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Abstract. Real time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. Those points often coincide with gauging stations, and the forecasts can eventually be compared with the corresponding observations for post-event analysis. We are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system, by feeding the forecasted streamflow to a hydraulics model. While this additional new information (flood extent, depth, velocity, etc.) can potentially be useful for decision makers, it also has the potential to be overwhelming. This is especially true for probabilistic and ensemble forecasting systems. While ensemble streamflow forecasts for a given point in space can be visualized relatively easily, the visualization and communication of probabilistic forecasts for water depth and extent brings additional challenges. The uncertainty becomes three dimensional and it becomes difficult to convey all the important information to support decision-making, while a confusion that could arise from too much information, counter-intuitive interpretation, or simply too much complexity in the representation of the forecast. In this paper, we synthesize the results of a large-scale survey across multiple categories of users of hydrological forecasts (28 government representatives, 52 municipalities, 9 organizations, 37 citizens and farmers, for a total of 139 persons) regarding their preferences in terms of visualizing probabilistic flood forecasts over an entire river reach. Those users have different roles and realities, which influence their needs and preferences. The survey was performed through individual and group interviews during which the interviewees were asked about their needs in terms of hydrological forecasting and their preferences in terms of communication and visualization of the information. In particular, we presented the interviewees with four prototypes representing alternative visualizations of the same probabilistic forecast in order to understand their preferences in terms of colour maps, wording, and the representation of uncertainty. Our results highlight several issues related to the understanding of probabilities in the specific context of visualizing forecasted flood maps. We propose several suggestions for visualizing probabilistic flood maps in order to convey all the relevant information while limiting the confusion of decision makers, and also describe several potential adaptations for different categories of end users.
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Granular dynamics driven by fluid flow is ubiquitous in many industrial and natural processes, such as fluvial and coastal sediment transport. Yet, their complex multiphysics nature challenges the accuracy and efficiency of numerical models. Here, we study the dynamics of rapid fluid-driven granular erosion through a mesh-free particle method based on the enhanced weakly-compressible Moving Particle Semi-implicit (MPS) method. To that end, we develop and validate a new multi-resolution multiphase MPS formulation for the consistent and conservative form of the governing equations, including particle stabilization techniques. First, we discuss the numerical accuracy and convergence of the proposed approximation operators through two numerical benchmark cases: the multi-viscosity Poiseuille flow and the multi-density hydrostatic pressure. Then, coupling the developed model with a generalized rheology equation, we investigate the water dam-break waves over movable beds. The particle convergence study confirms that the proposed multi-resolution formulation predicts the analytical solutions with acceptable accuracy and order of convergence. Validating the multiphase granular flow reveals that the mechanical behavior of this fluid-driven problem is highly sensitive to the water-sediment density ratio; the bed with lighter grains experiences extreme erosion and interface deformations. For the bed with a heavier material but different geometrical setups, the surge speed and the transport layer thickness remain almost identical (away from the gate). Furthermore, while the multi-resolution model accurately estimates the global sediment dynamics, the single-resolution model underestimates the flow evolution. Overall, the qualitative and quantitative analysis of results emphasizes the importance of multi-scale multi-density interactions in fluid-driven modeling.
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Despite being recognized as a key component of shallow-water ecosystems, submerged aquatic vegetation (SAV) remains difficult to monitor over large spatial scales. Because of SAV’s structuring capabilities, high-resolution monitoring of submerged landscapes could generate highly valuable ecological data. Until now, high-resolution remote sensing of SAV has been largely limited to applications within costly image analysis software. In this paper, we propose an example of an adaptable open-sourced object-based image analysis (OBIA) workflow to generate SAV cover maps in complex aquatic environments. Using the R software, QGIS and Orfeo Toolbox, we apply radiometric calibration, atmospheric correction, a de-striping correction, and a hierarchical iterative OBIA random forest classification to generate SAV cover maps based on raw DigitalGlobe multispectral imagery. The workflow is applied to images taken over two spatially complex fluvial lakes in Quebec, Canada, using Quickbird-02 and Worldview-03 satellites. Classification performance based on training sets reveals conservative SAV cover estimates with less than 10% error across all classes except for lower SAV growth forms in the most turbid waters. In light of these results, we conclude that it is possible to monitor SAV distribution using high-resolution remote sensing within an open-sourced environment with a flexible and functional workflow.
