The influence of rainfall on the incidence of microbial faecal indicators and the dominant sources of faecal pollution in a Florida river

The mediatory role of water quality on the association between extreme precipitation events and infectious diarrhea in the Yangtze River Basin, China

Extreme precipitation is exacerbating the burden of infectious diarrhea in the context of climate change, it is necessary to identify the critical and easy-to-intervene intermediate factors for public health strategies. Water quality may be the most important mediator, while relevant empirical evidence is limited. This study aimed to examine the role of water quality in the process of infectious diarrhea caused by extreme precipitation. Weekly infectious diarrhea cases, meteorological factors and water quality data in Yangtze River Basin in China between October 29, 2007 to February 19, 2017 were obtained. Two-stage statistical models were used to estimate city-specific extreme precipitation, water quality and infectious diarrhea relationships that were pooled to derive regional estimates. A causal mediation analysis was used to assess the mediation effect of water quality. In Yangtze River Basin, extreme precipitation events had a significant impact on infectious diarrhea (Incidence Rate Ratios [IRR]: 1.027, 95% Confidence Interval [CI]: 1.013∼1.041). After extreme precipitation events, the dissolved oxygen (DO) in surface water decreased (-0.123 mg/L, 95%CI: -0.159 mg/L∼-0.086 mg/L), while the un-ionized ammonia (NH(3)-N) increased (0.004 mg/L, 95%CI: 0.001 mg/L∼0.006 mg/L). The combined overall effect of DO and NH(3)-N on infectious diarrhea showed that both low and high concentrations were associated with an increased risk of infectious diarrhea. The causal mediation analysis showed that the mediation proportion of the two water quality indexes (DO and NH(3)-N) is 70.54% (P < 0.001). To reduce the health effects of extreme precipitation, in contrast to current population-oriented health strategies, those that take into account more direct and easy-to-intervene water quality indicators should be encouraged by future policies.

Growing coastal tourism: Can biomonitoring provide insights into the health of coastal ecosystems?

Coastal tourism's surge raises concerns for Morocco's Agadir marine environment, notably with Taghazout Bay's impact. Our study assesses Taghazout's health, employing a comprehensive approach. Our study evaluates Taghazout's health, adopting a comprehensive approach covering physicochemical, microbiological aspects, macrobenthic fauna, metal pollution, and biomarkers in D. trunculus mollusks. Seawater quality aligns with Moroccan standards, indicating good bathing water. The intertidal zone hosts ten species, dominated by D. trunculus. Biomarker responses in D. trunculus suggest chemical stress. Land-use maps expose significant changes driven by the Taghazout Bay project, impacting approximately 37.99 % of the landscape. Construction activities notably encroached upon the Arganeraie and the coastal zone, creating a stark contrast from 2003. These findings form a crucial database for future studies, contributing significantly to environmental management and sustainable development, aiding informed decision-making and effective coastal ecosystem preservation strategies.

Association between rainfall and Escherichia coli in live bivalve molluscs harvested in Sardinia, Italy

Rainfall is generally accepted as one of the most important factors associated with an increased level of E. coli in bivalve molluscs. Performing microbiological risk assessment is relevant to official control authorities to determine the sanitary status of harvesting areas and, therefore, develop monitoring strategies and identify management practices that could be used to improve the quality and safety of the final product. The present study aimed to investigate the impact of rainfall on the content of E. coli in bivalve molluscs farmed in Sardinia (Italy). Enumeration of E. coli was performed according to the Most Probable Number (MPN) method (ISO 16649-3) on 1,920 bivalve samples collected from 7 regional counties between 2018 and 2020. Bivalve molluscs samples included 955 mussels (Mytilus galloprovincialis), 500 oysters (Crassostrea gigas), 325 clams (Ruditapes decussatus), 94 warty venus (Venus verrucosa), and 46 lagoon cockles (Cerastoderma glaucum). Rainfall data were obtained by the Department of Meteorology of the ARPA Sardegna. For each sampling site, GPS coordinates were used to identify gauge stations within catchment areas. Cumulative rain (mm) was recorded 1, 3, 5, 7, and 15 days before sampling, among which the 7-day cumulative rain was the strongest predictor of E. coli counts. Several thresholds of 7-day cumulative rain (from <10 mm up to >300 mm) before sampling were used to estimate the chances of a non-compliant sample (E. coli levels above the limit for sanitary class A; 230 MPN/100 g). The 7-day cumulative rain was positively associated with the chances of non-compliance. When the 7-day cumulative rain before sampling was >300 mm, 80.5 % of the samples were non-compliant, and the odds of a non-compliant sample were 23.6 times higher, as compared to samples harvested when the 7-day cumulative rainfall was <10 mm. Precipitation data could be a useful tool for interpreting anomalous results from official control authorities and reduce the costs that originate from closure of production areas.

Sampling frequency optimization of the water quality monitoring network in São Paulo State (Brazil) towards adaptive monitoring in a developing country

Water quality monitoring networks (WQMNs) that capture both the temporal and spatial dimensions are essential to provide reliable data for assessing water quality trends in surface waters, as well as for supporting initiatives to control anthropogenic activities. Meeting these monitoring goals as efficiently as possible is crucial, especially in developing countries where the financial resources are limited and the water quality degradation is accelerating. Here, we asked if sampling frequency could be reduced while maintaining the same degree of information as with bimonthly sampling in the São Paulo State (Brazil) WQMN. For this purpose, we considered data from 2004 to 2018 for 56 monitoring sites distributed into four out of 22 of the state's water resources management units (UGRHIs, "Unidades de Gerenciamento de Recursos Hídricos"). We ran statistical tests for identifying data redundancy among two-month periods in the dry and wet seasons, followed by objective criteria to develop a sampling frequency recommendation. Our results showed that the reduction would be feasible in three UGRHIs, with the number of annual samplings ranging from two to four (instead of the original six). In both seasons, dissolved oxygen and Escherichia coli required more frequent sampling than the other analyzed parameters to adequately capture variability. The recommendation was compatible with flexible monitoring strategies observed in well-structured WQMNs worldwide, since the suggested sampling frequencies were not the same for all UGRHIs. Our approach can contribute to establishing a methodology to reevaluate WQMNs, potentially resulting in less costly and more adaptive strategies in São Paulo State and other developing areas with similar challenges.

Microbial source tracking to elucidate the impact of land-use and physiochemical water quality on fecal contamination in a mixed land-use watershed

Escherichia coli has been widely used as a fecal indicator bacterium (FIB) for monitoring water quality in drinking water sources and recreational water. However, fecal contamination sources remain difficult to identify and mitigate, as millions of cases of infectious diseases are reported yearly due to swimming and bathing in recreational water. The objective of this study was to apply molecular techniques for microbial source tracking (MST) to identify sources of fecal contamination in a representative mixed land-use watershed located in the Appalachian Mountains of the United States of America (USA). Monthly samples were collected over one year at 11 sites, including the confluence of key first-order streams in the study watershed representing distinct land-use types and anticipated fecal sources. Results indicated that coupled monitoring of host-specific MST markers with the FIB E. coli effectively identified sources and quantified fecal contamination in the study watershed. Human-associated MST markers were abundant primarily at developed sites, suggesting septic or sewer failure is a key source of fecal input to the watershed. Across the dataset, samples positive for E. coli and human MST markers were associated with a higher pH than those samples from which each target was not detected, thereby suggesting that acid mine drainage in the watershed likely contributed to inactivation or loss of culturability in E. coli. In addition, this research provides the first evidence that the BacCan-UCD marker is present in fox feces and can influence MST results in areas where substantial wildlife activity is present. Identifying the sources of fecal contamination and better understanding the impact of in-stream physiochemistry throughout this study will help to develop sustainable and effective watershed management plans to control fecal contamination to protect drinking water sources and recreational water.

