Modeling the dry-weather tidal cycling of fecal indicator bacteria in surface waters of an intertidal wetland

Current status of microbial source tracking applications in constructed wetlands serving as nature-based solutions for water management and wastewater treatment

Microbial source tracking (MST) has been recognised as an effective tool for determining the origins and sources of faecal contamination in various terrestrial and aquatic ecosystems. Thus, it has been widely applied in environmental DNA (eDNA) surveys to define specific animal- and human-associated faecal eDNA. In this context, identification of and differentiation between anthropogenic and zoogenic faecal pollution origins and sources are pivotal for the evaluation of waterborne microbial contamination transport and the associated human, animal, and environmental health risks. These concerns are particularly pertinent to diverse nature-based solutions (NBS) that are being applied specifically to secure water safety and human and ecosystem well-being, for example, constructed wetlands (CWs) for water and wastewater treatment. The research in this area has undergone a constant evolution, and there is a solid foundation of publications available across the world. Hence, there is an early opportunity to synthesise valuable information and relevant knowledge on this specific topic, which will greatly benefit future work by improving NBS design and performance. By selecting 15 representative research reports published over 20 years, we review the current state of MST technology applied for faecal-associated contamination measures in NBS/CWs throughout the world.

Modelling faecal microbe dynamics within stormwater constructed wetlands

Modelling faecal microbe levels is performed widely in natural and wastewater wetlands, yet these predictions can be challening due to highly stochastic storm events. In our study, a coupled hydrodynamic and microorganism model was developed and tested to predict the long-term faecal microbial removal in stormwater constructed wetlands. The microorganism model simulates the fate and transport of the faecal indicator organism Escherichia coli (E. coli), resolving advection-dispersion, sedimentation, resuspension and die-off based on temperature and UV exposure. The model was tested using a two-year monitoring dataset collected from Troups Creek wetland, a multiple-inflow stormwater wetland in Melbourne, Australia. The model parameter values applied in the coupled model were based on a mixture of site-specific data and values obtained from literature. The only adjusted parameter in our microorganism model was the die-off rate in dark conditions in the stormwater wetlands. An urban stormwater microorganism model, MOPUS, was used to generate continuous catchment E. coli loading rates as input to the wetland. The hydrodynamic model was evaluated using flow rate monitored at the outlet weir, achieving Nash- Sutcliffe Efficiency (E) values of 0.86 over the two-year monitoring period. The E. coli model was tested using outflow E. coli concentration data and achieved an overall E of 0.37. The performance of the microbial model was variable across the 22 monitored events, with E ranging from <0 to 0.8. Sensitivity tests were performed to evaluate the model outputs and the results indicated that (a) the importance of collecting high-quality data for stormwater inputs into wetlands and (b) the importance of accurate estimation of the die-off rate in wetland microbial removal models. Our research showed that this model can be used to help design and rectify stormwater constructed wetlands for better faecal microbial removal, vegetation maintenance and support future real-time decision-making.

Fecal indicator bacteria diversity and decay in an estuarine mangrove ecosystem of the Xuan Thuy National Park, Vietnam

Mangroves are complex and dynamic ecosystems that are highly dependent on diverse microbial activities. In this study, laboratory experiments and field studies for fecal indicator bacteria (FIB) decay rates are carried out for the first time in the Xuan Thuy Mangrove Forest Reserve of Vietnam. Results show that there are significant differences in bacterial diversity in the water of mangrove areas that have been deforested compared to those which have been planted. The highest mean total coliform (TC) and Escherichia coli (EC) values were found in the natural mangroves (3,807±2,922 and 964±1133 CFU 100 ml^-1, respectively). The results indicated that the source of contamination and seasonal changes affect the abundance of fecal bacteria. These results were exceeding by far the safety guidelines for individual, non-commercial water supplies in most of the samples. In the planted mangrove sampling sites, the highest mean Fecal streptococci (FS) values of 1,520±1,652 CFU 100 ml^-1 were found. Microbial die-off rates were calculated over 5 days, and observed to be systematically higher for TC than for EC.

Indexes for the assessment of bacterial pollution in bathing waters from point sources: The northern Adriatic Sea CADEAU service

This paper presents a novel set of water quality indexes to identify the area potentially affected by point sources of bacterial pollution in coastal bathing waters. The indexes, developed in the framework of the CADEAU service, are evaluated on the results of a modelling system based on the integration of a high-resolution ocean model, remote sensing observations and in situ monitoring data for the northern Adriatic Sea. In particular, the system is a downscaling of the Mediterranean Copernicus Marine Environment Monitoring Service and exploits data produced within the Bathing Waters Directive, the Water Framework Directive and the Urban Waste Water Treatment Directive to create added value products. The aim of the proposed indexes is to support the identification of areas of influence for bathing waters by identifying the potential threat from point sources of bacterial pollution, both in standard conditions and peculiar events such as a total bypass of wastewater treatment plants. The results for the Chioggia Municipality case study show the potential of the indexes to significantly improve the geographical identification and quantitative evaluation of the impacts of bacterial pollution sources on bathing waters, facilitating the design of mitigation measures. The proposed methodology represents a new management approach to support local authorities in defining the area of influence within the water bathing profile through the proper characterization of the point sources of bacterial pollution.

Genetic Microbial Source Tracking Support QMRA Modeling for a Riverine Wetland Drinking Water Resource

Riverine wetlands are important natural habitats and contain valuable drinking water resources. The transport of human- and animal-associated fecal pathogens into the surface water bodies poses potential risks to water safety. The aim of this study was to develop a new integrative modeling approach supported by microbial source tracking (MST) markers for quantifying the transport pathways of two important reference pathogens, Cryptosporidium and Giardia, from external (allochthonous) and internal (autochthonous) fecal sources in riverine wetlands considering safe drinking water production. The probabilistic-deterministic model QMRAcatch (v 1.1 python backwater) was modified and extended to account for short-time variations in flow and microbial transport at hourly time steps. As input to the model, we determined the discharge rates, volumes and inundated areas of the backwater channel based on 2-D hydrodynamic flow simulations. To test if we considered all relevant fecal pollution sources and transport pathways, we validated QMRAcatch using measured concentrations of human, ruminant, pig and bird associated MST markers as well as E. coli in a Danube wetland area from 2010 to 2015. For the model validation, we obtained MST marker decay rates in water from the literature, adjusted them within confidence limits, and simulated the MST marker concentrations in the backwater channel, resulting in mean absolute errors of < 0.7 log₁₀ particles/L (Kruskal–Wallis p > 0.05). In the scenarios, we investigated (i) the impact of river discharges into the backwater channel (allochthonous sources), (ii) the resuspension of pathogens from animal fecal deposits in inundated areas, and (iii) the pathogen release from animal fecal deposits after rainfall (autochthonous sources). Autochthonous and allochthonous human and animal sources resulted in mean loads and concentrations of Cryptosporidium and Giardia (oo)cysts in the backwater channel of 3–13 × 10⁹ particles/hour and 0.4–1.2 particles/L during floods and rainfall events, and in required pathogen treatment reductions to achieve safe drinking water of 5.0–6.2 log₁₀. The integrative modeling approach supports the sustainable and proactive drinking water safety management of alluvial backwater areas.

