Evaluating a microbial water quality prediction model for beach management under the revised EU Bathing Water Directive

A critical review of model construction and performance for nowcast systems for faecal contamination in recreational beaches

Faecal contamination is a widespread environmental and public health problem on recreational beaches around the world. The implementation of predictive models has been recommended by the World Health Organization as a complement to traditional monitoring to assist decision-makers and reduce health risks. Despite several advances that have been made in the modeling of faecal coliforms, tools and algorithms from machine learning are still scarcely used in the field and their implementation in nowcast systems is delayed. Here, we perform a literature review on modeling strategies to predict faecal contamination in recreational beaches in the last two decades and the implementation of models in nowcast systems to aid management. Models constructed for surface waters of continental (lakes, rivers and streams), estuarine and marine coastal ecosystems were analyzed and compared based on performance metrics for continuous (i.e. regression; R2, Root Mean Square Error: RMSE) and categorical (i.e. classification; accuracy, sensitivity, specificity) responses. We found 67 articles matching the search criteria and 40 with information allowing to evaluate and compare predictive ability. In early 2000, Multiple Linear Regressions were common, followed by a peak of Artificial Neural Networks (ANNs) from 2010 to 2015, and the rise of Machine learning techniques, such as decision trees (CART and Random Forest) since 2015. ANNs and decision trees presented better accuracy than the remaining models. Rainfall and its lags were important predictor variables followed by water temperature. Specificity was much higher than sensitivity in all modeling strategies, which is typical in data sets where one category (e.g. closed beach) is far less common than the normal state (i.e. unbalanced data sets). We registered the implementation of statistical models in early warning systems in 6 countries, mainly by public beach quality management institutions, followed by NGOs in conjunction with universities. We identified critical steps towards improving model construction, evaluation and usage: i) the need to balance the data set previous to model training, ii) the need to separate data set in training, validation and test to perform an honest evaluation of model performance and iii) the transduction of model outputs to plain language to relevant stakeholders. Integrating into a single framework in situ monitoring, model construction and nowcasting systems could help to improve decision making systems to protect users from bathing in contaminated waters. Still the reduction of arrival of faecal coliforms to aquatic ecosystems (e.g. by improving sewage treatment systems) will be the ultimate factor in reducing health risk.

ADSWIM and WATERCARE Projects Meet Kids and Youth: The Challenge of Bringing the World of Research to School to Merge Research, Education and Communication

The transfer of communication and knowledge from science and research to the general public is a paramount step to raise people’s awareness about environmental issues and their negative and positive impacts on each of us. Many projects and initiatives seek to raise awareness among citizens, with particular attention to young people, about the importance of maintaining clean and healthy oceans. With this paper, we aim to present the successful communication initiatives developed during two Interreg projects, AdSWiM and WATERCARE, with schools and educational organisations on the local and national levels in Italy and Croatia. Both projects make a special effort to realize dedicated communication strategies with the objective of raising the awareness of environmental topics and issues among young people (i.e., students of different school grades) and teachers. The promotion of ocean literacy among students is crucial, as children and young people represent the future citizens and consumers who will develop attitudes and make decisions that will inevitably affect the environment.

Evaluating the potential for exposure to organisms of public health concern in naturally occurring bathing waters in Europe: A scoping review

