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Abstract Numerous studies have examined the impact of prairie pothole wetlands on overall watershed dynamics. However, very few have looked at individual wetland dynamics across a continuum of alteration status using subdaily hydrometric data. Here, the importance of surface and subsurface water storage dynamics in the prairie pothole region was documented by (1) characterizing surface fill–spill dynamics in intact and consolidated wetlands; (2) quantifying water‐table fluctuations and the occurrence of overland flow downslope of fully drained wetlands; (3) assessing the relation (or lack thereof) between intact, consolidated or drained wetland hydrological behaviour, and stream dynamics; and (4) relating wetland hydrological behaviour to landscape characteristics. Focus was on southwestern Manitoba, Canada, where ten intact, three consolidated, seven fully drained wetlands, and a nearby creek were monitored over two years with differing antecedent storage conditions. Hourly hydrological time series were used to compute behavioural metrics reflective of year‐specific and season‐specific wetland dynamics. Behavioural metrics were then correlated to wetland physical characteristics to identify landscape controls on wetland hydrology. Predictably, more frequent spillage or overland flow was observed when antecedent storage was high. Consolidated wetlands had a high degree of water permanence and a greater frequency of fill–spill events than intact wetlands. Shallow and highly responsive water tables were present downslope of fully drained wetlands. Potential wetland–stream connectivity was also inferred via time‐series analysis, while some landscape characteristics (e.g., wetland surface, catchment area, and storage volume) strongly correlated with wetland behavioural metrics. The nonstationarity of dominant processes was, however, evident through the lack of consistent correlations across seasons. This, therefore, highlights the importance of combining multiyear high‐frequency hydrometric data and detailed landscape analyses in wetland hydrology studies.

This study evaluates projected changes to rain-on-snow (ROS) characteristics (i.e., frequency, rainfall amount, and runoff) for the future 2041–2070 period with respect to the current 1976–2005 period over North America using six simulations, based on two Canadian RCMs, driven by two driving GCMs for RCP4.5 and 8.5 emission pathways. Prior to assessing projected changes, the two RCMs are evaluated by comparing ERA-Interim driven RCM simulations with available observations, and results indicate that both models reproduce reasonably well the observed spatial patterns of ROS event frequency and other related features. Analysis of current and future simulations suggest general increases in ROS characteristics during the November–March period for most regions of Canada and for northwestern US for the future period, due to an increase in the rainfall frequency with warmer air temperatures in future. Future ROS runoff is often projected to increase more than future ROS rainfall amounts, particularly for northeastern North America, during snowmelt months, as ROS events usually accelerate snowmelt. The simulations show that ROS event is a primary flood generating mechanism over most of Canada and north-western and -central US for the January–May period for the current period and this is projected to continue in the future period. More focused analysis over selected basins shows decreases in future spring runoff due to decreases in both snow cover and ROS runoff. The above results highlight the need to take into consideration ROS events in water resources management adaptation strategies for future climate.

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. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020–2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5–10% per decade (or 15–30% in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10% per decade (30% in total) are projected across southern Canada.

Generalized Additive Models (GAMs) are introduced in this study for the regional estimation of low-flow characteristics at ungauged basins and compared to other approaches commonly used for this purpose. GAMs provide more flexibility in the shape of the relationships between the response and explanatory variables in comparison to classical models such as multiple linear regression (MLR). Homogeneous regions are defined here using the methods of hierarchical cluster analysis, canonical correlation analysis and region of influence. GAMs and MLR are then used within the delineated regions and also for the whole study area. In addition, a spatial interpolation method is also tested. The different models are applied for the regional estimation of summer and winter low-flow quantiles at stations in Quebec, Canada. Results show that for a given regional delineation method, GAMs provide improved performances compared to MLR.

Abstract Flow duration curves (FDC) are used to obtain daily streamflow series at ungauged sites. In this study, functional multiple regression (FMR) is proposed for FDC estimation. Its natural framework for dealing with curves allows obtaining the FDC as a whole instead of a limited number of single points. FMR assessment is performed through a case study in Quebec, Canada. FMR provides a better mean FDC estimation when obtained over sites by considering simultaneously all FDC quantiles in the assessment of each given site. However, traditional regression provides a better mean FDC estimation when obtained over given FDC quantiles by considering all sites in the assessment of each quantile separately. Mean daily streamflow estimation is similar; yet FMR provides an improved estimation for most sites. Furthermore, FMR represents a more suitable framework and provides a number of practical advantages, such as insight into descriptor influence on FDC quantiles. Hence, traditional regression may be preferred if only few FDC quantiles are of interest; whereas FMR would be more suitable if a large number of FDC quantiles is of interest, and therefore to estimate daily streamflows.