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Au Québec, chaque année, les inondations printanières présentent un défi majeur pour les autorités québécoises. Ainsi, l'élaboration de nouveaux outils et de nouvelles méthodes pour diffuser et visualiser des données massives spatiotemporelles 3D dynamiques d'inondation est très important afin de mieux comprendre et gérer les risques reliés aux inondations. Cette recherche s'intéresse à la diffusion de données géospatiales massives 3D (modèles de bâtiments 3D, arbres, modèles numériques d'élévation de terrain (MNE), données LiDAR, imageries aériennes, etc.) en relation avec les inondations. Le problème est qu'il n'existe pas, à travers la littérature, des systèmes de diffusion efficaces des données massives 3D adaptées aux besoins de cette recherche. En ce sens, notre objectif général consiste à développer un outil de diffusion des données géospatiales massives 3D qui sont des bâtiments 3D et des modèles de terrains de haute résolution à l'échelle de la province du Québec. Les défis de diffusion du flux de données massives, nous ramènent à considérer la technique de tuilage 3D pour convertir les données brutes en formats et structures vectoriels plus légers et adaptés à la diffusion comme la spécification "3D Tiles" pour tuiler les bâtiments 3D, les nuages de points LiDAR et d'autres modèles géoréférencés 3D et le maillage irrégulier, notamment les TIN, pour tuiler les modèles numériques de terrain. Aussi, l'utilisation des techniques de traitement parallèle permet de gérer efficacement les flux massifs de données et d'améliorer le temps de traitement permettant ainsi la scalabilité et la flexibilité des systèmes existants. A cet effet, deux pipelines de tuilage ont été développés. Le premier pipeline concerne la création des tuiles de bâtiments 3D selon la spécification "3D Tiles". Le deuxième est pour créer des tuiles de terrain basées sur des maillages irréguliers. Ces pipelines sont ensuite intégrés dans un système de traitement distribué basé sur des conteneurs Docker afin de paralléliser les processus de traitements. Afin de tester l'efficacité et la validité du système développé, nous avons testé ce système sur un jeux de données massif d'environ 2.5 millions bâtiments 3D situés au Québec. Ces expérimentations ont permis de valider et de mesurer l'efficacité du système proposé par rapport à sa capacité de se mettre à l'échelle (Scalabilité) pour prendre en charge, efficacement, les flux massifs de données 3D. Ces expérimentations ont aussi permis de mettre en place des démarches d'optimisation permettant une meilleure performance dans la production et la diffusion des tuiles 3D.
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Les politiques québécoises de prévention des risques liés aux inondations ont été sujettes à débat ces dernières années, avec une remise en cause du modèle centralisé et uniforme à travers le Québec, pour une approche plus intégrée. Celle-ci fait notamment la promotion de mesures axées sur la vulnérabilité et d’une participation plus active des acteurs territoriaux. On en sait toutefois très peu sur les déclinaisons locales de l’approche intégrée dans le contexte québécois. Ce mémoire propose d’interroger les différentes approches locales de la prévention et de soulever les enjeux qu’elles posent du point de vue des autorités qui y participent. L’étude se penche sur le cas des territoires concernés par les inondations du lac des Deux Montagnes (Région hydrographique de l'Outaouais et de Montréal). Le cadre d’analyse met de l’avant l’approche des instruments d’action publique pour comprendre leur appropriation par les acteurs locaux et une approche pragmatique qui consiste à centrer notre regard sur les pratiques et les stratégies de réduction des risques d’inondation. La recherche s’appuie sur trois sources de données : une analyse documentaire des régimes provinciaux de régulation des risques d’inondation, un recensement des pratiques de prévention déployées par les autorités locales concernées par les inondations du lac des Deux Montagnes et une série de 15 entretiens réalisés avec les personnes travaillant au sein de ces différentes autorités. Le cas illustre la difficulté et le faible engagement de prévenir les risques autrement que par l’approche de réduction de l’exposition aux risques imposée par la Politique de protection des rives, du littoral et des plaines inondables (PPRLPI). Toutefois, après les inondations de 2017 et de 2019, des approches alternatives propres aux contextes territoriaux ont été envisagées par différentes organisations. Celles-ci devraient davantage être documentées et mises en débat afin d’envisager un régime provincial de la gestion des risques plus flexible et ouvert à leur coexistence. <br /><br /> Uniformed and centralized model of Quebec's flood prevention policies have been recently debated. Integrated approach to flood risk prevention is now put forward, which focus more on vulnerability and foster an active participation of local authorities. Local declinations of the approach are relatively unknown in Quebec. This study presents different local approaches to flood risk prevention and raise issues they pose from the perspective of local authorities involved. It is based on the authority’s concerns by Lac des Deux Montagnes flooding (Outaouais and Montreal hydrographic region). Combining a political sociology approach to policy instruments and a pragmatic approach, we focus on risk regulation regimes, practices and risk reduction strategies. Three sources of data were used: an analysis of flood risk regulation regimes, an inventory of prevention practices deployed by local authorities and 15 interviews conducted with professionals among these authorities. Results show the difficulty and low commitment to implement local distinct approaches apart from prohibiting and discouraging exposure to flood risk enforced by the Protection Policy for Lakeshores, Riverbanks, Littoral Zones and Floodplains. However, after the floods of 2017 and 2019, alternative strategies specific to different territorial contexts were considered. These should be better documented and debated in order to consider a more flexible and coexistence provincial policy.
