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Freshwater resources play a pivotal role in sustaining life and meeting various domestic, agricultural, economic, and industrial demands. As such, there is a significant need to monitor the water quality of these resources. Water quality index (WQI) models have gradually gained popularity since their maiden introduction in the 1960s for evaluating and classifying the water quality of aquatic ecosystems. WQIs transform complex water quality data into a single dimensionless number to enable accessible communication of the water quality status of water resource ecosystems. To screen relevant articles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed to include or exclude articles. A total of 17 peer-reviewed articles were used in the final paper synthesis. Among the reviewed WQIs, only the Canadian Council for Ministers of the Environment (CCME) index, Irish water quality index (IEWQI) and Hahn index were used to assess both lotic and lentic ecosystems. Furthermore, the CCME index is the only exception from rigidity because it does not specify parameters to select. Except for the West-Java WQI and the IEWQI, none of the reviewed WQI performed sensitivity and uncertainty analysis to improve the acceptability and reliability of the WQI. It has been proven that all stages of WQI development have a level of uncertainty which can be determined using statistical and machine learning tools. Extreme gradient boosting (XGB) has been reported as an effective machine learning tool to deal with uncertainties during parameter selection, the establishment of parameter weights, and determining accurate classification schemes. Considering the IEWQI model architecture and its effectiveness in coastal and transitional waters, this review recommends that future research in lotic or lentic ecosystems focus on addressing the underlying uncertainty issues associated with the WQI model in addition to the use of machine learning techniques to improve the predictive accuracy and robustness and increase the domain of application., (© 2023. The Author(s).)

Best Management Practices and Beneficial Management Practices ("MP") are two ideational elements, that have emerged in water quality literature. This research explores the questions of where has the lesser utilized term 'Beneficial' emerged and why? To answer these questions, articles obtained from the Web of Science by searching keywords "Best MP"/"Beneficial MP" and "Water" are analyzed using bibliometric techniques through VOS Viewer including time trend of publications, and indicators including keywords, disciplines, institutions, geographies, influential authors and journals, and key funders of these two terms. This paper also employs document analysis and semi-structured interviews with key policy stakeholders. Beneficial Management Practices emerged in Canada (although the term was used in a few instances elsewhere) in Canadian government policy documents starting in 2003. The term 'Beneficial' refers to a lesser standard than "Best" and is exclusive to agricultural practices in risk and environmental farm policy; "Best Management Practices" refer to a wider set of practices (in other sectors like mining) utilized by a more substantive and diverse set of institutions (predominately American and significantly populated by universities). Explanations for the emergence of the term include that it is more 'honest,' it allows for more choices and trade-offs, it reflects the strong economic driver of agriculture, and several interviewees referred to it better reflecting the uncertainty of science. While the strength of the agricultural sector in influencing the 'Beneficial' discourse is not surprising, the failure to measure the improvement to the water quality of Beneficial Management Programs and measure policy's effectiveness is noteworthy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Benthic invertebrates are important trophic links in food webs and useful bioindicators of environmental conditions, but long‐term benthic organism abundance data across broad geographic areas are rare and historic datasets are often not readily accessible. This dataset provides densities of benthic macroinvertebrates collected from 1930 to 2019 during surveys in Lake Erie, a Laurentian Great Lake. The surveys were funded by the governments of the United States and Canada to investigate the status and changes in the benthic community. From the total of 21 lake‐wide and basin‐wide benthic surveys conducted in Lake Erie from 1929 to 2019, we were able to acquire data for 17 surveys, including species‐level data for 10 surveys and data by higher taxonomic groups for seven surveys. Our amassed Lake Erie dataset includes data from 11 surveys (including five with species‐level data) conducted in the western basin in 1930–2019, seven surveys (six with species‐level data) in the central basin, and eight surveys (seven with species‐level data) in the eastern basin (1973–2019). This Lake Erie dataset represents the most extensive temporal dataset of benthic invertebrates available for any of the Laurentian Great Lakes. Benthic samples were collected using Ponar or Shipek bottom dredges and taxa densities were calculated as individuals per square meter using the area of the dredge. Density data are provided for taxa in the Annelida, Arthropoda, Mollusca, Cnidaria, Nemertea, and Platyhelminthes phyla. Current taxonomy was used for most groups but, in a few cases, older taxonomic names were used for consistency with historical data. Analysis of this dataset indicates that eutrophication, water quality improvement, and dreissenid introduction were the major drivers of changes in the benthic community in the western basin, while hypoxia was a major factor in the central basin, and dreissenid introduction was the most important driver in the eastern basin. Considering the rarity of high taxonomic resolution long‐term benthic data for lake ecosystems, this dataset could be useful to explore broader aspects of ecological theory, including effects of eutrophication, hypoxia, invasive species, and other factors on community organization, phylogenetic and functional diversity, and spatial and temporal scales of variation in community structure. In addition, the dataset could be useful for studies on individual species, including abundance and distribution, species co‐occurrence, and how the patterns of dominance and rarity change over space and time. Use of this dataset for academic or educational purposes is encouraged as long as this data paper is properly cited. [ABSTRACT FROM AUTHOR]