The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981–2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40–60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

This study focuses on the evaluation of daily precipitation and temperature climate indices and extremes simulated by an ensemble of 12 Regional Climate Model (RCM) simulations from the ARCTIC-CORDEX experiment with surface observations in the Canadian Arctic from the Adjusted Historical Canadian Climate Dataset. Five global reanalyses products (ERA-Interim, JRA55, MERRA, CFSR and GMFD) are also included in the evaluation to assess their potential for RCM evaluation in data sparse regions. The study evaluated the means and annual anomaly distributions of indices over the 1980–2004 dataset overlap period. The results showed that RCM and reanalysis performance varied with the climate variables being evaluated. Most RCMs and reanalyses were able to simulate well climate indices related to mean air temperature and hot extremes over most of the Canadian Arctic, with the exception of the Yukon region where models displayed the largest biases related to topographic effects. Overall performance was generally poor for indices related to cold extremes. Likewise, only a few RCM simulations and reanalyses were able to provide realistic simulations of precipitation extreme indicators. The multi-reanalysis ensemble provided superior results to individual datasets for climate indicators related to mean air temperature and hot extremes, but not for other indicators. These results support the use of reanalyses as reference datasets for the evaluation of RCM mean air temperature and hot extremes over northern Canada, but not for cold extremes and precipitation indices.

