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

Environmental predictors of Escherichia coli concentration at marine beaches in Vancouver, Canada: a Bayesian mixed-effects modelling analysis

Understanding historical environmental determinants associated with the risk of elevated marine water contamination could enhance monitoring marine beaches in a Canadian setting, which can also inform predictive marine water quality models and ongoing climate change preparedness efforts. This study aimed to assess the combination of environmental factors that best predicts Escherichia coli (E. coli) concentration at public beaches in Metro Vancouver, British Columbia, by combining the region's microbial water quality data and publicly available environmental data from 2013 to 2021. We developed a Bayesian log-normal mixed-effects regression model to evaluate predictors of geometric E. coli concentrations at 15 beaches in the Metro Vancouver Region. We identified that higher levels of geometric mean E. coli levels were predicted by higher previous sample day E. coli concentrations, higher rainfall in the preceding 48 h, and higher 24-h average air temperature at the median or higher levels of the 24-h mean ultraviolet (UV) index. In contrast, higher levels of mean salinity were predicted to result in lower levels of E. coli. Finally, we determined that the average effects of the predictors varied highly by beach. Our findings could form the basis for building real-time predictive marine water quality models to enable more timely beach management decision-making.

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

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

Spatio-temporal assessment of water quality of a tropical decaying river in India for drinking purposes and human health risk characterization

River water pollution and water-related health problems are common issues across the world. The present study aims to examine the Jalangi River's water quality to assess its suitability for drinking purposes and associated human health risks. The 34 water samples were collected from the source to the mouth of Jalangi River in 2022 to depict the spatial dynamics while another 119 water samples (2012-2022) were collected from a secondary source to portray the seasonal dynamics. Results indicate better water quality in the lower reach of the river in the monsoon and post-monsoon seasons. Principal component analysis reveals that K+, NO3-, and total alkalinity (TA) play a dominant role in controlling the water quality of the study region, while, CaCO3, Ca2+, and EC in the pre-monsoon, EC, TDS, Na+, and TA in the monsoon, and EC, TDS and TA in the post-monsoon controlled the water quality. The results of ANOVA reveal that BOD, Ca2+, and CaCO3 concentrations in water have significant spatial dynamics, whereas pH, BOD, DO, Cl-, SO42-, Na+, Mg2+, Ca2+, CaCO3, TDS, TA, and EC have seasonal dynamics (p < 0.05). The water quality index depicts that the Jalangi River's water quality ranged from 6.23 to 140.83, i.e., excellent to unsuitable for drinking purposes. Human health risk analysis shows that 32.35% of water samples have non-carcinogenic health risks for all three groups of people, i.e., adults, children, and infants while only 5.88% of water samples have carcinogenic health risks for adults and children. The gradual decay of the Jalangi River coupled with the disposal of urban and agricultural effluents induces river pollution that calls for substantial attention from the various stakeholders to restore the water quality.

Active acoustic surveys reveal coastal fish community resistance to an environmental perturbation in South Florida

Coastal fish communities are under increasing levels of stress associated with climate variation and anthropogenic activities. However, the high degree of behavioral plasticity of many species within these communities allow them to cope with altered environmental conditions to some extent. Here, we combine meteorological information, data from hydroacoustic surveys, and recordings of goliath grouper sound production to examine the response of coastal fish communities to heavy rainfall events in South Florida, USA, that resulted in the release of excess storm water into surrounding estuaries and coastal waters. We observed a nearly 12,000% increase in water column acoustic backscatter following a heavy rainfall event of September 16th, 2015. Interestingly, estimates of school backscatter, a proxy for biomass, increased by 172% with the onset of the perturbation. Schooling fish density also increased by 182%, as did acoustically derived estimates of mean schooling fish length (21%). Following the perturbed period, school backscatter decreased by 406%, along with schooling density (272%), and mean schooling fish length (35%). Hydrophone and hydroacoustic data also revealed that goliath grouper (Epinephelus itajara) spawning aggregations were persistent in the region throughout the duration of the study and continued to exhibit courtship behavior during the perturbed period. Our observations demonstrate the high level of resistance common in coastal species but raises new questions regarding the threshold at which fish communities and reproductive activities are disrupted. As coastal land use continues to increase, and the effects of global climate change become more pronounced, more Before-After Control Impact (BACI) studies will provide improved insight into the overall response of nearshore communities to future perturbations and the cumulative effect of repeated perturbations over extended periods.

