A Low-Cost, Low-Power Water Velocity Sensor Utilizing Acoustic Doppler Measurement.

Current commercial sensors to monitor water flow velocities are expensive, bulky, and require significant effort to install. Low-cost sensors open the possibility of monitoring storm and waste water systems at a much greater spatial and temporal resolution without prohibitive costs and resource investment. To aid in this, this work developed a low-cost, low-power velocity sensor based on acoustic Doppler velocimetry. The sensor, costing less than 50 USD is open-source, open-hardware, compact, and easily interfaceable to a wide range of data-logging systems. A freely available sensor design at this price point does not currently exist, and its novelty is in enabling high-resolution real-time monitoring schemes. The design is capable of measuring water velocities up to 1200 mm/s. The sensor is characterised and then verified in an in-field long-term test. Finally, the data from this test are then used to evaluate the performance of the sensor in a real-world scenario. The analysis concludes that the sensor is capable of effectively measuring water velocity.

Performance analysis of a stormwater green infrastructure model for flow and water quality predictions.

Nature-based solutions or Green infrastructure (GI) used for managing stormwater pollution are growing in popularity across the globe. Stormwater GI models are important tools to inform the planning of these systems (type, design, size), in the most efficient and cost-effective manner. MUSIC, an example of such a tool, uses regression and first order decay models. Studies validating MUSIC model performance are, however, scarce, hindering future model development and transferability of the model for systems operating under different design and climatic conditions. To close this gap, this paper evaluates MUSIC for a field scale bioretention system, stormwater wetland and vegetated swale operating under Singapore tropical climate. The treatment modules were able to simulate outflows and effluent pollutant concentrations reasonably well for cumulative event volumes (mostly within ±25%) and cumulative TP and TN loads (within ±30%). Outflow TSS loads were significantly under-estimated as a result of greater variability in measured TSS concentrations across events. The findings indicate that simple empirical models such as MUSIC can be transferred to different regions provided that management decisions are based on long-term modelling efforts. The modules generally simulated the outflow hydrographs and pollutographs of the different inflow and drying/wetting conditions relatively poorly.

Passive Sampling of SARS-CoV-2 for Wastewater Surveillance.

The shedding of pathogens by infected humans enables the use of sewage monitoring to conduct wastewater-based epidemiology (WBE). Although most WBE studies use data from large sewage treatment plants, timely data from smaller catchments are needed for targeted public health action. Traditional sampling methods, like autosamplers or grab sampling, are not conducive to quick ad hoc deployments and high-resolution monitoring at these smaller scales. This study develops and validates a cheap and easily deployable passive sampler unit, made from readily available consumables, with relevance to the COVID-19 pandemic but with broader use for WBE. We provide the first evidence that passive samplers can be used to detect SARS-CoV-2 in wastewater from populations with low prevalence of active COVID-19 infections (0.034 to 0.34 per 10,000), demonstrating their ability for early detection of infections at three different scales (lot, suburb, and city). A side by side evaluation of passive samplers (n = 245) and traditionally collected wastewater samples (n = 183) verified that the passive samplers were sensitive at detecting SARS-CoV-2 in wastewater. On all 33 days where we directly compared traditional and passive sampling techniques, at least one passive sampler was positive when the average SARS-CoV-2 concentration in the wastewater equaled or exceeded the quantification limit of 1.8 gene copies per mL (n = 7). Moreover, on 13 occasions where wastewater SARS-CoV-2 concentrations were less than 1.8 gene copies per mL, one or more passive samplers were positive. Finally, there was a statistically significant (p < 0.001) positive relationship between the concentrations of SARS-CoV-2 in wastewater and the levels found on the passive samplers, indicating that with further evaluation, these devices could yield semi-quantitative results in the future. Passive samplers have the potential for wide use in WBE with attractive feasibility attributes of cost, ease of deployment at small-scale locations, and continuous sampling of the wastewater. Further research will focus on the optimization of laboratory methods including elution and extraction and continued parallel deployment and evaluations in a variety of settings to inform optimal use in wastewater surveillance.