Globally, water-based bathing pastimes are important for both mental and physical health. However, exposure to waterborne organisms could present a substantial public health issue. Bathing waters are shown to contribute to the transmission of illness and disease and represent a reservoir and pathway for the dissemination of antimicrobial resistant (AMR) organisms. Current bathing water quality regulations focus on enumeration of faecal indicator organisms and are not designed for detection of specific waterborne organisms of public health concern (WOPHC), such as antimicrobial resistant (AMR)/pathogenic bacteria, or viruses. This investigation presents the first scoping review of the occurrence of waterborne organisms of public health concern (WOPHC) in identified natural bathing waters across the European Union (EU), which aimed to critically evaluate the potential risk of human exposure and to assess the appropriateness of the current EU bathing water regulations for the protection of public health. Accordingly, this review sought to identify and synthesise all literature pertaining to a selection of bacterial (Campylobacter spp., Escherichia coli, Salmonella spp., Shigella spp., Vibrio spp., Pseudomonas spp., AMR bacteria), viral (Hepatitis spp., enteroviruses, rotavirus, adenovirus, norovirus), and protozoan (Giardia spp., and Cryptosporidium spp.) contaminants in EU bathing waters. Sixty investigations were identified as eligible for inclusion and data was extracted. Peer-reviewed investigations included were from 18 countries across the EU, totalling 87 investigations across a period of 35 years, with 30% published between 2011 and 2015. A variety of water bodies were identified, with 27 investigations exclusively assessing coastal waters. Waterborne organisms were classified into three categories; bacteria, viruses, and protozoa; amounting to 58%, 36% and 17% of the total investigations, respectively. The total number of samples across all investigations was 8,118, with detection of one or more organisms in 2,449 (30%) of these. Viruses were detected in 1281 (52%) of all samples where WOPHC were found, followed by bacteria (865(35%)) and protozoa (303(12%)). Where assessed (442 samples), AMR bacteria had a 47% detection rate, emphasising their widespread occurrence in bathing waters. Results of this scoping review highlight the potential public health risk of exposure to WOPHC in bathing waters that normally remain undetected within the current monitoring parameters.

Water quality integrated system: A strategic approach to improve bathing water management

In the Adriatic Sea, massive rainfall events are causing flooding of rivers and streams, with severe consequences on the environment. The consequent bacterial contamination of bathing water poses public health risks besides damaging tourism and the economy. This study was conducted in the framework of WATERCARE, an EU Interreg Italy-Croatia Project, which aims at reducing the impact of microbial contamination on Adriatic bathing water due to heavy rainfall events drained in the local sewage network and; enhancing the quality of local waters; and providing support for the decision-making processes regarding the management of bathing water in line with EU regulations. The study involved the development of an innovative water quality integrated system that helps meet these objectives. It consists of four components: a real time hydro-meteorological monitoring system; an autosampler to collect freshwater samples during and after significant rainfall events; a forecast system to simulate the dispersion of pollutants in seawater; and a real-time alert system that can predict the potential ecological risk from the microbial contamination of seawater. The system was developed and tested at a pilot site (Fano, Italy). These preliminary results will be used to develop guidelines for urban wastewater and coastal system quality assessments to contribute to develop policy actions and final governance decisions.

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.

Hydro-epidemiological modelling of bacterial transport and decay in nearshore coastal waters

In recent years, society has become more aware and concerned with the environmental and human health impacts of population growth and urbanisation. In response, a number of legislative measures have been introduced within Europe (and globally), which have sparked much cross-disciplinary research aimed at predicting and quantifying these impacts, and suggesting mitigation measures. In response to such measures this paper is focused on improving current understanding of, and simulating water quality, in the form of bacterial transport and decay, in the aquatic environment and particularly in macro-tidal environments. A number of 2D and 3D hydro-epidemiological models were developed using the TELEMAC suite to predict faecal bacterial levels for a data rich pilot site, namely Swansea Bay, located in the south west of the UK, where more than 7,000 FIO samples were taken and analysed over a two year period. A comparison of 2D and 3D modelling approaches highlights the importance of accurately representing source momentum terms in hydro-epidemiological models. Improvements in 2D model bacterial concentration predictions were achieved by the application of a novel method for representing beach sources within the nearshore zone of a macro-tidal environment. In addition, the use of a depth-varying decay rate was found to enhance the prediction of Faecal Indicator Organism concentrations in 3D models. Recommendations are made for the use of these novel approaches in future modelling studies.

Correlation between antimicrobial resistance and faecal contamination in small urban streams and bathing waters

Antibiotic resistance represents the greatest challenge to healthcare systems around the world. As antibiotic resistance genes (ARGs) are shed in faeces, many studies have focused on how wastewater effluent contributes to ARG pollution in rivers. However, small urban streams and bathing waters not impacted by treated wastewater have received little attention though they may be important reservoirs of ARGs. The main objective of this study was to assess the extent to which ARG and faecal pollution impact small urban streams and bathing waters and to determine if there is a relationship between these contaminants. For one year, bi-monthly water samples were collected from two urban streams and Dublin city's three designated bathing waters. The Liffey Estuary, that receives treated wastewater, was also sampled. The sul1, tet(O), qnrS, bla_TEM, bla_SHV and bla_CTX-M ARGs were quantified. E. coli and intestinal enterococci levels were determined and the source of faecal pollution (human, dog, gull) quantified by microbial source tracking. Our results show that the Liffey Estuary, the urban streams and the bathing waters are highly impacted by ARGs and human faeces. There were clear correlations between all of the studied faecal indicators and ARGs in the Liffey Estuary. In the urban streams relationships were observed for only some of the ARGs and faecal indicators, which is likely a result of non-continuous sewage leaks and overflows to the streams. Similarly, only some ARGs correlated with faecal indicators in the urban bathing waters. The source of ARGs in the bathing waters is likely to be multifaceted as we detected sporadic dog and gull faecal markers. This study demonstrates that small urban streams and bathing waters are reservoirs of ARGs and that they may pose a previously unrecognised public health risk as they have the potential to transmit enteric pathogens and antibiotic resistance determinants.

