Votre recherche

Objectifs  Malgré l’existence de plusieurs traitements en ligne pour les personnes avec un trouble de stress posttraumatique (TSPT), peu d’études se sont penchées sur les données d’utilisation d’une telle intervention. Étant donné le potentiel de la modalité en ligne à pallier les obstacles limitant l’accès à l’aide psychologique, il importe de documenter les interactions des usagers avec ces outils en lien avec l’amélioration des symptômes ciblés. L’objectif de cette étude est de documenter les données d’utilisation de la plateforme de traitement en ligne RESILIENT par les personnes évacuées des feux de Fort McMurray, Alberta (Canada), et d’examiner leur association avec l’efficacité du traitement sur les symptômes de trouble de stress posttraumatique (TSPT), d’insomnie et de dépression, et l’adhésion au traitement, mesurée par le nombre de modules consultés par les participants. Méthode  Quatre-vingt-dix-sept personnes évacuées des feux de Fort McMurray présentant des symptômes de TSPT, d’insomnie et de dépression sont incluses dans la présente étude. Les participants étaient invités à utiliser la plateforme RESILIENT, un autotraitement en ligne guidé par un thérapeute qui cible les symptômes de TSPT, le sommeil et l’humeur, et comprend 12 modules offrant des stratégies de thérapies cognitives et comportementales (TCC) basées sur les données probantes. Des données d’utilisation objectives (p. ex. nombre de modules consultés) et subjectives (p. ex. niveau d’efforts investis) ont été recueillies. Résultats  Afin de prédire la réduction des symptômes de TSPT, de dépression et d’insomnie, ainsi que le nombre de modules consultés par les participants, des modèles de régressions séquentielles ont été effectués, avec un contrôle statistique pour les symptômes prétraitement, l’âge et le genre. Les modèles finaux ont révélé qu’une réduction des symptômes de TSPT, de dépression et d’insomnie était prédite significativement par le nombre de modules consultés (β = - 0,41 ; - 0,53 ; - 0,49 respectivement, tous p < 0,001) ainsi que par le niveau d’efforts moyen autorapporté au module 7 (mi-parcours) (β = - 0,43 ; p < 0,001 ; β = - 0,38 ; p = 0,005 et β = - 0,36 ; p = 0,007 respectivement). Le nombre de modules consultés, par ailleurs, était prédit significativement par le nombre de mots dans le 4 e  module (β = 0,34 ; p < 0,001) et dans le 7 e  module (β = 0,44 ; p < 0,001), ainsi que par le nombre d’entrées dans le journal du sommeil (β = 0,28 ; p < 0,001). Conclusion  Les résultats ont confirmé qu’une plus grande interaction avec la plateforme influence positivement l’efficacité du traitement et qu’une utilisation accrue en début de traitement semble être un bon prédicteur de l’achèvement de celui-ci. Cette étude confirme l’importance de soutenir l’engagement des participants envers le traitement en ligne afin d’optimiser son efficacité. , Objectives Despite the existence of several online treatments for people with posttraumatic stress disorder (PTSD), few studies have examined usage data for such interventions. Given the potential of the online modality to alleviate barriers limiting access to psychological help, it is important to document users’ interactions with these tools in relation to the improvement of targeted symptoms. The objective of this study is to document usage data of the online treatment platform RESILIENT by people evacuated from the Fort McMurray, Alberta (Canada) fires, and to examine their association with the effectiveness of treatment on symptoms of posttraumatic stress disorder (PTSD), insomnia and depression, and adherence to treatment, as measured by the number of modules accessed by participants. Methods Ninety-seven people evacuated from the Fort McMurray fires with symptoms of PTSD, insomnia and depression were included in this study. Participants were invited to use the RESILIENT platform, an online therapist-assisted self-help treatment program that targets PTSD symptoms, sleep and mood, and includes 12 modules offering evidence-based cognitive-behavioural therapy (CBT) strategies. Both objective (e.g., number of modules accessed) and subjective (e.g., level of effort invested) usage data were collected. Results In order to predict the reduction in PTSD, depression and insomnia symptoms, as well as the number of modules accessed by participants, sequential regression models were conducted, with statistical control for pretreatment symptoms, age and gender. The final models revealed that a reduction in PTSD, depression and insomnia symptoms was significantly predicted by the number of modules accessed (β = -.41; -.53; -.49 respectively, all p <.001) as well as the mean self-reported level of effort at module 7 (midway) (β = -.43; p <.001; β = -.38; p  = .005 and β = -.36; p = .007 respectively). The number of modules accessed, on the other hand, was significantly predicted by the number of words in the 4th module (β = .34; p <.001) and 7th module (β = .44; p <.001) and the number of sleep diary entries (β = .28; p <.001). Conclusion These results confirmed that increased interaction with the platform positively influences treatment effectiveness and that increased use at the beginning of treatment appears to be a good predictor of treatment completion. This study confirms the importance of sustaining participants’ commitment to online treatment in order to optimize its effectiveness.