Effect of Tidal Cycle on Escherichia coli Variability in a Tropical Estuary

A faecal indicator bacteria, Escherichia coli (E. coli), is widely used in monitoring health of estuaries, where tidal amplitude plays a critical role in its variability. Mahanadi estuary, formed at the mouth of a major tropical river Mahanadi, has large socio-economic importance. This anthropogenically stressed estuary remains understudied with respect to E. coli. Hence, this study addressed E. coli variability in Mahanadi estuary with novel sampling strategy that can be implemented at other tropical estuaries. The sampling strategy includes simultaneous measurements, at lesser-saline upper-estuary and higher-saline lower-estuary, over a tidal cycle. Although no significant variability of E. coli was observed between upper and lower-estuary, overall average count was higher during low tide and lower during high tide attributed to salinity fluctuations. Intermittent surpass of E. coli counts above recommended limits in Mahanadi estuary, indicated potential health risk, thus demands for frequent water quality monitoring and management strategies.

Evaluating the impacts of foreshore sand and birds on microbiological contamination at a freshwater beach

Beaches along the Great Lakes shorelines are important recreational and economic resources. However, contamination at the beaches can threaten their usage during the swimming season, potentially resulting in beach closures and/or advisories. Thus, understanding the dynamics that control nearshore water quality is integral to effective beach management. There have been significant improvements in this effort, including incorporating modeling (empirical, mechanistic) in recent years. Mechanistic modeling frameworks can contribute to this understanding of dynamics by determining sources and interactions that substantially impact fecal indicator bacteria concentrations, an index routinely used in water quality monitoring programs. To simulate E. coli concentrations at Jeorse Park beaches in southwest Lake Michigan, a coupled hydrodynamic and wave-current interaction model was developed that progressively added contaminant sources from river inputs, avian presence, bacteria-sediment interactions, and bacteria-sand-sediment interactions. Results indicated that riverine inputs affected E. coli concentrations at Jeorse Park beaches only marginally, while avian, shoreline sand, and sediment sources were much more substantial drivers of E. coli contamination at the beach. By including avian and riverine inputs, as well as bacteria-sand-sediment interactions at the beach, models can reasonably capture the variability in observed E. coli concentrations in nearshore water and bed sediments at Jeorse Park beaches. Consequently, it will be crucial to consider avian contamination sources and water-sand-sediment interactions in effective management of the beach for public health and as a recreational resource and to extend these findings to similar beaches affected by shoreline embayment.

Particle association of Enterococcus sp. increases growth rates and simulated persistence in water columns of varying light attenuation and turbulent diffusivity

Predicting water quality and the human health risks associated with sewage-derived microbes requires understanding the fate and transport of these contaminants. Sewage-derived pathogen risks are typically assessed and monitored by measuring concentrations of fecal indicating bacteria (FIB), like Enterococcus sp. Previous research demonstrated that a high fraction of FIB is particle-associated, which can alter FIB dynamics within secondary water bodies. In this study, we experimentally quantified the effect of particle association on dark, temperature- and light-dependent growth and sinking rates of enterococci. Particle association significantly increased dark growth rates, light-dependent growth rates (i.e. decreased mortality), and sinking rates, relative to free-living enterococci. Simulations using a novel, 1-dimensional model parameterized by these rates indicate greater persistence (T₉₀) for particle-associated enterococci in water bodies across a wide range of diffuse attenuation coefficients of light (K_d) and turbulent diffusivity (D) values. In addition, persistence of both fractions increased in simulated turbid and turbulent waters, compared to clear and/or quiescent conditions. Simulated persistence of both fractions also increased when enterococci discharges occurred later in a diel cycle (towards sunset, as opposed to sunrise), especially for the free-living population, because later discharges under our model conditions allowed both fractions to mix deeper before inactivation via sunlight. Model sensitivity testing revealed that T₉₀ variability was greatest when dark growth rates were altered, suggesting that future empirical studies should focus on quantifying these rates for free-living and particle-associated sewage-derived microbes. Despite greater sensitivity of T₉₀ to variability in dark growth rates, omitting light-dependent growth rates from simulations dramatically influenced T₉₀ values. Our results demonstrate that particle association can increase enterococci persistence in receiving waters and highlight the importance of incorporating particle association in future water quality models.

Numerical Modeling of Microbial Fate and Transport in Natural Waters: Review and Implications for Normal and Extreme Storm Events

Degradation of water quality in recreational areas can be a substantial public health concern. Models can help beach managers make contemporaneous decisions to protect public health at recreational areas, via the use of microbial fate and transport simulation. Approaches to modeling microbial fate and transport vary widely in response to local hydrometeorological contexts, but many parameterizations include terms for base mortality, solar inactivation, and sedimentation of microbial contaminants. Models using these parameterizations can predict up to 87% of variation in observed microbial concentrations in nearshore water, with root mean squared errors ranging from 0.41 to 5.37 log10 Colony Forming Units (CFU) 100 mL−1. This indicates that some models predict microbial fate and transport more reliably than others and that there remains room for model improvement across the board. Model refinement will be integral to microbial fate and transport simulation in the face of less readily observable processes affecting water quality in nearshore areas. Management of contamination phenomena such as the release of storm-associated river plumes and the exchange of contaminants between water and sand at the beach can benefit greatly from optimized fate and transport modeling in the absence of directly observable data.

Coastal Wetlands: Ecosystems Affected by Urbanization?