L’algue Didymosphenia geminata est une diatomée à potentiel envahissant. Cette algue microscopique, attachée au substrat, peut sécréter des quantités phénoménales de mucilage et créer de vaste amas fibreux tapissant le lit d’une rivière. Autrefois considérée très rare et représentative d’une qualité d’eau impeccable, elle est maintenant répertoriée omniprésente dans les rivières oligotrophes à travers le monde. Au cours des deux dernières décennies, son émergence a créé un intérêt marqué de la part des écologistes et gestionnaires de rivières puisque sa biologie et les facteurs régissant son occurrence et sa sévérité sont méconnus. Au Québec, c’est à l’été 2006 que les premières proliférations massives de l’algue didymo ont été observées dans la rivière Matapédia. Le manque de connaissances à son égard, plus précisément sur sa distribution, les causes de l’apparition des proliférations et de l’impact négatif possible de cet envahissement sur le réseau trophique mais surtout sur le cycle de vie du saumon atlantique en rivière a créé un état de panique chez les gestionnaires et les utilisateurs des rivières à saumon. Il existait dès lors un urgent besoin de combler ces lacunes. Afin de mieux comprendre les facteurs régissant tant la croissance cellulaire que la croissance des amas mucilagineux, un modèle conceptuel a été élaboré grâce à la collaboration de plusieurs chercheurs travaillant au Colorado, à l’île de Vancouver, en Nouvelle-Zélande et au Québec afin de colliger les observations et les données de terrain. Ce travail de synthèse a permis d’identifier les facteurs favorisant sa colonisation, sa croissance et sa persistance en rivière. La dynamique spatio-temporelle de l’algue didymo est dépendante de divers facteurs (ou conditions environnementales) dont les seuils critiques déterminent son comportement de prolifération. En rivière, la croissance d’algues benthiques est principalement déterminée par les variations saisonnières du débit, la température, la lumière et la chimie de l’eau. Ainsi, la connaissance des paramètres d’habitats favorables permet de déterminer si un bassin versant est favorable à la présence cellulaire de l’algue didymo et à la probabilité que celle-ci puisse y proliférer. Le modèle conceptuel permet d’établir la variabilité et la sévérité saisonnière du comportement envahissant de l’algue didymo en rivière. Afin d’appliquer le modèle conceptuel développé à l’échelle du bassin versant, nous avons mis sur pied un réseau de suivi volontaire des proliférations d’algue didymo dans le bassin versant de la rivière Restigouche. Vingt-deux organisations différentes totalisant 70 bénévoles ont été formés à identifier et quantifier les proliférations d’algue didymo. Entre 2010 et 2015, 1 228 observations ont été réalisées. L’analyse de cette base de données, nous a permis de déterminer que 71% de la variabilité de la sévérité des proliférations durant l’été est inversement proportionnelle à l’intensité de la crue printanière. À l’échelle du tronçon, l’analyse des proliférations pour différents types de faciès-substrat a permis de d’identifier une préférence accrue pour les seuils. Par la suite, afin d’appliquer le modèle conceptuel à l’échelle régionale, nous avons comparé la distribution de l’algue didymo dans trois régions de l’est du Québec (i.e. Gaspésie, Bas-St-Laurent et Côte-Nord) avec divers paramètres physico-chimiques de vingt-neuf rivières à saumon. Le principal facteur régissant la présence-absence de cellules est le pH. Les diatomées ont des optimums de pH très spécifiques et la géologie contrastante de la Côte-Nord (Bouclier canadien) par rapport aux basses terres du Saint-Laurent et les Appalaches en Gaspésie, a permis d’identifier que les eaux acides riches en tanins et lignines ne sont pas favorables à la survie et la croissance de l’algue didymo. Grâce à une meilleure connaissance des facteurs de contrôle de l’algue didymo à diverses échelles spatiales, nous pouvons déterminer les rivières à risque de proliférations massives. Au sein des rivières exhibant des proliférations, nous avons déterminé que les préférences d’habitat de l’algue didymo sont identiques à celles du saumon atlantique juvénile (i.e. eaux rapides, peu profondes, claires, froides, faible en nutriments avec un substrat grossier). Afin de déterminer l’ampleur de l’impact de la présence des proliférations sur le réseau trophique, nous avons vérifié son impact sur la communauté algale. La structure dense et fibreuse crée un environnement physique dans lequel plusieurs diatomées peuvent s’y loger. Nos résultats confirment que l’algue crée un habitat de choix pour les plus petites diatomées favorisant ainsi une plus grande diversité taxonomique. Malgré une augmentation de la complexité du biofilm suivant son épaississement, il n’y a pas d’impact supplémentaire sur la structure et la diversité taxonomique des échantillons. Puisque la structure de l’habitat est modifiée par les tapis et que ces derniers sont susceptibles d’altérer la structure et le fonctionnement de l’écosystème, nous avons évalué l’effet des proliférations sur le comportement alimentaire des saumons juvéniles. Grâce à l’observation en apnée du comportement, nous pouvons conclure que les saumons juvéniles effectuent une plus grande proportion de quêtes benthiques en fonction du pourcentage de recouvrement algal. Ce changement de comportement n’est pas attribuable à une diminution des proies disponibles au sein de la dérive. Notre étude confirme la grande plasticité comportementale des saumons juvéniles face aux modifications de l’habitat. Afin de vérifier l’impact des proliférations sur les ressources alimentaires et la diète des saumons juvéniles, nous avons utilisé l’approche par analyse d’isotopes stables. Cette approche permet d’établir un portrait intégré de l’utilisation des ressources par les poissons. Les signatures isotopiques divergentes entre les différents tissus des saumons confirment une modification de la diète saisonnière. Les saumons juvéniles en présence de l’algue didymo ont une diète moins diversifiée et appauvrie en carbone principalement composée de petits chironomides et de trichoptères. Malgré que l’indice de condition physique des saumons juvéniles soit similaire entre les deux sites, leur taille est plus petite dans le site avec proliférations. Les travaux futurs devront tenter de valider l’impact de la diminution de la qualité de la diète par les proliférations d’algue didymo sur le contenu en lipides des juvéniles. Suite aux diverses collaborations internationales et discussions avec les gestionnaires, nous nous sommes rendus à l’évidence qu’il devait y avoir une recommandation sur les mesures de gestion vis-à-vis cette espèce. En fonction des connaissances scientifiques développées au fil des ans et plusieurs cas de gestion dans divers pays, nous avons recommandé aux gestionnaires d’éduquer les utilisateurs à vérifier, nettoyer, sécher et congeler leurs équipements. Que l’algue didymo soit une espèce exotique ou indigène, elle peut être propagée. De plus, la mise en valeur des saines pratiques permettent de limiter la propagation d’autres organismes pouvant potentiellement être plus dévastateurs que l’algue didymo. Les résultats de cette thèse contribuent à l’avancement des connaissances sur les facteurs de contrôle de l’algue didymo tant à l’échelle microscopique que macroscopique. En plus d’avoir contribué à élaborer le modèle conceptuel, nous l’avons amélioré en l’appliquant à diverses échelles spatiales : à l’échelle du tronçon et du bassin versant ainsi qu’à l’échelle régionale. C’est d’ailleurs la première étude à élaborer un réseau de suivi des proliférations par l’implication des acteurs du milieu ainsi qu’une des seules études à avoir examiné la variabilité interannuelle sur une période de six ans. C’est également la première étude à avoir évalué l’impact de l’algue didymo sur les communautés périphytiques dans l’est du Canada. De surcroît, c’est la première étude exhaustive qui a évalué l’effet des proliférations sur l’écologie du saumon atlantique juvénile. Les recherches menées sur le comportement alimentaire est également novateur et contribue considérablement à la compréhension des mécanismes et les interactions entre les divers niveaux trophiques et l’impact sur les salmonidés.<br /><br />Didymosphenia geminata is mat-forming nuisance diatom. This epilithic microscopic alga can secrete copious amounts of mucilage creating thick and extensive mats covering the entire riverbed. Once considered very rare and representative of pristine water quality, it is now ubiquitous in rivers around the world. Over the past two decades, this alga has emerged as a nuisance diatom and generated much interest among freshwater ecologists and river managers alike. Nonetheless, controlling factors governing the occurrence and severity of D. geminata are still not well understood. In Quebec, the first massive proliferations of D. geminata were reported in 2006 in the Matapedia River. There was an urgency to fill this knowledge gap as managers and government agencies panicked at the lack of knowledge regarding its distribution, the causes of its onset and mostly, fear of that this alga would act as an additional stressor to Atlantic salmon populations. To better understand controlling factors of both cell division and mat formation, a conceptual model was developed with the collaboration of several researchers working in Colorado, Vancouver Island, New Zealand and Quebec to collate observations and field data. This synthesis work helped identify the factors favoring its colonization, growth and persistence in rivers. The spatiotemporal dynamics of D. geminata are dependent on various dynamic thresholds of flow, temperature, light and water chemistry within the habitat window. We can therefore test various arrays of these parameters to determine whether rivers are likely to present occasional to persistent D. geminata mats. To test and improve upon the conceptual model at various spatial scales, we developed a monitoring network for D. geminata mat presence. Twenty-two different organizations totaling 70 volunteers were trained to identify and quantify the proliferations of D. geminata. Between 2010 and 2015, 1 228 observations were made. The analysis of this database helped determine that 71% of the variability of D. geminata severity is inversely proportional to the intensity of the spring flood. At the reach scale, habitat type was determinant for presence-absence of mats with a strong significant preference for riffles. At the provincial scale, we compared the distribution of D. geminata in three regions of eastern Quebec (i.e. Gaspesie, Bas-St-Laurent and Cote-Nord) against numerous water chemistry parameters for twentynine rivers. At the broad regional scale, pH was the most important factor governing the presence-absence of cells. Diatoms have very specific pH optima and the contrasting geologies between regions confirmed that low pH and high tannins and lignin are not favorable to the survival and growth of D. geminata. Habitat preferences for D. geminata mats are identical to those of juvenile Atlantic salmon (i.e. shallow, fast, clear, cool, low nutrient and coarse substrate). To determine the extent of the impact of the presence of mats on the food web, we verified its impact on the algal community. The dense interwoven matrix creates a suitable physical environment for small diatoms, thus promoting greater taxonomic diversity. Despite an increase in the complexity of the biofilm with mat accrual, there is no additional impact on the structure and taxonomic diversity of the samples. D. geminata effects to higher trophic levels have been suspected since the structure of the habitat is modified and could alter the structure and functioning of the ecosystem. We studied the foraging behaviour of juvenile Atlantic salmon in contrasting D. geminata severities. With increasing percent cover of the alga, juvenile Atlantic salmon switch from a drift-foray to benthic-foray strategy. This change in behavior is not due to limited drifting prey availability. Our results reinforce the notion that juvenile Atlantic salmon have high behavioral plasticity in response to habitat changes. To test the impact of mats on juvenile salmon diet, we used a stable isotope analysis approach. This approach provides an integrated view of resource use by fish. Contrasting isotopic signatures between the liver and muscle tissues confirm a change in the seasonal diet. Juvenile salmon sampled in the D. geminata impacted site have a less diversified and carbon-depleted diet composed mainly of small chironomids and Trichoptera. Juvenile salmon condition factors and C:N ratios were not different between sites, though their size is smaller in the impacted site. Future work should focus on the effects of reduced prey quality on lipid content of fish. Over various international collaborations and discussions with managers, it became clear that there was a need for a clear and standardized recommendation on management measures for this nuisance species. Based on recent scientific knowledge and several management cases in various countries, we recommended that managers educate users to check, clean, dry and freeze their equipment. Regardless of whether D. geminata is an exotic or native species, it can be spread. In addition, the development of best practices limits the spread of aquatic organisms as others may be far more devastating than D. geminata. The results of this thesis contribute to the advancement of knowledge on the controlling factors of D. geminata for both cells and mats. In addition to contributing to the development of the conceptual model, we have tested and improved it by applying it to a variety of spatial scales: at the reach, watershed and regional scales. This is the first study to develop a monitoring network for mat severity with the involvement of local stakeholders. It is also the first study to evaluate the impact of D. geminata on periphytic communities in eastern Canada. Moreover, it is the first comprehensive study that has evaluated the effect D. geminata mats on juvenile Atlantic salmon ecology. Research on foraging behavior is also innovative and contributes significantly to the understanding of the mechanisms and interactions by which D. geminata impacts various trophic levels and salmonids.