RÉSUMÉ : Peu d’outils permettent de faire un audit des aléas hydrogéomorphologiques (HGM) auxquels les petits cours d’eau (PCE) sont sujets, pourtant à ces PCE sont associés plusieurs aléas HGM qui compromettent l’intégrité d’enjeux qui y sont exposés. L’objectif du projet vise à appliquer des outils SIG (ExZeco et Geomorphon landform) employés avec un modèle numérique d’élévation à haute résolution, pour l’évaluation préliminaire du risque lié aux aléas HGM des PCE. Cette évaluation préliminaire ne tient pas compte de la probabilité d’occurrence de l’aléa. Elle est plutôt basée sur la position des enjeux par rapport aux aléas HGM simulés sur les cônes alluviaux et les plaines d’inondations. Pour ce faire, quatre bassins versants de la région du Bas-Saint-Laurent ont été identifiés comme sites d’étude. La méthodologie se base dans un premier temps sur l’établissement d’un portrait d’aléa HGM, puis dans un deuxième temps sur la caractérisation de ces aléas en évaluant leur intensité, leur étendue et leur distribution spatiale et finalement, l’évaluation de l’exposition des enjeux vis-à-vis des aléas. Les résultats montrent que des enjeux (parcelle agricole, route, résidences) sont exposés à l’aléa torrentiel sur deux cônes alluviaux cartographiés dans les bassins versants pilotes, et des résidences sont exposées à un débordement probable de cours d’eau. L’analyse du risque a été réalisée avec obstruction probable des ponceaux sur le LiDAR et sans obstruction des ponceaux. L’aléa est de forte intensité dans le risque probable lié aux obstructions, et les enjeux exposés sont notamment les résidences, les routes et des portions de terre agricole. Des témoignages de riverains ont permis de valider l’intensité des aléas prédits par ExZeco. -- Mot(s) clé(s) en français : Aléa HGM, Évaluation préliminaire, cône alluvial, plaine d’inondation, LiDAR. -- ABSTRACT : Few tools are available for auditing the hydrogeomorphic hazards (HGM) to which small watercourses (PCE) are subject, yet these PCE are associated with several HGM hazards that compromise the integrity of issues exposed to them. The aim of the project is to apply GIS tools (ExZeco and Geomorphon landform) used in conjunction with a high-resolution digital elevation model, for the preliminary assessment of the risk associated with HGM hazards in PCE. This is an assessment based solely on the position of issues in relation to the HGM hazards to which alluvial fans and floodplains are subject. To this end, four watersheds in the Lower St. Lawrence region were identified as study sites. The methodology is based firstly on the establishment of a HGM hazard profile, then on the characterization of these hazards by assessing their intensity, extent and spatial distribution, and finally on the assessment of the level of exposure of issues to these hazards. The results show that issues (agricultural plots, roads, residences) are exposed to torrential hazards on two alluvial fans mapped in the pilot watersheds, and residences are exposed to probable river overflow. The risk analysis was carried out with probable culvert obstructions on the LiDAR and without culvert obstructions. The probable risk associated with obstructions is of high intensity, and the stakes exposed include residences, roads and portions of agricultural land. Testimonials from residents validated the intensity of the hazards predicted by ExZeco. -- Mot(s) clé(s) en anglais : HGM Hazard, Preliminary Assessment, Alluvial Fan, Floodplain, LiDAR.

This study is focused on social cognitive variables that motivate information seeking and information sharing related to Hurricane Harvey. Survey results from a nationally representative sample and a quota sample of Houston residents indicate that climate change beliefs and issue salience are consistent predictors of risk perception, which increases individuals’ negative emotions and information insufficiency. This need for information subsequently motivates information seeking and information sharing. Informational subjective norms are significantly related to seeking and sharing in the Houston sample, whereas perceived information gathering capacity and trust in media are significant predictors in the national sample.

