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Abstract. During the last decade, most European countries have produced hazard maps of natural hazards, but little is known about how to communicate these maps most efficiently to the public. In October 2011, Zurich's local authorities informed owners of buildings located in the urban flood hazard zone about potential flood damage, the probability of flood events and protection measures. The campaign was based on the assumptions that informing citizens increases their risk awareness and that citizens who are aware of risks are more likely to undertake actions to protect themselves and their property. This study is intended as a contribution to better understand the factors that influence flood risk preparedness, with a special focus on the effects of such a one-way risk communication strategy. We conducted a standardized mail survey of 1500 property owners in the hazard zones in Zurich (response rate main survey: 34 %). The questionnaire included items to measure respondents' risk awareness, risk preparedness, flood experience, information-seeking behaviour, knowledge about flood risk, evaluation of the information material, risk acceptance, attachment to the property and trust in local authorities. Data about the type of property and socio-demographic variables were also collected. Multivariate data analysis revealed that the average level of risk awareness and preparedness was low, but the results confirmed that the campaign had a statistically significant effect on the level of preparedness. The main influencing factors on the intention to prepare for a flood were the extent to which respondents evaluated the information material positively as well as their risk awareness. Respondents who had never taken any previous interest in floods were less likely to read the material. For future campaigns, we therefore recommend repeated communication that is tailored to the information needs of the target population.
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Analyse des variables associées aux comportements préventifs à l'inondation, Hountondji, Lionel, 2023, Université Laval. Copyright by the author unless stated otherwise.
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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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Abstract. One of the key priorities for disaster risk reduction is to ensure decision makers, stakeholders, and the public understand their exposure to disaster risk, so that they can take protective action. Flood maps are a potentially valuable tool for facilitating this understanding of flood risk, but previous research has found that they vary considerably in availability and quality. Using an evaluation framework comprising nine criteria grounded in existing scholarship, this study assessed the quality of flood maps available to the public in Canadian communities located in designated flood risk areas. It found that flood maps in most municipalities (62 %) are low quality (meeting less than 50 % of the criteria) and the highest score was 78 % (seven of nine criteria met). The findings suggest that a more concerted effort to produce high-quality, publicly accessible flood maps is required to support Canada's international commitment to disaster risk reduction. Further questions surround possible weighting of quality assessment criteria, whether and how individuals seek out flood maps, and how flood risk information could be better communicated using modern technology.
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Snow avalanches are a major natural hazard for road users and infrastructure in northern Gaspesie. Over the past 11 years, the occurrence of nearly 500 snow avalanches on the two major roads servicing the area was reported. No management program is currently operational. In this study, we analyze the weather patterns promoting snow avalanche initiation and use logistic regression (LR) to calculate the probability of avalanche occurrence on a daily basis. We then test the best LR models over the 2012–2013 season in an operational forecasting perspective: Each day, the probability of occurrence (0–100%) determined by the model was classified into five classes avalanche danger scale. Our results show that avalanche occurrence along the coast is best predicted by 2 days of accrued snowfall [in water equivalent (WE)], daily rainfall, and wind speed. In the valley, the most significant predictive variables are 3 days of accrued snowfall (WE), daily rainfall, and the preceding 2 days of thermal amplitude. The large scree slopes located along the coast and exposed to strong winds tend to be more reactive to direct snow accumulation than the inner-valley slopes. Therefore, the probability of avalanche occurrence increases rapidly during a snowfall. The slopes located in the valley are less responsive to snow loading. The LR models developed prove to be an efficient tool to forecast days with high levels of snow avalanche activity. Finally, we discuss how road maintenance managers can use this forecasting tool to improve decision making and risk rendering on a daily basis.