Coastal wetlands are ecosystems that provide multiple benefits to human settlements; nonetheless, they are seriously threatened due to both a lack of planning instruments and human activities associated mainly with urban growth. An understanding of their functioning and status is crucial for their protection and conservation. Two wetlands with different degrees of urbanization, Rocuant-Andalién (highly urbanized) and Tubul-Raqui (with little urbanization), were analyzed using temperature, salinity, dissolved oxygen, pH, turbidity, granulometry, fecal coliform, and macroinvertebrate assemblage variables in summer and winter. In both wetlands marked seasonality in salinity, temperature and sediment texture classification, regulated by oceanic influence and changes in the freshwater budget, was observed. In the Rocuant-Andalién wetland, the increases in pH, dissolved oxygen, gravel percentage, and coliform concentration were statistically significant. Urbanization generated negative impacts on macroinvertebrate assemblage structure that inhabit the wetlands; greater richness and abundance (8.5 times greater) were recorded in the Tubul-Raqui wetland than in the more urbanized wetland. The multivariate statistical analysis reflects the alteration of these complex systems.

Development of a Nowcasting System Using Machine Learning Approaches to Predict Fecal Contamination Levels at Recreational Beaches in Korea

Microbial contamination in beach water poses a public health threat due to waterborne diseases. To reduce the risk of exposure to fecal contamination, informing beachgoers in advance about the microbial water quality is important. Currently, determining the level of fecal contamination takes 24 h. The objective of this study is to predict the current level of fecal contamination (enterococcus [ENT] and ) using readily available environmental variables. Artificial neural network (ANN) and support vector regression (SVR) models were constructed using data from the Haeundae and Gwangalli Beaches in Busan City. The input variables included the tidal level, air and water temperature, solar radiation, wind direction and velocity, precipitation, discharge from the wastewater treatment plant, and suspended solid concentration in beach water. The dependence of fecal contamination on the input variables was statistically evaluated; precipitation, discharge from the wastewater treatment plant, and wind direction at the two beaches were positively correlated to the changes in the two bacterial concentrations ( < 0.01), whereas solar radiation was negatively correlated ( < 0.01). The performance of the ANN model for predicting ENT and at Gwangalli Beach was significantly higher than that of the SVR model with the training dataset ( < 0.05). Based on the comparison of residual values between the predicted and observed fecal indicator bacteria concentrations in two models, the ANN demonstrated better performance than SVR. This study suggests an effective prediction method to determine whether a beach is safe for recreational use.

Real-Time Nowcasting of Microbiological Water Quality at Recreational Beaches: A Wavelet and Artificial Neural Network-Based Hybrid Modeling Approach

The number of beach closings caused by bacterial contamination has continued to rise in recent years, putting beachgoers at risk of exposure to contaminated water. Current approaches predict levels of indicator bacteria using regression models containing a number of explanatory variables. Data-based modeling approaches can supplement routine monitoring data and provide highly accurate short-term forecasts of beach water quality. In this paper, we apply the nonlinear autoregressive network with exogenous inputs (NARX) method with explanatory variables to predict Escherichia coli concentrations at four Lake Michigan beach sites. We also apply the nonlinear input-output network (NIO) and nonlinear autoregressive neural network (NAR) methods in addition to a hybrid wavelet-NAR (WA-NAR) model and demonstrate their application. All models were tested using 3 months of observed data. Results revealed that the NARX models provided the best performance and that the WA-NAR model, which requires no explanatory variables, outperformed the NIO and NAR models; therefore, the WA-NAR model is suitable for application to data scarce regions. The models proposed in this paper were evaluated using multiple performance metrics, including sensitivity and specificity measures, and produced results comparable or superior to those of previous mechanistic and statistical models developed for the same beach sites. The relatively high R² values between data and the NARX models ( R² values of ∼0.8 for the beach sites and ∼0.9 for the river site) indicate that the new class of models shows promise for beach management.

Modelling the transport and decay processes of microbial tracers in a macro-tidal estuary

The Loughor Estuary is a macro-tidal coastal basin, located along the Bristol Channel, in the South West of the U.K. The maximum spring tidal range in the estuary is up to 7.5 m, near Burry Port Harbour. This estuarine region can experience severe coastal flooding during high spring tides, including extreme flooding of the intertidal saltmarshes at Llanrhidian, as well as the lower industrial and residential areas at Llanelli and Gowerton. The water quality of this estuarine basin needs to comply with the designated standards for safe recreational bathing and shellfish harvesting industries. The waterbody however, potentially receives overloading of bacterial inputs that enter the estuarine system from both point and diffuse sources. Therefore, a microbial tracer study was carried out to get a better understanding of the faecal bacteria sources and to enable a hydro-environmental model to be refined and calibrated for both advection and dispersion transport. A two-dimensional hydro-environmental model has been refined and extended to predict the highest water level covering the intertidal floodplains of the Loughor Estuary. The validated hydrodynamic model for both water levels and currents, was included with the injected mass of microbial tracer, i.e. MS2 coliphage from upstream of the estuary, and modelled as a non-conservative tracer over several tidal cycles through the system. The calibration and validation of the transport and decay of microbial tracer was undertaken, by comparing the model results and the measured data at two different sampling locations. The refined model developed as a part of this study, was used to acquire a better understanding of the water quality processes and the potential sources of bacterial pollution in the estuary.

Norwegian study on microbial source tracking for water quality control and pollution removal in constructed wetland treating catchment run-off

This study describes the first Norwegian microbial source tracking (MST) approach for water quality control and pollution removal from catchment run-off in a nature-based treatment system (NBTS) with a constructed wetland. The applied MST tools combined microbial analyses and molecular tests to detect and define the source(s) and dominant origin(s) of faecal water contamination. Faecal indicator bacteria Escherichia coli and host-specific Bacteroidales 16 s rRNA gene markers have been employed. The study revealed that the newly developed contribution profiling of faecal origin derived from the Bacteroidales DNA could quantitatively distinguish between human and non-human pollution origins. Further, the outcomes of the MST test have been compared with the results of both physicochemical analyses and tests of pharmaceutical and personal care products (PPCPs). A strong positive correlation was discovered between the human marker and PPCPs. Gabapentin was the most frequently detected compound and it showed the uppermost positive correlation with the human marker. The study demonstrated that the NBTS performs satisfactorily with the removal of E. coli but not PPCPs. Interestingly, the presence of PPCPs in the water samples was not correlated with high concentrations of E. coli. Neither has the latter an apparent correlation with the human marker.