Freshwater ecosystems are biologically important habitats that provide many ecosystem services. Calcium concentration and pH are two key variables that are linked to multiple chemical processes in these environments, influence the biology of organisms from diverse taxa, and can be important factors affecting the distribution of native and non-native species. However, it can be challenging to obtain high-resolution data for these variables at regional and national scales. To address this data gap, water quality data for lakes and rivers in Canada and the continental USA were compiled and used to generate high-resolution (10 × 10 km) interpolated raster layers, after comparing multiple spatial interpolation approaches. This is the first time that such data have been made available at this scale and resolution, providing a valuable resource for research, including projects evaluating risks from environmental change, pollution, and invasive species. This will aid the development of conservation and management strategies for these vital habitats. [ABSTRACT FROM AUTHOR]

Over the past decade, plastic pollution has been documented throughout the Laurentian Great Lakes basin. Here, we demonstrate the application of a published ecological risk assessment and management framework for microplastics in aquatic environments by comparing proposed thresholds for risk to monitoring data from the Great Lakes region. Our results suggest that there may be measurable risks from microplastics to aquatic communities in parts of the Great Lakes where current concentrations are relatively high. For example, 89% of surface water samples collected across the region exceed the proposed risk thresholds for food dilution toxicity. However, all sediment samples remain below the proposed risk thresholds. Accordingly, we suggest that an appropriate and necessary next step for management may include convening a working group of local experts to develop an ecological risk assessment and management framework for the region comprising thresholds of concern for microplastics in surface water and sediment. Ultimately, microplastic pollution should be addressed in the Great Lakes Water Quality Agreement to ensure coordinated and sustained efforts are taken by the governments of Canada and the United States to reduce their release and impact. [ABSTRACT FROM AUTHOR]

Benthic invertebrates are important trophic links in aquatic food webs and serve as useful bioindicators of environmental conditions because their responses integrate the effects of both water and sediment qualities. However, long‐term data sets for benthic invertebrate assemblages across broad geographic areas are rare and, even if collected, historic data sets are often not readily accessible. This data set provides densities of benthic macroinvertebrates for all taxa collected during lake‐wide surveys in Lake Ontario, a Laurentian Great Lake, from 1964 to 2018. This information resulted from surveys funded by the governments of the United States and Canada to investigate the status and changes of Lake Ontario benthic community. Of the 13 lake‐wide benthic surveys conducted in Lake Ontario over the course of 54 yr, we were able to acquire taxonomic data to the species level for 11 of the surveys and data to the group level for the other two surveys. Density data are provided for taxa representing the Annelida, Arthropoda, Mollusca, Cnidaria, Nemertea, and Platyhelminthes phyla. Univariate and multivariate analyses revealed that the compositional structure of Lake Ontario invertebrate assemblages differed markedly by depth and were also significantly altered by the Dreissena spp. invasion in early 1990s. The introduction of invasive dreissenids has changed the community historically dominated by Diporeia, Oligochaeta, and Sphaeriidae, to a community dominated by quagga mussels and Oligochaeta. Considering the rarity of long‐term benthic data of high taxonomic resolution in lake ecosystems, this data set could be useful to explore broader aspects of ecological theory, including effects of different environmental factors and invasive species on community organization, functional and phylogenetic diversity, and spatial scale of variation in community structure. The data set could also be useful for studies on individual species including abundance and distribution, species co‐occurrence, and how the patterns of dominance and rarity change over space and time. Use of this data set for academic or educational purposes is encouraged as long as the data source is properly cited using the title of this Data Paper, the names of the authors, the year of publication, the journal name, and the article number. [ABSTRACT FROM AUTHOR]

Lake water quality plays a vital role in the lake ecosystem, including biotic (for living creatures, such as plants, animals, and micro-organisms) and abiotic interactions. In this research, various types of machine learning (ML) methodologies, such as classification and regression tree (CART), chi-squared automatic interaction detector (CHAID), C5 tree, quick, unbiased, and efficient statistical tree (QUEST), along with multilayer perceptron (MLP) neural network, and radial basis function (RBF) neural network, are employed to predict the concentration of water quality parameters (P, EC, TDS, pH, DO, NH3, SO4, and θ). Lake Erie is situated at the international border of the USA and Canada. The C5 tree and QUEST tree are used to classify data and predict the number of groups, while the other methods are used to predict the concentration of water quality parameters in the form of a 3-year moving average. The greater matching between the observed and predicted data of dissolved oxygen (NSE = 0.978, bias = 0.126) shows that the CART decision tree has higher accuracy in correctly detecting the concentration of this parameter. The C5 tree could identify 33 groups correctly out of 36 total groups, which shows better accuracy for the C5 tree in classifying the data for this parameter. [ABSTRACT FROM AUTHOR]