Huge anthropogenic microbial load during southwest monsoon season in coastal waters of Kakinada, Bay of Bengal

To examine the influence of anthropogenic activities on the marine ecosystem near the coastal waters of the port city, Kakinada, a study was conducted to investigate the abundance of heterotrophic, indicator and pathogenic bacteria during the spring inter monsoon (SIM) and southwest monsoon (SWM) seasons. A drastic change in the marine bacteria due to the input of allochthonous bacteria during SWM was noticed. An order of magnitude higher abundance of indicators (Escherichia coli and Enterococcus faecalis) and bacterial pathogens (Proteus mirabilis and Pseudomonas aeruginosa) was observed during SWM. In contrast, Chlorophyll-a, heterotrophic bacterial abundance, Aeromonas hydrophila and Klebsiella pneumoniae were higher during SIM. A significant increase in some of the indicator and pathogenic bacterial abundance due to moderate rainfall suggests that the improper drainage system in the city could spread these bacteria, posing a considerable threat to both environment and human health.

Genetic fecal source identification in urban streams impacted by municipal separate storm sewer system discharges

Municipal stormwater systems are designed to collect, transport, and discharge precipitation from a defined catchment area into local surface waters. However, these discharges may contain unsafe levels of fecal waste. Paired measurements of Escherichia coli, precipitation, three land use metrics determined by geographic information system (GIS) mapping, and host-associated genetic markers indicative of human (HF183/BacR287 and HumM2), ruminant (Rum2Bac), dog (DG3), and avian (GFD) fecal sources were assessed in 231 urban stream samples impacted by two or more municipal stormwater outfalls. Receiving water samples were collected twice per month (n = 24) and after rain events (n = 9) from seven headwaters of the Anacostia River in the District of Columbia (United States) exhibiting a gradient of impervious surface, residential, and park surface areas. Almost 50% of stream samples (n = 103) were impaired, exceeding the local E. coli single sample maximum assessment level (410 MPN/100 ml). Fecal scores (average log10 copies per 100 ml) were determined to prioritize sites by pollution source and to evaluate potential links with land use, rainfall, and E. coli levels using a recently developed censored data analysis approach. Dog, ruminant, and avian fecal scores were almost always significantly increased after rain or when E. coli levels exceeded the local benchmark. Human fecal pollution trends showed the greatest variability with detections ranging from 9.1% to 96.7% across sites. Avian fecal scores exhibited the closest connection to land use, significantly increasing in catchments with larger residential areas after rain events (p = 0.038; R2 = 0.62). Overall, results demonstrate that combining genetic fecal source identification methods with GIS mapping complements routine E. coli monitoring to improve management of urban streams impacted by stormwater outfalls.

Fecal indicators and antibiotic resistance genes exhibit diurnal trends in the Chattahoochee River: Implications for water quality monitoring

Water bodies that serve as sources of drinking or recreational water are routinely monitored for fecal indicator bacteria (FIB) by state and local agencies. Exceedances of monitoring thresholds set by those agencies signal likely elevated human health risk from exposure, but FIB give little information about the potential source of contamination. To improve our understanding of how within-day variation could impact monitoring data interpretation, we conducted a study at two sites along the Chattahoochee River that varied in their recreational usage and adjacent land-use (natural versus urban), collecting samples every 30 min over one 24-h period. We assayed for three types of microbial indicators: FIB (total coliforms and Escherichia coli); human fecal-associated microbial source tracking (MST) markers (crAssphage and HF183/BacR287); and a suite of clinically relevant antibiotic resistance genes (ARGs; blaCTX-M, blaCMY, MCR, KPC, VIM, NDM) and a gene associated with antibiotic resistance (intl1). Mean levels of FIB and clinically relevant ARGs (blaCMY and KPC) were similar across sites, while MST markers and intI1 occurred at higher mean levels at the natural site. The human-associated MST markers positively correlated with antibiotic resistant-associated genes at both sites, but no consistent associations were detected between culturable FIB and any molecular markers. For all microbial indicators, generalized additive mixed models were used to examine diurnal variability and whether this variability was associated with environmental factors (water temperature, turbidity, pH, and sunlight). We found that FIB peaked during morning and early afternoon hours and were not associated with environmental factors. With the exception of HF183/BacR287 at the urban site, molecular MST markers and intI1 exhibited diurnal variability, and water temperature, pH, and turbidity were significantly associated with this variability. For blaCMY and KPC, diurnal variability was present but was not correlated with environmental factors. These results suggest that differences in land use (natural or urban) both adjacent and upstream may impact overall levels of microbial contamination. Monitoring agencies should consider matching sample collection times with peak levels of target microbial indicators, which would be in the morning or early afternoon for the fecal associated indicators. Measuring multiple microbial indicators can lead to clearer interpretations of human health risk associated with exposure to contaminated water.

Locating illicit discharges in storm sewers in urban areas using multi-parameter source tracking: Field validation of a toolbox composite index to prioritize high risk areas

In urban areas served by separate sewerage systems, illicit connections to the storm drain system from residences or commercial establishments are frequent whether these misconnections were made accidentally or deliberately. As a result, untreated and contaminated wastewater enters into storm sewers leading to pollution of receiving waters and non-compliance with water quality standards. Typical procedures for detecting illicit connections to the storm sewer system are time consuming and expensive, especially in a highly urbanised area. In this study, we investigated the use of human wastewater micropollutants WWMPs (caffeine, theophylline, and carbamazepine) and advanced DNA molecular markers (human specific Bacteroides HF183 and mitochondrial DNA) as anthropogenic tracers in order to assist identifying potential cross connections. Water samples from storm outfalls and storm sewer pipes in three urban subcatchments were collected in dry weather from 2013 to 2018. All samples contained various concentrations of these markers especially HF183, caffeine and theophylline, suggesting that the storm pipe system studied is widely contaminated by sanitary sewers. None of the traditional indicators or markers tested is sufficient alone to determine the origin of fecal pollution. In a highly urbanised area, the combination of at least three specific human markers was needed in order to locate the residential section with likely misconnections. The human specific Bacteroides HF183, and theophylline appeared to be the most effective markers (along with E. coli) of crossconnections, whereas carbamazepine can provide an indication of contamination through sanitary sewer exfiltration. A composite sewer cross-connection index was developed, and eight misconnected houses were identified and corrected. The index approach enables the reduction of false positives that could lead to expensive interventions to identify cross-connected households. The results show the multiparameter source tracking toolbox as an effective method to identify sewer cross connections for sustainable storm water management.

Spatial optimization of the water quality monitoring network in São Paulo State (Brazil) to improve sampling efficiency and reduce bias in a developing sub-tropical region

Water quality monitoring networks (WQMNs) are essential to provide good data for management decisions. Nevertheless, some WQMNs may not appropriately reflect the conditions of the water bodies and their temporal/spatial dimensions, more particularly in developing countries. Also, some WQMNs may use more resources to attain management goals than necessary and can be improved. Here we analyzed the São Paulo State (Brazil) WQMN design in order to evaluate and increase its spatial representativeness based on cluster analysis and stratified sampling strategy focused on clear monitoring goals. We selected water resources management units (UGRHIs) representative of contrasting land uses in the state, with bimonthly data from 2004 to 2018 in 160 river/stream sites. Cluster analysis indicated monitoring site redundancy above 20% in most of the UGRHIs. We identified heterogeneous spatial strata based on land use, hydrological, and geological features through a stratified sampling strategy. We identified that monitoring sites overrepresented more impacted areas. Thus, the network is biased against determination of baseline conditions and towards highly modified aquatic systems. Our proposed spatial strategy suggested the reduction of the number of sites up to 12% in the UGRHIs with the highest population densities, while others would need expansions based on their environmental heterogeneity. The final densities ranged from 1.6 to 13.4 sites/1,000km². Our results illustrate a successful approach to be considered in the São Paulo WQMN strategy, as well as providing a methodology that can be broadly applied in other developing countries.

Community monitoring of coliform pollution in Lake Tanganyika

Conventional water quality monitoring has been done for decades in Lake Tanganyika, under different national and international programs. However, these projects utilized monitoring approaches, which were temporally limited, labour intensive and costly. This study examines the use of citizen science to monitor the dynamics of coliform concentrations in Lake Tanganyika as a complementary method to statutory and project-focused measurements. Persons in five coastal communities (Kibirizi, Ilagala, Karago, Ujiji and Gombe) were trained and monitored total coliforms, faecal coliforms and turbidity for one year on a monthly basis, in parallel with professional scientists. A standardized and calibrated Secchi tube was used at the same time to determine turbidity. Results indicate that total and faecal coliform concentrations determined by citizen scientists correlated well to those determined by professional scientists. Furthermore, citizen scientist-based turbidity values were shown to provide a potential indicator for high FC and TC concentrations. As a simple tiered approach to identify increased coliform loads, trained local citizen scientists could use low-cost turbidity measurements with follow up sampling and analysis for coliforms, to inform their communities and regulatory bodies of high risk conditions, as well as to validate local mitigation actions. By comparing the spatial and temporal dynamics of coliform concentrations to local conditions of infrastructure, population, precipitation and hydrology in the 15 sites (3 sites per community) over 12 months, potential drivers of coliform pollution in these communities were identified, largely related to precipitation dynamics and the land use.