Evaluating multiple predictive models for beach management at a freshwater beach in the Great Lakes region

Recreational water quality is currently monitored at Sandpoint Beach on Lake St. Clair using culture-based enumeration of Escherichia coli. Using water quality and weather data collected over 4 yr, several multiple linear regression (MLR)-based models were developed for near real-time prediction of E. coli concentration and were tested using independent data from the fifth year. Model performance was assessed by the determination of metrics such as RMSE, accuracy, specificity, sensitivity, and area under the receiver operating characteristic curve (AUROC). Each of the developed MLR models described herein resulted in increased correct responses for both exceedance and non-exceedance of the applicable standard as compared to predictions based on E. coli measurements (persistence models, using the previous day's E. coli concentration), which is the method currently being used. The AUROC values for persistence models are between 0.5 and 0.6, as compared to >0.7 for all the MLR models described herein. Among the MLR models, model performance improved when qualitative sky weather condition, which is commonly reported but was not previously used in similar models, was included. To select the best model, a principal coordinate analysis was used to combine multiple model performance metrics and provide a more sensitive tool for model comparison. Although models developed using 2, 3, and 4 yr of monitoring data provided reasonable performance, the model developed using the most recent 2-yr data was marginally better. Thus, data from the most recent 2 yr are likely sufficient as a training dataset for updating the MLR model for Sandpoint Beach in the future.

Prevendo os níveis de poluição fecal na água e nos moluscos produzidos em fazendas marinhas das baías da Ilha de Santa Catarina

Modelos matemáticos vêm sendo utilizados ao redor do mundo para prever os níveis de poluição em áreas costeiras e comunicar ao público quando a segurança para banho ou consumo de moluscos pode estar comprometido. Estudos recentes da Epagri desenvolveram modelos baseados em regressão que permitem prever os níveis de coliformes em áreas utilizadas para o cultivo de moluscos nas baías Norte e Sul da Ilha de Santa Catarina. Este trabalho apresenta os principais achados desses estudos de forma didática e sugere aplicações práticas para técnicos da área de maricultura, pesca e gestão de recursos hídricos que atuam na região. Termos para indexação: Saúde pública; modelos matemáticos; aquicultura; balneabilidade.

Differential decay and prediction of persistence of Enterococcus spp. and Escherichia coli culturable cells and molecular markers in freshwater and seawater environments

To quantify the impact of fecal pollution on the microbiological bathing water quality, predictive modeling is being increasingly used in which the decay rate of the fecal indicators plays an important role. The decay of sewage-sourced enterococci and Escherichia coli culturable cells and their associated molecular markers (16SrRNA) quantified by Quantitative Reverse transcription PCR were measured in controlled microcosms as well in in situ conditions using different water types, from marine waters to fresh waters with intermediate salinity. All bacterial decays were fitted to a first order decay model. In the laboratory study, the light radiation was the most influent factor affecting E. coli and enterococci survival by culture methods although environmental conditions weakly impacted the decay of molecular markers. The results also indicated differential persistence of genetic markers and culturable organisms of fecal indicator bacteria in different water systems. For each bacteria indicator and analytical method, four equations were obtained to predict the time required to have a 90% reduction (T90) according irradiance, salinity and temperature parameters. The weighted model RMSE (Root Mean Square Error) calculated for all field experiments showed that quantification obtained with the equations defined by laboratory-based study compared reasonably well with in-situ observed quantification (0.4 and 0.2 log by standard culture methods for E. coli and Enterococcus spp. and 0.6 and 0.3 log by RT-qPCR for E. coli and Enterococcus spp. respectively). The modeling tool can be used to predict the presence of fecal pollution in marine and fresh waters in combination with either culture based- or rapid molecular methods.