A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks.

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA's probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor's inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors.

Salmonella from a Microtidal Estuary Are Capable of Invading Human Intestinal Cell Lines.

Faecal contamination poses health risks for the recreational users of urban estuaries. However, our understanding of the potential pathogenicity of faecal microbes in these environments is limited. To this end, a study was conducted to understand the spatial and seasonal distribution of Salmonella in water and sediments of the Yarra River estuary, Melbourne, Australia. Among 210 samples in total, culturable Salmonella were recovered from 27%, 17%, and 19% of water, bank, and bed sediment samples, respectively. The combined detection increased from 15% in winter to 32% in summer (p < 0.05) indicating seasonal variation as potential part of public health risk assessments. Further, pathogenic potential of the Salmonella isolates was characterised via the quantification of attachment and invasion capacity using human epithelial colorectal cell line Caco-2 on a subset of isolates (n = 62). While all of these isolates could attach and invade Caco-2 cells, 52% and 13% of these showed greater attachment and invasiveness, respectively, than the corresponding mean values for S. Typhimurium ATCC14028 control. Isolates from winter were on average more invasive (seven out of eight isolates with the highest invasiveness recovered from the colder sampling period) than the isolates from summer, and Salmonella collected during summer showed lower invasion (p < 0.05) compared with the control. Similar low invasion compared with the same control was observed for isolates recovered from bank sediment (p < 0.05). While the higher prevalence in summer may imply higher risks during these peak recreational periods, it is essential that this information is used in combination with quantitative microbial risk assessments to fully understand the health risks posed by Salmonella in microtidal estuaries.

Testing of new stormwater pollution build-up algorithms informed by a genetic programming approach.

Pollution build-up and wash-off processes are often included in urban stormwater quality models. However, these models are often unreliable and have poor performance at large scales and in complicated catchments. This study tried to improve stormwater quality models by adopting the genetic programming (GP) approach to generate new build-up algorithms for three different pollutants (total suspend solids - TSS, total phosphorus - TP and total nitrogen - TN). This was followed by testing of the new models (also traditional build-up and wash-off models as benchmark) using data collected from different catchments in Australia and the USA. The GP approach informed new sets of build-up algorithms with the inclusion of not just the typical antecedent dry weather period (ADWP), but also other less 'traditional' variables - previous rainfall depth for TSS and maximum air temperatures for TP and TN simulation. The traditional models had relatively poor performance (Nash-Sutcliffe coefficient, E < 0.0), except for TP at Gilby Road (GR) (E = 0.21 in calibration and 0.43 in validation). Improved performance was observed using the models with new build-up algorithms informed by GP. Taking TP at GR for example, the best performing model had E of 0.46 in calibration and 0.54 in validation. The best performing models for TSS, TP, and TN are often different, suggesting that specific models shall be used for different pollutants. Insights into further improvements possible for stormwater quality models were given. It is recommended that in addition to the typical build-up and wash-off process, new generations of stormwater quality models should be able to account for the non-conventional pollutant sources (e.g. cross-connections, septic tank leakage, illegal discharges) through stochastic approaches. Emission inventories with information like intensity-frequency-duration (IFD) of pollutant loads from each type of non-conventional source are suggested to be built for stochastic modelling.

Understanding spatiotemporal variability of in-stream water quality in urban environments - A case study of Melbourne, Australia.

