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Geohazards associated with the dynamics of the liquid and solid water of the Earth’s hydrosphere, such as floods and glacial processes, may pose significant risks to populations, activities and properties [...]

Compound dry-hot events enlarge homogenously due to teleconnected land-atmosphere feedbacks. , Using over a century of ground-based observations over the contiguous United States, we show that the frequency of compound dry and hot extremes has increased substantially in the past decades, with an alarming increase in very rare dry-hot extremes. Our results indicate that the area affected by concurrent extremes has also increased significantly. Further, we explore homogeneity (i.e., connectedness) of dry-hot extremes across space. We show that dry-hot extremes have homogeneously enlarged over the past 122 years, pointing to spatial propagation of extreme dryness and heat and increased probability of continental-scale compound extremes. Last, we show an interesting shift between the main driver of dry-hot extremes over time. While meteorological drought was the main driver of dry-hot events in the 1930s, the observed warming trend has become the dominant driver in recent decades. Our results provide a deeper understanding of spatiotemporal variation of compound dry-hot extremes.

UNDRR report published to mark the International Day for Disaster Risk Reduction on October 13, 2020, confirms how extreme weather events have come to dominate the disaster landscape in the 21st century.

Abstract As losses from extreme weather events grow, many governments are looking to privatize the financing and incentivization of climate adaptation through insurance markets. In a pure market approach to insurance for extreme weather events, individuals become responsible for ensuring they are adequately covered for risks to their own properties, and governments no longer contribute funds to post‐disaster recovery. Theoretically, insurance premiums signal the level of risk faced by each household, and incentivize homeowners to invest in adaptive action, such as retrofitting, or drainage work, to reduce premiums. Where risk is considered too high by insurance markets, housing is devalued, in theory leading to retreat from risky areas. In this review article, we evaluate the suitability of private insurance as a mechanism for climate adaptation at a household and community level. We find a mismatch between social understandings of responsibility for climate risks, and the technocratic, market‐based home insurance products offered by private insurance markets. We suggest that by constructing increasingly individualized, technical, and calculative evaluations of risk, market‐based models of insurance for extreme weather events erode the solidaristic and collective discourses and practices that support adaptive behavior. This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation

RÉSUMÉ: Les événements de submersion sont en augmentation sur les côtes du fleuve Saint-Laurent en raison des tempêtes, de la hausse du niveau marin et de la diminution de la glace de mer. À ce jour, le Québec ne possède pas de zonage de la submersion. Dans le cadre de cette thèse, une approche de cartographie de la submersion est développée en intégrant les vagues, les niveaux d'eau et la morphologie des plages de l'estuaire et du golfe du Saint-Laurent (EGSL). Deux types d'approches cartographiques ont été comparés : la simulation empirique qui projette un niveau total statique sur le territoire (niveau d'eau observé + effet des vagues sur la côte, le jet de rive ou runup), et le modèle numérique XBeach en mode surfbeat. Ces deux approches nécessitent une surface topo-bathymétrique précise et actualisée de la plage. Grâce au développement d'un réseau de suivi des plages par vidéo, nous évaluons dans un premier temps l'efficacité d'une méthode de topographie intertidale par vidéo par rapport à des levés LiDAR terrestres, et améliorons sa performance en intégrant les niveaux d'eau près de la plage au module d'élévation des lignes d'eau. Ce projet a permis la création de surfaces topographiques à précision centimétrique comparable au LiDAR et d'y extraire des paramètres morphologiques, comme la pente de la plage, nécessaire aux modèles empiriques de niveaux d'eau. La capacité des deux approches de cartographie à simuler la submersion du 6 décembre 2010 au Bas-Saint-Laurent a ensuite été analysée en comparant les surfaces inondées. La correspondance spatiale entre les simulations et les observations de submersion a été évaluée. Il en ressort que malgré la complexité du modèle XBeach et une légère surprédiction du modèle empirique (36%), les surfaces submergées obtenues par les deux approches sont similaires et correctement prédites à hauteur de 66-78%. Dans le cadre d'une troisième étude, XBeach a également été utilisé dans la baie des Chaleurs pour évaluer l'impact d'un événement extrême pour l'horizon 2100 sur l'aléa de submersion. Les simulations montrent que les débordements côtiers ont été engendrés par des vagues de relativement faible amplitude à la côte (Hs < 1 m) et que malgré des profondeurs d'eau avoisinant 1,2 m, des vitesses de courants élevées se sont produites dans les espaces urbanisés (U > 2 m/s). L'analyse de la cartographie de la submersion à Maria suggère qu'en 2100, l'impact de la hausse du niveau marin sur les communautés riveraines du Saint-Laurent pourrait provoquer des submersions plus vastes avec des profondeurs d'eau et vitesses de courants plus élevées, ce qui pourraient intensifier l'aléa auquel fait face la population. Même si les simulations numériques permettent de comprendre comment les phénomènes physiques engendrent la submersion, l'intérêt de la méthode statique réside dans sa rapidité d'application, mais son efficacité est fonction de la validité et l'applicabilité des modèles empiriques de runup utilisés. Ainsi, le dernier volet de la thèse porte sur le paramétrage d'un modèle empirique de runup adapté à l'EGSL. L'observation du runup (et de ses composantes moyenne et haute fréquence, le setup et le swash) par vidéo réalisée sur 5 plages couvre un large spectre de paramètres environnementaux et de types de côte sur une période de 3 ans. Des analyses de corrélation entre les niveaux d'eau à la côte et les caractéristiques de vagues au large et la pente de plage ont été réalisées. Les résultats montrent que l'influence des paramètres hydrodynamiques sur le runup, setup, et swash est paramétrée de façon similaire. Le rôle de la morphologie de la plage sur le setup est par ailleurs paramétré par une fonction inverse de la pente, alors que le swash est fonction de la racine carrée de la pente. Avec une erreur moyenne de 23 cm et un biais de 2 cm, l'équation de runup proposée offre un fort potentiel d'estimation des niveaux d'eau totaux sur les environnements côtiers diversifiés à fetch limité. Les résultats de la thèse montrent qu'il apparaît pertinent d'utiliser une approche statique p ur identifier les zones les plus vulnérables à la submersion, en autant que l'équation utilisée soit validée sur le type d'environnement en question. En combinant cette approche à des modélisations numériques en zones à forte concentration d'enjeux, il sera possible d'instaurer un premier zonage de la submersion au Québec. -- Mot(s) clé(s) en français : Cartographie de la submersion, Runup, Topographie par vidéo, Vagues infragravitaires, XBeach. -- ABSTRACT: Coastal flood events are increasing on the shores of the St. Lawrence River due to storms, rising sea levels and decreasing sea ice. To date, the province of Québec does not have a coastal flood mapping guideline. In this thesis, a coastal flood mapping approach is developed by integrating waves, water levels and beach morphology of the Estuary and Gulf of St. Lawrence (EGSL). Two types of cartographic approaches were compared: the empirical simulation that projects a static total level overland (observed water level + wave effect on the coast, known as wave runup), and the numerical model XBeach in surfbeat mode. These two approaches require a precise and updated topo-bathymetric surface of the beach. Through the development of a shore-based video monitoring network, we first evaluate the effectiveness of a video intertidal topography method against terrestrial LiDAR surveys, and improve its performance by integrating water levels near the beach as a proxy to beach contour elevetion. This project enabled the creation of centimeter-scale topographic surfaces comparable to LiDAR and the extraction of morphological parameters, such as the beach slope, necessary for empirical runup models. The ability of both mapping approaches to simulate the flood of December 6, 2010 in Bas-Saint-Laurent was analyzed by comparing flooded areas. Spatial correspondence between simulations and the observed flood extent was evaluated. Despite the complexity of XBeach and a slight over-prediction of the empirical model (36%), the flooded areas obtained by the two approaches are similar and correctly predicted by 66-78%. In a third study, XBeach was also used in the Chaleur Bay to assess the impact of an extreme event for the 2100 horizon on coastal flood hazards. The simulations show that the overland flow was generated by waves of relatively low amplitude at the coast (Hs <1 m) and that despite water depths close to 1.2 m, high current velocities occurred in the urbanized areas (U> 2 m/s). The analysis of the flood maps in Maria suggests that by 2100, the impact of sea level rise on coastal communities in the St. Lawrence could lead to larger flooded areas, with deeper water depths and higher flow velocity, intensifying the risk to the population. Although numerical simulations offer an understanding of the physical phenomena that cause coastal flooding, the interest of the static method lies in its convenience, but its effectiveness depends on the validity of the empirical runup models employed. Thus, the last part of the thesis deals with the parameterization of an empirical runup model in the EGSL. Video-based wave runup observations (and of its mean and high frequency components, setup and swash, respectively) on 5 beaches was carried out on a broad spectrum of environmental parameters and coast type over a period of 3 years. Correlation analyzes between coastal water levels (runup, setup, and swash) and offshore wave characteristics and beach slope were performed. The results show that the influence of the hydrodynamic parameters on wave runup, setup, and swash is similarly parameterized. The role of the morphology of the range on the setup is however parameterized by an inverse function of the slope, while the swash is a function of the square root of the slope. With an average error of 23 cm and a 2 cm bias, the original runup equation offers a high potential for estimating total water levels over diverse fetch-limited coastal environments. This thesis shows that it seems appropriate to use a static approach to identify the areas most vulnerable to coastal flooding, as long as the equation used is validated on the specific coastal environment. By combining this approach with numerical modeling in coastal hotspots with multiple issues at stake, it will be possible to introduce a first coasta flood zoning in the province of Québec. -- Mot(s) clé(s) en anglais : Coastal flooding, Runup, Video-derived topography, Infragravity waves, XBeach.