Integrating culture and molecular quantification of microbial contaminants into a predictive modeling framework in a low-lying, tidally-influenced coastal watershed

Examinations of stormwater delivery in the context of tidal inundation are lacking. Along the coastal plains of the southeastern United States, tidal inundation is increasing in frequency and severity, often with dramatic adverse impacts on timely stormwater discharge, coastal flooding hazards, and even "sunny day flooding". Therefore, a comprehensive study was conducted to examine tidally-influenced stormwater outfalls discharging to Taylor's Creek, an estuary proximal to Beaufort, NC used regularly for recreation and tourism. Over a wide range of meteorological conditions, water samples were collected and analyzed for fecal indicator bacteria (FIB, used for water quality management) and previously published quantitative microbial source tracking (qMST) markers. Nineteen sampling events were conducted from July 2017-June 2018 with samples classified according to tidal state and defined as either inundated, receding, or transition. A first-of-its-kind multiple linear regression model was developed to predict concentrations of Enterococcus sp. by tidal cycle, salinity and antecedent rainfall. We demonstrated that the majority of variability associated with the concentration of Enterococcus sp. could be predicted by E. coli concentration and tidal phase. FIB concentrations were significantly (<0.05) influenced by tide with higher concentrations observed in samples collected during receding (low) tides (EC: log 3.12 MPN/100 mL; ENT: 2.67 MPN/100 mL) compared to those collected during inundated (high) (EC: log 2.62 MPN/100 mL; ENT: 2.11 MPN/100 mL) or transition (EC: log 2.74 MPN/100 mL; ENT: 2.53 MPN/100 mL) tidal periods. Salinity, was also found to significantly (<0.05) correlate with Enterococcus sp. concentrations during inundated (high) tidal conditions (sal: 17 ppt; ENT: 2.04 MPN/100 mL). Tide, not precipitation, was shown to be a significant driver in explaining the variability in Enterococcus sp. concentrations. Precipitation has previously been shown to be a driver of Enterococcus sp. concentrations, but our project demonstrates the need for tidal parameters to be included in the future development of water quality monitoring programs.

Classification and Prediction of Fecal Coliform in Stream Waters Using Decision Trees (DTs) for Upper Green River Watershed, Kentucky, USA

The classification of stream waters using parameters such as fecal coliforms into the classes of body contact and recreation, fishing and boating, domestic utilization, and danger itself is a significant practical problem of water quality prediction worldwide. Various statistical and causal approaches are used routinely to solve the problem from a causal modeling perspective. However, a transparent process in the form of Decision Trees is used to shed more light on the structure of input variables such as climate and land use in predicting the stream water quality in the current paper. The Decision Tree algorithms such as classification and regression tree (CART), iterative dichotomiser (ID3), random forest (RF), and ensemble methods such as bagging and boosting are applied to predict and classify the unknown stream water quality behavior from the input variables. The variants of bagging and boosting have also been looked at for more effective modeling results. Although the Random Forest, Gradient Boosting, and Extremely Randomized Tree models have been found to yield consistent classification results, DTs with Adaptive Boosting and Bagging gave the best testing accuracies out of all the attempted modeling approaches for the classification of Fecal Coliforms in the Upper Green River watershed, Kentucky, USA. Separately, a discussion of the Decision Support System (DSS) that uses Decision Tree Classifier (DTC) is provided.

Prevalence of multidrug resistance in Pseudomonas spp. isolated from wild bird feces in an urban aquatic environment

Antimicrobial resistance (AMR) has been detected in the microbiota of wildlife, yet little is known about the origin and impact within the ecosystem. Due to the shortage of nonepizootic surveillance, there is limited understanding of the natural prevalence and circulation of AMR bacteria in the wild animal population, including avian species. In this surveillance study, feces from wild birds in proximity to the River Cam, Cambridge, England, were collected and Pseudomonas spp. were isolated. Of the 115 samples collected, 24 (20.9%; 95% CI, 12.6%‒29.2%) harbored Pseudomonas spp. of which 18 (75%; 95% CI, 58%‒92%) had a multiple antibiotic resistance (MAR) index greater than 0.2. No Pseudomonas spp. isolate in this study was pansusceptible. Resistance was found among the 24 isolates against ciprofloxacin (87.5%; 95% CI, 74.3%‒100%) and cefepime (83.3%; 95% CI, 68.4%‒98.2%), both of which are extensively used to treat opportunistic Pseudomonas spp. infections. The prevalence of Pseudomonas spp. in the wild bird feces sampled during this study is greater than previous, similar studies. Additionally, their multidrug resistance profile provides insight into the potential risk for ecosystem contamination. It further highlights the importance of a One Health approach, including ongoing surveillance efforts that help to develop the understanding of how wildlife, including avifauna, may contribute and disperse AMR across the ecosystem.

Tracking Major Sources of Water Contamination Using Machine Learning

Current microbial source tracking techniques that rely on grab samples analyzed by individual endpoint assays are inadequate to explain microbial sources across space and time. Modeling and predicting host sources of microbial contamination could add a useful tool for watershed management. In this study, we tested and evaluated machine learning models to predict the major sources of microbial contamination in a watershed. We examined the relationship between microbial sources, land cover, weather, and hydrologic variables in a watershed in Northern California, United States. Six models, including K-nearest neighbors (KNN), Naïve Bayes, Support vector machine (SVM), simple neural network (NN), Random Forest, and XGBoost, were built to predict major microbial sources using land cover, weather and hydrologic variables. The results showed that these models successfully predicted microbial sources classified into two categories (human and non-human), with the average accuracy ranging from 69% (Naïve Bayes) to 88% (XGBoost). The area under curve (AUC) of the receiver operating characteristic (ROC) illustrated XGBoost had the best performance (average AUC = 0.88), followed by Random Forest (average AUC = 0.84), and KNN (average AUC = 0.74). The importance index obtained from Random Forest indicated that precipitation and temperature were the two most important factors to predict the dominant microbial source. These results suggest that machine learning models, particularly XGBoost, can predict the dominant sources of microbial contamination based on the relationship of microbial contaminants with daily weather and land cover, providing a powerful tool to understand microbial sources in water.

Relationships among microbial indicators of fecal pollution, microbial source tracking markers, and pathogens in Costa Rican coastal waters

Tropical coastal waters are understudied, despite their ecological and economic importance. They also reflect projected climate change scenarios for other climate zones, e.g., increased rainfall and water temperatures. We conducted an exploratory microbial water quality study at a tropical beach influenced by sewage-contaminated rivers, and tested the hypothesis that fecal microorganisms (fecal coliforms, enterococci, Clostridium perfringens, somatic and male-specific coliphages, pepper mild mottle virus (PMMoV), Bacteroides HF183, norovirus genogroup I (NoVGI), Salmonella, Cryptosporidium and Giardia) would vary by season and tidal stage. Most microorganisms' concentrations were greater in the rainy season; however, NoVGI was only detected in the dry season and Cryptosporidium was the only pathogen most frequently detected in rainy season. Fecal indicator bacteria (FIB) levels exceeded recreational water quality criteria standards in >85% of river samples and in <50% of ocean samples, regardless of the FIB or regulatory criterion. Chronic sewage contamination was demonstrated by detection of HF183 and PMMoV in 100% of river samples, and in >89% of ocean samples. Giardia, Cryptosporidium, Salmonella, and NoVGI were frequently detected in rivers (39%, 39%, 26%, and 39% of samples, respectively), but infrequently in ocean water, particularly during the dry season. Multivariate analysis showed that C. perfringens, somatic coliphage, male-specific coliphage, and PMMoV were the subset of indicators that maximized the correlation with pathogens in the rivers. In the ocean, the best subset of indicators was enterococci, male-specific coliphage, and PMMoV. We also executed redudancy analyses on environmental parameters and microorganim concentrations, and found that rainfall best predicted microbial concentrations. The seasonal interplay of rainfall and pathogen prevalence undoubtedly influences beach users' health risks. Relationships are likely to be complex, with some risk factors increasing and others decreasing each season. Future use of multivariate approaches to better understand linkages among environmental conditions, microbial predictors (fecal indicators and MST markers), and pathogens will improve prediction of high-risk scenarios at recreational beaches.