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The increasing severity and frequency of disasters across the USA is revealing a landscape that is not entirely prepared to cope with these exposures. Resilience as a socio-ecological concept has become progressively more important as a means of assessing and mitigating these losses. Technological advances and planning have improved many outcomes, but all populations have not experienced the benefits. In this paper, we focus on the shortcomings of current resilience measures in capturing neighborhood disparities. Much like vulnerability and sustainability, local disparities will have a deleterious impact on the community as a whole. We use the Baseline Resilience Indicators for Communities (BRIC) framework and downscale the index using neighborhood-level Census data (tracts) and variations in household access to community resources. These added variables represent the variation of resilience indicators across a community and capture cross-scale relationships that exist between county and Census tract characteristics. We apply scaled variables in the Pensacola Bay Watershed to demonstrate cross-scaled interactions in the Florida panhandle. Potential modifications and applications of the concepts are also discussed.
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Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA's 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.
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During the last several decades, numerous researchers have provided evidence that physical and biogeochemical processes at air-snow/ice-water interfaces are very complex, and, in many cases, interlinked. , During the last several decades, numerous researchers have provided evidence that physical and biogeochemical processes at air-snow/ice-water interfaces are very complex, and, in many cases, interlinked. This review focuses on the current state of knowledge regarding snow-borne particles. It integrates snow science from different angles: from the formation of snow and precipitation to transformations through natural and anthropogenic processes and impacts and snow management in urban areas sites. We discuss the physical, chemical, and biological characteristics of particles in snow, such as their composition, abundance, size distribution, ice nucleation properties, genomic features, and microphysical processes, in urban settings, remote areas of the Arctic, and remote industrial regions (oil sands). We explore physicochemical processes of snow particles: from microbial to emerging contaminants, like nano/microplastics, light-absorbing carbonaceous organics, halogenated and nanometals particles. We review the possible contributions of snow particles to atmospheric radiation and climate, biogeochemistry, human health, and urban snow management. We propose further research directions to improve understanding of air-snow feedback, and sustainable snow management in urban areas, in the age of emerging contaminants in a changing climate.
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<sec><title>Background</title><p>Youth are increasingly aware of the negative effects of climate change on the planet and human health, but this knowledge can often come with significant affective responses, such as psychological distress, anger, or despair. Experiencing major “negative” emotions, like worry, guilt, and hopelessness in anticipation of climate change has been identified with the term eco-anxiety. Emerging literature focuses on adults' experience; however, little is known about the ways in which children and youth experience eco-anxiety.</p></sec><sec><title>Objectives</title><p>The aim of this review was to: (1) identify the available evidence on the topic of eco-anxiety in children, (2) clarify the mental health consequences brought by the awareness of climate change in this population, and (3) identify knowledge gaps in the literature and considerations for future research.</p></sec><sec><title>Methods</title><p>Given that the research on the topic of eco-anxiety in children is limited, that there are very few randomized controlled trials, and that the goal is not to analyze individual studies in-depth, a scoping review was used. Keywords pertaining to the themes of eco-anxiety, climate change and children (aged < 18 years) were used as search terms in five databases. Journal articles using qualitative and quantitative methods, as well as gray literature were examined by two independent reviewers. A descriptive-analytical method was used to chart the data that emerged from the literature. Eighteen articles were considered in the final analysis.</p></sec><sec><title>Results</title><p>Evidence confirms that children experience affective responses and eco-anxiety in reaction to then awareness of climate change. Mental health outcomes include depression, anxiety, and extreme emotions like sadness, anger, and fear. Youth from vulnerable communities, like indigenous communities, or those who have strong ties to the land are often identified as being emotionally impacted by climate change. The literature analyzed also describes how children and youth are coping with eco-anxiety, including maladaptive (e.g., denial) and adaptive responses (such as constructive hope, used as a positive coping mechanism). Preliminary considerations for parents, teachers and educators, mental health care providers, school systems, adults and people of power include adding age-appropriate climate education to the school curriculum, considering youth's emotions, and promoting healthy coping through empowerment. Important gaps exist in the definition of eco-anxiety in youth, as various characterizations of this emerging concept are found across articles.</p></sec>
