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Water quality remains a major issue in Canada. This paper reviews recent research on the impacts of urbanization, agriculture and forestry on water quality in Canada. Specific water quality issues such as mining, sewage treatment and waste treatment are not included in this paper. For each land use, a brief summary of the dominant processes linking runoff to water quality is provided and recent findings are summarized. With respect to urbanized watersheds, the relatively large proportion of impervious areas, lower vegetation cover and the presence of high-density drainage systems alter surface water routing and timing of peak flows. High concentrations of heavy metals are considered to be the most important water quality problem in urban runoff, but nutrients, pathogens, concentration of pharmaceuticals and water temperature also often contribute. In watersheds dominated by agricultural activities, overland flow is an important vector of pollutants, but subsurface flow such as macropore and tile-drain flo...

This review presents a summary of the influences of floods on river ecology, both instream and on the adjacent floodplain, mostly in a Canadian context. It emphasizes that ecological impacts and benefits can be highly dependent on flood-generation processes and their magnitude and timing. In Canada, floods can occur under open-water or ice-influenced river conditions. The ecological impacts of floods generated from ice jamming are particularly relevant in Canadian ecosystems due to the potentially higher water levels produced and suspended sediment concentrations that can be detrimental to instream aquatic habitat, but beneficial to floodplains. Large floods provide a major source of physical disturbance. Moderate floods with shorter return periods can be beneficial to aquatic habitats by providing woody debris that contributes to habitat complexity and diversity, by flushing fine sediments and by providing important food sources from terrestrial origins. Floods also influence water-quality variables such...

Summary Impacts of global climate change on water resources systems are assessed by downscaling coarse scale climate variables into regional scale hydro-climate variables. In this study, a new multisite statistical downscaling method based on beta regression (BR) is developed for generating synthetic precipitation series, which can preserve temporal and spatial dependence along with other historical statistics. The beta regression based downscaling method includes two main steps: (1) prediction of precipitation states for the study area using classification and regression trees, and (2) generation of precipitation at different stations in the study area conditioned on the precipitation states. Daily precipitation data for 53years from the ANUSPLIN data set is used to predict precipitation states of the study area where predictor variables are extracted from the NCEP/NCAR reanalysis data set for the same interval. The proposed model is applied to downscaling daily precipitation at ten different stations in the Campbell River basin, British Columbia, Canada. Results show that the proposed downscaling model can capture spatial and temporal variability of local precipitation very well at various locations. The performance of the model is compared with a recently developed non-parametric kernel regression based downscaling model. The BR model performs better regarding extrapolation compared to the non-parametric kernel regression model. Future precipitation changes under different GHG (greenhouse gas) emission scenarios also projected with the developed downscaling model that reveals a significant amount of changes in future seasonal precipitation and number of wet days in the river basin.

This study evaluates predictive uncertainties in the snow hydrology of the Fraser River Basin(FRB) of British Columbia(BC), Canada, using the Variable Infiltration Capacity(VIC) model forced with several high-resolution gridded climate datasets. These datasets include the Canadian Precipitation Analysis and the thin-plate smoothing splines(ANUSPLIN), North American Regional Reanalysis(NARR), University of Washington(UW) and Pacific Climate Impacts Consortium(PCIC) gridded products. Uncertainties are evaluated at different stages of the VIC implementation, starting with the driving datasets, optimization of model parameters, and model calibration during cool and warm phases of the Pacific Decadal Oscillation(PDO). The inter-comparison of the forcing datasets (precipitation and air temperature) and their VIC simulations (snow water equivalent – SWE – and runoff) reveals widespread differences over the FRB, especially in mountainous regions. The ANUSPLIN precipitation shows a considerable dry bias in the Rocky Mountains, whereas the NARR winter air temperature is 2°C warmer than the other datasets over most of the FRB. In the VIC simulations, the elevation-dependent changes in the maximum SWE(maxSWE) are more prominent at higher elevations of the Rocky Mountains, where the PCIC-VIC simulation accumulates too much SWE and ANUSPLIN-VIC yields an underestimation. Additionally, at each elevation range, the day of maxSWE varies from 10to 20days between the VIC simulations. The snow melting season begins early in the NARR-VIC simulation, whereas the PCIC-VIC simulation delays the melting, indicating seasonal uncertainty in SWE simulations. When compared with the observed runoff for the Fraser River main stem at Hope, BC, the ANUSPLIN-VIC simulation shows considerable underestimation of runoff throughout the water year owing to reduced precipitation in the ANUSPLIN forcing dataset. The NARR-VIC simulation yields more winter and spring runoff and earlier decline of flows in summer due to a nearly 15-day earlier onset of the FRB springtime snowmelt. Analysis of the parametric uncertainty in the VIC calibration process shows that the choice of the initial parameter range plays a crucial role in defining the model hydrological response for the FRB. Furthermore, the VIC calibration process is biased toward cool and warm phases of the PDO and the choice of proper calibration and validation time periods is important for the experimental setup. Overall the VIC hydrological response is prominently influenced by the uncertainties involved in the forcing datasets rather than those in its parameter optimization and experimental setups.