To support sustainable urban planning and the design of water pollution mitigation strategies, the spatial and temporal trends of water quality in urban streams needs to be further understood. This study analyses over ten years of surface water quality data from 53 upstream catchments (20 of them predominated by a single type of land use) and two lowland sites across Greater Melbourne, Australia. We evaluated the impact of various catchment characteristics, especially urban land uses, on spatial and temporal urban water quality trends. Here, we focused on common urban pollutants: total suspended solids (TSS), total phosphorous (TP), total nitrogen (TN), zinc (Zn), copper (Cu) and nickel (Ni). Site median nutrient and heavy metal concentrations were negatively correlated with the catchment's elevation and its average annual rainfall. Further analysis shows that such trends were driven by the geographical pattern of Melbourne - i.e. low-laying sites tend to have less rainfall and be more urbanised. Only median concentrations of heavy metals (Zn and Cu) were correlated to catchment imperviousness. Further characterising of the urban environment was done into specific land uses (residential, industrial and commercial), yet median concentrations of all pollutants were not significantly correlated with land uses. This is because simple metrics, such as land use proportions, do not adequately reflect the significant variability in pollution sources that can exist even within the same land use type. Indeed, our temporal analysis found that the water quality difference between catchments with similar land uses is likely caused by their site-specific pollutant sources (construction and illegal discharge) and environmental management actions (wastewater management actions) regardless of similarities in land use. A 3-stage urbanisation cycle (development, operation and renewal) is suggested to further explain the urban water quality variance, but more data from small areas of an urban catchment is required to directly understand the unique impact of each urbanisation stage on water quality.

Current Stormwater Harvesting Guidelines Are Inadequate for Mitigating Risk from Campylobacter During Nonpotable Reuse Activities.

Campylobacter is a pathogen frequently detected in urban stormwater worldwide. It is one of the leading causes of enteric disease in many developed countries and is the leading cause of enteric disease in Australia. Prior to harvesting stormwater, adequate treatment is necessary to mitigate risks derived from such harmful pathogens. The goal of this research was to estimate the health risks associated with the exposure to Campylobacter when harvesting urban stormwater for toilet flushing and irrigation activities, and the role treatment options play in limiting risks. Campylobacter data collected from several urban stormwater systems in Victoria, Australia, were the inputs of a Quantitative Microbial Risk Assessment model. The model included seven treatment scenarios, spanning wetlands, biofilters, and more traditional treatment trains including those recommended by the Australian Guidelines for Water Recycling. According to our modeling and acceptable risk thresholds, only two treatment scenarios could supply water of sufficient quality for toilet flushing and irrigation end-uses: (1) using stormwater biofilters coupled with UV-treatment and (2) a more conventional coagulation, filtration, UV, and chlorination treatment plant. Importantly, our modeling results suggest that current guidelines in place for stormwater reuse are not adequate for protecting against exposure to Campylobacter. However, more research is required to better define whether the Campylobacter detectable in stormwater are pathogenic to humans.

Can we model the implementation of water sensitive urban design in evolving cities?

This study showcases the dynamic simulation capabilities of the Urban Biophysical Environments And Technologies Simulator (UrbanBEATS) on a Melbourne catchment. UrbanBEATS simulates the planning, design and implementation of water sensitive urban design (WSUD) infrastructure in urban environments. It considers explicitly the interaction between urban and water infrastructure planning through time. The model generates a large number of realizations of different WSUD interventions and their evolution through time based on a user-defined scenario. UrbanBEATS' dynamics was tested for the first time on a historical case study of Scotchman's Creek catchment and was trained using historical data (e.g. planning documents, narratives, urban development and societal information) to adequately reproduce patterns of uptake of specific WSUD technologies. The trained model was also used to explore the implications of more stringent future water management objectives. Results highlighted the challenges of meeting this legislation and the opportunities that can be created through the mix of multiple spatial scales.

Passive sampling of microbes in various water sources: A systematic review.