Sources and persistence of fecal indicator bacteria and Bacteroidales in sand as measured by culture-based and culture-independent methods: A case study at Santa Monica Pier, California

This study investigated causes of persistent fecal indicator bacteria (FIB) in beach sand under the pier in Santa Monica, CA. FIB levels were up to 1,000 times higher in sand underneath the pier than that collected from adjacent to the pier, with the highest concentrations under the pier in spring and fall. Escherichia coli (EC) and enterococci (ENT) under the pier were significantly positively correlated with moisture (ρ = 0.61, p < 0.001, n = 59; ρ = 0.43, p < 0.001, n = 59, respectively), and ENT levels measured by qPCR (qENT) were much higher than those measured by membrane filtration (cENT). Microcosm experiments tested the ability of EC, qENT, cENT, and general Bacteroidales (GenBac) to persist under in-situ moisture conditions (10% and 0.1%). Decay rates of qENT, cENT, and GenBac were not significantly different from zero at either moisture level, while decay rates for EC were relatively rapid during the microcosm at 10% moisture (k = 0.7 days-1). Gull/pelican marker was detected at eight of 12 sites and no human-associated markers (TaqHF183 and HumM2) were detected at any site during a one-day site survey. Results from this study indicate that the high levels of FIB observed likely stem from environmental sources combined with high persistence of FIB under the pier.

Investigating the fate and transport of fecal coliform contamination in a tidal estuarine system using a three-dimensional model

A three-dimensional fecal coliform transport model was developed and incorporated into a hydrodynamic and suspended sediment transport model to better understand the microbiological water quality in the tidal Tamsui River estuarine system of northern Taiwan, which includes three main tributaries: Dahan River, Xindian River, and Keelung River. The model was calibrated using the water level, salinity, suspended sediment concentration, and fecal coliform data measured in 2010. The predictive skill, a statistical approach, is used to evaluate the model performance. There was quantitatively good agreement between the simulation and measurement results. Further, the calibrated model underwent model sensitivity analysis by varying the model parameters which include the settling velocity, darkness decay rate, partition coefficient, and fecal coliform concentration in the sediment bed. The results indicated that the settling velocity played the most important role in affecting fecal coliform concentrations followed by partition coefficient, darkness decay rate, and fecal coliform concentration in the sediment bed. The model was also used to investigate the effects of salinity and suspended sediment on fecal coliform contamination. The salinity module was excluded in the simulations, resulting in an increase of fecal coliform concentration. However the effect of salinity on fecal coliform concentration is minor. If the suspended sediment transport was excluded in the simulations, the predicted results of fecal coliform concentration decrease to be underestimated the measured data. The modeling results revealed that the inclusion of the suspended sediment transport model in the simulations was of crucial importance because the fecal coliform concentrations were significantly influenced by the suspended sediment concentration in the estuarine system.

Comparative Evaluation of Statistical and Mechanistic Models of Escherichia coli at Beaches in Southern Lake Michigan

Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term "tracer" transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.

Distribution of Escherichia coli in a coastal lagoon (Venice, Italy): Temporal patterns, genetic diversity and the role of tidal forcing

Despite its worldwide importance as fecal indicator in aquatic systems, little is known about the diversity of Escherichia coli in the environment and the factors driving its spatial distribution. The city of Venice (Italy), lying at the forefront of a large European lagoon, is an ideal site to study the mechanisms driving the fate of fecal bacteria, due to the huge fluxes of tourists, the city's unique architecture (causing poor efficiency of sewages treatment), and the long branching network of canals crossing the city. We summarize the results of a multi-year investigation to study the temporal dynamics of E. coli around the city, describe the population structure (by assigning isolates to their phylogenetic group) and the genotypic diversity, and explore the role of environmental factors in determining its variability. E. coli abundance in water was highly variable, ranging from being undetectable up to 10(4) Colony Forming Units (CFU) per 100 ml. Abundance did not display significant relationships with the water physico-chemical variables. The analysis of the population structure showed the presence of all known phylogroups, including extra-intestinal and potentially pathogenic ones. The genotypic diversity was very high, as likely consequence of the heterogeneous input of fecal bacteria from the city, and showed site-specific patterns. Intensive sampling during the tidal fluctuations highlighted the prominent role of tides, rather than environmental variables, as source of spatial variation, with a more evident influence in water than sediments. These results, the first providing information on the genetic properties, spatial heterogeneity and influence of tides on E. coli populations around Venice, have implications to manage the fecal pollution, and the associated waterborne disease risks, in coastal cities lying in front of lagoons and semi-enclosed basins.

Modelling the fate and transport of faecal bacteria in estuarine and coastal waters

This paper details a numerical model developed to predict the fate and transport of faecal bacteria in receiving surface waters. The model was first validated by comparing model predicted faecal bacteria concentrations with available field measurements. The model simulations agreed well with the observation data. After calibration, the model was applied to investigate the effects of different parameters, including: tidal processes, river discharges from the upstream boundaries and bacteria inputs from the upstream boundaries, wastewater treatment works (WwTWs), rivers and combined sewer overflows (CSO), on the concentrations of faecal bacteria in the Ribble Estuary. The results revealed that the tide and upstream boundary bacteria inputs were the primary factors controlling the distribution of faecal bacteria. The bacteria inputs from the WwTWs in the model domain were generally found not to have a significant impact on distribution of faecal bacteria in the estuary.

Modeling system for predicting enterococci levels at Holly Beach

This paper presents a new modeling system for nowcasting and forecasting enterococci levels in coastal recreation waters at any time during the day. The modeling system consists of (1) an artificial neural network (ANN) model for predicting the enterococci level at sunrise time, (2) a clear-sky solar radiation and turbidity correction to the ANN model, (3) remote sensing algorithms for turbidity, and (4) nowcasting/forecasting data. The first three components are also unique features of the new modeling system. While the component (1) is useful to beach monitoring programs requiring enterococci levels in early morning, the component (2) in combination with the component (1) makes it possible to predict the bacterial level in beach waters at any time during the day if the data from the components (3) and (4) are available. Therefore, predictions from the component (2) are of primary interest to beachgoers. The modeling system was developed using three years of swimming season data and validated using additional four years of independent data. Testing results showed that (1) the sunrise-time model correctly reproduced 82.63% of the advisories issued in seven years with a false positive rate of 2.65% and a false negative rate of 14.72%, and (2) the new modeling system was capable of predicting the temporal variability in enterococci levels in beach waters, ranging from hourly changes to daily cycles. The results demonstrate the efficacy of the new modeling system in predicting enterococci levels in coastal beach waters. Applications of the modeling system will improve the management of recreational beaches and protection of public health.