Detection of human fecal pollution in environmental waters using human mitochondrial DNA and correlation with general and human-associated fecal genetic markers

Human mitochondrial DNA (mtDNA) genetic markers are abundant in sewage and highly human-specific, suggesting a great potential for the environmental application as human fecal pollution indicators. Limited data are available on the occurrence and co-occurrence of human mtDNA with fecal bacterial markers in surface waters, and how the abundance of these markers is influenced by rain events. A 1-year sampling study was conducted in a suburban watershed impacted by human sewage contamination to evaluate the performance of a human mtDNA-based marker along with the bacterial genetic markers for human-associated Bacteroidales (BacHum and HF183) and Escherichia coli. Additionally, the human mtDNA-based assay was correlated with rain events and other markers. The mtDNA marker was detected in 92% of samples (n = 140) with a mean concentration of 2.96 log₁₀ copies/100 ml throughout the study period. Human mtDNA was detected with greater abundance than human-associated Bacteroidales that could be attributed to differences in the decay of these markers in the environment. The abundance of all markers was positively correlated with rain events, and human mtDNA abundance was significantly correlated with various bacterial markers. In general, these results should support future risk assessment for impacted watersheds, particularly those affected by human fecal pollution, by evaluating the performance of these markers during rain events.

Factors Impacting the Prevalence of Foodborne Pathogens in Agricultural Water Sources in the Southeastern United States

Surface water poses a great risk to fruit and vegetable crops when contaminated by foodborne pathogens. Several factors impact the microbial quality of surface waters and increase the risk of produce contamination. Therefore, evaluating the factors associated with the prevalence of pathogenic microorganisms in agricultural water sources is critical to determine and establish preventive actions that may minimize the incidence of foodborne outbreaks associated with contaminated production water. In the Southeastern U.S. environmental factors such as rainfall, temperature, and seasonal variations have been associated with the prevalence of pathogens or microbial indicators of fecal contamination in water. Also, the geographical location of the irrigation sources as well as surrounding activities and land use play an important role on the survival and prevalence of pathogenic bacteria. Therefore, these factors may be determinants useful in the evaluation of production water quality and may help to preemptively identify scenarios or hazards associated with the incidence of foodborne pathogenic microorganisms.

From Mosaic to Systemic Redux: The Conceptual Foundation of Resilience and Its Operational Implications for Water Resource Management

Preserving and enhancing the resilience of water supply systems is an important goal for managers to help ensure the ongoing availability of a resource necessary to both economic activity and basic survival. If not explicitly identified as a goal, it can be inferred from the desire to preserve water supply against a variety of stressors for current and future generations. Pursuing resilience is less than straightforward as there are multiple concurrent theoretical paradigms. Furthermore, operationalizing even one of these can be challenging. The authors survey several dominant paradigms with an eye towards distilling the essential, combinative properties of resilience. The contention underwriting this approach is that each paradigm yields important insights about resilience as a complex, emergent system characteristic. This survey lays the foundation for the operationalized approach that is the central thrust of the paper. Specifically, the authors develop an equation based on these properties and identify water resource metrics that correspond to each property. The analysis concludes with a preliminary causal loop diagram intended to capture key system variables and relationships between them. The authors argue that a systemic, conceptually robust approach to resilience is necessary to (1) assess current levels, and (2) improve levels of water resource system resilience.

A new method to evaluate the vulnerability of watersheds facing several stressors: A case study in mediterranean Chile

Freshwater systems are subjected to multiple anthropogenic stressors and natural disturbances that act as debilitating agents and modifiers of river systems, causing cumulative and synergistic effects that deteriorate their health and result in watershed vulnerability. This study proposes an easy-to-apply spatial method of watershed vulnerability evaluation using Geographic Information Systems (GIS) in the Andalién River watershed, located in the Chilean mediterranean. A watershed vulnerability index (WVI) based on three sub-indices - anthropogenic stressors, environmental fragility and natural disturbances - was developed. To determine the index grouping weights, expert surveys were carried out using the Delphi method. We subsequently normalized and integrated the factors of each sub-index with relative weights. The ranges of each thematic layer were re-classified to establish vulnerability scores. The watershed was divided into three sections: headwaters zone, transfer zone and depositional zone. The watershed vulnerability index showed that 41% of the watershed had very low vulnerability and 42% had medium vulnerability, while only 1% - in the depositional zone - had high vulnerability. A one-way ANOVA was carried out to analyze the vulnerability differences among the three sections of the watershed; it showed significant differences (F (2, 16) = 8.15: p < 0.05). The a posteriori test showed differences between the headwaters and depositional zones (Tukey test, p = 0.005) and between the transfer and depositional zones (Tukey test, p = 0.014). To validate the WVI, water quality was measured at 16 stations in the watershed; there was a significant correlation between vulnerability level and NO₂^- levels (r = 0.8; p = 0.87; α = 0.05) and pH (r = 0.8; p = 0.80; α = 0.05). The WVI showed the cumulative effects of multiple stressors in the depositional zone of the watershed. This is the first study to evaluate and validate non-regulated watershed vulnerability with GIS using multiple anthropogenic and natural stressors.

Linking landscape patterns to sources of water contamination: Implications for tracking fecal contaminants with geospatial and Bayesian approaches

Microbial source tracking (MST) techniques have been designed to identify the host source of fecal contamination in water. However, current MST techniques cannot provide geographic origins of particular sources because they do not provide any spatial information beyond the points of observation. In this study, the associations between landscape patterns and the major sources of microbial contamination were examined and the application of geospatial techniques (e.g., remote sensing and geographic information systems) and Bayesian modeling was explored to track microbial sources over the landscape. The land cover information of three watersheds (the lower Dungeness Watershed, the Middle Rio Grande Watershed, and the Arroyo Burro Watershed) in the United States was obtained either by classifying high resolution satellite images or directly using land cover datasets (e.g., National Land Cover Dataset, 2006 and 2011). Then, the relationship between land use/land cover (LULC) and microbial sources from these three geographically disparate watersheds were analyzed using Bayesian hierarchical models. The results showed the predictive positive associations between human sources of fecal contamination and developed area, between dog sources and grassland, and between bird sources and water, but negative associations between human sources and forest and water areas. Furthermore, the diversity of microbial sources had positive associations with landscape fragmentation and diversity indices. This study demonstrates associations between landscape patterns and major microbial sources and offers new insight in tracking the dominant sources of fecal contamination in water using geospatial and Bayesian techniques.

Kū Hou Kuapā: Cultural Restoration Improves Water Budget and Water Quality Dynamics in Heʻeia Fishpond

In Hawaiʻi, the transition from customary subsistence flooded taro agroecosystems, which regulate stream discharge rate trapping sediment and nutrients, to a plantation-style economy (c. the 1840s) led to nearshore sediment deposition—smothering coral reefs and destroying adjacent coastal fisheries and customary fishpond mariculture. To mitigate sediment transport, Rhizophora mangle was introduced in estuaries across Hawaiʻi (c. 1902) further altering fishpond ecosystems. Here, we examine the impact of cultural restoration between 2012–2018 at Heʻeia Fishpond, a 600–800-year-old walled fishpond. Fishpond water quality was assessed by calculating water exchange rates, residence times, salinity distribution, and abundance of microbial indicators prior to and after restoration. We hypothesized that R. mangle removal and concomitant reconstruction of sluice gates would increase mixing and decrease bacterial indicator abundance in the fishpond. We find that Heʻeia Fishpond’s physical environment is primarily tidally driven; wind forcing and river water volume flux are secondary drivers. Post-restoration, two sluice gates in the northeastern region account for >80% of relative water volume flux in the fishpond. Increase in water volume flux exchange rates during spring and neap tide and shorter minimum water residence time corresponded with the reconstruction of a partially obstructed 56 m gap together with the installation of an additional sluice gate in the fishpond wall. Lower mean salinities post-restoration suggests that increased freshwater water volume influx due to R. mangle removal. Spatial distribution of microbial bio-indicator species was inversely correlated with salinity. Average abundance of Enterococcus and Bacteroidales did not significantly change after restoration efforts, however, average abundance of a biomarker specific to birds nesting in the mangroves decreased significantly after restoration. This study demonstrates the positive impact of biocultural restoration regimes on water volume flux into and out of the fishpond, as well as water quality parameters, encouraging the prospect of revitalizing this and other culturally and economically significant sites for sustainable aquaculture in the future.

