Modern space/time geostatistics using river distances: data integration of turbidity and E. coli measurements to assess fecal contamination along the Raritan River in New Jersey.
ABSTRACT: Escherichia coli (E. coli) is a widely used indicator of fecal contamination in water bodies. External contact and subsequent ingestion of bacteria coming from fecal contamination can lead to harmful health effects. Since E. coli data are sometimes limited, the objective of this study is to use secondary information in the form of turbidity to improve the assessment of E. coli at unmonitored locations. We obtained all E. coli and turbidity monitoring data available from existing monitoring networks for the 2000-2006 time period for the Raritan River Basin, New Jersey. Using collocated measurements, we developed a predictive model of E. coli from turbidity data. Using this model, soft data are constructed for E. coli given turbidity measurements at 739 space/time locations where only turbidity was measured. Finally, the Bayesian Maximum Entropy (BME) method of modern space/time geostatistics was used for the data integration of monitored and predicted E. coli data to produce maps showing E. coli concentration estimated daily across the river basin. The addition of soft data in conjunction with the use of river distances reduced estimation error by about 30%. Furthermore, based on these maps, up to 35% of river miles in the Raritan Basin had a probability of E coli impairment greater than 90% on the most polluted day of the study period.
Project description:BACKGROUND: The river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management. METHODS: Data covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability. RESULTS: Generally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile) was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2). Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons. CONCLUSIONS: Rainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better control of sources of pollution.
Project description:We investigated the effect of rainfall on the levels and sources of microbial contamination in the Han River, Korea. Thirty-four samples were collected at two sampling sites located upstream and downstream in the river from July 2010 to February 2011. Various fecal indicator microorganisms, including total coliform, fecal coliform, Escherichia coli, Enterococcus spp., somatic and male-specific (F+) coliphage, and four major enteric viruses were analyzed. Rainfall was positively correlated with the levels of fecal coliform and norovirus at both sampling sites. Additionally, rainfall was positively correlated with the levels of total coliform, E. coli, Enterococcus spp., and F+ coliphage at the upstream site. To identify the source of fecal contamination, microbial source tracking (MST) was conducted using both male-specific (F+) RNA coliphage and the Enterococcus faecium esp gene as previously described. Our results clearly indicated that the majority of fecal contamination at the downstream Han River site was from a human source. At the upstream sampling site, contamination from human fecal matter was very limited; however, fecal contamination from non-point animal sources increased following rainfall. In conclusion, our data suggest that rainfall significantly affects the level and source of fecal contamination in the Han River, Korea.
Project description:Storm water runoff is a major source of pollution, and understanding the components of storm water discharge is essential to remediation efforts and proper assessment of risks to human and ecosystem health. In this study, culturable Escherichia coli and ampicillin-resistant E. coli levels were quantified and microbial source tracking (MST) markers (including markers for general Bacteroidales spp., human, ruminant/cow, gull, and dog) were detected in storm water outfalls and sites along the Humber River in Toronto, Ontario, Canada, and enumerated via endpoint PCR and quantitative PCR (qPCR). Additionally, chemical source tracking (CST) markers specific for human wastewater (caffeine, carbamazepine, codeine, cotinine, acetaminophen, and acesulfame) were quantified. Human and gull fecal sources were detected at all sites, although concentrations of the human fecal marker were higher, particularly in outfalls (mean outfall concentrations of 4.22 log10 copies, expressed as copy numbers [CN]/100 milliliters for human and 0.46 log10 CN/100 milliliters for gull). Higher concentrations of caffeine, acetaminophen, acesulfame, E. coli, and the human fecal marker were indicative of greater raw sewage contamination at several sites (maximum concentrations of 34,800 ng/liter, 5,120 ng/liter, 9,720 ng/liter, 5.26 log10 CFU/100 ml, and 7.65 log10 CN/100 ml, respectively). These results indicate pervasive sewage contamination at storm water outfalls and throughout the Humber River, with multiple lines of evidence identifying Black Creek and two storm water outfalls with prominent sewage cross-connection problems requiring remediation. Limited data are available on specific sources of pollution in storm water, though our results indicate the value of using both MST and CST methodologies to more reliably assess sewage contamination in impacted watersheds.Storm water runoff is one of the most prominent non-point sources of biological and chemical contaminants which can potentially degrade water quality and pose risks to human and ecosystem health. Therefore, identifying fecal contamination in storm water runoff and outfalls is essential for remediation efforts to reduce risks to public health. This study employed multiple methods of identifying levels and sources of fecal contamination in both river and storm water outfall sites, evaluating the efficacy of using culture-based enumeration of E. coli, molecular methods of determining the source(s) of contamination, and CST markers as indicators of fecal contamination. The results identified pervasive human sewage contamination in storm water outfalls and throughout an urban watershed and highlight the utility of using both MST and CST to identify raw sewage contamination.
