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How decentralized government structure influences public service delivery has been a major focus of debate in the public finance literature. In this paper, we empirically examine the effect of fiscal decentralization on natural disaster damages across the U.S. states. We construct a unique measure of decentralization using state and local government expenditures on natural resources, which include investment in flood control and mitigation measures, among others. Using state‐level panel data from 1982 to 2011, we find that states that are more decentralized in natural resource expenditures have experienced more economic losses from floods and storms. This effect is only pronounced in states that are at higher risks of flooding. Our findings suggest that fiscal decentralization may lead to inefficient protection against natural disasters and provide implications for the assignment of disaster management responsibilities across different levels of government in the U.S. federal system.
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The effects of wetlands on stream flows are well established, namely mitigating flow regimes through water storage and slow water release. However, their effectiveness in reducing flood peaks and sustaining low flows is mainly driven by climate conditions and wetland type with respect to their connectivity to the hydrographic network (i.e. isolated or riparian wetlands). While some studies have demonstrated these hydrological functions/services, few of them have focused on the benefits to the hydrological regimes and their evolution under climate change (CC) and, thus, some gaps persist. The objective of this study was to further advance our knowledge with that respect. The PHYSITEL/HYDROTEL modelling platform was used to assess current and future states of watershed hydrology of the Becancour and Yamaska watersheds, Quebec, Canada. Simulation results showed that CC will induce similar changes on mean seasonal flows, namely larger and earlier spring flows leading to decreases in summer and fall flows. These expected changes will have different effects on 20-year and 100-year peak flows with respect to the considered watershed. Nevertheless, conservation of current wetland states should: (i) for the Becancour watershed, mitigate the potential increase in 2-year, 20-year and 100-year peak flows; and (ii) for the Yamaska watershed, accentuate the potential decrease in the aforementioned indicators. However, any loss of existing wetlands would be detrimental for 7-day 2-year and 10-year as well as 30-day 5-year low flows.
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This chapter presents current knowledge of observed and projected impacts from extreme weather events, based on recorded events and their losses, as well as studies that project future impacts from anthropogenic climate change. The attribution of past changes in such impacts focuses on the three key drivers: changes in extreme weather hazards that can be due to natural climate variability and anthropogenic climate change, changes in exposure and vulnerability, and risk reduction efforts. The chapter builds on previous assessments of attribution of extreme weather events, to drivers of changes in weather hazard, exposure and vulnerability. Most records of losses from extreme weather consist of information on monetary losses, while several other types of impacts are underrepresented, complicating the assessment of losses and damages. Studies into drivers of losses from extreme weather show that increasing exposure is the most important driver through increasing population and capital assets. Residual losses (after risk reduction and adaptation) from extreme weather have not yet been attributed to anthropogenic climate change. For the Loss and Damage debate, this implies that overall it will remain difficult to attribute this type of losses to greenhouse gas emissions. For the future, anthropogenic climate change is projected to become more important for driving future weather losses upward. However, drivers of exposure and especially changes in vulnerability will interplay. Exposure will continue to lead to risk increases. Vulnerability on the other hand may be further reduced through disaster risk reduction and adaptation. This would reduce additional losses and damages from extreme weather. Yet, at the country scale and particularly in developing countries, there is ample evidence of increasing risk, which calls for significant improvement in climate risk management efforts.
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Right after a devastating multi-year drought, a number of flood events with unprecedented spatial extent hit different parts of Iran over the 2-week period of March 17th to April 1st, 2019, causing a human disaster and substantial loss of assets and infrastructure across urban and rural areas. Here, we investigate natural (e.g., rainfall, snow accumulation/melt, soil moisture) and anthropogenic drivers (e.g., deforestation, urbanization, and management practices) of these events using a range of ground-based data and satellite observations. These drivers can range from exceptionally extreme rainfall intensities, to cascades of several extreme and moderate events, and various anthropogenic interventions that exacerbated flooding. Our results reveal strong compounding impacts of natural drivers and anthropogenic triggers in escalating flood risks to unprecedented levels. We argue that a new form of floods, i.e. anthropogenic floods, is becoming more common and should be recognized during the “Anthropocene”. This specific form of floods refers to high to extreme streamflow/runoff events that are primarily caused, or largely exacerbated, by anthropogenic drivers. We demonstrate how the growing risk of anthropogenic floods can be assessed using a wide range of climatic and non-climatic satellite and in-situ data.
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Abstract The estimation of the Intensity–Duration–Frequency (IDF) relation is often necessary for the planning and design of various hydraulic structures and design storms. It has been an increasingly greater challenge due to climate change conditions. This paper therefore proposes an integrated extreme rainfall modeling software package (SDExtreme) for constructing the IDF relations at a local site in the context of climate change. The proposed tool is based on a temporal downscaling method to describe the relationships between daily and sub-daily extreme precipitation using the scale-invariance General Extreme Value (GEV) distribution. In addition, SDExtreme provides a modified bootstrap technique to determine confidence intervals (CIs) of the estimated IDF curves for current and the future climate conditions. The feasibility and accuracy of SDExtreme were assessed using rainfall data available from the selected rain gauge stations in Quebec and Ontario provinces (Canada) and climate simulations under three different climate change scenarios provided by the Canadian Earth System Model (CanESM2) and the Canadian Regional Climate Model (CanRCM4).
