microcystin-biodegradation pathways and products and to confirm biodegradation rates in pure culture isolates.

Lake Erie↗

USGS2020

Predicting microcystin concentration action-level exceedances resulting from cyanobacterial blooms in selected lake sites in Ohio

Cyanobacterial harmful algal blooms and the toxins they produce are a global water-quality problem. Monitoring and prediction tools are needed to quickly predict cyanotoxin action-level exceedances in recreational and drinking waters used by the public. To address this need, data were collected at eight locations in Ohio, USA, to identify factors significantly related to observed concentrations of microcystins (a freshwater cyanotoxin) that could be used in two types of site-specific regression models. Real-time models include easily- or continuously-measured factors that do not require that a sample be collected; comprehensive models use a combination of discrete sample-based measurements and real-time factors. The study sites included two recreational sites and six water treatment plant sites. Real-time models commonly included variables such as phycocyanin, pH, specific conductance, and streamflow or gage height. Many real-time factors were averages over time periods antecedent to the time the microcystin sample was collected, including water-quality data compiled from continuous monitors. Comprehensive models were useful at some sites with lagged variables for cyanobacterial toxin genes, dissolved nutrients, and (or) nitrogen to phosphorus ratios. Because models can be used for management decisions, important measures of model performance were sensitivity, specificity, and accuracy of estimates above or below the microcystin concentration threshold standard or action level. Sensitivity is how well the predictive tool correctly predicts exceedance of a threshold, an important measure for water-resource managers. Sensitivities >90% at four Lake Erie water treatment plants indicated that models with continuous monitor data were especially promising. The planned next steps are to collect more data to build larger site-specific datasets and validate models before they can be used for management decisions.

Ohio↗

USGS2020

Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17

Manure and wastewater from large livestock operations have the potential to negatively affect surface water and groundwater, including the eutrophication of surface waters and harmful algal blooms. In the Western Lake Erie Basin, where there is a high density of animal agriculture, harmful algal blooms have been attributed, in part, to phosphorus loading from dairy manure and fertilizer applications. Liquid lagoon manure produced by dairy operations typically has low nutrient concentrations and high-water content, so transportation costs are high relative to the value of the nutrients when applied to fields. Treatment systems are needed to transform manure into a dewatered product that is more economical to transport greater distances and that slows and (or) reduces the release of nutrients in soil, allowing nutrients to remain available for crop growth. This study was designed to pilot test a treatment solution in the Western Lake Erie Basin. The U.S. Geological Survey and Bowling Green State University field tested a dewatering treatment process (coagulant/polymer mixture) for dairy manure at pilot-scale test plots at The Ohio State University Agricultural Research and Development Center Northwest Agricultural Research Station. Automatic samplers were used to collect samples during 13 baseline and 9 post-manure application rainfall events that resulted in substantial surface runoff and (or) tile flow from October 2015 through early November 2017. Results are reported for three test plots that received liquid lagoon manure (raw manure) and three test plots that received polymer-treated manure (treated manure). Nutrient concentrations and flow volumes in surface runoff and tile flow were determined in baseline and post-manure application rainfall events. Nutrient concentration ranges are reported for 9 baseline and 9 post-manure application events as follows: dissolved reactive phosphorus, less than (<) 0.013−2.16 milligrams per liter (mg/L); nitrate plus nitrite, filtered, 0.32−77 mg/L; ammonia, filtered, <0.05−2.6 mg/L; total phosphorus, <0.01−12.8 mg/L; and total nitrogen, 1.49−77.2 mg/L. Volumes are reported for 6 baseline and 9 post-manure application rainfall events. None of the post-manure application runoff volumes were significantly different by plot or by treatment type (raw manure versus treated manure). Because concentrations alone do not reflect the true effects of different manure treatments, loads and flow-weighted mean concentrations of nutrients during post-manure application rainfall events were compared between plots with treated manure and those with raw manure. Loads of dissolved reactive phosphorus, total phosphorus, nitrate plus nitrite, and total nitrogen were calculated using the U.S. Geological Survey Graphical Constituent Loading and Analysis System. Loads of ammonia were not calculated because many of the ammonia concentrations were below the reporting limit. During the post-manure application period, higher nitrogen loads resulted from tile flow than surface runoff. For phosphorus, the opposite was true in that higher loads resulted from surface runoff than tile flow. Combined loads (surface runoff and tile flow) of dissolved reactive phosphorus were significantly different between raw manure and treated manure plots, but there was no significant difference in combined loads of total phosphorus, nitrate plus nitrite, or total nitrogen between raw manure and treated manure plots. Flow-weighted mean concentrations were calculated for the combined loads for the post-manure application rainfall events. Flow-weighted mean concentrations of dissolved reactive phosphorus and, to a lesser extent, total phosphorus were significantly different between raw manure and treated manure plots. Flow-weighted mean concentrations of nitrate plus nitrite and total nitrogen were not significantly different between raw manure and treated manure plots. The differences in loads and flow-weighted mean concentrations between raw manure and treated manure plots indicate that dissolved reactive phosphorus was likely retained in the soil and hydrological transport was reduced for the plots amended with the treated manure as compared to raw manure. Although confirmation field testing needs to be done, these results indicate that the use of this coagulant/polymer mixture shows potential in helping to reduce flow of dissolved phosphorus from agricultural fields with applied manure.