Industrial control charts are used in manufacturing to quickly and robustly indicate the status of production and to prompt any necessary corrective actions. The library of tools available for these tasks has grown over time and many have been used in other disciplines with similar objectives, including environmental monitoring. While the utility of control charts in environmental monitoring has been recognized, and the tools have already been used in many individual studies, they may be underutilized in some types of programs. For example, control charts may be especially useful for reporting and evaluating data from regional surveillance monitoring programs, but they are not yet routinely used. The purpose of this study was to promote the use of control charts in regional environmental monitoring by surveying the literature for control charting techniques suitable for the various types of data available from large programs measuring multiple indicators at multiple locations across various physical environments. Example datasets were obtained for Canada's Oil Sands Region, including water quality, air quality, facility production and performance, and bird communities, and were analyzed using univariate (e.g., x-bar) and multivariate (e.g., Hotelling's T2) control charts. The control charts indicated multiple instances of unexpected observations and highlighted subtle patterns in all of the example data. While control charts are not uniquely able to identify potentially relevant patterns in data and can be challenging to apply in some monitoring analyses, this work emphasizes the broad utility of the tools for straightforwardly presenting the results from standardized and routine surveillance monitoring. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Snow, glaciers, wetlands, frozen ground and permafrost needed in hydrological models. • Water quality export by coupling biochemical transformations to cold regions processes. • Hydrological sensitivity to land use depends on cold regions processes. • Strong cold regions hydrological sensitivity to climate warming. Cold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM's capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations. [ABSTRACT FROM AUTHOR]

Effective determination of water quality and water pollution assessment is crucial and challenging processes. Evaluating water quality in rivers, researchers have referred to various statistical, probabilistic and stochastic methods to obtain efficient information from the monitoring network. As data are greatly random, the information content can be obtained by utilizing various methods including but not limited to the "entropy." Monitoring is a difficult process due to high measurement costs, while it is also difficult to optimize the network in terms of time, space, and especially the variable to be monitored. In the presented study, it is aimed to create an effective approach to be used in optimizing the monitoring network by determining the "prior" variables by entropy that measures the uncertainty by using all the data without time difference. The presented study proposes an alternative method to define the water quality variables that should be monitored much more frequently. Study is exemplified for demonstrating its potential use in a case study level, Grand River in Canada, by assessing water quality data obtained from 15 water quality monitoring stations. Results showed that BOD, Cl, and NO2-N among examined 8 different variables are as the "prior" variables should be monitored. It is being proven that the prior variable that should be monitored for optimization of the network can be easily determined with the information obtained from the data statistically evaluated with entropy, and it can be stated as an effective method for managers to use in the decision-making process. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Canada is home to more lakes than any other nation, but there is a fragmented and limited understanding of the ecological status of these water bodies. Zooplankton are excellent bioindicators of lake health, given their central food web position. To date, many studies have investigated the effect of individual stressors on zooplankton communities, mediated through changes in water quality (e.g., macronutrients, temperature, or chemicals). Increasingly, stressors act simultaneously in lakes, often over extended periods of time. As part of the NSERC Canadian Lake Pulse Network project, pelagic zooplankton were sampled in 624 lakes across Canada, spanning six continental drainage basins. We evaluated the effect of 40+ environmental variables on zooplankton diversity and community composition, considering both taxonomic and functional approaches. We also tested specific hypotheses on the relationships between zooplankton communities and environmental conditions, including eutrophication, calcium, chloride, and fish predation. We found that lake morphometry variables were among the most important predictors of zooplankton diversity, while water quality metrics were more critical in explaining variation in community composition. Our results also reveal significant heterogeneity across Canada, with contrasting effects of environmental drivers among continental watersheds, highlighting that response models cannot be assumed to apply universally. [ABSTRACT FROM AUTHOR]