Traditional methods for monitoring pathogens in environmental waters have numerous drawbacks. Sampling approaches that are low-cost and time efficient that can capture temporal variation in microbial contamination are needed. Passive sampling of aquatic environments has shown promise as an alternative water monitoring technique for waterborne pathogens and microbial contaminants. The present systematic review aimed to compile and synthesize existing literature on the use of passive samplers for the monitoring of microbes in different water sources and identify research gaps. The review summarizes current knowledge on materials used for detection, deployment durations, analytical methods, quantification as well as benefits and limitations of passive sampling. This review found that electronegative nitrocellulose membrane filters are effective for both detection and quantification of viruses in wastewater, while gauze passive samplers have been effective for detecting bacterial targets in wastewater. There is a large knowledge gap in the use of passive samplers in a quantitative manner, especially for the back-calculation of water-column microbial concentrations or for correlation to outcomes of interest (e.g. prevalence rates). Further, there is very limited attention paid to the use of membrane filters for the monitoring of bacteria in any water source as well as a lack of studies utilizing passive sampling approaches for protozoa.

Wastewater-based epidemiology surveillance as an early warning system for SARS-CoV-2 in Indonesia.

BACKGROUND: Wastewater-based epidemiology (WBE) surveillance has been proposed as an early warning system (EWS) for community SARS-CoV-2 transmission. However, there is limited data from low-and middle-income countries (LMICs). This study aimed to assess the ability of WBE surveillance to detect SARS-CoV-2 in formal and informal environments in Indonesia using different methods of sample collection, to compare WBE data with patterns of clinical cases of COVID-19 within the relevant communities, and to assess the WBE potential to be used as an EWS for SARS-CoV-2 outbreaks within a community. MATERIALS AND METHODS: We conducted WBE surveillance in three districts in Yogyakarta province, Indonesia, over eleven months (27 July 2021 to 7 January 2022 [Delta wave]; 18 January to 3 June 2022 [Omicron wave]). Water samples using grab, and/or passive sampling methods and soil samples were collected either weekly or fortnightly. RNA was extracted from membrane filters from processed water samples and directly from soil. Reverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) was performed to detect the SARS-CoV-2 N and ORF1ab genes. RESULTS: A total of 1,582 samples were collected. Detection rates of SARS-CoV-2 in wastewater reflected the incidence of community cases, with rates of 85% at the peak to 2% at the end of the Delta wave and from 94% to 11% during the Omicron wave. A 2-week lag time was observed between the detection of SARS-CoV-2 in wastewater and increasing cases in the corresponding community. CONCLUSION: WBE surveillance for SARS-CoV-2 in Indonesia was effective in monitoring patterns of cases of COVID-19 and served as an early warning system, predicting the increasing incidence of COVID-19 cases in the community.

Low-cost monitoring systems for urban water management: Lessons from the field.

Sound urban water management relies on extensive and reliable monitoring of water infrastructure. As low-cost sensors and networks have become increasingly available for environmental monitoring, urban water researchers and practitioners must consider the benefits and disadvantages of such technologies. In this perspective paper, we highlight six technical and socio-technological considerations for low-cost monitoring technology to reach its full potential in the field of urban water management, including: technical barriers to implementation, complementarity with traditional sensing technologies, low-cost sensor reliability, added value of produced information, opportunities to democratize data collection, and economic and environmental costs of the technology. For each consideration, we present recent experiences from our own work and broader literature and identify future research needs to address current challenges. Our experience supports the strong potential of low-cost monitoring technology, in particular that it promotes extensive and innovative monitoring of urban water infrastructure. Future efforts should focus on more systematic documenting of experiences to lower barriers to designing, implementing, and testing of low-cost sensor networks, and on assessing the economic, social, and environmental costs and benefits of low-cost sensor deployments.

Phage resistance in Klebsiella pneumoniae and bidirectional effects impacting antibiotic susceptibility.