A predictive model for microbial counts on beaches where intertidal sand is the primary source

Human health protection at recreational beaches requires accurate and timely information on microbiological conditions to issue advisories. The objective of this study was to develop a new numerical mass balance model for enterococci levels on nonpoint source beaches. The significant advantage of this model is its easy implementation, and it provides a detailed description of the cross-shore distribution of enterococci that is useful for beach management purposes. The performance of the balance model was evaluated by comparing predicted exceedances of a beach advisory threshold value to field data, and to a traditional regression model. Both the balance model and regression equation predicted approximately 70% the advisories correctly at the knee depth and over 90% at the waist depth. The balance model has the advantage over the regression equation in its ability to simulate spatiotemporal variations of microbial levels, and it is recommended for making more informed management decisions.

Stratification and loading of fecal indicator bacteria (FIB) in a tidally muted urban salt marsh

Stratification and loading of fecal indicator bacteria (FIB) were assessed in the main tidal channel of the Ballona Wetlands, an urban salt marsh receiving muted tidal flows, to (1) determine FIB concentration versus loading within the water column at differing tidal flows, (2) identify associations of FIB with other water quality parameters, and (3) compare wetland FIB concentrations to the adjacent estuary. Sampling was conducted four times during spring-tide events; samples were analyzed for FIB and turbidity (NTU) four times over a tidal cycle at pre-allocated depths, depending on the water level. Additional water quality parameters measured included temperature, salinity, oxygen, and pH. Loadings were calculated by integrating the stratified FIB concentrations with water column cross-sectional volumes corresponding to each depth. Enterococci and Escherichia coli were stratified both by concentration and loading, although these variables portrayed different patterns over a tidal cycle. Greatest concentrations occurred in surface to mid-strata levels, during flood tides when contaminated water flowed in from the estuary, and during ebb flows when sediments were suspended. Loading was greatest during flood flows and diminished during low tide periods. FIB concentrations within the estuary often were significantly greater than those within the wetland tide channel, supporting previous studies that the wetlands act as a sink for FIB. For public health water quality monitoring, these results indicate that more accurate estimates of FIB concentrations would be obtained by sampling a number of points within a water column rather than relying only on single surface samples.

Integrated modelling of faecal contamination in a densely populated river-sea continuum (Scheldt River and Estuary)

In order to simulate the long-term (months-years) median Escherichia coli distributions and variations in the tidal Scheldt River and Estuary, a dedicated module was developed for the Second-generation Louvain-la-Neuve Ice-ocean Model (SLIM, www.climate.be/slim). The resulting model (SLIM-EC2) presents two specific and new features compared to the older SLIM-EC model version. The first is that the E. coli concentrations in the river are split in three fractions: the free E. coli in the water column, the ones attached to suspended solids and those present in the bottom sediments, each with their own transport, decay and settling-resuspension dynamics. The bacteria attached to particles can settle and survive on the bottom, where they can be brought back in the water column during resuspension events. The second new feature of the model is that it is coupled to the catchment model SENEQUE-EC, which thus provides upstream boundary conditions to SLIM-EC2. The result is an integrated and multi-scale model of the whole Scheldt drainage network from its source down to the Belgian/Dutch coastal zone. This new model reproduces the long-term median E. coli concentration along the Scheldt River and Estuary. An extensive sensitivity study is performed demonstrating the relative robustness of the model with respect to the chosen parameterisations. In addition to reproducing the observed E. coli concentrations in 2007-2008 at various stations, two extreme wastewater management scenarios were considered. Overall, there is no doubt that the Scheldt Estuary acts as a cleaning filter of faecal contamination originating from large Belgian cities. As a result, at the mouth of the Scheldt Estuary E. coli concentration is negligible in all investigated conditions.

An assessment of fecal indicator and other bacteria from an urbanized coastal lagoon in the City of Los Angeles, California, USA

A study was performed in Del Rey Lagoon, City of Los Angeles, to determine if the lagoon was as a source or sink for fecal indicator bacteria (FIB: total coliforms, Escherichia coli, enterococci) and to screen for the presence of other potentially pathogenic bacteria. The lagoon receives tidal flows from the adjacent Ballona Estuary whose water usually is contaminated with FIB originating from the highly urbanized Ballona Creek Watershed. During 16 sampling events from February 2008 through March 2009, replicate water samples (n = 3) were collected 1 h prior to the high tide and 1 h prior to the following low tide. FIB concentrations were measured by the defined substrate method (IDEXX, Westbrook, Me) followed by culturing of bacterial isolates sampled from positive IDEXX Quanti-Tray wells and were identified using the Vitek 2 Compact (bioMérieux, Durham, NC). Mean concentrations of FIB often differed by an order of magnitude from flood to ebb flow conditions. The lagoon tended to act as a sink for total coliforms based on the ratio of mean flood to ebb densities (R (F/E)) >1.0 during 56 % of the sampling events and during ebb flows, as a source for E. coli and enterococci (R (F/E) <1.69 % of events). Approximately 54 species were identified from 277 isolates cultured from the IDEXX Quanti-Trays. Of these, 54 % were species known to include pathogenic strains that can be naturally occurring, introduced in runoff, or originated from other sources. Diversity and cluster analyses indicated a dynamic assemblage that changes in species composition with day-to-day fluctuations as well as tidal action. The concept of monitoring the lagoon and estuary as a sentinel habitat for pathogenic assemblages is discussed.