Les inondations constituent l’un des risques naturels les plus fréquents. Une inondation historique survenue au Québec s’est produite aux abords de la rivière Richelieu entre avril et juin 2011. Suite aux dommages et aux frais occasionnés par cet épisode, l’INRS s’est engagé avec la ville de Saint-Jean-sur-Richelieu afin de la doter d’un système de Gestion et d’Analyse du Risque d’Inondation (GARI) : le niveau d’eau constitue une donnée essentielle pour l’évaluation de l’ampleur d’une inondation en temps réel. Ce travail de recherche a pour objectif de détecter automatiquement la ligne d’eau sur des images acquises par des caméras placées aux abords de la rivière Richelieu par des méthodes d’analyse d’images et de convertir cette dernière en niveau d’eau par stéréoscopie (transfert des valeurs en pixels en unité métrique). Le premier volet de ce travail de recherche s’intéresse à l’extraction automatique de la ligne d’eau à partir de données acquises par des caméras de surveillance. Afin de répondre à cette exigence, des séquences d’images de durée déterminée (une minute) ont été enregistrées et une image moyenne a été calculée pour chaque séquence. L’image moyenne est ensuite segmentée puis classifiée à l’aide d’une technique supervisée. Pour la première séquence d’images à traiter, des sites d’entraînement décrivant les parties immergées et libres sont créées afin d’obtenir deux classes de sortie correspondant aux surfaces d’eau et au reste de l’image. Une détection de contour permet d’isoler les pixels de la ligne d’eau. Pour les séquences suivantes, l’algorithme utilise automatiquement la ligne d’eau créée à la séquence précédente pour définir les sites d’entraînements à la séquence considérée. Le taux de réussite d’extraction de la ligne d’eau avoisine 90%. Le second volet consiste à convertir les coordonnées des pixels de la ligne d’eau du système bidimensionnel image vers un système tridimensionnel dans un référentiel connu. Les observations par stéréoscopie permettent cette transformation via les procédures d’orientation intérieure des caméras et d’orientation extérieure des couples stéréoscopiques. Pour le modèle de caméra considéré, les tests effectués montrent que les erreurs de positionnement planimétrique de la ligne d’eau sont inférieures au mètre et l’erreur de positionnement altimétrique (niveau d’eau) est inférieure à 10 cm lorsque le rapport entre la base stéréoscopique et la distance avec l’objet à modéliser est supérieur à 0.1.<br /><br />Flooding is one of the most common natural hazards. A historic flood occurred in the vicinity of the Richelieu River (Province of Quebec, Canada) between April and June 2011. After the damages and expenses incurred by this episode, INRS and the city of Saint-Jean-sur-Richelieu decided to create a flood risk management and analysis system : water level is an essential factor for assessing magnitude of a flood in real time. This research project aims to automatically detect the water line on images acquired by cameras located near the Richelieu River with image analysis methods and to convert it to water level by stereoscopy (transfer of values from pixel unit to metric unit). The first part of this research work focuses on automatic extraction of water line from data acquired by surveillance cameras. In order to meet this requirement, fixed-duration (one minute) image sequences were recorded and an average image was calculated for each sequence. Average image is then segmented and classified using a supervised technique. For the first sequence of images to be processed, training sites describing submerged and free portions are created to obtain two output classes corresponding to water and the rest of the image. Then, a contour detection is used to determine water line. For the following sequences, the algorithm automatically uses water line created in the previous sequence to define training sites for the present sequence. Success rate of water line extraction is around 90%. Second part consists in converting pixels coordinates of water line known in a two-dimensional image system to a three-dimensional system in a known reference frame. Stereoscopic observations allow this transformation via interior and exterior orientations procedures. For the camera model considered in this project, tests highlight that planimetric positioning errors of the water line are lower than 1 m and altimetric positioning error (water level) is lower than 10 cm when the ratio between stereoscopic basis and distance to the object to be modeled is higher than 0.1.