OBJECTIVES: Bacteriophage (phage) therapy is a promising anti-infective option to combat antimicrobial resistance. However, the clinical utilization of phage therapy has been severely compromised by the potential emergence of phage resistance. Although certain phage resistance mechanisms can restore bacterial susceptibility to certain antibiotics, a lack of knowledge of phage resistance mechanisms hinders optimal use of phages and their combination with antibiotics. METHODS: Genome-wide transposon screening was performed with a mutant library of Klebsiella pneumoniae MKP103 to identify phage pKMKP103_1-resistant mutants. Phage-resistant phenotypes were evaluated by time-kill kinetics and efficiency of plating assays. Phage resistance mechanisms were investigated with adsorption, one-step growth, and mutation frequency assays. Antibiotic susceptibility was determined with broth microdilution and population analysis profiles. RESULTS: We observed a repertoire of phage resistance mechanisms in K pneumoniae, such as disruption of phage binding (fhuA::Tn and tonB::Tn), extension of the phage latent period (mnmE::Tn and rpoN::Tn), and increased mutation frequency (mutS::Tn and mutL::Tn). Notably, in contrast to the prevailing view that phage resistance re-sensitizes antibiotic-resistant bacteria, we observed a bidirectional steering effect on bacterial antibiotic susceptibility. Specifically, rpoN::Tn increased susceptibility to colistin while mutS::Tn and mutL::Tn increased resistance to rifampicin and colistin. DISCUSSION: Our findings demonstrate that K pneumoniae employs multiple strategies to overcome phage infection, which may result in enhanced or reduced antibiotic susceptibility. Mechanism-guided phage steering should be incorporated into phage therapy to better inform clinical decisions on phage-antibiotic combinations.

A planning algorithm for quantifying decentralised water management opportunities in urban environments.

With global change bringing about greater challenges for the resilient planning and management of urban water infrastructure, research has been invested in the development of a strategic planning tool, DAnCE4Water. The tool models how urban and societal changes impact the development of centralised and decentralised (distributed) water infrastructure. An algorithm for rigorous assessment of suitable decentralised stormwater management options in the model is presented and tested on a local Melbourne catchment. Following detailed spatial representation algorithms (defined by planning rules), the model assesses numerous stormwater options to meet water quality targets at a variety of spatial scales. A multi-criteria assessment algorithm is used to find top-ranking solutions (which meet a specific treatment performance for a user-defined percentage of catchment imperviousness). A toolbox of five stormwater technologies (infiltration systems, surface wetlands, bioretention systems, ponds and swales) is featured. Parameters that set the algorithm's flexibility to develop possible management options are assessed and evaluated. Results are expressed in terms of 'utilisation', which characterises the frequency of use of different technologies across the top-ranking options (bioretention being the most versatile). Initial results highlight the importance of selecting a suitable spatial resolution and providing the model with enough flexibility for coming up with different technology combinations. The generic nature of the model enables its application to other urban areas (e.g. different catchments, local municipal regions or entire cities).

BioRTC model enables exploration of real time control strategies for stormwater biofilters.

Biofilters with real time control (RTC) have great potential to remove microbes from stormwater to protect human health for uses such as swimming and harvesting. However, RTC strategies need to be further explored and optimised for each specific location or end-use. This paper demonstrates that the newly developed BioRTC model can fulfil this requirement and allow effective and efficient exploration of the potential of RTC applications. We describe the development of BioRTC as the first RTC model for stormwater biofilters, including: selection of a 'base' model for microbial removal prediction, its modification to include RTC capabilities, as well as calibration and validation. BioRTC adequately predicted the performance of two previously developed RTC strategies, with Nash Sutcliffe Efficiency (Ec) ranging from 0.65 to 0.80. In addition, high parameter transferability was demonstrated during model validation, where we employed the parameter sets calibrated for another biofilter study without RTC to predict the performance of RTC biofilters. We then employed the BioRTC model to explore RTC applications on a hypothetical biofilter system located at the outlet of an existing catchment. With different scenarios, we tested the impact of input parameters such as RTC set-points and design characteristics, and evaluated the influence of operational conditions on the microbial removal performance of the hypothetical biofilter with RTC. The results showed that strategy rules, set-point values, and biofilter design all govern the performance of RTC biofilters, and that operational conditions could impact the suitability of different RTC strategies. Particularly, the presence of Pareto fronts established that muti-objective optimisation is necessary to balance competing needs. These results underscore the importance of RTC, which allows for local experimentation, climate change adaptation, and adjustment to changing demands for the harvested water. Furthermore, they illustrate the practical use of the newly developed BioRTC model, enabling researchers and practitioners to explore and assess potential RTC strategies and scenarios quickly and cost-effectively.