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Abstract By using risk-adjusted price signals to transfer responsibility for property-level flood protection and recovery from governments to property owners, flood insurance represents a key tenet of the flood risk management (FRM) paradigm. The Government of Canada has worked with insurers to introduce flood insurance for the first time as a part of a broader shift towards FRM to limit the growing costs of flooding. The viability of flood insurance in Canada, however, has been questioned by research that disputes the utility of purchasing coverage by property owners. This study tested this assumption by drawing on public opinion survey data to assess factors that influence decisions about the utility of insurance. The findings reveal that Canadians have limited knowledge of flood insurance coverage, exhibit a low willingness-to-pay for both insurance and property-level flood protection measures, and expect governments to shoulder much of the financial burden of flood recovery through disaster assistance.
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Intensity Duration Frequency (IDF) curves are among the most common tools used in water resources management. They are derived from historical rainfall records under the assumption of stationarity. Change of climatic conditions makes the use of historical data for development of IDFs for the future unjustifiable. The IDF_CC, a web based tool, is designed, developed and implemented to allow local water professionals to quickly develop estimates related to the impact of climate change on IDF curves for almost any local rain monitoring station in Canada. The primary objective of the presented work was to standardize the IDF update process and make the results of current research on climate change impacts on IDF curves accessible to everyone. The tool is developed in the form of a decision support system (DSS) and represents an important step in increasing the capacity of Canadian water professionals to respond to the impacts of climate change. Climate change impact on IDF curves investigated.Standardized IDF update process.Two theoretical contributions incorporated: downscaling method and skill score computation method.Web based tool developed and implemented for updating IDF curves under climate change.
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In recent years, geospatial data (e.g. remote sensing imagery), and other relevant ancillary datasets (e.g. land use land cover, climate conditions) have been utilized through sophisticated algorithms to produce global population datasets. With a handful of such datasets, their performances and skill in flood exposure assessment have not been explored. This study proposes a comprehensive framework to understand the dynamics and differences in population flood exposure over Canada by employing four global population datasets alongside the census data from Statistics Canada as the reference. The flood exposure is quantified based on a set of floodplain maps (for 2015, 1 in 100-yr and 1 in 200-yr event) for Canada derived from the CaMa-Flood global flood model. To obtain further insights at the regional level, the methodology is implemented over six flood-prone River Basins in Canada. We find that about 9% (3.31 million) and 11% (3.90 million) of the Canadian population resides within 1 in 100-yr and 1 in 200-yr floodplains. We notice an excellent performance of WorldPop, and LandScan in most of the cases, which is unaffected by the representation of flood hazard, while Global Human Settlement and Gridded Population of the World showed large deviations. At last, we determined the long-term dynamics of population flood exposure and vulnerability from 2006 to 2019. Through this analysis, we also identify the regions that contain a significantly larger population exposed to floods. The relevant conclusions derived from the study highlight the need for careful selection of population datasets for preventing further amplification of uncertainties in flood risk. We recommend a detailed assessment of the severely exposed regions by including precise ground-level information. The results derived from this study may be useful not only for flood risk management but also contribute to understanding other disaster impacts on human-environment interrelationships. • Five population datasets are considered for quantifying flood exposure over Canada. • WorldPop and LandScan provide the closest estimates when compared with census data. • Skill of population datasets is tested over six flood-prone River Basins of Canada. • Long-term changes in degree of exposure is characterized at census-division level. • Highly exposed divisions are identified for ensuring detailed flood-risk assessment
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Les bassins versants du Moyen‐Nord quebecois (49e au 55e parallele) se distinguent par leur climatologie et le pourcentage eleve de territoires couverts par des lacs et milieux humides (de l’ordre de 20 a 30 %) et, surtout, par leur importante contribution a la production electrique du Quebec; le complexe de la riviere La Grande generant environ 40% de l’electricite quebecoise. Dans le contexte de la gestion de la production d’electricite, Hydro‐Quebec Production fait la prevision des apports aux reservoirs de ce complexe a l’aide d’un modele hydrologique global. Par ailleurs, depuis les annees 1980, le milieu boreal quebecois a subi des hausses de temperature et de precipitation qui ont modifie le regime des apports aux reservoirs. Compte tenu de ces changements et des caracteristiques physiographiques des bassins boreaux, il a ete propose d’utiliser un modele hydrologique distribue a base physique pour examiner l’impact sur ces apports des projections climatiques