Weather and gastrointestinal disease in Spain: A retrospective time series regression study

BACKGROUND

A few studies in high-income countries have investigated the relationship between ambient temperature and/or precipitation and the occurrence of gastroenteritis. In most of the cases, hot temperatures and heavy precipitation events have been related to increases in infections. This is of concern as climate change predictions indicate an increase of those extreme events. Our aim was to evaluate the association between meteorological variables and daily gastroenteritis hospitalizations in Spain for the period 1997-2013.

METHODS

We obtained data on all hospitalizations which occurred in Spain for the study period from administrative databases and selected those with gastroenteritis as the main diagnosis. Meteorological data was obtained from the European Climate Assessment & Dataset. Daily counts of hospitalizations were linked to meteorological variables in a retrospective ecological time series study using quasi-Poisson regression models with overdispersion and applying the Distributed Lag Non-linear Model (DLNM) framework.

RESULTS

Both high and cold temperatures increased the risk of gastroenteritis hospitalizations (relative risk (RR) = 1.21, 95% confidence interval (CI): 1.09, 1.34; and RR = 1.07, 95% CI: 1.00, 1.15, respectively), whereas heavy precipitation was found protective for those hospitalizations (RR = 0.74, 95% CI: 0.63, 0.86). Hot temperatures increased hospitalizations for gastroenteritis classified as foodborne or idiopathic but not those in the group of Others, which were composed mainly of infections by rotavirus and were associated with cold temperatures.

CONCLUSIONS

Our findings suggest an important role of ambient temperatures, especially hot temperatures, in increasing gastroenteritis hospitalizations, while the exposure to heavy precipitation events pose opposite and unexpected effects on these infections.

Fecal source tracking and eDNA profiling in an urban creek following an extreme rain event

Fecal contamination of recreational waters (i.e. lakes, rivers, beaches) poses an on-going problem for environmental and public health. Heavy rainfall can exacerbate existing problems with fecal contamination. As there could be variable sources of fecal contamination, identifying the source is critical for remediation efforts. This study utilized microbial source tracking (MST), chemical source tracking (CST) markers and environmental DNA (eDNA) metabarcoding to profile sampling areas and identify sources of fecal contamination in creek, stormwater outfall and beach sites in the Etobicoke Creek watershed (Toronto, ON). Water samples were collected before and immediately following an extreme rain event. MST and CST identified stormwater outfalls as an important source of human fecal contamination during dry and wet conditions. eDNA metabarcoding allowed for potential identification of additional sources of fecal contamination and provided additional evidence of human fecal contamination. The extreme rainfall event altered the eDNA profiles, causing creek and beach sites to reflect a greater diversity of mammal and bird eDNA sequences. The profiles provided by eDNA metabarcoding provide a proof of concept suggesting that eDNA metabarcoding can be a useful tool to complement MST and CST methods for profiling sources of fecal contamination and studying impacts of extreme rain events.

Fecal source tracking methods to elucidate critical sources of pathogens and contaminant microbial transport through New Zealand agricultural watersheds - A review

In New Zealand, there is substantial potential for microbial contaminants from agricultural fecal sources to be transported into waterways. The flow and transport pathways for fecal contaminants vary at a range of scales and is dependent on chemical, physical and biological attributes of pathways, soils, microorganisms and landscape characteristics. Understanding contaminant transport pathways from catchment to stream can aid water management strategies. It is not practical, however to conduct direct field measurement for all catchments on the fate and transport of fecal pathogens due to constraints on time, personnel, and material resources. To overcome this problem, fecal source tracking can be utilised to link catchment characteristics to fecal signatures identifying critical sources. In this article, we have reviewed approaches to identifying critical sources and pathways for fecal microorganisms from agricultural sources, and make recommendations for the appropriate use of these fecal source tracking (FST) tools.

Effect of Rainfall on the Microbial Water Quality of a Tropical Urban Catchment

Wet weather conditions have been associated with increased bacterial and viral counts in surface waters. Moreover, heavy rainfall and flooding were found to be the most common events preceding waterborne disease outbreaks associated with extreme weather conditions. This study aimed to examine the effect of rainfall on the quality of surface waters and to determine its suitability for primary contact recreation during wet weather conditions. A total of 228 catchment water samples were collected during wet and dry periods. Parameters that were found to increase with increasing rainfall were , enterococci, somatic coliphages, and turbidity, whereas total dissolved solids were found to decrease. Positive correlations ( < 0.05) were observed between cumulative rainfall and geometric mean concentrations of , enterococci, somatic coliphages, and turbidity ( = 0.69-0.95), whereas a negative correlation was observed between cumulative rainfall and total dissolved solids ( = -0.58). In addition, a rapid decline in water quality was observed during heavy rainfall that resulted in failure to meet recreational water quality guidelines. In view of public health and safety, primary recreational activities in the water catchment may not be advisable during or immediately after a rainfall event due to poor water quality.

Environmental Factors Correlated with Culturable Enterococci Concentrations in Tropical Recreational Waters: A Case Study in Escambron Beach, San Juan, Puerto Rico

Enterococci concentration variability at Escambron Beach, San Juan, Puerto Rico, was examined in the context of environmental conditions observed during 2005–2015. Satellite-derived sea surface temperature (SST), turbidity, direct normal irradiance, and dew point were combined with local precipitation, winds, and mean sea level (MSL) observations in a stepwise multiple regression analyses (Akaike Information Criteria model selection). Precipitation, MSL, irradiance, SST, and turbidity explained 20% of the variation in observed enterococci concentrations based upon these analyses. Changes in these parameters preceded increases in enterococci concentrations by 24 h up to 11 days, particularly during positive anomalies of turbidity, SST, and 480–960 mm of accumulated (4 days) precipitation, which relates to bacterial ecology. Weaker, yet still significant, increases in enterococci concentrations were also observed during positive dew point anomalies. Enterococci concentrations decreased with elevated irradiance and MSL anomalies. Unsafe enterococci concentrations per US EPA recreational water quality guidelines occurred when 4-day cumulative precipitation ranged 481–960 mm; irradiance < 667 W·m⁻²; daily average turbidity anomaly >0.005 sr⁻¹; SST anomaly >0.8 °C; and 3-day average MSL anomaly <−18.8 cm. This case study shows that satellite-derived environmental data can be used to inform future water quality studies and protect human health.

Identification of Factors Affecting Fecal Pollution in Beaver Lake Reservoir

Standard methods for the evaluation of recreational water quality rely on generic bacterial indicators such as . However, does not provide enough information to determine fecal source or public health risk. The stsudy objective was to determine factors influencing the presence of and host-specific markers (HSM) from upstream to downstream in Beaver Lake Reservoir (BLR). From February 2014 to September 2015, 420 base flow and rain event samples were collected from seven sites-two sites from streams (White River [WR] and War Eagle Creek) draining into BLR and five sites from within BLR. Each sample was analyzed for and by quantitative polymerase chain reaction for HSM related to human, bovine, and poultry. The data indicate that overall levels of were significantly greater in the WR and significantly lower at the most downstream sampling location in BLR. is more likely present during spring (adjusted odds ratio [aOR] = 1.86), at the WR sampling site (aOR = 3.39), or during a rain event (aOR = 2.73). Moreover, the HSM HumM2 is more likely present (aOR = 1.99) when is present. These same factors were associated with concentrations >126 most probable number 100 mL (aOR = 2.76-12.48), except the poultry marker CL was more likely associated (aOR = 3.81) than HumM2. This study revealed that both seasonal and locational factors are important variables for fecal pollution in BLR. Moreover, these same factors may apply to fecal pollution in manmade reservoirs within similar types of watersheds across the United States, as well as internationally.