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Abstract. In response to the EU Floods Directive (2007/60/EC), flood hazard maps are currently produced all over Europe, reflecting a wider shift in focus from "flood protection" to "risk management", for which not only public authorities but also populations at risk are seen as responsible. By providing a visual image of the foreseen consequences of flooding, flood hazard maps can enhance people's knowledge about flood risk, making them more capable of an adequate response. Current literature, however, questions the maps' awareness raising capacity, arguing that their content and design are rarely adjusted to laypeople's needs. This paper wants to complement this perspective with a focus on risk communication by studying how these tools are disseminated and marketed to the public in the first place. Judging from communication theory, simply making hazard maps publicly available is unlikely to lead to attitudinal or behavioral effects, since this typically requires two-way communication and material or symbolic incentives. Consequently, it is relevant to investigate whether and how local risk managers, who are well positioned to interact with the local population, make use of flood hazard maps for risk communication purposes. A qualitative case study of this issue in the German state of Baden-Württemberg suggests that many municipalities lack a clear strategy for using this new information tool for hazard and risk communication. Four barriers in this regard are identified: perceived disinterest/sufficient awareness on behalf of the population at risk; unwillingness to cause worry or distress; lack of skills and resources; and insufficient support. These barriers are important to address – in research as well as in practice – since it is only if flood hazard maps are used to enhance local knowledge resources that they can be expected to contribute to social capacity building.
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Flood hazards are the most common and destructive of all natural disasters. For decades, experts have been examining how flood losses can be mitigated. Just as in other risk domains, the study of risk perception and risk communication has gained increasing interest in flood risk management. Because of this research growth, a review of the state of the art in this domain is believed necessary. The review comprises 57 empirically based peer‐reviewed articles on flood risk perception and communication from the Web of Science and Scopus databases. The characteristics of these articles are listed in a comprehensive table, presenting research design, research variables, and key findings. From this review, it follows that the majority of studies are of exploratory nature and have not applied any of the theoretical frameworks that are available in social science research. Consequently, a methodological standardization in measuring and analyzing people's flood risk perceptions and their adaptive behaviors is hardly present. This heterogeneity leads to difficulties in comparing results among studies. It is also shown that theoretical and empirical studies on flood risk communication are nearly nonexistent. The article concludes with a summary on methodological issues in the fields of flood‐risk perception and flood‐risk communication and proposes an agenda for future research.
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Abstract Ephemeral ponds (EPs) are seasonally flooded isolated wetlands that provide a variety of hydroecological benefits, including the provision of breeding habitat for several amphibian and invertebrate species. However, the lack of their explicit representation in hydrological models limits a comprehensive understanding of their interaction with surrounding landscapes and their vulnerability in the context of human interventions and climate change. The purpose of this research was to improve the isolated wetland module of the Soil Water Assessment Tool (SWAT) to better represent EP hydrology. The changes include (1) representation of groundwater and hypodermic flow as the only inflows from the pond drainage surface, due to the intermittent and negligible presence of inflow from surface runoff in forested ponds, (2) revision of how evapotranspiration within EPs is represented and (3) implementation of distinct volume‐area‐depth relationships for ponds based on their geometrical shape. The accuracy of these improvements was assessed against that of a previous isolated wetland formulation in replicating water depth observations of 10 EPs of a portion of the Kenauk forest (68 km 2 ) in the Canadian Shield of the Outaouais region (Québec, Canada). The comparison results show that the revised SWAT model presented here significantly improves the distinct filling and drying water cycle of EPs (average root mean square error of 0.1 m of the revised model vs. 0.23 m for the original model). Besides, the new module allowed to identify that hypodermic flow, evapotranspiration and seepage to the underlying soil are the main EP source and sinks. The new module also allowed to explicitly quantify the differences in filling/drying pattern of the EPs of the Kenauk forest and unlike the original model structure, the new module was able to closely replicate the interannual variation of spring and annual hydroperiod duration.
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Purpose Driven by the New Urban Agenda and the Sustainable Development Goals, decision makers have been striving to reorientate policy debates towards the aspiration of achieving urban resilience and monitoring the effectiveness of adaptive measures through the implementation of standardised indicators. Consequently, there has been a rise of indicator systems measuring resilience. This paper aims to argue that the ambition of making cities resilient does not always make them less vulnerable, more habitable, equitable and just. Design/methodology/approach Using an inductive policy analysis of ISO standard 37123:2019 “Sustainable cities and communities — Indicators for resilient cities”, the authors examine the extent to which the root causes of risks are being addressed by the urban resilience agenda. Findings The authors show that the current standardisation of resilience fails to adequately address the political dimension of disaster risk reduction, reducing resilience to a management tool and missing the opportunity to address the socio-political sources of risks. Originality/value Such critical analysis of the Standard is important as it moves away from a hazard-centric approach and, instead, permits to shed light on the socio-political processes of risk creation and to adopt a more nuanced and sensitive understanding of urban characteristics and governance mechanisms.
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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.