Modelling importance of sediment effects on fate and transport of enterococci in the Severn Estuary, UK

The paper detailed a water quality modelling study of a hyper-tidal estuary, undertaken to assess the impact of various bacteria input loads on the receiving waters in a coastal basin in the UK, by using the model developed in previous study of the same authors enterococci, used as the indicators for bathing water quality under the new European Union (EU) Bathing Water Directive, were numerically modelled using a hydro-environmental model. In particular, the numerical model used in this study includes the effects of sediment on bacteria transport processes in surface water. Finally, the importance of sediment bacteria inputs on the bathing water quality was also investigated under different weather and tidal condition. During spring tide, the bacteria input from the bed sediments are dominant for both wet and dry weather conditions. During neap tides and during dry weather conditions the inputs of bacteria from the bed sediment were still dominant, but during wet weather conditions the inputs from river were dominant. Under different tidal flow conditions some parameters had a more significant role than others. During high flow conditions the sediment re-suspensions processes were dominant, therefore the bed bacteria concentrations played a dominant role on the overall bacteria concentration levels in the water column. In contrast, during low flow conditions sediment deposition prevails and bacteria are removed from the water column. The partition coefficient was found to be more important than the bed bacteria concentrations, during low flow conditions.

Physical dynamics controlling variability in nearshore fecal pollution: fecal indicator bacteria as passive particles

We present results from a 5-h field program (HB06) that took place at California's Huntington State Beach. We assessed the importance of physical dynamics in controlling fecal indicator bacteria (FIB) concentrations during HB06 using an individual based model including alongshore advection and cross-shore variable horizontal diffusion. The model was parameterized with physical (waves and currents) and bacterial (Escherichia coli and Enterococcus) observations made during HB06. The model captured surfzone FIB dynamics well (average surfzone model skill: 0.84 {E. coli} and 0.52 {Enterococcus}), but fell short of capturing offshore FIB dynamics. Our analyses support the hypothesis that surfzone FIB variability during HB06 was a consequence of southward advection and diffusion of a patch of FIB originating north of the study area. Offshore FIB may have originated from a different, southern, source. Mortality may account for some of the offshore variability not explained by the physical model.

Development of predictive models for determining enterococci levels at Gulf Coast beaches

The US EPA BEACH Act requires beach managers to issue swimming advisories when water quality standards are exceeded. While a number of methods/models have been proposed to meet the BEACH Act requirement, no systematic comparisons of different methods against the same data series are available in terms of relative performance of existing methods. This study presents and compares three models for nowcasting and forecasting enterococci levels at Gulf Coast beaches in Louisiana, USA. One was developed using the artificial neural network (ANN) in MATLAB Toolbox and the other two were based on the US EPA Virtual Beach (VB) Program. A total of 944 sets of environmental and bacteriological data were utilized. The data were collected and analyzed weekly during the swimming season (May-October) at six sites of the Holly Beach by Louisiana Beach Monitoring Program in the six year period of May 2005-October 2010. The ANN model includes 15 readily available environmental variables such as salinity, water temperature, wind speed and direction, tide level and type, weather type, and various combinations of antecedent rainfalls. The ANN model was trained, validated, and tested using 308, 103, and 103 data sets (collected in 2007, 2008, and 2009) with an average linear correlation coefficient (LCC) of 0.857 and a Root Mean Square Error (RMSE) of 0.336. The two VB models, including a linear transformation-based model and a nonlinear transformation-based model, were constructed using the same data sets. The linear VB model with 6 input variables achieved an LCC of 0.230 and an RMSE of 1.302 while the nonlinear VB model with 5 input variables produced an LCC of 0.337 and an RMSE of 1.205. In order to assess the predictive performance of the ANN and VB models, hindcasting was conducted using a total of 430 sets of independent environmental and bacteriological data collected at six Holly Beach sites in 2005, 2006, and 2010. The hindcasting results show that the ANN model is capable of predicting enterococci levels at the Holly Beach sites with an adjusted RMSE of 0.803 and LCC of 0.320 while the adjusted RMSE and LCC values are 1.815 and 0.354 for the linear VB model and 1.961 and 0.521 for the nonlinear VB model. The results indicate that the ANN model with 15 parameters performs better than the VB models with 6 or 5 parameters in terms of RMSE while VB models perform better than the ANN model in terms of LCC. The predictive models (especially the ANN and the nonlinear VB models) developed in this study in combination with readily available real-time environmental and weather forecast data can be utilized to nowcast and forecast beach water quality, greatly reducing the potential risk of contaminated beach waters to human health and improving beach management. While the models were developed specifically for the Holly Beach, Louisiana, the methods used in this paper are generally applicable to other coastal beaches.

A model for predicting resuspension of Escherichia coli from streambed sediments

To improve the modeling of water quality in watersheds, a model is developed to predict resuspension of Escherichia coli from sediment beds in streams. The resuspension rate is expressed as the product of the concentration of E. coli attached to sediment particles and an erosion rate adapted from work on sediment transport. The model uses parameter values mostly taken from previous work, and it accounts for properties of the flow through the bottom shear stress and properties of the sediment through the critical shear stresses for cohesive and non-cohesive sediment. Predictions were compared to resuspension rates inferred from a steady mass balance applied to measurements at sixteen locations in a watershed. The model's predictions matched the inferred rates well, especially when the diameter of particles to which E. coli attach was allowed to depend on the bottom shear stress. The model's sensitivity to the parameters depends on the contributions of particle packing and binding effects of clay to the critical shear stress. For the current data set, the uncertainty in the predictions is controlled by the concentration of E. coli attached to sediment particles and the slope used to estimate the bottom shear stress.

Modelling Escherichia coli concentrations in the tidal Scheldt river and estuary

Recent observations in the tidal Scheldt River and Estuary revealed a poor microbiological water quality and substantial variability of this quality which can hardly be assigned to a single factor. To assess the importance of tides, river discharge, point sources, upstream concentrations, mortality and settling a new model (SLIM-EC) was built. This model was first validated by comparison with the available field measurements of Escherichia coli (E. coli, a common fecal bacterial indicator) concentrations. The model simulations agreed well with the observations, and in particular were able to reproduce the observed long-term median concentrations and variability. Next, the model was used to perform sensitivity runs in which one process/forcing was removed at a time. These simulations revealed that the tide, upstream concentrations and the mortality process are the primary factors controlling the long-term median E. coli concentrations and the observed variability. The tide is crucial to explain the increased concentrations upstream of important inputs, as well as a generally increased variability. Remarkably, the wastewater treatment plants discharging in the study domain do not seem to have a significant impact. This is due to a dilution effect, and to the fact that the concentrations coming from upstream (where large cities are located) are high. Overall, the settling process as it is presently described in the model does not significantly affect the simulated E. coli concentrations.