produites par Ouranos. En l’occurrence le modele HYDROTEL dont la prise en mains est en train d’etre completee par Hydro‐Quebec Production. Le modele qui est maintenant convenablement cale pour un certain nombre de bassins repond aux attentes dans les bassins du sud du Quebec. Toutefois, pour les grands bassins du Nord comme ceux du Complexe La Grande, l’utilisation du modele requiert des travaux d’adaptations, entre autres, aux niveaux de la modelisation des milieux humides et de la desagregation spatiale des precipitations simulees par les modeles climatiques. Les objectifs generaux de ce projet etaient d’accroitre notre comprehension de l’hydrologie du moyen nord afin qu’elle soit bien representee dans HYDROTEL tout en tenant compte des incertitudes parametriques associees aux differentes equations gouvernant les processus physiques. Ces objectives ont ete declines en trois activites de travail : (AT1) modelisation des processus hydrologiques; (AT2) calage et analyses de sensibilite, d’identifiabilite et d’incertitudes des parametres de calage d’HYDROTEL; et (AT3) amelioration des plateformes informatiques HYDROTEL et PHYSITEL, ce dernier etant un SIG dedie a la construction des bases de donnees de modeles hydrologiques distribues. Pour Ouranos et Hydro‐Quebec les principales realisations issues de ce projet incluent : (i) le developpement d’une methode eprouvee de desagregation sous grille de la precipitation mesoechelle permettant d’evaluer a fine echelle spatiale l’impact des changements climatiques sur les precipitations; (ii) une meilleure comprehension de la dynamique des ecoulements, du stockage de l’eau et de l’evapotranspiration d’un petit bassin versant boreal incluant une grande une tourbiere minerotrophe aqualysee; (iii) l’evaluation du parametrage de la sublimation et la relocalisation de la neige dues au vent et l’identification du besoin d’inclure le rayonnement sous la canopee pour bien reproduire la crue avec un modele complexe de l'evolution du couvert nival; (iv) la detection de la quasi neutralite frequente (~76% du temps, majoritairement le jour) de l’atmosphere au‐dessus d’un milieu humide causee par une turbulence mecanique forte et une grande inertie thermique; conditions ayant permises le developpement d’un modele simple d’evapotranspiration des milieux humides base le transfert massique et la stabilite atmospherique; (v) le developpement d’un modele de rayonnement net base uniquement sur des donnees de temperatures journalieres (min, max) et une estimation des parametres permettant de valider l’utilisation de l’equation de Penman‐Monteith dans le nord quebecois; (vi) la hierarchisation des parametres de calage d’HYDROTEL selon la saison et le developpement d’une methode permettant d’evaluer l’incertitude sur les debits simules et d’identifier son importance durant la fonte et l’etiage estival; (vii) dans un contexte d’analyse frequentielle des debits simules, evaluation de l’incertitude parametrique par rapport a l’incertitude statistique, cette derniere dominant pour les periodes de retour superieures a cinq ans; (viii) a l’aide de PHYSITEL, la premiere discretisation du complexe de la riviere La Grande (136 648 km2) en six sousbassins (LG1, LG2, LG3, LG4, La Forge 1 & 2,et Caniapiscau) leur subdivision en versants permettant le calcul de crues maximales probables a l’aide d’HYDROTEL; et (ix) le developpement d’une version 64 bits d’HYDROTEL incluant de nouveaux modules de de calculs de la temperature du sol et des bilans hydriques des milieux humides et isoles. L'avancement de nos comprehensions de l'hydrologie des milieux humides et du milieu boreal en general a ete a la base du developpement des versions adaptees d'HYDROTEL et de PHYSITEL qui permettront a Hydro‐Quebec d'apprehender, avec une modelisation distribuee, l'impact des changements climatiques sur le complexe de la riviere La Grande. Ces logiciels sont transposables a l’ensemble du milieu boreal canadien. Une entente conclut, depuis 2005, entre l’INRS et Hydro‐Quebec (HQ) permet d’ailleurs une distribution commerciale des differentes versions d’HYDROTEL avec interfaces usagers de meme qu’une distribution communautaire du noyau de calcul. Cette synergie a permis de mettre en commun des ressources et des expertises qui facilitent les echanges scientifiques et techniques entre les concepteurs d’HYDROTEL, le Centre d’expertise hydrique du Quebec (CEHQ), HQ, l’IREQ (Institut de recherche en electricite du Quebec) et d’autres usagers (ex. : l’IMTA, Instituto Mexicano de Technologia del Agua). Au total, plus d’une quarantaine de licences ont ete distribuees tant pour des besoins d’enseignement (Universite de Sherbrooke) et de recherche (Universite Laval, UQTR, UQAC, IREQ, Ecole de Technologie Superieure, INRA de Montpellier, Environnement Canada, Agriculture et Agroalimentaire Canada), que des besoins de prevision hydrologique (IMTA, Ville de Quebec, Centre d’expertise hydrique du Quebec, HQ). La modularite informatique d’HYDROTEL se prete egalement bien a cette synergie car elle offre la possibilite de partager le savoir‐faire et, par l’entremise d’un site internet public (CodePlex), de mettre a la disponibilite de tous les nouvelles versions du noyau de calcul. Ces developpements ont permis a l’equipe de l’INRS‐ETE d’acquerir une reconnaissance internationale en modelisation hydrologique distribuee. En effet, HYDROTEL et PHYSITEL ont dans le passe ete identifie comme les outils a utiliser dans le cadre d’appels de proposition de projets de determination du potentiel hydroelectrique finances par la Banque Mondiale [World Bank, 2009].
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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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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.