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Climate variability is recognized as an important influence on the availability of water throughout Canada, and projected climate change is anticipated to alter the amount, timing and distribution of water. This is Part II of a three-part (Parts I and III, this issue) analysis of water availability in Canada. Part II surveys current research, primarily Canadian in origin, on historical trends in climate and hydrologic indicators relevant to assessing water availability. Information on hydro-climate trends is not evenly distributed across Canada. Hydrologic trend research focuses on the North, British Columbia and the Prairies (Saskatchewan) with some research in Quebec, very little in Ontario and minimal analysis for Atlantic Canada. Overall, there is less research on trends in climatological indicators (drought, evapotranspiration, soil moisture); generally, the focus is on the Prairies. Hydrologic trends from basin-scale case studies are reported but inter-comparison is constrained by different periods ...

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.

Abstract Retrospective estimation of daily streamflow for all rivers within a territory is of practical interest for sustainable and optimal water management. This implies, however, the availability of methods for providing accurate estimations of flow for ungauged rivers. This study compares the potential of statistical interpolation (SI)—a simple data assimilation technique that combines observations and simulations from hydrological modelling—with four other approaches: nearest neighbour, direct use of outputs from hydrological modelling, ordinary and topological kriging. Through subsampling cross-validation analyses based on the modified Kling-Gupta efficiency indicator, we show that SI compares favourably with these other approaches. While the performance of other methods depends on the configuration of the ungauged site in regards to the neighbouring reference sites, SI is less affected by these configurations. SI outperforms the other approaches particularly where the ungauged site is relatively distant from observation sites. In these cases, SI performance depends on the performance of the background model that relies on simulations of hydrological processes forced by precipitation and temperature observations. Our findings offer the potential for heightened performance estimates through an improvement of hydrological modelling and the use of more complex assimilation techniques for exploiting the model.

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Climate variability influences the availability of water resources throughout Canada, and projected climate change is anticipated to affect future water availability. This is the first paper of a three-part analysis of water availability indicators in Canada (Parts II and III, this issue). The concept of water availability has been described in different ways in the literature. In Part I, the various approaches for estimating water availability are reviewed and compared, with a focus on Canadian studies. Global examples are used when necessary. The approaches to estimate water availability are organized into three categories: (1) climate-based indicators, (2) hydrology-based indicators and (3) water demand/supply-based indicators. Climate-based indicators use variables such as precipitation, and potential or actual evapotranspiration to calculate water budgets. Widely used meteorological drought indices that calculate moisture surpluses and deficits are also examined. Hydrology-based indicators focus on v...

This study quantified the contributions of overland and tile flow to total runoff (sum of overland and tile flow) and nutrient losses in a Vertisolic soil in the Red River valley (Manitoba, Canada), a region with a cold climate where tile drainage is rapidly expanding. Most annual runoff occurred as overland flow (72–89%), during spring snowmelt and large spring and summer storms. Tile drains did not flow in early spring due to frozen ground. Although tiles flowed in late spring and summer (33–100% of event flow), this represented a small volume of annual runoff (10–25%), which is in stark contrast with what has been observed in other tile‐drained landscapes. Median daily flow‐weighted mean concentrations of soluble reactive P (SRP) and total P (TP) were significantly greater in overland flow than in tile flow ( p < 0.001), but the reverse pattern was observed for NO 3 –N ( p < 0.001). Overland flow was the primary export pathway for both P and NO 3 –N, accounting for >95% of annual SRP and TP and 50 to 60% of annual NO 3 –N losses. Data suggest that tile drains do not exacerbate P export from Vertisols in the Red River valley because they are decoupled from the surface by soil‐ice during snowmelt, which is the primary time for P loss. However, NO 3 –N loading to downstream water bodies may be exacerbated by tiles, particularly during spring and summer storms after fertilizer application. Core Ideas Overland flow was the primary pathway for runoff and nutrient loss at field edge. Most runoff and nutrient loss occurred during spring snowmelt and rain events. Tile drains are unlikely to exacerbate P losses from Vertisolic soils. Tile drains may enhance N loading in this region.

Quantification of climate change impacts on the thermal regimes of rivers in British Columbia (BC) is crucial given their importance to aquatic ecosystems. Using the Air2Stream model, we investigate the impact of both air temperature and streamflow changes on river water temperatures from 1950 to 2015 across BC’s 234,000 km2 Fraser River Basin (FRB). Model results show the FRB’s summer water temperatures rose by nearly 1.0°C during 1950–2015 with 0.47°C spread across 17 river sites. For most of these sites, such increases in average summer water temperature have doubled the number of days exceeding 20°C, the water temperature that, if exceeded, potentially increases the physiological stress of salmon during migration. Furthermore, river sites, especially those in the upper and middle FRB, show significant associations between Pacific Ocean teleconnections and regional water temperatures. A multivariate linear regression analysis reveals that air temperature primarily controls simulated water temperatures in the FRB by capturing ~80% of its explained variance with secondary impacts through river discharge. Given such increases in river water temperature, salmon returning to spawn inthe Fraser River and its tributaries are facing continued and increasing physical challenges now and potentially into the future.

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.