Climate change and more frequent severe storms have caused persistent flooding, storm surges, and erosion in the northeastern coastal region of the United States. These weather-related disasters have continued to generate negative environmental consequences across many communities. This study examined how coastal residents’ exposure to flood risk information and information seeking behavior were related to their threat appraisal, threat-coping efficacy, and participation in community action in the context of building social resilience. A random sample of residents of a coastal community in the Northeastern United States was selected to participate in an online survey (N = 302). Key study results suggested that while offline news exposure was weakly related to flood vulnerability perception, online news exposure and mobile app use were both weakly associated with flood-risk information seeking. As flood vulnerability perception was strongly connected to flood severity perception but weakly linked to lower self-efficacy beliefs, flood severity perception was weakly and moderately associated with response-efficacy beliefs and information seeking, respectively. Furthermore, self-efficacy beliefs, response efficacy beliefs, and flood-risk information seeking were each a weak or moderate predictor of collective efficacy beliefs. Lastly, flood risk information-seeking was a strong predictor and collective efficacy beliefs were a weak predictor of community action for flood-risk management. This study tested a conceptual model that integrated the constructs from risk communication, information seeking, and protection motivation theory. Based on the modeling results reflecting a set of first-time findings, theoretical and practical implications are discussed.

The paper identifies a role for public relations in disaster management by analysing disaster and communication managers' understanding of community resilience and their use of communication in the context of two different cultural environments.,The research study comprised 51 in-depth qualitative interviews with disaster managers in Sri Lanka and New Zealand, which were thematically analysed using the software programme NVivo 10.,The study identified cultural differences in Sri Lanka and New Zealand that impact on how managers' communicate in natural disaster situations. The findings indicated that public relations’ understanding of communities’ cultures, their communication, networking and lobbying skills could further enhance the effectiveness of efforts to build community resilience to disasters.,Nations are complex multicultural realities; the findings cannot be generalized to make claims about how natural disasters are managed in different national contexts.,The paper identifies the unrealized potential of public relations’ expertise in communication, community relations, networking and lobbying to contribute to building community resilience to natural disasters.,By supporting efforts to build community resilience to disasters, public relations practitioners can contribute to social well-being in times of catastrophic natural disasters.,The paper adds an innovative perspective to public relations crisis literature by identifying the potential contribution of public relations’ concepts and practices to build community resilience to natural disasters. It demonstrates how sociocultural differences may affect disaster communication strategies.

In Canada, floods are the most common largely distributed hazard to life, property, the economy, water systems, and the environment costing the Canadian economy billions of dollars. Arising from this is FloodNet: a transdisciplinary strategic research network funded by Canadas Natural Sciences and Engineering Research Council, as a vehicle for a concerted nation-wide effort to improve flood forecasting and to better assess risk and manage the environmental and socio-economic consequences of floods. Four themes were explored in this network which include 1) Flood regimes in Canada; 2) Uncertainty of floods; 3) Development of a flood forecasting and early warning system and 4) Physical, socio-economic and environmental effects of floods. Over the years a range of statistical, hydrologic, modeling, and economic and psychometric analyses were used across the themes. FloodNet has made significant progress in: assessing spatial and temporal variation of extreme events; updating intensity-duration-frequency (IDF) curves; improving streamflow forecasting using novel techniques; development and testing of a Canadian adaptive flood forecasting and early warning system (CAFFEWS); a better understanding of flood impacts and risk. Despite these advancements FloodNet ends at a time when the World is still grappling with severe floods (e.g., Europe, China, Africa) and we report on several lessons learned. Mitigating the impact of flood hazards in Canada remains a challenging task due to the countrys varied geography, environment, and jurisdictional political boundaries. Canadian technical guide for developing IDF relations for infrastructure design in the climate change context has been recently updated. However, national guidelines for flood frequency analyses are needed since across the country there is not a unified approach to flood forecasting as each jurisdiction uses individual models and procedures. From the perspective of risk and vulnerability, there remains great need to better understand the direct and indirect impacts of floods on society, the economy and the environment.

&lt;p&gt;Spring floods have generated colossal damages to residential areas in the Province of Quebec, Canada, in 2017 and 2019. Government authorities need accurate modelling of the impact of theoretical floods in order to prioritize pre-disaster mitigation projects to reduce vulnerability. They also need accurate modelling of forecasted floods in order to direct emergency responses.&amp;#160;&lt;/p&gt;&lt;p&gt;We present a governmental-academic collaboration that aims at modelling flood impact for both theoretical and forecasted flooding events over all populated river reaches of meridional Quebec. The project, funded by the minist&amp;#232;re de la S&amp;#233;curit&amp;#233; publique du Qu&amp;#233;bec (Quebec ministry in charge of public security), consists in developing a diagnostic tool and methods to assess the risk and impacts of flooding. Tools under development are intended to be used primarily by policy makers.&amp;#160;&lt;/p&gt;&lt;p&gt;The project relies on water level data based on the hydrological regimes of nearly 25,000 km of rivers, on high-precision digital terrain models, and on a detailed database of building footprints and characterizations. It also relies on 24h and 48h forecasts of maximum flow for the subject rivers. The developed tools integrate large data sets and heterogeneous data sources and produce insightful metrics on the physical extent and costs of floods and on their impact on the population. The software also provides precise information about each building affected by rising water, including an estimated cost of the damages and impact on inhabitants.&amp;#160;&amp;#160;&lt;/p&gt;