Project description:Restoration of degraded aquatic habitats is critical to preserve and maintain ecosystem processes and economic viability. Effective restoration requires contaminant sources identification. Microbial communities are increasingly used to characterize fecal contamination sources. The objective was to determine whether nearshore and adjacent beach bacterial contamination originated from the Grand Calumet River, a highly urbanized aquatic ecosystem, and to determine if there were correlations between pathogens/feces associated bacteria in any of the samples to counts of the pathogen indicator species Escherichia coli. Water samples were collected from the river, river mouth, nearshore, and offshore sites along southern Lake Michigan. Comparisons among communities were made using beta diversity distances (weighted and unweighted Unifrac, and Bray Curtis) and Principal Coordinate Analysis of 16S rRNA gene Illumina sequence data that indicated river bacterial communities differed significantly from the river mouth, nearshore lake, and offshore lake samples. These differences were further supported using Source Tracker software that indicated nearshore lake communities differed significantly from river and offshore samples. Among locations, there was separation by sampling date that was associated with environmental factors (e.g., water and air temperature, water turbidity). Although about half the genera (48.1%) were common to all sampling sites, linear discriminant analysis effect size indicated there were several taxa that differed significantly among sites; there were significant positive correlations of feces-associated genera with E. coli most probable numbers. Results collectively highlight that understanding microbial communities, rather than relying solely on select fecal indicators with uncertain origin, are more useful for developing strategies to restore degraded aquatic habitats.
Project description:Taihu Lake is one of the largest freshwater lakes in China, serving as an important source of drinking water; >60% of source water to this lake is provided by the Tiaoxi River. This river faces serious fecal contamination issues, and therefore, a comprehensive investigation to identify the sources of fecal contamination was carried out and is presented here. The performance of existing universal (BacUni and GenBac), human (HF183-Taqman, HF183-SYBR, BacHum, and Hum2), swine (Pig-2-Bac), ruminant (BacCow), and avian (AV4143 and GFD) associated microbial source tracking (MST) markers was evaluated prior to their application in this region. The specificity and sensitivity results indicated that BacUni, HF183-TaqMan, Pig-2-Bac, and GFD assays are the most suitable in identifying human and animal fecal contamination. Therefore, these markers along with marker genes specific to selected bacterial pathogens were quantified in water and sediment samples of the Tiaoxi River, collected from 15 locations over three seasons during 2014 and 2015. Total/universal Bacteroidales markers were detected in all water and sediment samples (mean concentration 6.22 log10 gene copies/100 ml and 6.11 log10 gene copies/gram, respectively), however, the detection of host-associated MST markers varied. Human and avian markers were the most frequently detected in water samples (97 and 89%, respectively), whereas in sediment samples, only human-associated markers were detected more often (86%) than swine (64%) and avian (8.8%) markers. The results indicate that several locations in the Tiaoxi River are heavily polluted by fecal contamination and this correlated well with land use patterns. Among the five bacterial pathogens tested, Shigella spp. and Campylobacter jejuni were the most frequently detected pathogens in water (60% and 62%, respectively) and sediment samples (91% and 53%, respectively). Shiga toxin-producing Escherichia coli (STEC) and pathogenic Leptospira spp. were less frequently detected in water samples (55% and 33%, respectively) and sediment samples (51% and 13%, respectively), whereas E. coli O157:H7 was only detected in sediment samples (11%). Overall, the higher prevalence and concentrations of Campylobacter jejuni, Shigella spp., and STEC, along with the MST marker detection at a number of locations in the Tiaoxi River, indicates poor water quality and a significant human health risk associated with this watercourse. GRAPHICAL ABSTRACTTracking fecal contamination and pathogens in watersheds using molecular methods.