Geographic Scale Influences the Interactivities Between Determinism and Stochasticity in the Assembly of Sedimentary Microbial Communities on the South China Sea Shelf

Determinism and stochasticity in microbial community composition decisions have attracted wide attention. However, there is no consensus on their interrelationships and relative importance, and the mechanism controlling the interaction between the two ecological processes remains to be revealed. The interaction of the two ecological processes on the continental shelf of the South China Sea was studied by performing 16S rRNA gene amplicon sequencing on 90 sediments at multiple depths in five sites. Three nearshore sites have higher microbial diversity than those two close to the shelf margin. Different microbial composition was observed between sites and microbial composition of nearshore sites was positively correlated with total nitrogen, total sulfur, total organic carbon, and dissolved oxygen, while that of offshore was positively correlated with total carbon, salinity, and photosynthetically active radiation. The null model test showed that the community composition among layers of the same site and between nearby sites was mainly dominated by the homogeneous selection, while that between distant sites was mainly affected by dispersal limitation, which indicates that geographic scale influences the interactivities of determinism and stochasticity. Our research indicates that the balance of these two ecological processes along the geographic scale is mainly determined by the dispersal ability of microbes and environmental heterogeneity between areas. The study provides new insights into how deterministic and stochastic processes shape microbial community composition on the continental shelf.

Spatial and Seasonal Assessment of Water Quality in the Lobo Stream River Basin, Brazil Using Multivariate Statistical Techniques

In view of the complexity of the processes associated to water quality, this study objective is to identify the main factors related to spatial and seasonal variability in water courses of the Lobo Stream River Basin. To this, multivariate statistical techniques were used. Data collection for water quality and streamflow variables were carried out monthly, from May 2018 to April 2019, at 10 monitoring points along basin's tributaries. The results show that, during the dry season, the main causes for water quality decrease are related to erosion process on the river margins, which is intensified by inadequate handling in livestock activities in some monitoring points. In the rainy season, the main causes are related to soil leaching in agricultural areas that increases the nitrogen compounds concentration and reduces water quality. However, in addition to this, it was noted that regardless the environmental conditions, the most impactful factor is the point pollution from the effluent discharge of Itirapina City sewage treatment plant, responsible for nutrient concentration increase, organic contamination, OD reduction, and, consequently, water quality deterioration. With this, the study shows how multivariate statistical analysis enables more relevant evaluation of water quality data variability and supports further studies in the basin.

Occurrence and distribution of microbial pollutants in coastal areas of the Adriatic Sea influenced by river discharge

The transport of a variety of pollutants from agricultural, industrial and urbanised areas makes rivers major contributors to the contamination of coastal marine environments. Too little is known of their role in carrying pathogens to the coast. We used DNA-based metabarcoding data to describe the microbial community composition in seawater and sediment collected in front of the estuary of the Tronto, the Chienti and the Esino, three Italian rivers with different pollution levels that empty into the north-central Adriatic Sea, and to detect and measure within these communities the relative abundance of microbial pollutants, including traditional faecal indicators and alternative faecal and sewage-associated pollutants. We then applied the FORENSIC algorithm to distinguish human from non-human sources of microbial pollution and FAPROTAX to map prokaryotic clades to established metabolic or other ecologically relevant functions. Finally, we searched the dataset for other common pathogenic taxa. Seawater and sediment contained numerous potentially pathogenic bacteria, mainly faecal and sewage-associated. The samples collected in front of the Tronto estuary showed the highest level of contamination, likely sewage-associated. The pathogenic signature showed a weak but positive correlation with some nutrients and strong correlations with some polycyclic aromatic hydrocarbons. This study confirms that rivers transport pathogenic bacteria to the coastal sea and highlights the value of expanding the use of HTS data, source tracking and functional identification tools to detect microbial pollutants and identify their sources with a view to gaining a better understanding of the pathways of sewage-associated discharges to the sea.

Potential Impacts of Climate and Land Use Change on the Water Quality of Ganga River around the Industrialized Kanpur Region

The heavily industrialised Kanpur region is the most polluted stretch of the Ganga river because of excessive pollutant discharge from the industries. Agricultural runoff along with climate change further adds to the pollution risk in this industrialised stretch of Ganga. In this paper, we analyse the potential impacts of climate change and land use change on the water quality in this stretch under hypothetical scenarios using the water quality model, QUAL2K. Water quality indicators of Dissolved Oxygen (DO), Biochemical Oxygen Demand, ammonia, nitrate, total nitrogen, organic-, inorganic- and total phosphorous and faecal coliform are assessed for eight climate change and six land use land cover scenarios. Eutrophic conditions are observed in this stretch of the river for all scenarios, implying severe impacts on aquatic life. DO is identified as the most sensitive indicator to the climate change scenarios considered, while nutrients and faecal coliform are more sensitive to the land use scenarios. Increase in agricultural land area leads to larger nutrient concentration while increase in built-up area causes an increase in faecal coliform concentration. Results from this hypothetical study could provide valuable guidance for improving the water quality of the Ganges in future climate change and land use change scenarios.