The disparity between regulatory measurements of E. coli in public bathing waters and the public expectation of bathing water quality

The main objectives of the European Union (EU) Bathing Water Directive (BWD) 2006/7/EC are to safeguard public health and protect designated aquatic environments from microbial pollution. The BWD is implemented through legislation by individual EU Member States and uses faecal indicator organisms (FIOs) as microbial pollution compliance parameters to determine season-end bathing water classifications (either 'Excellent', 'Good', 'Sufficient' or 'Poor'). These classifications are based on epidemiological studies that have linked human exposure to FIOs with the risk of contracting a gastrointestinal illness (GI). However, understanding public attitudes towards bathing water quality, together with perceptions of relative exposure risks, is often overlooked and yet critically important for informing environmental management decisions at the beach and ensuring effective risk communication. Therefore, this study aimed to determine the effectiveness of current regulatory strategies for informing beach users about bathing water quality, and to assess public understanding of the BWD classifications in terms of exposure risk and public health. Two UK designated bathing waters were selected as case studies, and questionnaires were deployed to beach-users. The bathing waters had different classification histories and both had electronic signage in operation for communicating daily water quality predictions. The majority of respondents did not recognise the standardised EU bathing water quality classification signs, and were unaware of information boards or the electronic signs predicting the water quality on that particular day. In general, respondents perceived the bathing water at their respective beach to be either 'good' or 'sufficient', which were also the lowest classifications of water quality they would be willing to accept for bathing. However, the lowest level of risk of contracting a gastrointestinal illness that respondents would be willing to accept suggested a significant misunderstanding of the BWD classification system, with the majority (91%) of respondents finding only a <1% risk level acceptable. The 'Good' classification is much less stringent in terms of likelihood of GI. This study has shown that the current public understanding of the BWD classifications in terms of exposure risk and public health is limited, and an investment in methods for disseminating information to the public is needed in order to allow beach-users to make more informed decisions about using bathing waters.

Hotspots and main drivers of fecal pollution in Neusiedler See, a large shallow lake in Central Europe

To minimize the risk of negative consequences for public health from fecal pollution in lakes, the continuous surveillance of microbiological water quality parameters, alongside other environmental variables, is necessary at defined bathing sites. Such routine surveillance may prove insufficient to elucidate the main drivers of fecal pollution in a complex lake/watershed ecosystem, and it may be that more comprehensive monitoring activities are required. In this study, the aims were to identify the hotspots and main driving factors of fecal pollution in a large shallow Central European lake, the Neusiedler See, and to determine to what degree its current monitoring network can be considered representative spatially. A stochastic and geostatistical analysis of a huge data set of water quality data (~ 164,000 data points, representing a 22-year time-series) of standard fecal indicator bacteria (SFIB), water quality and meteorological variables sampled at 26 sampling sites was conducted. It revealed that the hotspots of fecal pollution are exclusively related to sites with elevated anthropogenic activity. Background pollution from wildlife or diffuse agricultural run-off at more remote sites was comparatively low. The analysis also showed that variability in the incidence of SFIB was driven mainly by meteorological phenomena, above all, temperature, number of sunny hours, and wind (direction and speed). Due to antagonistic effects and temporal undersampling, the influence of precipitation on SFIB variance could not be clearly determined. Geostatistical analysis did reveal that the current spatial sampling density is insufficient to cover SFIB variance over the whole lake, and that the sites are therefore in the most part representative of local phenomena. Suggestions for the future monitoring and managing of fecal pollution are offered. The applied statistical approach may also serve as a model for the study of other such areas, and in general indicate a method for dealing with similarly large and spatiotemporally heterogeneous datasets.

Long term development of Bathing Water Quality at the German Baltic coast: spatial patterns, problems and model simulations

Bathing water quality plays a key role for public health, is highly important for recreational tourism and therefore monitored in the EU-Directive 2006/7/EC. To identify pollution hot spots, sources and impacts of the directive-change in 2006, including a change of indicator organisms, we evaluated monitoring data of the past 15 years, collected own data, determined survival rates of indicator organisms and applied hydrodynamic modelling in a micro-tidal-system. Due to higher survival rates under turbid conditions and restricted water exchange, shallow, eutrophic bays and lagoons are hot spots of microbial pollution. Rain events cause high microbial emission and distribution. Based on different decay rates, the ratio of E. coli to Enterococci can hint towards a pollution source. Including rain predictions, currents and winds, hydrodynamic models can then assess the daily risk of microbial pollution at each bathing site. They are an important tool to modify beach management and event-based monitoring.