A water quality modeling study of non-point sources at recreational marine beaches

A model study was conducted to understand the influence of non-point sources including bather shedding, animal fecal sources, and near shore sand, as well as the impact of the environmental conditions, on the fate and transport of the indicator microbe, enterococci, at a subtropical recreational marine beach in South Florida. The model was based on an existing finite element hydrodynamic and transport model, with the addition of a first order microbe deactivation function due to solar radiation. Results showed that dog fecal events had a major transient impact (hundreds of Colony Forming Units/100 ml [CFU/100 ml]) on the enterococci concentration in a limited area within several hours, and could partially explain the high concentrations observed at the study beach. Enterococci released from beach sand during high tide caused mildly elevated concentration for a short period of time (ten to twenty of CFU/100 ml initially, reduced to 2 CFU/100 ml within 4 h during sunny weather) similar to the average baseline numbers observed at the beach. Bather shedding resulted in minimal impacts (less than 1 CFU/100 ml), even during crowded holiday weekends. In addition, weak current velocity near the beach shoreline was found to cause longer dwelling times for the elevated concentrations of enterococci, while solar deactivation was found to be a strong factor in reducing these microbial concentrations.

Beach boundary layer: a framework for addressing recreational water quality impairment at enclosed beaches

Nearshore waters in bays, harbors, and estuaries are frequently contaminated with human pathogens and fecal indicator bacteria. Tracking down and mitigating this contamination is complicated by the many point and nonpoint sources of fecal pollution that can degrade water quality along the shore. From a survey of the published literature, we propose a conceptual and mathematical framework, the "beach boundary layer model", for understanding and quantifying the relative impact of beach-side and bay-side sources of fecal pollution on nearshore water quality. In the model, bacterial concentration in ankle depth water C(ankle) [bacteria L(-3)] depends on the flux m'' [bacteria L(-2) T(-1)] of fecal bacteria from beach-side sources (bather shedding, bird and dog feces, tidal washing of sediments, decaying vegetation, runoff from small drains, and shallow groundwater discharge), a cross-shore mass transfer velocity k [L T(-1)] that accounts for the physics of nearshore transport and mixing, and a background concentration C(bay) [bacteria L(-3)] attributable to bay-side sources of pollution that impact water quality over large regions (sewage outfalls, creeks and rivers): C(ankle) = m''/k + C(bay). We demonstrate the utility of the model for identifying risk factors and pollution sources likely to impact shoreline water quality, and evaluate the model's underlying assumptions using computational fluid dynamic simulations of flow, turbulence, and mass transport in a trapezoidal channel.

Budget analysis of Escherichia coli at a Southern Lake Michigan Beach

Escherichia coli (EC) concentrations at two beaches impacted by river plume dynamics in southern Lake Michigan were analyzed using three-dimensional hydrodynamic and transport models. The relative importance of various physical and biological processes influencing the fate and transport of EC were examined via budget analysis and a first-order sensitivity analysis of model parameters. The along-shore advective flux of EC (CFU/m(2).s) was found to be higher compared to its cross-shore counterpart; however, the sum of diffusive and advective components was of a comparable magnitude in both directions showing the importance of cross-shore exchange in EC transport. Examination of individual terms in the EC mass balance equation showed that vertical turbulent mixing in the water column dominated the overall EC transport for the summer conditions simulated. Dilution due to advection and diffusion accounted for a large portion of the total EC budget in the nearshore, and the net EC loss rate within the water column (CFU/m(3).s) was an order of magnitude smaller compared to the horizontal and vertical transport rates. This result has important implications for modeling EC at recreational beaches; however, the assessment of the magnitude of EC loss rate is complicated due to the strong coupling between vertical exchange and depth-dependent EC loss processes such as sunlight inactivation and settling. Sensitivity analysis indicated that solar inactivation has the greatest impact on EC loss rates. Although these results are site-specific, they clearly bring out the relative importance of various processes involved.

Ecological control of fecal indicator bacteria in an urban stream

Fecal indicator bacteria (FIB) have long been used as a marker of fecal pollution in surface waters subject to point source and non-point source discharges of treated or untreated human waste. In this paper, we set out to determine the source(s) of elevated FIB concentrations in Cucamonga Creek, a concrete-lined urban stream in southern California. Flow in the creek consists primarily of treated and disinfected wastewater effluent, mixed with relatively smaller but variable flow of runoff from the surrounding urban landscape. Dry and wet weather runoff contributes nearly 100% of FIB loading to Cucamonga Creek, while treated wastewater contributes significant loading of nutrients, including dissolved organic carbon (DOC), phosphorus, nitrate, and ammonium. FIB concentrations are strongly positively correlated with DOC concentration in runoff (Spearman's rho >or= 0.66, P <or= 0.037), and microcosm studies reveal that the survival of Escherichia coli and enterococci bacteria in runoff is strongly dependent on the concentration of both DOC and phosphorus. Below threshold concentrations of 7 and 0.07 mg/L, respectively, FIB die off exponentially (die-off rate 0.09 h(-1)). Above these thresholds, FIB either grow exponentially (growth rate 0.3 h(-1)) or exhibit a periodic steady-state in which bacterial concentrations fluctuate around some mean value. The periodic steady-state pattern is consistent with a Lotka-Volterra predator-prey oscillation model, and the clearance rate (20 microL predator(-1) h(-1)) obtained by fitting the model to our data is consistent with the hypothesis that predacious protozoa regulate FIB concentrations in runoff at high DOC concentrations. Collectively, these results indicate that FIB impairment of Cucamonga Creek is best viewed as an ecological phenomenon characterized by both bottom-up and top-down control.

Calibrating and validating bacterial water quality models: a Bayesian approach

Water resource management decisions often depend on mechanistic or empirical models to predict water quality conditions under future pollutant loading scenarios. These decisions, such as whether or not to restrict public access to a water resource area, may therefore vary depending on how models reflect process, observation, and analytical uncertainty and variability. Nonetheless, few probabilistic modeling tools have been developed which explicitly propagate fecal indicator bacteria (FIB) analysis uncertainty into predictive bacterial water quality model parameters and response variables. Here, we compare three approaches to modeling variability in two different FIB water quality models. We first calibrate a well-known first-order bacterial decay model using approaches ranging from ordinary least squares (OLS) linear regression to Bayesian Markov chain Monte Carlo (MCMC) procedures. We then calibrate a less frequently used empirical bacterial die-off model using the same range of procedures (and the same data). Finally, we propose an innovative approach to evaluating the predictive performance of each calibrated model using a leave-one-out cross-validation procedure and assessing the probability distributions of the resulting Bayesian posterior predictive p-values. Our results suggest that different approaches to acknowledging uncertainty can lead to discrepancies between parameter mean and variance estimates and predictive performance for the same FIB water quality model. Our results also suggest that models without a bacterial kinetics parameter related to the rate of decay may more appropriately reflect FIB fate and transport processes, regardless of how variability and uncertainty are acknowledged.

