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Countries with literature relating to water quality in drinking water distribution systems.

Protecting freshwater biodiversity is considered an ultimate challenge but depends on reliable surveys of species distribution and abundance which eDNA metabarcoding (environmental DNA metabarcoding) may offer. To do so, a better understanding of the sources of temporal variation among species eDNA abundance and of data transformation in eDNA metabarcoding studies is needed. Here, we show that transformation based on relative abundance is critical to suitable analyses of eDNA metabarcoding data and that Hellinger transformation performed slightly better than other methods. Furthermore, we show that site localities significantly explain eDNA metabarcoding variation, while no variation is explained by time of sampling. This indicates that species communities vary more spatially than temporally within a dendritic system composed of small rivers. We then further documented the community structure in the St. Charles River (Québec City, Canada) and six of its tributaries. This revealed the existence of eight species communities explaining 82.1% of eDNA read variation within this river network. Moreover, variation in environmental variables among sites explained 53.0% of eDNA reads, while sampling events and temporal environmental variation explained no eDNA metabarcoding variation. Altogether, this supports the claim that eDNA metabarcoding is a powerful tool to document and monitor fish communities in watersheds composed of small river dendritic systems.

The spatial-temporal behaviour of contaminants of emerging concern (CECs) are not well-documented in drinking water sources, including in Quebec, Canada. In this study, a set of seven contaminants, which are more frequently reported in water sources, were monitored from May 2016 to August 2017 at ten locations within an urbanized watershed (lakes and rivers) in Quebec, Canada. Samples were collected between a wastewater plant discharge (upstream) and the intake of a drinking water plant (downstream). The results showed that three (acetaminophen, salicylic acid, caffeine) out of seven CECs were consistently detected at a range of up to a few hundred ng L

Surface waters are widely used as sources of drinking water in Canada. The identification of the main sources of pollutants to surface waters, often associated with increasing urbanization, is need...

The goal of this work was to investigate the occurrence of contaminants of emerging interest (CEI) in source surface water (SW; river water) and drinking water (DW; tap water) from five drinking water treatment plants (DWTPs) in the Province of Québec, Canada. A total of 28 sampling campaigns were conducted to collect SW and DW samples from each DWTP from June 2016 to July 2017. The seven targeted CEI, including acetaminophen, salicylic acid, caffeine, carbamazepine, ibuprofen, sulfamethoxazole and drospirenone, were analyzed using solid-phase extraction-ultra pressure liquid chromatography-mass spectrometry (SPE-UPLC-MS/MS) for all collected water samples. The selected CEI were detected in all SW and DW samples, with the exception of drospirenone, which occurred in amounts that were below the limit of detection in one DWTP in June and July 2016. In all the SW samples, caffeine was detected and had the highest median concentration range (12.3-91.0 ng/L), followed by acetaminophen (7.9-85.0 ng/L) and salicylic acid (21.6-39.0 ng/L). In the DW samples, salicylic acid was detected and had the highest median concentration range (20.5-50 ng/L), followed by caffeine (5.2-21.8 ng/L), and acetaminophen (5.0-7.7 ng/L). Carbamazepine, ibuprofen, and sulfamethoxazole primarily occurred in amounts between the limit of detection and limit of quantification in SW and occurred below the limit of detection in DW. All the DWTPs exhibited a similar trend in the removal of CEI, which include acetaminophen (≤97.6%), followed by caffeine (71.0-86.5%) and salicylic acid (50.0%). Varying levels of efficiencies were observed among the removal strategies for CEI under study, which were mainly associated with the contaminant concentration in SW in the case of acetaminophen, and with the treatment processes in the case of caffeine and salicylic acid.

Ozonation is becoming a common disinfection method for drinking water treatment. This has prompted the investigation of ozonation disinfection by-products (ODBPs) in drinking water. Ozonation generates a diverse range of carbonyl disinfection by-products, including carboxylic acids, aldehydes, ketones and aldo-ketoacids. Among these ODBPs, carboxylic acid by-products (CABPs) are observed in higher concentrations compared to other carbonyl by-products. However, relatively little research has been conducted on CABPs, including their precursors, formation and occurrence, methods of detection and toxicity. This review outlines the occurrence and variability of CABPs in a number of water sources treated and disinfected with ozonation. It considers the effect of ozonation parameters, including ozone dose, temperature and time of ozonation on the formation of CABPs. The review also discusses the various analytical approaches for CABP quantification, as well as their possible toxicity in drinking water.