Abstract It is undeniable that coastal regions worldwide are facing unprecedented damages from catastrophic floods attributable to storm-tide (tidal) and extreme rainfall (pluvial). For flood-risk assessment, although recognizing compound impact of these drivers is a conventional practice, the marginal/individual impacts cannot be overlooked. In this letter, we propose a new measure, Tide-Rainfall Flood Quotient (TRFQ), to quantify the driver-specific flood potential of a coastal region arising from storm-tide or rainfall. A set of inundation and hazard maps are derived through a series of numerical and hydrodynamic flood model simulations comprising of design rainfall and design storm-tide. These experiments are demonstrated on three different geographically diverse flood-affected coastal regions in India. The new measure throws light on existing knowledge gaps on the propensity of coastal flooding induced by the marginal/individual contribution of storm-tide and rainfall. It shall prove useful in rationalizing long-term flood management strategies customizable for storm-tide and pluvial dominated global coastal regions.

Abstract Recent policy changes highlight the need for citizens to take adaptive actions to reduce flood‐related impacts. Here, we argue that these changes represent a wider behavioral turn in flood risk management (FRM). The behavioral turn is based on three fundamental assumptions: first, that the motivations of citizens to take adaptive actions can be well understood so that these motivations can be targeted in the practice of FRM; second, that private adaptive measures and actions are effective in reducing flood risk; and third, that individuals have the capacities to implement such measures. We assess the extent to which the assumptions can be supported by empirical evidence. We do this by engaging with three intellectual catchments. We turn to research by psychologists and other behavioral scientists which focus on the sociopsychological factors which influence individual motivations (Assumption 1). We engage with economists, engineers, and quantitative risk analysts who explore the extent to which individuals can reduce flood related impacts by quantifying the effectiveness and efficiency of household‐level adaptive measures (Assumption 2). We converse with human geographers and sociologists who explore the types of capacities households require to adapt to and cope with threatening events (Assumption 3). We believe that an investigation of the behavioral turn is important because if the outlined assumptions do not hold, there is a risk of creating and strengthening inequalities in FRM. Therefore, we outline the current intellectual and empirical knowledge as well as future research needs. Generally, we argue that more collaboration across intellectual catchments is needed, that future research should be more theoretically grounded and become methodologically more rigorous and at the same time focus more explicitly on the normative underpinnings of the behavioral turn. This article is categorized under: Engineering Water > Planning Water Human Water > Water Governance Science of Water > Water Extremes

Abstract Flood risk management decisions in many countries are based on decision‐support frameworks which rely on cost‐benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the distribution of risk reduction and apply it to support flood risk management decisions on a transboundary stretch of the Rhine River. Three types of interventions are considered: embankment heightening, making Room for the River, and changing the discharge distribution of the river branches. The analysis involves solving a flood risk management problem according to four alternative formulations, based on different ethical principles. Formulations based on cost optimization lead to very poor performances in some areas for the sake of reducing the overall aggregated costs. Formulations that also include equity criteria have different results depending on how these are defined. When risk reduction is distributed equally, very poor economic performance is achieved. When risk is distributed equally, results are in line with formulations based on cost optimization, while a fairer risk distribution is achieved. Risk reduction measures also differ, with the cost optimization approach strongly favoring the leverage of changing the discharge distribution and the alternative formulations spending more on embankment heightening and Room for the River, to rebalance inequalities in risk levels. The proposed method advances risk‐based decision‐making by allowing to consider risk distribution aspects and their impacts on the choice of risk reduction measures.