Multiple lines of evidence to identify sewage as the cause of water quality impairment in an urbanized tropical watershed

Indicator bacteria, which are conventionally used to evaluate recreational water quality, can originate from various non-human enteric and extra-enteric sources, hence they may not be indicative of human health risk nor do they provide information on the sources of contamination. In this study we utilized traditional (enterococci and Escherichia coli) and alternative (Clostridium perfringens) indicator bacteria, F⁺-specific coliphage, molecular markers for microorganisms associated with human sewage (human-associated Bacteroides and polyomaviruses), and microbial community analysis tools (16S rRNA gene fragment amplicon sequencing), to identify and evaluate human sewage-related impact in the Manoa watershed in Honolulu, Hawaii. Elevated concentrations of enterococci (geometric mean ranging from 1604 to 2575 CFU 100 mL^-1) and C. perfringens (45-77 CFU 100 mL^-1) indicated impairment of the urbanized section of the stream, while indicator bacteria concentrations decreased downstream in the tidally influenced Ala Wai Canal. The threshold values triggering water quality violation notifications in Hawaii were exceeded in 33.3-75.0% of samples collected at sites in the urbanized section of Manoa Stream, but were not exceeded in any of the samples collected at an upstream site located in a forested area. Correlation between indicator bacteria concentrations and rainfall amounts was weak to moderate but significant (E. coli R = 0.251, P = 0.009; enterococci R = 0.369, P < 0.001; C. perfringens R = 0.343, P < 0.001), while concentrations of human fecal-associated molecular markers were not significantly correlated with rainfall (human-associated Bacteroides, R = 0.131, P = 0.256; human-associated polyomaviruses, R = 0.213, P = 0.464). Presence of human sewage was confirmed by detection of human-associated Bacteroides and human polyomavirus in the urbanized section of Manoa Stream (83.3-100% and 41.7-66.7% positive samples respectively). It was further confirmed by microbial community analyses which suggested that an average 2.4-3.4% of the total bacterial population in this section was associated with sewage. Microbial community profiles were significantly influenced by rainfall (R² = 0.4390, P < 0.001), pH (R² = 0.3077, P = 0.006), salinity (R² = 0.2614, P = 0.038), and conductivity (R² = 0.2676, P = 0.031). Although microbial diversity fluctuated throughout the watershed, it was lower in the impaired section. Leaking sewer systems and illegal cross-connections are implicated in the impairment of the watershed, hence both the sewer and the storm water lines should be routinely inspected. Collectively, our data suggest that information derived from the analysis of microbial communities complements current marker-based microbial source tracking techniques and environmental monitoring programs.

The occurrence of antibiotic resistance genes in a Mediterranean river and their persistence in the riverbed sediment

The spread of antibiotic resistance genes (ARGs) in the environment is a serious concern. Bacterial ARGs can spread via different mobile genetic elements as phage particles, which thereby emerge as novel vectors for environmental dissemination. To assess how climate events, such as heavy rains or water scarcity, could affect the spread of ARGs, it is necessary to know their prevalence and abundance in aquatic environments as well as the potential reservoirs from which they could become mobile. This study evaluates the occurrence of ARGs in the water and sediment of a Mediterranean river. Six clinically relevant ARGs (bla_TEM, bla_CTX-M, qnrA, qnrS, mecA and sul1) were quantified by qPCR in the bacterial and phage fractions of 69 water and 70 sediment samples from the River Llobregat (NE Spain), collected during both dry and rainy periods. bla_TEM and sul1 were the most prevalent and abundant ARGs; the others were more variable. Significant seasonal differences in ARG prevalences and abundances were observed. Since ARGs were detected in the sediment, the persistence of the most abundant ARGs naturally occurring in that sediment (bla_TEM and sul1) was evaluated under three conditions. No ARG inactivation occurred in fresh sediment over 14 days; while the ARGs declined by less than 2 log₁₀ units over 35 days in semi-dry and dry sediment. The occurrence of ARGs in water and sediment is influenced by seasonal conditions and they can be mobilized by bacteria and phage particles. In sediment, ARGs persist for long periods and hence sediment can be a natural reservoir of ARGs, from where they can spread and cause the emergence of new resistant strains.

Association of land use and its change with beach closure in the United States, 2004-2013

Land use and its change have great influences on water quality. However, their impacts on microbial contamination of beach water have rarely been investigated and their relationship with beach actions (e.g., advisories or closure) is still unknown. Here, we analyzed beach closure data obtained from 2004 to 2013 for >500 beaches in the United States, and examined their associations with land use around beaches in 2006 and 2011, as well as the land use change between 2006 and 2011. The results show that the number of beach closures due to elevated indicators of health risk is negatively associated with the percentages of forest, barren land, grassland and wetland, while positively associated with the percentages of urban area. The results from multi-level models also indicate the negative association with forest area but positive association with urban area and agriculture. The examination of the change of land use and the number of beach closures between 2006 and 2011 indicates that the increase in the number of beach closures is positively associated with the increase in urban (β=1.612, p<0.05) and agricultural area including pasture (β=0.098, p<0.05), but negatively associated with the increase in forest area (β=-1.789, p<0.05). The study suggests that urbanization and agriculture development near beaches have adverse effects on beach microbial water quality, while afforestation may protect beach water quality and reduce the number of beach closures.

Assessing the microbial quality of a tropical watershed with an urbanization gradient using traditional and alternate fecal indicators

Urbanization affects the microbial loading into tropical streams, but its impact on water quality varies across watersheds. Rainfall in tropical environments also complicates microbial dynamics due to high seasonal and annual variations. Understanding the dynamics of fecal contamination in tropical surface waters may be further hindered by limitations from the utilization of traditional microbial indicators. We measured traditional (Enterococcus spp. and Escherichia coli), as well as alternate (enterophages and coliphages) indicators of fecal contamination in a tropical watershed in Puerto Rico during a 1-year period, and examined their relationship with rainfall events across an urbanization gradient. Enterococcus spp. and E. coli concentrations were 4 to 5 logs higher in non-urbanized or pristine sites when compared to enterophages and coliphages, suggesting that traditional fecal indicator bacteria may be natural inhabitants of pristine tropical waters. All of the tested indicators were positively correlated with rainfall and urbanization, except in the most urbanized sites, where rainfall may have had a dilution effect. The present study indicates that utilizing novel indicators of microbial water quality may improve the assessment of fecal contamination and pathogen risk for tropical watersheds.

Effect of land use and hydrological processes on Escherichia coli concentrations in streams of tropical, humid headwater catchments

Lack of access to clean water and adequate sanitation continues to be a major brake on development. Here we present the results of a 12-month investigation into the dynamics of Escherichia coli, a commonly used indicator of faecal contamination in water supplies, in three small, rural catchments in Laos, Thailand and Vietnam. We show that land use and hydrology are major controlling factors of E. coli concentrations in streamwater and that the relative importance of these two factors varies between the dry and wet seasons. In all three catchments, the highest concentrations were observed during the wet season when storm events and overland flow were highest. However, smaller peaks of E. coli concentration were also observed during the dry season. These latter correspond to periods of intense farming activities and small, episodic rain events. Furthermore, vegetation type, through land use and soil surface crusting, combined with mammalian presence play an important role in determining E. coli loads in the streams. Finally, sampling during stormflow revealed the importance of having appropriate sampling protocols if information on maximum contamination levels is required as grab sampling at a fixed time step may miss important peaks in E. coli numbers.

Impact of Different Land Uses on the Escherichia coli Concentrations, Physical and Chemical Water Quality Parameters in a Tropical Stream

Rural streams are important source of water for the nearby communities. However, bacterial contamination from agriculture and human settlement may render the water unsuitable for drinking and body contact recreation. Hence, the objective of this study was to determine the impact of different land uses such as animal farming and human settlement on E. coli concentrations in the Serin River, a tropical stream. Samplings were conducted at 9 stations from September 2009 to March 2010. Results showed that E. coli concentrations ranged from 2,000-6,900,000 CFU/100 mL with E. coli concentrations in fish aquaculture water exceeding the WHO standard. Animal and crop farming stations showed the highest E. coli concentrations in the tributaries. Re-suspension from stream sediment and non-point sources such as runoff contributed to the high concentrations observed in the main river. Multiple linear regressions indicated that total suspended solids and dissolved oxygen were significant water quality parameters and they explained 68.1% of the total E. coli variations observed.