This paper presents the conceptual framework of a holistic, intelligent decision-support system (IDSS) to plan, manage and optimize water quality monitoring programs (WQMPs) for surface waters. WQMPs are a crucial component of water management because information on water quality is essential when taking action such as legislative compliance, environmental projects, urban and infrastructure development. Planning, managing and optimizing WQMPs is a complex process and requires multiple variables, rules and subject matter expert knowledge. The specific goals of this paper were to (1) assess to what extent the subject domain (WQMPs) is deemed appropriate for an IDSS; (2) describe the design process of the conceptual framework; (3) present the main elements of the system architecture; (4) present two case studies that served as potential end users; (5) illustrate the applicability of the IDSS and (6) describe subsequent steps to further test the IDSS. The IDSS was developed on the premise that the proposed system could (1) improve quality, (2) capture undocumented expertise that is perishable or in short supply (tacit knowledge), (3) provide accessible expertise to novice users, (4) have a training effect on users, and (5) show that the system, even partially complete, could still be useful. Our initial assumptions regarding these points were validated through interviews with subject matter experts. The conceptual framework was designed based on a literature review, interviews with 44 subject matter experts from Europe, Canada and the United States, interaction with end users from two case studies in the Province of Quebec, Canada, and five information technology experts from Canada and Germany. The IDSS presented in this paper will facilitate the planning, management and optimization of WQMPs. It will be exportable to various watersheds and consider the WQMP planner’s need to update the network rapidly if changes occur in human, financial and technical resources.HIGHLIGHTSHolistic and adaptable decision-support system to plan, manage and optimize surface water quality monitoring programsManagement and decision support system for knowledge acquisition processes on water qualitySystem integrates tacit and explicit knowledge on water quality monitoring challengesManagement and decision support system based on tacit knowledge from 44 experts and two case studiesAdapted design methodology for an Intelligent decision-support system Holistic and adaptable decision-support system to plan, manage and optimize surface water quality monitoring programs Management and decision support system for knowledge acquisition processes on water quality System integrates tacit and explicit knowledge on water quality monitoring challenges Management and decision support system based on tacit knowledge from 44 experts and two case studies Adapted design methodology for an Intelligent decision-support system

Contaminants of Emerging Concern (CECs) in natural water pose risks to ecosystems. The concentration of CECs varies spatially and temporally, and their estimated ecotoxicities differ widely by toxicological studies. This study extensively reviewed literature on ecological risk assessment and proposed a probabilistic framework for assessing ecological risk and its uncertainties (aleatory and epistemic). The framework integrated Adverse Outcome Pathway in risk assessment and was applied to a Canadian lake system for seven CECs: salicylic acid, acetaminophen, caffeine, carbamazepine, ibuprofen, drospirenone, and sulfamethoxazole. Altogether 264 water samples were collected and analyzed from 15 sites May 2016 to September 2017. Phytoplankton, zooplankton, and fish were also sampled and analyzed. The results show ecological risk estimates (Risk Quotient, RQ) varied considerably indicating a range of uncertainty. Based on the conservative estimate, the central tendency estimate of the ecological risk of mixture compounds was medium (RQ = 0.6) including drospirenone. However, the reasonably maximum estimate of the risk was high (RQ = 1.4) for mixture compounds including drospirenone. The high risk is primarily due to drospirenone as its individual risk was high (RQ = 1.1) to fish. The specific site and time of high drospirenone exposure was identified for implementing control measures. Classification of ecotoxicity values based on environmental parameters such as climate and water quality, can reduce uncertainty in the risk estimate.

Developing strategies to identify the origins of contaminants in watersheds is crucial for source water protection. The use of multiple tracers improves the ability to identify contamination events originating from various land use activities. The objective of this study was to evaluate the use of acesulfame and chloride as co-tracers to represent the impact of pollution originating from wastewater and road de-icing on water quality in a municipal drinking water source. The study included a two-year sampling and water quality analysis program in numerous locations within a drinking water reservoir comprising a lake (upstream) and a river (downstream) which supply raw water to a municipal water treatment plant. Results showed that the spatial variability of acesulfame and chloride within the watershed of the lake-river systems depends on the location of contaminant sources, mainly municipal wastewater and septic tank discharges (for acesulfame) and the presence of small tributaries of the lake and river (for chloride). Temporal variability of the tracers under study differed according to the sampling location and was mainly affected by seasonal conditions. Correlation analyses between the two tracers in lake and river waters (in terms of concentrations and loads) made it possible to pinpoint the probable origins of contamination. The assessment of the spatio-temporal variability of these co-tracers within the lake-river watersheds allowed for the delineation of priority intervention zones as a decision-making tool for municipal authorities in improving drinking water source protection.