Une coulee de slush (bouillie de neige fondante) est un ecoulement rapide constitue d’un melange de neige fondante, d’eau, de boue et de debris de toutes sortes. Les sept sites analyses demontrent que les coulees de slush peuvent survenir dans des contextes topographiques fort differents qui presentent toutefois des similitudes au niveau du mode d’enneigement et des conditions hydro-meteorologiques. Les coulees de slush etudiees demarrent dans des ruisseaux d’ordre 1 ou 2, etroits et peu profonds, de pente tres variable (de 1° a plus de 30°), qui sont combles par des bouchons de neige dense soufflee par le vent ou transportee par les avalanches. Parce qu’ils s’opposent a la libre circulation des eaux de fusion lors des periodes de fonte acceleree, ces bouchons de neige favorisent la saturation du manteau neigeux jusqu’a la rupture sous l’effet combine de la pression hydrostatique et de la gravite. Les onze coulees analysees, qui se sont produites entre 1936 et 2013, permettent de definir deux scenarios hydro-meteorologiques propices a leur declenchement : 1) des redoux de longue duree caracterises par des temperatures qui restent positives pendant plusieurs jours consecutifs sans apport de precipitations liquides; 2) des redoux relativement courts (moins de 48 heures) couples a des precipitations liquides abondantes. Largement meconnues au Quebec, les coulees de slush pourraient etre plus frequentes a l’avenir en reponse au rechauffement climatique en cours.

We analyzed annual peak flow series from 127 naturally flowing or naturalized streamflow gauges across western Canada to examine the impact of the Pacific Decadal Oscillation (PDO) on annual flood risk, which has been previously unexamined in detail. Using Spearman's rank correlation ρ and permutation tests on quantile-quantile plots, we show that higher magnitude floods are more likely during the negative phase of the PDO than during the positive phase (shown at 38% of the stations by Spearman's rank correlations and at 51% of the stations according to the permutation tests). Flood frequency analysis (FFA) stratified according to PDO phase suggests that higher magnitude floods may also occur more frequently during the negative PDO phase than during the positive phase. Our results hold throughout much of this region, with the upper Fraser River Basin, the Columbia River Basin, and the North Saskatchewan River Basin particularly subject to this effect. Our results add to other researchers' work questioning the wholesale validity of the key assumption in FFA that the annual peak flow series at a site is independently and identically distributed. Hence, knowledge of large-scale climate state should be considered prior to the design and construction of infrastructure.

Among natural-disaster risks, heat waves are responsible for a large number of deaths, diseases and economic losses around the world. As they will increase in severity, duration and frequency over the decades to come within the context of climate change, these extreme events constitute a genuine danger to human health, and heat-warning systems are strongly recommended by public health authorities to reduce this risk of diseases and of excessive mortality and morbidity. Thus, evidence-based public alerting criteria are needed to reduce impacts on human health before and during persistent hot weather conditions. The goal of this guide is to identify alert thresholds for heat waves in Canada based on evidence, and to propose an approach for better defining heat waves in the Canadian context in order to reduce the risks to human health and contribute to the well-being of Canadians. This guide is the result of the collaboration among various research and public institutions working on: 1) meteorological and climate aspects, i.e. the Meteorological Service of Canada (MSC, Environment and Climate Change Canada), and the ESCER centre at the Universite du Quebec a Montreal, and 2) public health, i.e. Health Canada and the Institut National de Sante Publique du Quebec.

This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affected by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. These results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.

In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping.

Flood events in Canada result in larger costs, in terms of property damage, than any other natural disaster. Changes in land use, and more recently the impacts of climate change, can lead to changes in the flood regime. This paper describes research examining changes in the flood regime for watersheds across Canada. To distinguish between changes resulting from land-use changes and those occurring due to changes in climate, the analysis of flood data is conducted only on watersheds that are either part of a formal Reference Hydrologic Network (RHN), or which exhibit RHN-like characteristics. A total of 280 gauging stations have been analyzed for changes to a number of attributes of the flood regime. Changes in the magnitude and timing of flood events as well as the frequency and duration of high-flow events are examined for all 280 sites. Using all 280 sites and different groupings of the sites, based on timing of floods, drainage area and the RHN designation, changes were determined in the annual number ...