Ohio↗

USGS2020

Nowcasting methods for determining microbiological water quality at recreational beaches and drinking-water source waters

Nowcasts are tools used to provide timely and accurate water-quality assessments of threats to drinking-water and recreational resources from fecal contamination or cyanobacterial harmful algal blooms. They use mathematical models and techniques to provide near-real-time estimates of fecal-indicator bacteria (FIB) and cyanotoxin concentrations. Techniques include logic-based thresholds, decision trees (built with machine learning), multiple linear and binary logistic regression, artificial neural networks, and process-based deterministic models. The type of site (freshwater, marine, or river) and dependent variable (FIB or cyanotoxin) dictate which explanatory variables are used in models. Nowcast systems notify the public of associated public-health risks and can also be used to manage data for FIB models; work is ongoing to incorporate cyanotoxin models into some nowcasts. The Great Lakes NowCast in the USA has been operational since 2010 and includes 25 lake beaches and one recreational river site. Examples of other operational FIB nowcasts are described for locations in the USA and around the world. In many cases, models predicted exceedances of FIB standards with accuracies as good as or better than using the previous measured FIB concentration (persistence method). Accuracy and timeliness are vital to beach management decisions that protect public health and support the local recreation-driven economy. Nowcasts benefit the public by providing estimates of water-quality conditions in near-real-time. Managers can use nowcasts at recreational and drinking-water treatment plant sites when FIB or cyanotoxins are projected to be elevated to target sample collection, to provide near-real-time recreational advisories to the public, or to preemptively optimize drinking-water treatments or change intake options to mitigate possible adverse effects on drinking-water quality.

Journal of Microbiological Methods↗

USGS2019

Real-time assessments of water quality—A nowcast for Escherichia coli and cyanobacterial toxins

Threats to our recreational and drinking waters include disease-causing (pathogenic) organisms from fecal contamination and toxins produced by some species of cyanobacteria (cyanotoxins) that can cause acute and (or) chronic illnesses. Because traditional laboratory methods for detecting these threats take too long for prompt public health protection, tools for real-time assessments are needed to protect public health. To address this need, the U.S. Geological Survey is collaborating with State and local partners to develop models that provide real-time estimates of Escherichia coli ( E . coli ) (for pathogens) and (or) microcystin (for freshwater cyanotoxins) levels at inland and Great Lakes beaches and drinking-water intakes. Model results are then used to inform the public of water-quality conditions in near-real time through the Great Lakes NowCast ( https://ny.water.usgs.gov/maps/nowcast/ ). Behind the scenes, the NowCast provides speed and efficiency for managers by automating data management and standardizing methods among agencies.