Changes in the form of precipitation have a considerable impact on the Arctic cryosphere and ecological system by influencing the energy balance and surface runoff. In this study, station observations and ERA-Interim data were used to analyze changes in the rainfall to precipitation ratio (RPR) in northern Canada during the spring–summer season (March–July) from 1979–2015. Our results indicate that ERA-Interim describes the spring–summer variations and trends in temperature and the RPR well. Both the spring–summer mean temperature [0.4°C–1°C (10 yr)-1] and the RPR [2%–6% (10 yr)-1] increased significantly in the Canadian Arctic Archipelago from 1979–2015. Moreover, we suggest that, aside from the contribution of climate warming, the North Atlantic Oscillation is probably another key factor influencing temporal and spatial differences in the RPR over northern Canada.

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.

Although numerous studies have looked at the long-term trend of the temporal variability of winter temperature and precipitation in southern Quebec, no study has focused on the shifts in series means and the dependence between these two types of climate variables associated with this long-term trend. To fill these gaps, we used the Lombard method to detect the shifts in mean values and the copula method to detect any change in dependence between extreme (maximum and minimum) temperatures and precipitation (snow and rain) over the periods 1950–2000 (17 stations) and 1950–2010 (7 stations). During these two periods, the shifts in mean values of temperature and precipitation were recorded at less than half of the stations. The only significant change observed at the provincial scale is a decrease in the amount of snowfall, which occurred in many cases during the 1970s. This decrease affected stations on the north shore (continental temperate climate) more strongly than stations on the south shore (maritime temperate climate) of the St Lawrence River. However, this decrease in the amount of snowfall had no impact on the dependence over time between temperature and precipitation as snow.

Abstract Debris slide occurrence on treed slopes of northeastern North America is still poorly documented, despite their abundance and their potential to change mountainous landscapes in short periods of time. To provide new information on their spatiotemporal dynamics, a study was undertaken in debris slide paths in the Wildlife Reserve of Port-Cartier-Sept-Iles, on the Quebec North-Shore region of eastern Canada. Tree-ring dating of growth anomalies (impact scars and reaction wood) in nine debris slides allowed the identification of four debris slide events that occurred in 2003, 2006, 2008, and 2010. By comparison to other hillslope processes such as snow avalanches and debris flows, debris slides produce a very strong tree-ring signal. Therefore they do not require a large sample size considering also that they do not occur twice at the same place. The position of growth anomalies within individual tree rings allowed to determine the timing of the debris slide events: injuries located within a ring correspond to debris slides occurring during the growing season, whereas injuries located between the end of a ring and the beginning of the following ring were caused by debris slides occurring during the dormant season. The meteorological data indicate that a daily precipitation of 70mm appears usually sufficient for the occurrence of debris slides.

Introduction:In July 2013, a train transporting oil derailed and exploded in Lac-Mégantic, causing major human, environmental, and economic impacts. A community-based survey of people aged 10-25, conducted in 2017, revealed that many young people suffer in silence and report feeling isolated. These observations led to the conclusion that we must make room for young people, and that opportunities for engagement and participation must be provided within the community.Aim:The Public Health Direction of Estrie aimed to identify strategies to promote health and wellbeing for young people living in and around Lac-Mégantic.Methods:A collective reflection half-day was hosted with sixty key stakeholders (school board, other education institutions, health and social services, community sector, municipal/political sector, parents, youth). Throughout the event, participants were invited to build on and learn from accomplishments and experiential knowledge, and develop a common vision of the solutions to be pursued or implemented. All qualitative data sources (verbal and written data from large- and sub-group activities) were analyzed through a content analysis.Results:Several themes (i.e. potential solutions) emerged from the analysis: common venue, diversified activities, communication, collaboration, involvement, support for at-risk youth, intergenerational component, etc. Participants agreed on four priorities for action: 1) creating a gathering place, 2) establishing a Youth Committee, 3) supporting adults working with youth, and 4) fostering a better flow of information.Discussion:Several positive outcomes of the collective reflection half-day were observed, including the mobilization of the participants who greatly appreciated the event, and many promising ideas launched by stakeholders. A social worker is now fully dedicated to supporting youth wellbeing and engagement in Lac-Mégantic. A Youth Committee has been established and projects by and for youth are being implemented. Bottom-up approaches to identify solutions to complex situations are not only effective but also respectful of the local culture.

In this study future flooding frequencies have been estimated for the Grand River catchment located in south - western Ontario, Canada. Historical and future climatic projections made by fifteen Coupled Model Inter - comparison Project - 3 climate models are bias - corrected and downscaled before they are used to obtain mid - and end of 21 st century streamflow projections. By comparing the future projected and historically observed precipitation and temperature record s it is found that the mean and extreme temperature events will intensify in future across the catchment. The increase is more drastic in the case of extreme events than the mean events. The sign of change in future precipitation is uncertain. Further flow extremes are expected to increase in magnitude and frequency in future across the catchment. The confidence in the projection is more for low return period (<10 years) extreme events than higher return period (10 - 100 years) events. It can be expected that increases in temperature will play a dominant role in increasing the magnitude of low return period flooding events while precipitation seems to play an important role in shaping the high return period events.

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada’s (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Quebec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

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.