We developed a holistic intelligent decision-support system (IDSS) to provide decision-support for all steps in planning, managing and optimizing water quality monitoring programs (WQMPs). The IDSS is connected to a previously developed database, EnkiTM. The IDSS integrates tacit and explicit knowledge on WQMPs to standardize decision making and to make decisions transparent and transferable. The optimization features of the IDSS were tested on a lake and a river WQMP from two case studies in Canada. We illustrate how the IDSS provides decision support to understanding the underlying rationale of the existing WQMPs, validating and storing data, selecting optimization procedures proposed in the literature, applying the optimization procedures and finalizing the optimization procedure. We demonstrated that the IDSS/EnkiTM is necessary to take and document decisions during all phases of a WQMP to obtain a clear idea of when and why changes are made and determine actionable tasks in the optimization process.

Water quality monitoring programs (WQMPs) must be based on monitoring objectives originating from the real knowledge needs of all stakeholders in a watershed and users of the resource. This paper proposes a participative approach to elicit knowledge needs and preferred modes of communication from citizens and representatives of organized stakeholders (ROS) on water quality and quantity issues. The participative approach includes six steps and is adaptable and transferable to different types of watersheds. These steps are: (1) perform a stakeholder analysis; (2) conduct an adaptable survey accompanied by a user-friendly public participation geographical information system (PPGIS); (3) hold workshops to meet with ROS to inform them of the results of the survey and PPGIS; discuss attainment of past monitoring objectives; exchange views on new knowledge needs and concerns on water quality and quantity; (4) meet with citizens to obtain the same type of input (as from ROS); (5) analyze the data and information collected to identify new knowledge needs and modes of communication and (6) identify, in collaboration with the individuals in charge of the WQMPs, the short-, medium- and long-term monitoring objectives and communication strategies to be pursued. The participative approach was tested on two distinct watersheds in the province of Quebec, Canada. It resulted in a series of optimization objectives of the existing WQMPs, new monitoring objectives and recommendations regarding communication strategies of the WQMPs' results. The results of this study show that the proposed methodology is appreciated by all parties and that the outcomes and monitoring objectives are acceptable. We also conclude that successful integrated watershed management is a question of scale, and that every aspect of integrated watershed management needs to be adapted to the surface watershed, the groundwater watershed (aquifers) and the human catchment area.

The reliable assessment of water quality through water quality monitoring programs (WQMPs) is crucial in order for decision-makers to understand, interpret and use this information in support of their management activities aiming at protecting the resource. The challenge of water quality monitoring has been widely addressed in the literature since the 1940s. However, there is still no generally accepted, holistic and practical strategy to support all phases of WQMPs. The purpose of this paper is to report on the use cases a watershed manager has to address to plan or optimize a WQMP from the challenge of identifying monitoring objectives; selecting sampling sites and water quality parameters; identifying sampling frequencies; considering logistics and resources to the implementation of actions based on information acquired through the WQMP. An inventory and critique of the information, approaches and tools placed at the disposal of watershed managers was proposed to evaluate how the existing information could be integrated in a holistic, user-friendly and evolvable solution. Given the differences in regulatory requirements, water quality standards, geographical and geological differences, land-use variations, and other site specificities, a one-in-all solution is not possible. However, we advance that an intelligent decision support system (IDSS) based on expert knowledge that integrates existing approaches and past research can guide a watershed manager through the process according to his/her site-specific requirements. It is also necessary to tap into local knowledge and to identify the knowledge needs of all the stakeholders through participative approaches based on geographical information systems and adaptive survey-based questionnaires. We believe that future research should focus on developing such participative approaches and further investigate the benefits of IDSS's that can be updated quickly and make it possible for a watershed manager to obtain a timely, holistic view and support for every aspect of planning and optimizing a WQMP.