Fact Sheet↗

USGS2016

Estimating microcystin levels at recreational sites in western Lake Erie and Ohio

Cyanobacterial harmful algal blooms (cyanoHABs) and associated toxins, such as microcystin, are a major global water-quality issue. Water-resource managers need tools to quickly predict when and where toxin-producing cyanoHABs will occur. This could be done by using site-specific models that estimate the potential for elevated toxin concentrations that cause public health concerns. With this study, samples were collected at three Ohio lakes to identify environmental and water-quality factors to develop linear-regression models to estimate microcystin levels. Measures of the algal community (phycocyanin, cyanobacterial biovolume, and cyanobacterial gene concentrations) and pH were most strongly correlated with microcystin concentrations. Cyanobacterial genes were quantified for general cyanobacteria, general Microcystis and Dolichospermum , and for microcystin synthetase ( mcyE ) for Microcystis , Dolichospermum , and Planktothrix. For phycocyanin, the relations were different between sites and were different between hand-held measurements on-site and nearby continuous monitor measurements for the same site. Continuous measurements of parameters such as phycocyanin, pH, and temperature over multiple days showed the highest correlations to microcystin concentrations. The development of models with high R 2 values (0.81–0.90), sensitivities (92%), and specificities (100%) for estimating microcystin concentrations above or below the Ohio Recreational Public Health Advisory level of 6 μg L −1 was demonstrated for one site; these statistics may change as more data are collected in subsequent years. This study showed that models could be developed for estimates of exceeding a microcystin threshold concentration at a recreational freshwater lake site, with potential to expand their use to provide relevant public health information to water resource managers and the public for both recreational and drinking waters.