Drinking water insecurity in small and rural, remote, or otherwise marginalized communities in Canada is pervasive and complex with multiple dimensions and impacts. These communities face challenges such as variable source water quality, lack of resources, inappropriate treatment technologies, lack of access to training, difficulties retaining qualified personnel, and ineffective governance structures. Currently, there is a gap in the academic literature with respect to drinking water security assessment frameworks or tools for small and rural, remote, or otherwise marginalized communities, particularly in high income countries. Thus, the objective of this study is to introduce a framework for assessing drinking water security, from headwater to consumer, in the context of small and rural, remote, or otherwise marginalized communities. An indicator-based framework has been developed to evaluate drinking water security, prioritize actions and investments, and support decision-making. The framework builds on expert knowledge and a critical review of security, sustainability, and performance indices of water supply and treatment processes obtained from the literature. The framework is organised into four dimensions of drinking water security from headwaters to consumer: upstream watershed security; source water security; community needs and engagement; and treatment and distribution infrastructure. A list of relevant indicators for each dimension has been compiled to support framework application in a format that is accessible to decision-makers in small and rural, remote, or otherwise marginalized communities. [ABSTRACT FROM AUTHOR]

Diatom cultures can help answer taxonomic, biogeographic and ecological questions on a local and global scale. Unialgal cultures are derived from a single cell and provide abundant material for morphological and molecular analyses. The link between the historic morphological species concept and molecular data is becoming increasingly important with the use of eDNA metabarcoding. Additionally, cultures provide insights into the life cycle of diatoms and thereby complement taxonomy and species ecology. In this study, we present an approach to extract benthic diatoms from an environmental sample to generate unialgal cultures. We explored diatom diversity in preserved assemblages and by culturing as many different taxa as possible from benthic freshwater samples taken on the same day from the Bow River in Calgary, Canada. With both methods we found a total of 221 different benthic diatom taxa, of which 182 were identified in the preserved diatom assemblages. Interestingly, an additional 39 taxa only appeared in the cultures. In total 129 strains were cultivated, representing 71 different taxa. This study includes pictures of living cells demonstrating the additional merits of unialgal cultures, as they provide information on plastid details, auxospores and endosymbionts. Both, the identification of the diatom assemblages and the generation and identification of strains provide the foundation for additional water quality assessment tools, taxonomic insights, and molecular references libraries. [ABSTRACT FROM AUTHOR]

Purpose: Surveillance monitoring programs can provide fast, relatively low-cost, synoptic information on key water quality drivers and help inform land management decisions. Here, we evaluate longitudinal changes in the geochemical composition and metal speciation of deposited sediment over a 967 km reach of a large glacier-fed river and its key tributaries in central Alberta, Canada. In particular, the work provides a basis to understand how a major urban conurbation influences the geochemical composition and trace element properties of deposited sediment. Methods: The concentrations and spatial distribution of major elements and sediment-associated metals (As, Cd, Cr, Cu, Pb, Hg, Ni, Zn) were determined and compared to consensus-based threshold effect concentrations (TEC). Metal partitioning to geochemical properties of sediment was evaluated by sequential extraction. Results: Levels of Cr exceeded the TEC in 28% and 20% of the samples in the North Saskatchewan River and tributary samples, respectively. One Ni sample (3%) also exceeds the TEC on the main stem of the North Saskatchewan River. No consistent downstream increase in major element or trace metal concentrations was observed. The majority of Cr was bound to the largely non-bioavailable silicate phase thus highlighting the importance of parent geology as a source of metals to receiving streams. Conclusion: The results of this surveillance monitoring provide preliminary data on the distribution and speciation of sediment-associated metals in the North Saskatchewan River and thereby address an evidence gap common to many large river basins in Canada. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Some wetlands in the northern Great Plains support hundreds to thousands of late-stage tadpoles providing important sources of recruitment to the Wood Frog (Lithobates sylvaticus) population while many other wetlands produce none. Relationships between water quality and late-stage tadpole abundance were determined to identify the water quality parameters associated with tadpole abundance. Water samples were collected, and late-stage tadpole abundances were assessed once each year in late June for 12 years in 26 wetlands. Catch or abundance was the number of tadpoles captured in 30 min with a dip-net. The catch of tadpoles was variable both among wetlands and over the long-term for individual wetlands, and ranged from 0 to several hundred individuals. Wood Frog tadpoles were especially sensitive to sodium and chloride concentrations. At Cl concentrations less than 5 mg/L, occupancy for late-stage tadpoles was 84%, and declined by about 8% for each 5 mg/L increase in Cl to 40.1 mg/L Cl, the maximum concentration associated with the detection of tadpoles. Optimal water quality for late-stage Wood Frog tadpoles included low concentrations of Na (x ¯ = 8.1 mg/L), and Cl (x ¯ = 4.2 mg/L) relative to total dissolved solids and other ions, and high concentrations of phosphorus. In a landscape where ion concentrations in wetlands can range over 3 orders of magnitude, water quality analyses suggest that abundant Wood Frog tadpole populations occur in wetlands dominated by snow-melt runoff with its characteristic low ion concentrations. The present study highlights the importance to amphibian conservation of the water quality environment of tadpole habitat. [ABSTRACT FROM AUTHOR]