Project description:Widespread fecal pollution of surface waters in developing countries is a threat to public health and may represent a significant pathway for the global dissemination of antibiotic resistance. The Minjiang River drainage basin in Fujian Province is one of China's most intensive livestock and poultry production areas and is home to several million people. In the study reported here, Escherichia coli isolates (n = 2,788) were sampled (2007 and 2008) from seven surface water locations in the basin and evaluated by PCR for carriage of selected genes encoding virulence factors, primarily for swine disease. A subset of isolates (n = 500) were evaluated by PCR for the distribution and characteristics of class 1 integrons, and a subset of these (n = 200) were evaluated phenotypically for resistance to a range of antibiotics. A total of 666 (24%) E. coli isolates carried at least one of the virulence genes elt, fedA, astA, fasA, estA, stx(2e), paa, and sepA. Forty-one percent of the isolates harbored class 1 integrons, and these isolates had a significantly higher probability of resistance to tobramycin, cefoperazone, cefazolin, ciprofloxacin, norfloxacin, azitromycin, and rifampin than isolates with no class 1 integron detected. Frequencies of resistance to selected antibiotics were as high as or higher than those in fecal, wastewater, and clinical isolates in published surveys undertaken in China, North America, and Europe. Overall, E. coli in the Minjiang River drainage basin carry attributes with public health significance at very high frequency, and these data provide a powerful rationale for investment in source water protection strategies in this important agricultural and urban setting in China.
Project description:Microbial source tracking and a mass balance approach were used to identify sources of fecal indicator bacteria (FIB) in the Hanalei River, Kaua'i, Hawai'i. Historically, concentrations enterococci and Clostridium perfringens were significantly higher during storm flows compared to non-storm flows in the Hanalei River, and correlated to total suspended solids in the river. During targeted dry weather studies, the Hanalei River bed sediments and streambank soils were documented to harbor E. coli, enterococci, and the human- and pig-specific fecal markers in Bacteroidales, suggesting that sediments and soils may be potential sources of these microorganisms to the Hanalei river. The human-specific marker in Bacteroidales was four times as likely to be detected in sediment and soil samples as in water samples. Furthermore, the occurrence of host-specific source tracking markers is indicative that a portion of FIB present in the Hanalei River are of fecal origin. A mass balance approach was used to explore causes of observed FIB loadings and losses along different reaches of the river. Resuspension or deposition of FIB-laden river sediments cannot account for changes in E. coli and enterococci concentrations along the river during dry weather. Additionally, losses due to bacterial inactivation were insignificant. Groundwater and ditches draining agricultural and urban lands were shown to provide sufficient FIB fluxes to account for the observed loads along some river reaches. The presence of the human-specific Bacteroidales marker in the river water, sediments and adjacent soils, as well as the presence of the human enterovirus marker in the water, suggests that there is widespread human fecal contamination in the Hanalei River that is likely a result of nearby wastewater disposal systems.