Untangling the Impacts of Climate Change on Waterborne Diseases: a Systematic Review of Relationships between Diarrheal Diseases and Temperature, Rainfall, Flooding, and Drought

Global climate change is expected to affect waterborne enteric diseases, yet to date there has been no comprehensive, systematic review of the epidemiological literature examining the relationship between meteorological conditions and diarrheal diseases. We searched PubMed, Embase, Web of Science, and the Cochrane Collection for studies describing the relationship between diarrheal diseases and four meteorological conditions that are expected to increase with climate change: ambient temperature, heavy rainfall, drought, and flooding. We synthesized key areas of agreement and evaluated the biological plausibility of these findings, drawing from a diverse, multidisciplinary evidence base. We identified 141 articles that met our inclusion criteria. Key areas of agreement include a positive association between ambient temperature and diarrheal diseases, with the exception of viral diarrhea and an increase in diarrheal disease following heavy rainfall and flooding events. Insufficient evidence was available to evaluate the effects of drought on diarrhea. There is evidence to support the biological plausibility of these associations, but publication bias is an ongoing concern. Future research evaluating whether interventions, such as improved water and sanitation access, modify risk would further our understanding of the potential impacts of climate change on diarrheal diseases and aid in the prioritization of adaptation measures.

Influence of Climate Extremes and Land Use on Fecal Contamination of Shallow Tubewells in Bangladesh

Climate extremes in conjunction with some land use practices are expected to have large impacts on water quality. However, the impacts of land use and climate change on fecal contamination of groundwater has not been well characterized. This work quantifies the influences of extreme weather events and land use practices on Escherichia coli presence and concentration in groundwater from 125 shallow wells, a dominant drinking water resource in rural Bangladesh, monitored over a 17 month period. The results showed that E. coli presence was significantly associated with the number of heavy rain days, developed land and areas with more surface water. These variables also had significant impacts on E. coli concentration, with risk ratios of 1.38 (95% CI = 1.16, 1.65), 1.07 (95% CI: 1.05, 1.09), and 1.02 (95% CI = 1.01, 1.03), respectively. Significant synergistic effects on E. coli presence and concentration were observed when land use and weather variables were combined. The findings suggest that climate extremes and land use practices, particularly urbanization, might promote fecal contamination of shallow well water, thus increasing the risk of diarrheal diseases.

The effects of precipitation, river discharge, land use and coastal circulation on water quality in coastal Maine

Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18-24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible.

Microbial Source Tracking in Adjacent Karst Springs

Modern man-made environments, including urban, agricultural, and industrial environments, have complex ecological interactions among themselves and with the natural surroundings. Microbial source tracking (MST) offers advanced tools to resolve the host source of fecal contamination beyond indicator monitoring. This study was intended to assess karst spring susceptibilities to different fecal sources using MST quantitative PCR (qPCR) assays targeting human, bovine, and swine markers. It involved a dual-time monitoring frame: (i) monthly throughout the calendar year and (ii) daily during a rainfall event. Data integration was taken from both monthly and daily MST profile monitoring and improved identification of spring susceptibility to host fecal contamination; three springs located in close geographic proximity revealed different MST profiles. The Giach spring showed moderate fluctuations of MST marker quantities amid wet and dry samplings, while the Zuf spring had the highest rise of the GenBac3 marker during the wet event, which was mirrored in other markers as well. The revelation of human fecal contamination during the dry season not connected to incidents of raining leachates suggests a continuous and direct exposure to septic systems. Pigpens were identified in the watersheds of Zuf, Shefa, and Giach springs and on the border of the Gaaton spring watershed. Their impact was correlated with partial detection of the Pig-2-Bac marker in Gaaton spring, which was lower than detection levels in all three of the other springs. Ruminant and swine markers were detected intermittently, and their contamination potential during the wet samplings was exposed. These results emphasized the importance of sampling design to utilize the MST approach to delineate subtleties of fecal contamination in the environment.

Identifying fecal pollution sources using 3M(™) Petrifilm (™) count plates and antibiotic resistance analysis in the Horse Creek Watershed in Aiken County, SC (USA)

Sources of fecal coliform pollution in a small South Carolina (USA) watershed were identified using inexpensive methods and commonly available equipment. Samples from the upper reaches of the watershed were analyzed with 3M(™) Petrifilm(™) count plates. We were able to narrow down the study's focus to one particular tributary, Sand River, that was the major contributor of the coliform pollution (both fecal and total) to a downstream reservoir that is heavily used for recreation purposes. Concentrations of total coliforms ranged from 2,400 to 120,333 cfu/100 mL, with sharp increases in coliform counts observed in samples taken after rain events. Positive correlations between turbidity and fecal coliform counts suggested a relationship between fecal pollution and stormwater runoff. Antibiotic resistance analysis (ARA) compared antibiotic resistance profiles of fecal coliform isolates from the stream to those of a watershed-specific fecal source library (equine, waterfowl, canines, and untreated sewage). Known fecal source isolates and unknown isolates from the stream were exposed to six antibiotics at three concentrations each. Discriminant analysis grouped known isolates with an overall average rate of correct classification (ARCC) of 84.3 %. A total of 401 isolates from the first stream location were classified as equine (45.9 %), sewage (39.4 %), waterfowl (6.2 %), and feline (8.5 %). A similar pattern was observed at the second sampling location, with 42.6 % equine, 45.2 % sewage, 2.8 % waterfowl, 0.6 % canine, and 8.8 % feline. While there were slight weather-dependent differences, the vast majority of the coliform pollution in this stream appeared to be from two sources, equine and sewage. This information will contribute to better land use decisions and further justify implementation of low-impact development practices within this urban watershed.

Effect of submarine groundwater discharge on bacterial indicators and swimmer health at Avalon Beach, CA, USA

Use of fecal indicator bacteria (FIB) for monitoring beach water quality is based on their co-occurrence with human pathogens, a relationship that can be dramatically altered by fate and transport processes after leaving the human intestine. We conducted a prospective cohort study at Avalon Beach, California (USA), where the indicator relationship is potentially affected by the discharge of sewage-contaminated groundwater and by solar radiation levels at this shallow, relatively quiescent beach. The goals of this study were to determine: 1) if swimmers exposed to marine water were at higher risk of illness than non-swimmers; 2) if FIB measured in marine water were associated with swimmer illness, and; 3) if the associations between FIB and swimmer health were modified by either submarine groundwater discharge or solar radiation levels. There were 7317 individuals recruited during the summers of 2007-08, 6165 (84%) of whom completed follow-up within two weeks of the beach visit. A total of 703 water quality samples were collected across multiple sites and time periods during recruitment days and analyzed for FIB using both culture-based and molecular methods. Adjusted odds ratios (AOR) indicated that swimmers who swallowed water were more likely to experience Gastrointestinal Illness (GI Illness) within three days of their beach visit than non-swimmers, and that this risk was significantly elevated when either submarine groundwater discharge was high (AOR [95% CI]:2.18 [1.22-3.89]) or solar radiation was low (2.45 [1.25-4.79]). The risk of GI Illness was not significantly elevated for swimmers who swallowed water when groundwater discharge was low or solar radiation was high. Associations between GI Illness incidence and FIB levels (Enterococcus EPA Method 1600) among swimmers who swallowed water were not significant when we did not account for groundwater discharge, but were strongly associated when groundwater discharge was high (1.85 [1.06, 3.23]) compared to when it was low (0.77 [0.42, 1.42]; test of interaction: P = 0.03). These results demonstrate the need to account for local environmental conditions when monitoring for, and making decisions about, public health at recreational beaches. The views expressed in this article are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.