Abstract Change point detection methods have an important role in many hydrological and hydraulic studies of river basins. These methods are very useful to characterize changes in hydrological regimes and can, therefore, lead to better understanding changes in extreme flows behavior. Flood events are generally characterized by a finite number of characteristics that may not include the entire information available in a discharge time series. The aim of the current work is to present a new approach to detect changes in flood events based on a functional data analysis framework. The use of the functional approach allows taking into account the whole information contained in the discharge time series of flood events. The presented methodology is illustrated on a flood analysis case study, from the province of Quebec, Canada. Obtained results using the proposed approach are consistent with those obtained using a traditional change point method, and demonstrate the capability of the functional framework to simultaneously consider several flood features and, therefore, presenting a comprehensive way for a better exploitation of the information contained in a discharge time series.

Abstract The present study analyses the impacts of past and future climate change on extreme weather events for southern parts of Canada from 1981 to 2100. A set of precipitation and temperature‐based indices were computed using the downscaled Coupled Model Intercomparison Project Phase 5 (CMIP5) multi‐model ensemble projections at 8 km resolution over the 21st Century for two representative concentration pathway (RCP) scenarios: RCP4.5 and RCP8.5. The results show that this region is expected to experience stronger warming and a higher increase in precipitation extremes in future. Generally, projected changes in minimum temperature will be greater than changes in maximum temperature, as shown by respective indices. A decrease in frost days and an increase in warm nights will be expected. By 2100 there will be no cool nights and cool days. Daily minimum and maximum temperatures will increase by 12 and 7°C, respectively, under the RCP8.5 scenario, when compared with the reference period 1981–2000. The highest warming in minimum temperature and decrease in cool nights and days will occur in Ontario and Quebec provinces close to the Great Lakes and Hudson Bay. The highest warming in maximum temperature will occur in the southern parts of Alberta and Saskatchewan. Annual total precipitation is expected to increase by about 16% and the occurrence of heavy precipitation events by five days. The highest increase in annual total precipitation will occur in the northern parts of Ontario and Quebec and in western British Columbia.

Short-duration precipitation extremes are widely used in the design of engineering infrastructure systems and they also lead to high impact flash flood events and landslides. Better understanding of these events in a changing climate is therefore critical. This study assesses characteristics of short-duration precipitation extremes of 1-, 3-, 6- and 12-h durations in terms of the precipitation-temperature (P–T) relationship in current and future climates for ten Canadian climatic regions using the limited area version of the global environment multiscale (GEM) model. The GEM simulations, driven by ERA-Interim reanalysis and two coupled global climate models (CanESM2 and MPI-ESM), reproduce the general observed regional P–T relationship characteristics in current climate (1981–2010), such as sub-CC (Clausius–Clapeyron) and CC scalings for the coastal and northern, and inland regions, respectively, albeit with some underestimation. Analysis of the transient climate change simulations suggests important shifts and/or extensions of the P–T curve to higher temperature bins in future climate (2071–2100) for RCP4.5 and 8.5 scenarios, particularly for 1-h duration. Analysis of the spatial patterns of dew point depression (temperature minus dew point temperature) and convective available potential energy (CAPE) corresponding to short-duration precipitation extremes for different temperature bins show their changing relative importance from low to high temperature bins. For the low-temperature bins, short-duration precipitation extremes are largely due to high relative humidity, while for high-temperature bins, strong convection due to atmospheric instability brought by surface warming is largely responsible. The analysis thus addresses some of the key knowledge gaps related to the behavior of P–T relationship and associated mechanisms for the Canadian regions.

Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events.