Project description:Areas of concern (AOCs) around the Great Lakes are characterized by historic and ongoing problems with microbial water quality, leading to beneficial use impairments (BUIs) such as beach postings and closures. In this study, we assessed river and beach sites within the Rouge River watershed, associated stormwater outfalls, and at Rouge Beach. The concentrations of Escherichia coli as well as human- and gull-specific qPCR microbial source tracking (MST) markers were assessed at all sites. A preliminary comparison of digital PCR (dPCR) methodologies for both MST markers was conducted regarding sensitivity and specificity. Within the watershed, the outfalls were found to be a prominent source of human fecal contamination, with two outfalls particularly affected by sewage cross-connections. However, the occurrence of human fecal contamination along Rouge Beach and in the lower portions of the watershed was largely dependent on rain events. Gull fecal contamination was the predominant source of contamination at the beach, particularly during dry weather. The multiplex human/gull dPCR methodology used in this study tended to be more sensitive than the individual quantitative PCR (qPCR) assays, with only a slight decrease in specificity. Both dPCR and qPCR methodologies identified the same predominance of human and gull markers in stormwater and beach locations, respectively; however, the dPCR multiplex assay was more sensitive and capable of detecting fecal contamination that was undetected by qPCR assays. These results demonstrate the dPCR assay used in this study could be a viable tool for MST studies to increase the ability to identify low levels of fecal contamination.IMPORTANCE Fecal contamination of recreational water poses a persistent and ongoing problem, particularly in areas of concern around the Great Lakes. The identification of the source(s) of fecal contamination is essential for safeguarding public health as well as guiding remediation efforts; however, fecal contamination may frequently be present at low levels and remain undetectable by certain methodologies. In this study, we utilized microbial source tracking techniques using both quantitative and digital PCR assays to identify sources of contamination. Our results indicated high levels of human fecal contamination within stormwater outfalls, while lower levels were observed throughout the watershed. Additionally, high levels of gull fecal contamination were detected at Rouge Beach, particularly during drier sampling events. Furthermore, our results indicated an increased sensitivity of the digital PCR assay to detect both human and gull contamination, suggesting it could be a viable tool for future microbial source tracking studies.
Project description:Water borne diarrheal pathogens might accumulate in river water and cause contamination of drinking and irrigation water. The La Paz River basin, including the Choqueyapu River, flows through La Paz city in Bolivia where it is receiving sewage, and residues from inhabitants, hospitals, and industry. Using quantitative real-time PCR (qPCR), we determined the quantity and occurrence of diarrheagenic Escherichia coli (DEC), Salmonella enterica, Klebsiella pneumoniae, Shigella spp. and total enterobacteria in river water, downstream agricultural soil, and irrigated crops, during one year of sampling. The most abundant and frequently detected genes were gapA and eltB, indicating presence of enterobacteria and enterotoxigenic E. coli (ETEC) carrying the heat labile toxin, respectively. Pathogen levels in the samples were significantly positively associated with high water conductivity and low water temperature. In addition, a set of bacterial isolates from water, soil and crops were analyzed by PCR for presence of the genes blaCTX-M, blaKPC, blaNDM, blaVIM and blaOXA-48. Four isolates were found to be positive for blaCTX-M genes and whole genome sequencing identified them as E. coli and one Enterobacter cloacae. The E. coli isolates belonged to the emerging, globally disseminated, multi-resistant E. coli lineages ST648, ST410 and ST162. The results indicate not only a high potential risk of transmission of diarrheal diseases by the consumption of contaminated water and vegetables but also the possibility of antibiotic resistance transfer from the environment to the community.
Project description:The Mara River Basin in East Africa is a trans-boundary basin of international significance experiencing excessive levels of sediment loads. Sediment levels in this river are extremely high (turbidities as high as 6,000 NTU) and appear to be increasing over time. Large wildlife populations, unregulated livestock grazing, and agricultural land conversion are all potential factors increasing sediment loads in the semi-arid portion of the basin. The basin is well-known for its annual wildebeest (Connochaetes taurinus) migration of approximately 1.3 million individuals, but it also has a growing population of hippopotami (Hippopotamus amphibius), which reside within the river and may contribute to the flux of suspended sediments. We used in situ pressure transducers and turbidity sensors to quantify the sediment flux at two sites for the Mara River and investigate the origin of riverine suspended sediment. We found that the combined Middle Mara-Talek catchment, a relatively flat but semi-arid region with large populations of wildlife and domestic cattle, is responsible for 2/3 of the sediment flux. The sediment yield from the combined Middle Mara-Talek catchment is approximately the same as the headwaters, despite receiving less rainfall. There was high monthly variability in suspended sediment fluxes. Although hippopotamus pools are not a major source of suspended sediments under baseflow, they do contribute to short-term variability in suspended sediments. This research identified sources of suspended sediments in the Mara River and important regions of the catchment to target for conservation, and suggests hippopotami may influence riverine sediment dynamics.