An assessment of fecal indicator bacteria-based water quality standards

Fecal indicator bacteria (FIB) are commonly used to assess the threat of pathogen contamination in coastal and inland waters. Unlike most measures of pollutant levels however, FIB concentration metrics, such as most probable number (MPN) and colony-forming units (CFU), are not direct measures of the true in situ concentration distribution. Therefore, there is the potential for inconsistencies among model and sample-based water quality assessments, such as those used in the Total Maximum Daily Load (TMDL) program. To address this problem, we present an innovative approach to assessing pathogen contamination based on water quality standards that impose limits on parameters of the actual underlying FIB concentration distribution, rather than on MPN or CFU values. Such concentration-based standards link more explicitly to human health considerations, are independent of the analytical procedures employed, and are consistent with the outcomes of most predictive water quality models. We demonstrate how compliance with concentration-based standards can be inferred from traditional MPN values using a Bayesian inference procedure. This methodology, applicable to a wide range of FIB-based water quality assessments, is illustrated here using fecal coliform data from shellfish harvesting waters in the Newport River Estuary, North Carolina. Results indicate that areas determined to be compliant according to the current methods-based standards may actually have an unacceptably high probability of being in violation of concentration-based standards.

Microbial indicators of faecal contamination in waters and sediments of beach bathing zones

This study presents the results obtained of the microbial characterization of waters and sediments of 18 coastal bathing zones of the south-western coast of the Iberian Peninsula. To make this characterization, two indicators of faecal contamination have been selected: faecal coliforms (FC) and Clostridium perfringens (CP). The results show that low concentrations of FC and CP in water not necessarily implies that their concentration in sediment and elutriates has to be low as well. The highest concentrations were found in locations close to the mouth of rivers, and in beaches of low energy and hence low water renewal, and high accumulation of fine sediments. The concentrations of FC were lower than those obtained for CP in most of the sampling locations. Although quality standards for bathing waters do not take the parameter CP into account, it has been demonstrated that it should be a good indicator of faecal contamination.

Frequent occurrence of the human-specific Bacteroides fecal marker at an open coast marine beach: relationship to waves, tides and traditional indicators

Molecular genetic markers, such as those from fecal Bacteroides microorganisms, can link microbial pollution with its source, and have been used successfully in studies of sheltered aquatic environments. Their applicability to wave-driven, open coast environments has not been tested. We assessed the contribution of a tidal outlet to surf zone water quality in coastal Orange County, California, USA by measuring three traditional culture-based fecal indicator bacteria (FIB) as well as the human-specific Bacteroides molecular marker (HF marker) at four shoreline locations. We found that total and fecal coliform levels were higher during low tides than high tides at two of the four stations, and that this effect was strongest at the mouth of the tidal lagoon and decayed with distance from the outlet. The HF marker was detected in 23% and 47% of samples from the tidal outlet and 26% and 41% of samples from an adjacent recreational beach in 2005 and 2006 respectively. Surprisingly, the station farthest from the tidal outlet had the highest occurrence of the HF marker. We found no relationship between FIB abundance and occurrence of the HF marker for individual samples, but that when the data were considered together by year, higher FIB abundance was correlated with a higher incidence of the HF marker. DNA sequences of the HF marker recovered from this site were > 99% similar to those recovered from other states and countries, suggesting low global diversity of this marker. These data provide strong support for the idea that multiple time points and physical conditions should be considered when assessing coastal water quality.

Solar and tidal modulations of fecal indicator bacteria in coastal waters at Huntington Beach, California

The coastal waters at many beaches in California and the United States are afflicted with fecal pollution, which poses a health risk for people exposed to the water through recreational activities such as swimming, surfing, and diving. Identifying sources of pollution is complicated by oceanographic transport/mixing processes and the nonconservative behavior of microorganisms exposed to sunlight and hostile marine conditions. This article investigates the variation of fecal indicator bacteria (FIB) concentrations in the surf zone and the adjacent coastal marsh by applying autocorrelation and cross-correlation analyses that illustrate solar and tidal modulations. A steady state bioreactor model was developed to explain solar inactivation in the surf zone, whereas a dynamic model was applied to explain tidally influenced disturbances in the coastal marsh. These models applied to intensive monitoring datasets on FIB and environmental variables have provided insights into the biologic and physical processes controlling coastal water quality, specifically the influence of sunlight and tides on bacterial levels.

Identifying pollutant sources in tidally mixed systems: case study of fecal indicator bacteria from marinas in Newport Bay, southern California

This study investigates the contribution of several marinas to fecal indicator bacteria impairment in Newport Bay, a regionally important tidal embayment in southern California. Three different fecal indicator bacteria groups were assayed, including total coliform, Escherichia coli, and enterococci bacteria, all measured using the IDEXX Colilert and Enterolert system. To document temporal variability in the fecal indicator bacteria signal, water column samples (n = 4132) were collected from two marinas over time scales ranging from hours to months. To document spatial variability of the fecal indicator bacteria signal, water column and sediment samples were collected from a number of sites (n = 11 to 36, depending on the study) in and around the two marinas, over spatial scales ranging from meters to kilometers. To identify the dominant temporal and spatial patterns in these data a statistical approach--Empirical Orthogonal Function analysis--was utilized. Finally, to clarify the transport pathways responsible for the observed temporal and spatial patterns, fecal indicator bacteria data were compared to simultaneous measurements of tidal flow, temperature, and salinity. The results of this field effort collectively implicate runoff--both dry weather runoff at sampling sites located near some storm drains and wet weather runoff at all sites--as a primary source of fecal indicator bacteria in the water column and subtidal sediments. The results and analysis presented here reinforce the growing body of evidence that management of fecal indicator bacteria impairment in the coastal waters of southern California will require developing long-term strategies for treating nonpoint sources of both dry weather and stormwater runoff.