Biofilters for stormwater harvesting: understanding the treatment performance of key metals that pose a risk for water use.

A large-scale stormwater biofilter column study was conducted to evaluate the impact of design configurations and operating conditions on metal removal for stormwater harvesting and protection of aquatic ecosystems. The following factors were tested over 8 months of operation: vegetation selection (plant species), filter media type, filter media depth, inflow volume (loading rate), and inflow pollutant concentrations. Operational time was also integrated to evaluate treatment performance over time. Vegetation and filter type were found to be significant factors for treatment of metals. A larger filter media depth resulted in increased outflow concentrations of iron, aluminum, chromium, zinc, and lead, likely due to leaching and mobilization of metals within the media. Treatment of all metals except aluminum and iron was generally satisfactory with respect to drinking water quality standards, while all metals met standards for irrigation. However, it was shown that biofilters could be optimized for removal of iron to meet the required drinking water standards. Biofilters were generally shown to be resilient to variations in operating conditions and demonstrated satisfactory removal of metals for stormwater-harvesting purposes.

Comparison of Auto Sampling and Passive Sampling Methods for SARS-CoV-2 Detection in Wastewater.

Wastewater-based surveillance is emerging as an important tool for the COVID-19 pandemic trending. Current methods of wastewater collection, such as grab and auto-composite sampling, have drawbacks that impede effective surveillance, especially from small catchments with limited accessibility. Passive samplers, which are more cost-effective and require fewer resources to process, are promising candidates for monitoring wastewater for SARS-CoV-2. Here, we compared traditional auto sampling with passive sampling for SARS-CoV-2 detection in wastewater. A torpedo-style 3D-printed passive sampler device containing both cotton swabs and electronegative filter membranes was used. Between April and June 2021, fifteen passive samplers were placed at a local hospital's wastewater outflow alongside an autosampler. Reverse transcription and quantitative polymerase chain reaction (RT-qPCR) was used to detect SARS-CoV-2 in the samples after processing and RNA extraction. The swab and membrane of the passive sampler showed similar detection rates and cycle threshold (Ct) values for SARS-CoV-2 RNA for the N1 and N2 gene targets. The passive method performed as well as the grab/auto sampling, with no significant differences between N1 and N2 Ct values. There were discrepant results on two days with negative grab/auto samples and positive passive samples, which might be related to the longer duration of passive sampling in the study. Overall, the passive sampler was rapid, reliable, and cost-effective, and could be used as an alternative sampling method for the detection of SARS-CoV-2 in wastewater.

Interactive effect of temperature and plant species on nitrogen cycling and treatment in stormwater biofiltration systems.

Stormwater biofiltration systems (also known as biofilters, bioretention, rain gardens) are engineered nature-based solutions, which help mitigate aquatic nitrogen pollution arising from storm runoff. These systems are being increasingly used in a range of climates across the world. A decline in treatment performance is frequently observed in cold weather conditions. While plant species comprise an important design factor influencing system performance, the effect of temperature on the fate of dissolved nitrogen forms, namely ammonium (NH4+) and nitrate (NO3-), in the presence of different plant species in these systems remains unclear. A large scale laboratory experiment was undertaken that measured potential rates of nitrification, denitrification and dissimilatory nitrate reduction to ammonium (DNRA) as well as the microbial community structure to investigate nitrogen fate and hence removal under two different temperature conditions (2 °C and 15 °C) in the presence of four distinct plant species. The results indicate that lower nitrification rates (reduced by a factor of 4) coupled with potential media NH4+ desorption could be contributing to reduced NH4+ removal during cold conditions. Planting with species exhibiting good nutrient uptake capacity can reduce the extent of this performance decline. While NO3- reduction generally remains problematic during cold weather (<0 to 55% reduction), which may not be significantly different from warmer periods, the study demonstrated that the denitrification potential and gene abundance (nap, nar, NirS, norB, nosZ) to be higher than those of nitrification (amoA). Denitrification may not proceeding at optimal rates due to lack of conducive environmental conditions. Nitrogen transformation via DNRA was found to be relatively insignificant. Future studies should investigate the potential of employing cold-resilient plant species to maintain both NH4+ and NO3- removal in cold weather conditions.