Extreme events are widely studied across the world because of their major implications for many aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature extreme indices that are often not adapted for regions affected by floods caused by snowmelt. The rain on snow index has been widely used, but it neglects rain-only events which are expected to be more frequent in the future. In this study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls the past and future evolution of these events in the Great Lakes region. The future evolution of this index was projected using temperature and precipitation from the Canadian Regional Climate Model large ensemble (CRCM5-LE). These climate data were used as input in Precipitation Runoff Modelling System (PRMS) hydrological model to simulate the future evolution of high flows in three watersheds in southern Ontario. We also used five recurrent large-scale atmospheric circulation patterns in north-eastern North America and identified how they control the past and future variability of the newly created index and high flows. The results show that daily precipitation higher than 10&thinsp;mm and temperature higher than 5&thinsp;∘C were necessary historical conditions to produce high flows in these three watersheds. In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (HP regime) and the Atlantic Ocean (South regime). These hydrometeorological extreme events will still be associated with the same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal variability of the climate system, as higher Z500 on the east coast will amplify the increase in the number of events, especially the warm events. The relationship between the extreme weather index and high flows will be modified in the future as the snowpack reduces and rain becomes the main component of high-flow generation. This study shows the value of the CRCM5-LE dataset in simulating hydrometeorological extreme events in eastern Canada and better understanding the uncertainties associated with internal variability of climate.

Abstract During spring 2011, an extreme flood occurred along the Richelieu River located in southern Quebec, Canada. The Richelieu River is the last section of the complex Richelieu basin, which is composed of the large Lake Champlain located in a valley between two large mountains. Previous attempts in reproducing the Richelieu River flow relied on the use of simplified lumped models and showed mixed results. In order to prepare a tool to assess accurately the change of flood recurrences in the future, a state‐of‐the‐art distributed hydrological model was applied over the Richelieu basin. The model setup comprises several novel methods and data sets such as a very high resolution river network, a modern calibration technique considering the net basin supply of Lake Champlain, a new optimization algorithm, and the use of an up‐to‐date meteorological data set to force the model. The results show that the hydrological model is able to satisfactorily reproduce the multiyear mean annual hydrograph and the 2011 flow time series when compared with the observed river flow and an estimation of the Lake Champlain net basin supply. Many factors, such as the quality of the meteorological forcing data, that are affected by the low density of the station network, the steep terrain, and the lake storage effect challenged the simulation of the river flow. Overall, the satisfactory validation of the hydrological model allows to move to the next step, which consists in assessing the impacts of climate change on the recurrence of Richelieu River floods. , Plain Language Summary In order to study the 2011 Richelieu flood and prepare a tool capable of estimating the effects of climate change on the recurrence of floods, a hydrological model is applied over the Richelieu basin. The application of a distributed hydrological model is useful to simulate the flow of all the tributaries of the Richelieu basin. This new model setup stands out from past models due to its distribution in several hydrological units, its high‐resolution river network, the calibration technique, and the high‐resolution weather forcing data set used to drive the model. The model successfully reproduced the 2011 Richelieu River flood and the annual hydrograph. The simulation of the Richelieu flow was challenging due to the contrasted elevation of the Richelieu basin and the presence of the large Lake Champlain that acts as a reservoir and attenuates short‐term fluctuations. Overall, the application was deemed satisfactory, and the tool is ready to assess the impacts of climate change on the recurrence of Richelieu River floods. , Key Points An advanced high‐resolution distributed hydrological model is applied over a U.S.‐Canada transboundary basin The simulated net basin supply of Lake Champlain and the Richelieu River discharge are in good agreement with observations of the 2011 flood The flow simulation is challenging due to the topographic and meteorological complexities of the basin and uncertainties in the observations

Canada’s vast regions are reacting to climate change in uncertain ways. Understanding of local disaster risks and knowledge of underlying causes for negative impacts of disasters are critical factors to working toward a resilient environment across the social, economic, and the built sectors. Historically, floods have caused more economical and social damage around the world than other types of natural hazards. Since the 1900s, the most frequent hazards in Canada have been floods, wildfire, drought, and extreme cold, in terms of economic damage. The recent flood events in the Canadian provinces of Ontario, New Brunswick, Quebec, Alberta, and Manitoba have raised compelling concerns. These include should communities be educated with useful knowledge on hazard risk and resilience so they would be interested in the discussion on the vital role they can play in building resilience in their communities. Increasing awareness that perceived risk can be very different from the real threat is the motivation behind this study. The main objectives of this study include identifying and quantifying the gap between people’s perception of exposure and susceptibility to the risk and a lack of coping capacity and objective assessment of risk and resilience, as well as estimating an integrated measure of disaster resilience in a community. The proposed method has been applied to floods as an example, using actual data on the geomorphology of the study area, including terrain and low lying regions. It is hoped that the study will encourage a broader debate if a unified strategy for disaster resilience would be feasible and beneficial in Canada.