Developing, cross-validating and applying regression models to predict the concentrations of faecal indicator organisms in coastal waters under different environmental scenarios

This study developed, cross-validated and applied a regression-based model to predict concentrations of faecal indicator organisms (FIOs) under different environmental conditions in the North and South bays of Santa Catarina, South of Brazil. The model was developed using a database of FIO concentrations in seawater sampled at 50 sites and the validation was performed using a different database by comparing 288 pairs of measured and modelled results for 15 sites. The index of agreement between the model outputs and the FIO concentrations measured during the validation period was 66%; the mean average error was 0.43 log₁₀ and the root mean square error was 0.58 log₁₀ MPN.100mL^-1. These validation results indicate that the model provides a fair representation of the FIO contamination in the bays for the meteorological conditions under which the model was trained. The simulation of different scenarios showed that under typical levels of resident human population in the catchments and median rainfall and solar radiation conditions, the median FIO concentration in the bays is 0.4 MPN.100mL^-1. Under extreme meteorological conditions, the combined effect of high rainfall and low solar radiation increased FIO concentrations up to 5 log₁₀ MPN.100mL^-1. The simulated scenarios also show that increases in resident population during the summer tourist season and average rainfall concentrations do not increase median FIO concentrations in the bays relative to periods of time with average population, possibly because of higher bacterial die-off in the waters. The models can be an effective tool for management of human health risks in bathing and shellfish waters impacted by sewage pollution.

The Flow Generator Relations for Water Renewal through the Flushing Culverts in Marinas

An understanding of the relationship between the flow generators and harbor design could result in an acceptable seawater renewal into an enclosed basin. The flushing culverts located in the breakwater are the most cost-effective technique for improving water renewal in port engineering. The aim of the paper was to identify and quantify the relation between flow generators and culvert flow to propose an optimal position for the flushing culverts. Mentioned relations are important for designing and positioning the flushing culverts in marinas to achieve optimal sea exchange in the marina basin. Field measurements in the marina Opatija were performed and the data served for calibrating a 3D circulation model and a wave generation/propagation model. The absolute volume of the flow through the culverts caused by wind waves has the more important contribution to the water renewal in the marina basin than the coastal springs have. The optimal flow rates through the culverts are performed by positioning the flushing culvert axis at the mean sea level in accordance with the main incident direction of the propagating waves.

Sources of nitrogen and phosphorus emissions to Irish rivers and coastal waters: Estimates from a nutrient load apportionment framework

More than half of surface water bodies in Europe are at less than good ecological status according to Water Framework Directive assessments, and diffuse pollution from agriculture remains a major, but not the only, cause of this poor performance. Agri-environmental policy and land management practices have, in many areas, reduced nutrient emissions to water. However, additional measures may be required in Ireland to further decouple the relationship between agricultural productivity and emissions to water, which is of vital importance given on-going agricultural intensification. The Source Load Apportionment Model (SLAM) framework characterises sources of phosphorus (P) and nitrogen (N) emissions to water at a range of scales from sub-catchment to national. The SLAM synthesises land use and physical characteristics to predict emissions from point (wastewater, industry discharges and septic tank systems) and diffuse sources (agriculture, forestry, etc.). The predicted annual nutrient emissions were assessed against monitoring data for 16 major river catchments covering 50% of the area of Ireland. At national scale, results indicate that total average annual emissions to surface water in Ireland are over 2700tyr^-1 of P and 82,000tyr^-1 of N. The proportional contributions from individual sources show that the main sources of P are from municipal wastewater treatment plants and agriculture, with wide variations across the country related to local anthropogenic pressures and the hydrogeological setting. Agriculture is the main source of N emissions to water across all regions of Ireland. These policy-relevant results synthesised large amounts of information in order to identify the dominant sources of nutrients at regional and local scales, contributing to the national nutrient risk assessment of Irish water bodies.