Relationships among hygiene indicators and enteric pathogens in irrigation water, soil and lettuce and the impact of climatic conditions on contamination in the lettuce primary production

Eight Belgian lettuce farms located in the West Flanders were sampled to establish the relationships between levels of indicator bacteria, detection of enteric zoonotic pathogens and the temperature and precipitation during primary production. Pathogenic bacteria (PCR EHEC positives, Salmonella spp. or Campylobacter spp.) and indicator bacteria (total psychrotrophic aerobic plate count (TPAC), total coliforms, Escherichia coli, enterococci) were determined over a period of one and a half year from seedling leaves, peat-soil of the seedling, lettuce crops, field soil and irrigation water. Neither Salmonella isolates nor PCR EHEC signals were detected from lettuce although one out of 92 field soil samples contained Salmonella spp. and five soil samples provided PCR positives for EHEC virulence factors (vt1 or vt2 and eae gene). A low prevalence of Campylobacter (8/88) was noted in lettuce. It was shown that irrigation water is a major risk factor with regard to the bacterial contamination of the fresh produce as the water samples showed on a regular basis E. coli presence (59.2% of samples≥1CFU/100ml) and occasionally detection of pathogens (25%, n=30/120), in particular Campylobacter spp. The highest correlations between indicator bacteria, pathogens, temperature and the amount of precipitation were observed for the water samples in contrast to the soil or lettuce samples where no correlations were observed. The high correlations between E. coli, total coliforms and enterococci in the water implicated redundancy between analyses. Presence of elevated levels of E. coli increased the probability for the presence of pathogens (Campylobacter spp., EHEC and Salmonella spp.), but had a low to moderate predictive value on the actual presence of pathogens. The presence of pathogens and indicator bacteria in the water samples showed a seasonal effect as they tend to be more present during the months with higher temperature.

Gastrointestinal illness among triathletes swimming in non-polluted versus polluted seawater affected by heavy rainfall, Denmark, 2010-2011

Recent years have seen an increase in the frequency of extreme rainfall and subsequent flooding across the world. Climate change models predict that such flooding will become more common, triggering sewer overflows, potentially with increased risks to human health. In August 2010, a triathlon sports competition was held in Copenhagen, Denmark, shortly after an extreme rainfall. The authors took advantage of this event to investigate disease risks in two comparable cohorts of physically fit, long distance swimmers competing in the sea next to a large urban area. An established model of bacterial concentration in the water was used to examine the level of pollution in a spatio-temporal manner. Symptoms and exposures among athletes were examined with a questionnaire using a retrospective cohort design and the questionnaire investigation was repeated after a triathlon competition held in non-polluted seawater in 2011. Diagnostic information was collected from microbiological laboratories. The results showed that the 3.8 kilometer open water swimming competition coincided with the peak of post-flooding bacterial contamination in 2010, with average concentrations of 1.5x10(4) E. coli per 100 ml water. The attack rate of disease among 838 swimmers in 2010 was 42% compared to 8% among 931 swimmers in the 2011 competition (relative risk (RR) 5.0; 95% CI: 4.0-6.39). In 2010, illness was associated with having unintentionally swallowed contaminated water (RR 2.5; 95% CI: 1.8-3.4); and the risk increased with the number of mouthfuls of water swallowed. Confirmed aetiologies of infection included Campylobacter, Giardia lamblia and diarrhoeagenic E. coli. The study demonstrated a considerable risk of illness from water intake when swimming in contaminated seawater in 2010, and a small but measureable risk from non-polluted water in 2011. This suggests a significant risk of disease in people ingesting small amounts of flood water following extreme rainfall in urban areas.

Microbial water quality in freshwater lakes with different land use

AIMS

The relationship between land use (undeveloped, cattle grazing, urban), faecal indicator bacteria (FIB) levels and microbial source tracking (MST) marker detection was investigated in lakes created following phosphate mining.

METHODS AND RESULTS

Faecal coliforms and enterococci were cultured, and MST markers were detected by PCR [Methanobrevibacter smithii, human polyomaviruses (HPyVs), ruminant, human (HF183) and general Bacteroidales]. FIB levels varied significantly by sampling date and were correlated with antecedent rainfall. FIB levels varied with land use category only in the case of faecal coliform levels in sediments of urban lakes, which were significantly greater than those in undeveloped or cattle-impacted lakes. Ruminant Bacteroidales were detected consistently in cattle-impacted lakes (57%) and rarely in other lakes. HPyVs was the only human source marker detected.

CONCLUSIONS

Rainfall was more strongly associated with FIB levels than land use category. The detection frequency of only the ruminant MST marker was associated with land use.

SIGNIFICANCE AND IMPACT OF STUDY

Microbial source tracking (MST) can fine-tune the assessment of human health risk from recreational use of inland waters, particularly when similar FIB levels but different surrounding land use and probable impacts exist.

Health effects of drought: a systematic review of the evidence

Introduction. Climate change projections indicate that droughts will become more intense in the 21 century in some areas of the world. The El Niño Southern Oscillation is associated with drought in some countries, and forecasts can provide advance warning of the increased risk of adverse climate conditions. The most recent available data from EMDAT estimates that over 50 million people globally were affected by drought in 2011. Documentation of the health effects of drought is difficult, given the complexity in assigning a beginning/end and because effects tend to accumulate over time. Most health impacts are indirect because of its link to other mediating circumstances like loss of livelihoods. Methods. The following databases were searched: MEDLINE; CINAHL; Embase; PsychINFO, Cochrane Collection. Key references from extracted papers were hand-searched, and advice from experts was sought for further sources of literature. Inclusion criteria for papers summarised in tables include: explicit link made between drought as exposure and human health outcomes; all study designs/methods; all countries/contexts; any year of publication. Exclusion criteria include: drought meaning shortage unrelated to climate; papers not published in English; studies on dry/arid climates unless drought was noted as an abnormal climatological event. No formal quality evaluation was used on papers meeting inclusion criteria. Results. 87 papers meeting the inclusion criteria are summarised in tables. Additionally, 59 papers not strictly meeting the inclusion criteria are used as supporting text in relevant parts of the results section. Main categories of findings include: nutrition-related effects (including general malnutrition and mortality, micronutrient malnutrition, and anti-nutrient consumption); water-related disease (including E coli, cholera and algal bloom); airborne and dust-related disease (including silo gas exposure and coccidioidomycosis); vector borne disease (including malaria, dengue and West Nile Virus); mental health effects (including distress and other emotional consequences); and other health effects (including wildfire, effects of migration, and damage to infrastructure). Conclusions. The probability of drought-related health impacts varies widely and largely depends upon drought severity, baseline population vulnerability, existing health and sanitation infrastructure, and available resources with which to mitigate impacts as they occur. The socio-economic environment in which drought occurs influences the resilience of the affected population. Forecasting can be used to provide advance warning of the increased risk of adverse climate conditions and can support the disaster risk reduction process. Despite the complexities involved in documentation, research should continue and results should be shared widely in an effort to strengthen drought preparedness and response activities.

Identification of human and animal fecal contamination after rainfall in the Han River, Korea

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.

Terrestrial sources homogenize bacterial water quality during rainfall in two urbanized watersheds in Santa Barbara, CA

Microbiological contamination from runoff is a human health concern in urbanized coastal environments, but the contamination sources are often unknown. This study quantified fecal indicator bacteria and compared the distributions of human-specific genetic markers and bacterial community composition during dry and wet weather in urban creeks draining two neighboring watersheds in Santa Barbara, CA. In a prior study conducted during exclusively dry weather, the creeks were contaminated with human waste as indicated by elevated numbers of the human-specific Bacteroidales marker HF183 (Sercu et al. in Environ Sci Technol 43:293-298, 2009). During the storm, fecal indicator bacterial numbers and loads increased orders of magnitude above dry weather conditions. Moreover, bacterial community composition drastically changed during rainfall and differed from dry weather flow by (1) increased bacterial diversity, (2) reduced spatial heterogeneity within and between watersheds, and (3) clone library sequences more related to terrestrial than freshwater taxa. Finally, the spatial patterns of human-associated genetic markers (HF183 and Methanobrevibacter smithii nifH gene) changed during wet weather, and the contribution of surface soils to M. smithii nifH gene detection was suspected. The increased fecal indicator bacteria numbers during wet weather were likely associated with terrestrial sources, instead of human waste sources that dominated during dry weather flow.