Abstract. Black carbon aerosol (BC), which is emitted from natural and anthropogenic sources (e.g., wildfires, coal burning), can contribute to magnify climate warming at high latitudes by darkening snow- and ice-covered surfaces, and subsequently lowering their albedo. Therefore, modeling the atmospheric transport and deposition of BC to the Arctic is important, and historical archives of BC accumulation in polar ice can help to validate such modeling efforts. Here we present a > 250-year ice-core record of refractory BC (rBC) deposition on Devon ice cap, Canada, spanning the years from 1735 to 1992. This is the first such record ever developed from the Canadian Arctic. The estimated mean deposition flux of rBC on Devon ice cap for 1963–1990 is 0.2 mg m−2 a−1, which is at the low end of estimates from Greenland ice cores obtained using the same analytical method ( ∼ 0.1–4 mg m−2 a−1). The Devon ice cap rBC record also differs from the Greenland records in that it shows only a modest increase in rBC deposition during the 20th century. In the Greenland records a pronounced rise in rBC is observed from the 1880s to the 1910s, which is largely attributed to midlatitude coal burning emissions. The deposition of contaminants such as sulfate and lead increased on Devon ice cap in the 20th century but no concomitant rise in rBC is recorded in the ice. Part of the difference with Greenland could be due to local factors such as melt–freeze cycles on Devon ice cap that may limit the detection sensitivity of rBC analyses in melt-impacted core samples, and wind scouring of winter snow at the coring site. Air back-trajectory analyses also suggest that Devon ice cap receives BC from more distant North American and Eurasian sources than Greenland, and aerosol mixing and removal during long-range transport over the Arctic Ocean likely masks some of the specific BC source–receptor relationships. Findings from this study suggest that there could be a large variability in BC aerosol deposition across the Arctic region arising from different transport patterns. This variability needs to be accounted for when estimating the large-scale albedo lowering effect of BC deposition on Arctic snow/ice.