Abstract. This study presents an analysis of the observed inter-annual variability and inter-decadal trends in river discharge across northern Canada for 1964–2013. The 42 rivers chosen for this study span a combined gauged area of 5.26×106km2 and are selected based on data availability and quality, gauged area and record length. Inter-annual variability in river discharge is greatest for the eastern Arctic Ocean (coefficient of variation, CV=16%) due to the Caniapiscau River diversion into the La Grande Riviere system for enhanced hydropower production. Variability is lowest for the study area as a whole (CV=7%). Based on the Mann–Kendall test (MKT), no significant (p>0.05) trend in annual discharge from 1964 to 2013 is observed in the Bering Sea, western Arctic Ocean, western Hudson and James Bay, and Labrador Sea; for northern Canada as a whole, however, a statistically significant (p

This paper provides an overview of the key processes that generate floods in Canada, and a context for the other papers in this special issue – papers that provide detailed examinations of specific floods and flood-generating processes. The historical context of flooding in Canada is outlined, followed by a summary of regional aspects of floods in Canada and descriptions of the processes that generate floods in these regions, including floods generated by snowmelt, rain-on-snow and rainfall. Some flood processes that are particularly relevant, or which have been less well studied in Canada, are described: groundwater, storm surges, ice-jams and urban flooding. The issue of climate change-related trends in floods in Canada is examined, and suggested research needs regarding flood-generating processes are identified.

Abstract Recent flood events in Canada have led to speculation that changes in flood behaviour are occurring; these changes have often been attributed to climate change. This paper examines flood data for a collection of 132 gauging stations in Canada. All of these watersheds are part of the Canadian Reference Hydrometric Basin Network (RHBN), a group of gauging stations specifically assembled to assist in the identification of the impacts of climate change. The RHBN stations are considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Daily flow data for each watershed are used to derive a peaks over threshold (POT) dataset. Several measures of flood behaviour are examined based on the POT data, which afford a more in‐depth analysis of flood behaviour than can be obtained using annual maxima data. Analysis is conducted for four time periods ranging from 50 to 80 years in duration; the latter period results in a much smaller number of watersheds that have data for the period. The changes in flood responses of the watersheds are summarized by grouping the watersheds by size (small, medium, and large) and also by hydrologic regime (nival, mixed, and pluvial). The results provide important insights into the nature of the changes that are occurring in flood regimes of Canadian rivers, which include more flood exceedances, reduced maximum flood exceedance magnitudes for snowmelt events, and earlier flood events. Copyright © 2016 John Wiley & Sons, Ltd.

The effects of wetlands on stream flows are well established, namely mitigating flow regimes through water storage and slow water release. However, their effectiveness in reducing flood peaks and sustaining low flows is mainly driven by climate conditions and wetland type with respect to their connectivity to the hydrographic network (i.e. isolated or riparian wetlands). While some studies have demonstrated these hydrological functions/services, few of them have focused on the benefits to the hydrological regimes and their evolution under climate change (CC) and, thus, some gaps persist. The objective of this study was to further advance our knowledge with that respect. The PHYSITEL/HYDROTEL modelling platform was used to assess current and future states of watershed hydrology of the Becancour and Yamaska watersheds, Quebec, Canada. Simulation results showed that CC will induce similar changes on mean seasonal flows, namely larger and earlier spring flows leading to decreases in summer and fall flows. These expected changes will have different effects on 20-year and 100-year peak flows with respect to the considered watershed. Nevertheless, conservation of current wetland states should: (i) for the Becancour watershed, mitigate the potential increase in 2-year, 20-year and 100-year peak flows; and (ii) for the Yamaska watershed, accentuate the potential decrease in the aforementioned indicators. However, any loss of existing wetlands would be detrimental for 7-day 2-year and 10-year as well as 30-day 5-year low flows.

ABSTRACTThis work explores the ability of two methodologies in downscaling hydrological indices characterizing the low flow regime of three salmon rivers in Eastern Canada: Moisie, Romaine and Ouelle. The selected indices describe four aspects of the low flow regime of these rivers: amplitude, frequency, variability and timing. The first methodology (direct downscaling) ascertains a direct link between large-scale atmospheric variables (the predictors) and low flow indices (the predictands). The second (indirect downscaling) involves downscaling precipitation and air temperature (local climate variables) that are introduced into a hydrological model to simulate flows. Synthetic flow time series are subsequently used to calculate the low flow indices. The statistical models used for downscaling low flow hydrological indices and local climate variables are: Sparse Bayesian Learning and Multiple Linear Regression. The results showed that direct downscaling using Sparse Bayesian Learning surpassed the other a...

Intensity Duration Frequency (IDF) curves are among the most common tools used in water resources management. They are derived from historical rainfall records under the assumption of stationarity. Change of climatic conditions makes the use of historical data for development of IDFs for the future unjustifiable. The IDF_CC, a web based tool, is designed, developed and implemented to allow local water professionals to quickly develop estimates related to the impact of climate change on IDF curves for almost any local rain monitoring station in Canada. The primary objective of the presented work was to standardize the IDF update process and make the results of current research on climate change impacts on IDF curves accessible to everyone. The tool is developed in the form of a decision support system (DSS) and represents an important step in increasing the capacity of Canadian water professionals to respond to the impacts of climate change. Climate change impact on IDF curves investigated.Standardized IDF update process.Two theoretical contributions incorporated: downscaling method and skill score computation method.Web based tool developed and implemented for updating IDF curves under climate change.