Drivers of water pollution and evaluating its ecological stress with special reference to macrovertebrates (fish community structure): a case of Churni River, India

The focus of this study is to measure ecological stress of Churni River based on the estimates of dissolved oxygen (DO), pH, biological oxygen demand (BOD), chemical oxygen demand (COD), nutrients imbalances of dissolved inorganic nitrogen or DIN (NO₃^- N and NO₂^- N) and dissolved inorganic phosphate or DIP (PO₄^3-). The present water quality measured in terms of overall index of pollution (OIP), eutrophication index (EI), organic pollution (OPI) and water pollution indexes for ecological status (WPI) portrays that the river is polluted having a high concentration of BOD, COD, nutrients (DIP and DIN) and a very low concentration of DO. Fish community structure taken as most sensitive indicator of ecological stress of water pollution depicts that out of 44 species, 28 fish species (63.63%) comprising 20.0% planktivore (PL), 9.09% benthic feeder (BE), 18.18% omnivorous (OM) and 15.90% carnivorous (CA) at Majhdia and 21 fish species (47.72%) comprising 18.18% PL, 4.59% BE, 13.63% OM and 11.36% CA at Ranaghat have been disappeared. The present investigation has found that anthropogenic interventions like disposal of industrial effluents and agricultural run-off from on-bed and off bed land use are the main drivers of the pollution. Furthermore, natural forcing in the form of neotectonic movements and monsoon regimes has intensified the problem.

Association Between Sporadic Legionellosis and River Systems in Connecticut

Background

There has been a dramatic increase in the incidence of sporadic legionnaires' disease in Connecticut since 1999, but the exact reasons for this are unknown. Therefore, there is a growing need to understand the drivers of legionnaires' disease in the community. In this study, we explored the relationship between the natural environment and the spatial and temporal distribution of legionellosis cases in Connecticut.

Methods

We used spatial models and time series methods to evaluate factors associated with the increase and clustering of legionellosis in Connecticut. Stream flow, proximity to rivers, and residence in regional watersheds were explored as novel predictors of disease, while controlling for testing intensity and correlates of urbanization.

Results

In Connecticut, legionellosis incidence exhibited a strong pattern of spatial clustering. Proximity to several rivers and residence in the corresponding watersheds were associated with increased incidence of the disease. Elevated rainfall and stream flow rate were associated with increases in incidence 2 weeks later.

Conclusions

We identified a novel relationship between the natural aquatic environment and the spatial distribution of sporadic cases of legionellosis. These results suggest that natural environmental reservoirs may have a greater influence on the spatial distribution of sporadic legionellosis cases than previously thought.

Assessment of relationship between rainfall and Escherichia coli in clams (Chamelea gallina) using the Bayes Factor

Consumption of bivalve shellfish harvested from water contaminated with sewage pollution presents a risk of human infections and targeting control measures require a good understanding of environmental factors influencing the transport and the fate of faecal contaminants within the hydrological catchments. Although there has been extensive development of regression models, the point of this paper, focused on the relationship between rainfall events and concentrations of Escherichia coli monitored in clams, was the use of a Bayesian approach, by the Bayes Factor. The study was conducted on clams harvested from the south coast of Marche Region (Italy), a coastal area impacted by continuous treated effluents, intermittent rainfalldependent untreated sewage spillage - as a consequence of stormwater overflowing - and rivers with an ephemeral flow regime. The work compared the different interpretation criteria of Bayes Factor, confirmed that E. coli concentrations in clams from the studied area varied in correlation with rainfall events, and demonstrated the effectiveness of Bayes Factor in the assessment of shellfish quality in coastal marine waters. However, it suggested that further investigations would be warranted to determine which environmental factors provide the better basis for accurate and timely predictions. Furthermore the gathered data could be useful, to the local authorities of Marche Region, in the definition of flexible monitoring programmes, taking into account the atmospheric events that could affect the correct functioning of sewage managing systems and the flow of tributary rivers.

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

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

Modelling of faecal indicator bacteria (FIB) in the Red River basin (Vietnam)

Many studies have been published on the use of models to assess water quality through faecal contamination levels. However, the vast majority of this work has been conducted in developed countries and similar studies from developing countries in tropical regions are lacking. Here, we used the Seneque/Riverstrahler model to investigate the dynamics and seasonal distribution of total coliforms (TC), an indicator of faecal contamination, in the Red River (Northern Vietnam) and its upstream tributaries. The results of the model showed that, in general, the overall correlations between the simulated and observed values of TC follow a 1:1 relationship at all examined stations. They also showed that TC numbers were affected by both land use in terms of human and livestock populations and by hydrology (river discharge). We also developed a possible scenario based on the predicted changes in future demographics and land use in the Red River system for the 2050 horizon. Interestingly, the results showed only a limited increase of TC numbers compared with the present situation at all stations, especially in the upstream Vu Quang station and in the urban Ha Noi station. This is probably due to the dominance of diffuse sources of contamination relative to point sources. The model is to our knowledge one of the first mechanistic models able to simulate spatial and seasonal variations of microbial contamination (TC numbers) in the whole drainage network of a large regional river basin covering both urban and rural areas of a developing country.