Peatlands occupy around 13% of the land cover of Canada, and thus play a key role in the water balance at high latitudes. They are well known for having substantial water loss due to evapotranspiration. Since measurements of evapotranspiration are scarce over these environments, hydrologists generally rely on models of varying complexity to evaluate these water exchanges in the global watershed balance. This study quantifies the water budget of a small boreal peatland-dominated watershed. We assess the performance of three evapotranspiration models in comparison with in situ observations and the impact of using these models in the hydrological modeling of the watershed. The study site (~1-km2) is located in the Eastern James Bay lowlands, Quebec, Canada. During summer 2012, an eddy flux tower measured evapotranspiration continuously, while a trapezoidal flume monitored streamflow at the watershed outlet. We estimated evapotranspiration with a combinational model (Penman), a radiation-based model (Priestle...

Abstract Low flow conditions are governed by short-to-medium term weather conditions or long term climate conditions. This prompts the question: given climate scenarios, is it possible to assess future extreme low flow conditions from climate data indices (CDIs)? Or should we rely on the conventional approach of using outputs of climate models as inputs to a hydrological model? Several CDIs were computed using 42 climate scenarios over the years 1961–2100 for two watersheds located in Quebec, Canada. The relationship between the CDIs and hydrological data indices (HDIs; 7- and 30-day low flows for two hydrological seasons) were examined through correlation analysis to identify the indices governing low flows. Results of the Mann-Kendall test, with a modification for autocorrelated data, clearly identified trends. A partial correlation analysis allowed attributing the observed trends in HDIs to trends in specific CDIs. Furthermore, results showed that, even during the spatial validation process, the methodological framework was able to assess trends in low flow series from: (i) trends in the effective drought index (EDI) computed from rainfall plus snowmelt minus PET amounts over ten to twelve months of the hydrological snow cover season or (ii) the cumulative difference between rainfall and potential evapotranspiration over five months of the snow free season. For 80% of the climate scenarios, trends in HDIs were successfully attributed to trends in CDIs. Overall, this paper introduces an efficient methodological framework to assess future trends in low flows given climate scenarios. The outcome may prove useful to municipalities concerned with source water management under changing climate conditions.