Ohio↗

USGS2015

Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin production. Monitoring for a variety of environmental and water-quality factors, for concentrations of cyanobacteria by molecular methods, and for algal pigments such as chlorophyll and phycocyanin by using optical sensors may provide data that can be used to predict the occurrence of cyanoHABs. To test these monitoring approaches, water-quality samples were collected at Ohio recreational sites during May–November in 2013 and 2014. In 2013, samples were collected monthly at eight sites at eight lakes to facilitate an initial assessment and select sites for more intensive sampling during 2014. In 2014, samples were collected approximately weekly at five sites at three lakes. Physical water-quality parameters were measured at the time of sampling. Composite samples were preserved and analyzed for dissolved and total nutrients, toxins, phytoplankton abundance and biovolume, and cyanobacterial genes by molecular methods. Molecular assays were done to enumerate (1) general cyanobacteria, (2) general Microcystis and Dolichospermum ( Anabaena ), (3) mcyE genes for Microcystis , Dolichospermum ( Anabaena ), and Planktothrix targeting deoxyribonucleic acid (DNA), and (4) mcyE transcripts for Microcystis , Dolichospermum ( Anabaena ), and Planktothrix targeting ribonucleic acid (RNA).The DNA assays for the mcyE gene provide data on cyanobacteria that have the potential to produce microcystin, whereas the RNA assays provide data on cyanobacteria that are actively transcribing the toxin gene. Environmental data were obtained from available online sources. Quality-control (QC) samples were collected and analyzed for all constituents to characterize bias and variability; however, QC data for molecular assays were examined in more detail than for the other constituents. The QC data for molecular assays suggested that sampling variability and qPCR variability were small in comparison with the combined variability associated with sample filtering, extraction and purification, and the matrix itself. A total of 46 water-quality samples were collected during 2013 at 8 beach sites—Buck Creek, Buckeye Crystal, Deer Creek, Harsha Main, Maumee Bay State Park (MBSP) Inland (negative control site), MBSP Lake Erie, Port Clinton, and Sandusky Bay. Microcystin was detected in 67–100 percent of samples at all sites except for MBSP Inland, where microcystin was detected in only 20 percent of samples. Microcystin concentrations ranged from <0.10 to 48 micrograms per liter (µ/L), with the widest range found at MBSP Lake Erie and the highest concentrations found at Buckeye Crystal. Saxitoxin was detected in five samples, and cylindrospermopsin was not detected in any samples. A total of 65 water-quality samples were collected during 2014 at 5 sites on 3 lakes—Buckeye Fairfield and Onion Island, Harsha Main and Campers, and MBSP Lake Erie beach. Four of the sites were bathing beaches and one site, Onion Island, was an offshore boater swim area. Concentrations of microcystin ranged from <0.10 to 240 µ/L and, as in 2013, the widest range was found at MBSP Lake Erie. At Buckeye Lake, microcystin concentrations were consistently high (greater than 20 µ/L), ranging from 23 to 81 µ/L. At Harsha Main and Campers, microcystin concentrations ranged from <0.10 to 15 µ/L. Saxitoxin was detected in four samples collected at MBSP Lake Erie. Throughout the 2014 season, the cyanobacterial community, as determined by molecular and microscopy methods, and the dominance associated with the highest microcystin concentrations were unique to individual lakes. At Buckeye Lake, Planktothrix dominated the cyanobacterial community throughout the season and Planktothrix DNA and RNA were found in 100 percent of samples; Microcystis mcyE DNA was found in low concentrations. At Harsha Lake, Dolichospermum and Microcystis were a substantial percentage of the community from late May through August, and the highest microcystin concentrations occurred in June and July. At MBSP Lake Erie, Microcystis generally dominated from mid-July through early November, and the highest microcystin concentrations occurred in August. Spearman’s correlation coefficient (rho) was computed to determine the relations between environmental and water-quality factors and microcystin concentrations at four sites—Buckeye Fairfield, Buckeye Onion Island, Harsha Main, and MBSP Lake Erie. Factors were evaluated for use as potential independent variables in two types of predictive models—daily and long-term models. Easily or continuously measured water-quality factors and available environmental data are used for daily predictions that do not require a site visit. Data from factors used in daily predictions and results from samples collected and analyzed in a laboratory are used for long-term predictions (a few days to several weeks). A few statistically significant correlations (p ≤ 0.05) between microcystin concentrations and factors for both daily and long-term predictions were found at Buckeye Onion Island, and many were found at Harsha Main and MBSP Lake Erie. There were only a few statistically significant factors for daily predictions at Buckeye Fairfield, likely because of the lack of variability in microcystin concentrations. Among factors for daily predictions, phycocyanin had the highest Spearman’s correlation to microcystin concentrations (rho = 0.79 to 0.93) at all sites except for Buckeye Fairfield. Turbidity, pH, algae category, and Secchi depth were significantly correlated to microcystin concentrations at Harsha Main and MBSP Lake Erie. Algae categories were observational categories from 0 (none) to 4 (extreme). Several discharge variables (Maumee River at Waterville, river mouth is approximately 3.5 miles from the beach) at MBSP Lake Erie were promising environmental factors for daily predictions. In addition to discrete water-quality measurements recorded at Harsha Main at the time of sampling, many manipulated measurements (factors derived from mathematical manipulation of time-series data) available from a nearby continuous monitor were strongly correlated to microcystin concentrations; the highest correlation was found for the relation between microcystin concentrations and the antecedent 7-day average phycocyanin (rho = 0.98). For long-term predictions, the most highly correlated molecular assays were Planktothrix mcyE DNA at Buckeye Onion Island and Microcystis mcyE DNA at Harsha Main and MBSP Lake Erie. Concentrations of several nutrient constituents were significantly correlated to microcystin concentrations including total nitrogen at Buckeye Onion Island, ammonia and nitrate plus nitrite (both negatively correlated) at Harsha Main and MBSP Lake Erie, and total phosphorus at MBSP Lake Erie. The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Ohio↗

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

Reply to “Ranking filter methods for concentrating pathogens in lake water”

Accurately comparing filtration methods is indeed difficult. Our method ( 1 ) and the method described by Borchardt et al. for determining recoveries are both acceptable approaches; however, each is designed to achieve a different research goal. Our study was designed to compare recoveries of multiple microorganisms in surface-water samples. Because, in practice, water-matrix effects come into play throughout filtration, concentration, and detection processes, we felt it important to incorporate those effects into the recovery results.