Riparian buffers: Disrupting the transport of E. coli from rural catchments to streams.

High levels of E. coli and associated faecal microbes in waterways as a result of agricultural and residential land use can pose environmental, human health, and economic risks. This study aims to understand the impacts of land use, climatic variables, and riparian buffers on in-stream E. coli concentrations. Flow, temperature, and E. coli were monitored during three sampling campaigns within eleven independent catchments. These catchments have varying land use and extents of riparian buffer coverage. Results showed that catchments with predominantly agricultural and residential land uses (average = 349.7 MPN/100 mL) had higher E. coli concentrations than predominantly forested catchments (average = 111.8 MPN/100 mL). However, there were no statistically significant differences in E. coli concentrations between the agricultural and residential land uses. Riparian buffers appear to reduce E. coli concentrations in streams, as indicated by significant negative correlations between in-stream E. coli concentrations with the riparian buffer areal coverage (Pearson's r = -0.95, Spearman's ρ = -0.90) and the ratio of buffer length to stream length (Pearson's r = -0.87, Spearman's ρ = -0.90). We find that riparian buffers potentially disrupt transport pathways that govern E. coli movement, which in-turn can affect the concentration-discharge relationship. This reinforces the importance of protecting and restoring riparian buffers along drainage lines in agricultural and rural-residential catchments to improve downstream microbial water quality.

The feasibility of SARS-CoV-2 surveillance using wastewater and environmental sampling in Indonesia.

BACKGROUND: Wastewater-based epidemiology (WBE) surveillance as an early warning system (EWS) for monitoring community transmission of SARS-CoV-2 in low- and middle-income country (LMIC) settings, where diagnostic testing capacity is limited, needs further exploration. We explored the feasibility to conduct a WBE surveillance in Indonesia, one of the global epicenters of the COVID-19 pandemic in the middle of 2021, with the fourth largest population in the world where sewer and non-sewered sewage systems are implemented. The feasibility and resource capacity to collect samples on a weekly or fortnightly basis with grab and/or passive sampling methods, as well as to conduct qualitative and quantitative identification of SARS-CoV-2 ribonucleic acid (RNA) using real-time RT-PCR (RT-qPCR) testing of environmental samples were explored. MATERIALS AND METHODS: We initiated a routine surveillance of wastewater and environmental sampling at three predetermined districts in Special Region of Yogyakarta Province. Water samples were collected from central and community wastewater treatment plants (WWTPs), including manholes flowing to the central WWTP, and additional soil samples were collected for the near source tracking (NST) locations (i.e., public spaces where people congregate). RESULTS: We began collecting samples in the Delta wave of the COVID-19 pandemic in Indonesia in July 2021. From a 10-week period, 54% (296/544) of wastewater and environmental samples were positive for SARS-CoV-2 RNA. The sample positivity rate decreased in proportion with the reported incidence of COVID-19 clinical cases in the community. The highest positivity rate of 77% in week 1, was obtained for samples collected in July 2021 and decreased to 25% in week 10 by the end of September 2021. CONCLUSION: A WBE surveillance system for SARS-CoV-2 in Indonesia is feasible to monitor the community burden of infections. Future studies testing the potential of WBE and EWS for signaling early outbreaks of SARS-CoV-2 transmissions in this setting are required.