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Introduction The COVID-19 pandemic and associated restrictive measures have caused important disruptions in economies and labour markets, changed the way we work and socialise, forced schools to close and healthcare and social services to reorganise. This unprecedented crisis forces individuals to make considerable efforts to adapt and will have psychological and social consequences, mainly on vulnerable individuals, that will remain once the pandemic is contained and will most likely exacerbate existing social and gender health inequalities. This crisis also puts a toll on the capacity of our healthcare and social services structures to provide timely and adequate care. The MAVIPAN (Ma vie et la pandémie/ My Life and the Pandemic) study aims to document how individuals, families, healthcare workers and health organisations are affected by the pandemic and how they adapt. Methods and analysis MAVIPAN is a 5-year longitudinal prospective cohort study launched in April 2020 across the province of Quebec (Canada). Quantitative data will be collected through online questionnaires (4–6 times/year) according to the evolution of the pandemic. Qualitative data will be collected with individual and group interviews and will seek to deepen our understanding of coping strategies. Analysis will be conducted under a mixed-method umbrella, with both sequential and simultaneous analyses of quantitative and qualitative data. Ethics and dissemination MAVIPAN aims to support the healthcare and social services system response by providing high-quality, real-time information needed to identify those who are most affected by the pandemic and by guiding public health authorities’ decision making regarding intervention and resource allocation to mitigate these impacts. MAVIPAN was approved by the Ethics Committees of the Primary Care and Population Health Research Sector of CIUSSS de la Capitale-Nationale (Committee of record) and of the additional participating institutions. Trial registration number NCT04575571.
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With the advent of the COVID-19 pandemic, in-person social interactions and opportunities for accessing resources that sustain health and well-being have drastically reduced. We therefore designed the pan-Canadian population-based prospective COVID-19: HEalth and Social Inequities across Neighbourhoods (COHESION) cohort to provide deeper understanding of how the COVID-19 pandemic context affects mental health and well-being, key determinants of health, and health inequities. This paper presents the design of the two-phase COHESION Study, and descriptive results from the first phase conducted between May 2020 and September 2021. During that period, the COHESION research platform collected monthly data linked to COVID-19 such as infection and vaccination status, perceptions and attitudes regarding pandemic-related measures, and information on participants’ physical and mental health, well-being, sleep, loneliness, resilience, substances use, living conditions, social interactions, activities, and mobility. The 1,268 people enrolled in the Phase 1 COHESION Study are for the most part from Ontario (47%) and Quebec (33%), aged 48 ± 16 years [mean ± standard deviation (SD)], and mainly women (78%), White (85%), with a university degree (63%), and living in large urban centers (70%). According to the 298 ± 68 (mean ± SD) prospective questionnaires completed each month in average, the first year of follow-up reveals significant temporal variations in standardized indexes of well-being, loneliness, anxiety, depression, and psychological distress. The COHESION Study will allow identifying trajectories of mental health and well-being while investigating their determinants and how these may vary by subgroup, over time, and across different provinces in Canada, in the unique context of the COVID-19 pandemic.
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Abstract Background Evidence continues to demonstrate that certain marginalised populations are disproportionately affected by COVID-19. While many studies document the impacts of COVID-19 on social inequalities in health, none has examined how public health responses to the pandemic have unfolded to address these inequities in Canada. The purpose of our study was to assess how social inequalities in health were considered in the design and planning of large-scale COVID-19 testing programs in Montréal (Québec, Canada). Methods Part of the multicountry study HoSPiCOVID, this article reports on a qualitative case study of large-scale testing for COVID-19 in Montréal. We conducted semi-structured interviews with 19 stakeholders involved in planning large-scale testing or working with vulnerable populations during the pandemic. We developed interview guides and a codebook using existing literature on policy design and planning, and analysed data deductively and inductively using thematic analysis in NVivo. Results Our findings suggest that large-scale COVID-19 testing in Montréal did not initially consider social inequalities in health in its design and planning phases. Considering the sense of urgency brought by the pandemic, participants noted the challenges linked to the uptake of an intersectoral approach and of a unified vision of social inequalities in health. However, adaptations were gradually made to large-scale testing to improve its accessibility, acceptability, and availability. Actors from the community sector, among others, played an important role in supporting the health sector to address the needs of specific subgroups of the population. Conclusions These findings contribute to the reflections on the lessons learned from COVID-19, highlighting that public health programs must tackle structural barriers to accessing healthcare services during health crises. This will be necessary to ensure that pandemic preparedness and response, including large-scale testing, do not further increase social inequalities in health.