Applied and Environmental Microbiology↗

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

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

Microbial source tracking markers at three inland recreational lakes in Ohio, 2011

During the 2011 recreational season, samples were collected for E. coli and microbial source tracking (MST) marker concentrations to begin to understand potential sources of fecal contamination at three inland recreational lakes in Ohio - Buckeye, Atwood, and Tappan Lakes. The results from 32 regular samples, 4 field blanks, and 7 field replicates collected at 5 sites are presented in this report. At the three lakes, the ruminant-associated marker was found most often (57-73 percent of samples) but at estimated quantities, followed by the dog-associated marker (30-43 percent of samples). The human-associated marker was found in 14 and 50 percent of samples from Atwood and Tappan Lakes, respectively, but was not found in any samples from the two Buckeye Lake sites. The gull-associated marker was detected in only two samples, both from Tappan Lake.

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↗

USGS2009

Use of predictive models and rapid methods to nowcast bacteria levels at coastal beaches

The need for rapid assessments of recreational water quality to better protect public health is well accepted throughout the research and regulatory communities. Rapid analytical methods, such as quantitative polymerase chain reaction (qPCR) and immunomagnetic separation/adenosine triphosphate (ATP) analysis, are being tested but are not yet ready for widespread use. Another solution is the use of predictive models, wherein variable(s) that are easily and quickly measured are surrogates for concentrations of fecal-indicator bacteria. Rainfall-based alerts, the simplest type of model, have been used by several communities for a number of years. Deterministic models use mathematical representations of the processes that affect bacteria concentrations; this type of model is being used for beach-closure decisions at one location in the USA. Multivariable statistical models are being developed and tested in many areas of the USA; however, they are only used in three areas of the Great Lakes to aid in notifications of beach advisories or closings. These “operational” statistical models can result in more accurate assessments of recreational water quality than use of the previous day's Escherichia coli (E. coli) concentration as determined by traditional culture methods. The Ohio Nowcast, at Huntington Beach, Bay Village, Ohio, is described in this paper as an example of an operational statistical model. Because predictive modeling is a dynamic process, water-resource managers continue to collect additional data to improve the predictive ability of the nowcast and expand the nowcast to other Ohio beaches and a recreational river. Although predictive models have been shown to work well at some beaches and are becoming more widely accepted, implementation in many areas is limited by funding, lack of coordinated technical leadership, and lack of supporting epidemiological data.

Aquatic Ecosystem Health & Management↗

USGS2009

Testing and refining the Ohio Nowcast at two Lake Erie beaches— 2008

The Ohio Nowcast has been providing real-time beach advisories to the public on the basis of predictive models since 2006. In support of the nowcast, data were collected during the recreational season of 2008 to validate and refine predictive models at two Lake Erie beaches. Predictive models yield data on the probability that the single-sample bathing-water standard for E. coli will be exceeded. Field personnel collected or compiled data on Escherichia coli (E. coli) concentrations as well as variables expected to affect these concentrations, including manual and automated measurements of turbidity, wave height, and water temperature; lake level; and radar and airport rainfall amounts. Two new variables were measured during 2008 - photosynthetically-active radiation at Huntington (Bay Village) and foreshore head at Edgewater (Cleveland). (The foreshore is a strip of land along a body of water between low and high water marks.) The performance of the nowcast was monitored during 2008. The Huntington nowcast yielded a greater percentage of correct responses (84.9 percent) than did the previous day's E. coli concentration (75.2 percent). In contrast, at Edgewater, the nowcast yielded a slightly higher percentage of correct responses (61.0 percent) as compared to the previous day's E. coli concentration (56.5 percent), but both percentages were relatively low. Lake levels in 2008 were significantly higher than levels in the data used to develop the Edgewater models (2004-7), confounding their abilities to provide correct responses. At Edgewater during 2008, the strongest relation (as measured by Pearson's correlation) was between E. coli concentrations and the difference in foreshore head over the past 24 hours (r=0.48), a variable not included in the models. At Huntington, photosynthetically-active radiation on the previous day showed a significant negative relation to E. coli concentrations (r=-0.33) during 2008. Refined models were developed for Huntington and Edgewater using data collected from 2005-8. The refined models included the variables wave height, log turbidity, radar or airport rainfall, and day of the year in various combinations for different dated segments of the recreational season. Water-resource managers will determine which models to apply to the Ohio Nowcast for issuing water-quality advisories in 2009.

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↗