The Saint-Jean River (SRJ) in Eastern Canada is prone to the formation of very large rafts of wood. Managers of the SJR suspected these jams to influence salmon migration and carried out a dismantling operation to remove large wood accumulated in a 1.2 km long wood raft. This operation became a great opportunity to address key issues relating to large wood dynamics in a fluvial system: residence time and flood contribution to wood recruitment and transport. During the dismantling, we systematically sampled 319 trees from which year of death could be estimated from dendrochronology and year of accumulation in the raft could be obtained from satellite and aerial photos. These two dates allowed us to quantify the residence time for 262 datable large wood (LW) within the fluvial system, to examine the peak years of LW recruitment and to correlate the raft growth rate with hydrometeorological conditions since 1993. The results also emphasized four types of LW flood related to wood dynamics: 1) an erosive flood that produces a large amount of wood in river, 2) a mobilizing flood that carries large quantities of wood, 3) a flood mix that both recruits and transports large quantities of wood, and 4) an ice-breakup flood.

ABSTRACTTrends in indices based on daily temperature and precipitation are examined for two periods: 1948–2016 for all stations in Canada and 1900–2016 for stations in the south of Canada. These in...

Quantile estimates are generally interpreted in association with the return period concept in practical engineering. To do so with the peaks‐over‐threshold (POT) approach, combined Poisson‐generalized Pareto distributions (referred to as PD‐GPD model) must be considered. In this article, we evaluate the incorporation of non‐stationarity in the generalized Pareto distribution (GPD) and the Poisson distribution (PD) using, respectively, the smoothing‐based B‐spline functions and the logarithmic link function. Two models are proposed, a stationary PD combined to a non‐stationary GPD (referred to as PD0‐GPD1) and a combined non‐stationary PD and GPD (referred to as PD1‐GPD1). The teleconnections between hydro‐climatological variables and a number of large‐scale climate patterns allow using these climate indices as covariates in the development of non‐stationary extreme value models. The case study is made with daily precipitation amount time series from southeastern Canada and two climatic covariates, the Arctic Oscillation (AO) and the Pacific North American (PNA) indices. A comparison of PD0‐GPD1 and PD1‐GPD1 models showed that the incorporation of non‐stationarity in both POT models instead of solely in the GPD has an effect on the estimated quantiles. The use of the B‐spline function as link function between the GPD parameters and the considered climatic covariates provided flexible non‐stationary PD‐GPD models. Indeed, linear and nonlinear conditional quantiles are observed at various stations in the case study, opening an interesting perspective for further research on the physical mechanism behind these simple and complex interactions.

Phosphorus (P) mobilization in agricultural landscapes is regulated by both hydrologic (transport) and biogeochemical (supply) processes interacting within soils; however, the dominance of these controls can vary spatially and temporally. In this study, we analyzed a 5‐yr dataset of stormflow events across nine agricultural fields in the lower Great Lakes region of Ontario, Canada, to determine if edge‐of‐field surface runoff and tile drainage losses (total and dissolved reactive P) were limited by transport mechanisms or P supply. Field sites ranged from clay loam, silt loam, to sandy loam textures. Findings indicate that biogeochemical processes (P supply) were more important for tile drain P loading patterns (i.e., variable flow‐weighted mean concentrations ([ C f ]) across a range of flow regimes) relative to surface runoff, which trended toward a more chemostatic or transport‐limited response. At two sites with the same soil texture, higher tile [ C f ] and greater transport limitations were apparent at the site with higher soil available P (STP); however, STP did not significantly correlate with tile [ C f ] or P loading patterns across the nine sites. This may reflect that the fields were all within a narrow STP range and were not elevated in STP concentrations (Olsen‐P, ≤25 mg kg −1 ). For the study sites where STP was maintained at reasonable concentrations, hydrology was less of a driving factor for tile P loadings, and thus management strategies that limit P supply may be an effective way to reduce P losses from fields (e.g., timing of fertilizer application). Core Ideas We used metrics to evaluate controls on edge‐of‐field phosphorus losses. We examined a 5‐yr database of stormflow events (all seasons, including winter). Tile P runoff trended toward being more supply limited than surface runoff.

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.

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.