Abstract Accurately modeling the interactions between inland water bodies and the atmosphere in meteorological and climate models is crucial, given the marked differences with surrounding landmasses. Modeling surface heat fluxes remains a challenge because direct observations available for validation are rare, especially at high latitudes. This study presents a detailed evaluation of the Canadian Small Lake Model (CSLM), a one-dimensional mixed-layer dynamic lake model, in reproducing the surface energy budget and the thermal stratification of a subarctic reservoir in eastern Canada. The analysis is supported by multiyear direct observations of turbulent heat fluxes collected on and around the 85-km 2 Romaine-2 hydropower reservoir (50.7°N, 63.2°W) by two flux towers: one operating year-round on the shore and one on a raft during ice-free conditions. The CSLM, which simulates the thermal regime of the water body including ice formation and snow physics, is run in offline mode and forced by local weather observations from 25 June 2018 to 8 June 2021. Comparisons between observations and simulations confirm that CSLM can reasonably reproduce the turbulent heat fluxes and the temperature behavior of the reservoir, despite the one-dimensional nature of the model that cannot account for energy inputs and outputs associated with reservoir operations. The best performance is achieved during the first few months after the ice break-up (mean error = −0.3 and −2.7 W m −2 for latent and sensible heat fluxes, respectively). The model overreacts to strong wind events, leading to subsequent poor estimates of water temperature and eventually to an early freeze-up. The model overestimated the measured annual evaporation corrected for the lack of energy balance closure by 5% and 16% in 2019 and 2020. Significance Statement Freshwater bodies impact the regional climate through energy and water exchanges with the atmosphere. It is challenging to model surface energy fluxes over a northern lake due to the succession of stratification and mixing periods over a year. This study focuses on the interactions between the atmosphere of an irregular shaped northern hydropower reservoir. Direct measurements of turbulent fluxes using an eddy covariance system allowed the model assessment. Turbulent fluxes were successfully predicted during the open water period. Comparison between observed and modeled time series showed a good agreement; however, the model overreacted to high wind episodes. Biases mostly occur during freeze-up and breakup, stressing the importance of a good representation of the ice cover processes.

Based on a statistical overview of natural disasters, this chapter presents the severe economic and social impacts in terms of human life, livelihoods and physical capital, with short- and long-term consequences for economic growth and development. Furthermore, the highly complex relationship between natural disasters and the level of a country’s development will be analysed.

The historical disparities in the socio-demographic structure of New Orleans shaped the social vulnerability of local residents and their responses to Hurricane Katrina and its aftermath. These disparities, derived from race, class, gender, and age differences, have resulted in the uneven impact of the catastrophe on various communities in New Orleans, and importantly, their ability to recover. This article examines how the pre-existing social vulnerabilities within New Orleans interacted with the level of flood exposure to produce inequities in the socio-spatial patterns of recovery. Utilizing a combination of statistical and spatial approaches, we found a distinct geographic pattern to the recovery suggesting that the social burdens and impacts from Hurricane Katrina are uneven—the less flooded and less vulnerable areas are recovering faster than tracts with more vulnerable populations and higher levels of flooding. However, there is a more nuanced story, which suggests that it is neighborhoods in the mid-range of social vulnerability where recovery is lagging. While private resources and government programs help groups in the high and low categories of social vulnerability, the middle group shows the slowest rates of recovery. Further, it appears that the congressionally funded State of Louisiana Road Home Program (designed to provide compensation to Louisiana’s homeowners who suffered impacts by Hurricanes Katrina and Rita for the damage to their home) is not having a significant effect in stimulating recovery within the city.

Redlining occurs when institutions decline to make mortgage loans in specific areas. The practice originated in the 1930s, when federal agencies encouraged lenders to rate neighbourhoods for mortgage risk. Since the 1960s, especially in the US, it has been associated with disinvestment, racial discrimination and neighbourhood decline. It has always been viewed as a feature of the inner city. Historical evidence indicates that across Canada the first areas to be redlined were the less-desirable suburbs. Land registry and property assessment data establish the emergent patterns in Hamilton, Ontario. Between 1931 and 1951, institutional lending became a social norm first on new dwellings in suburbs. Individual lenders, previously dominant, were relegated to older inner-city properties or cheaper dwellings in less-desirable suburbs. In 1931, there were only minor geographical variations in the incidence of mortgage finance, and specifically of institutional financing, across the urban area. By 1951, lending institutions, led by insurance companies, were discriminating sharply in favour of the West End, the Mountain and Bartonville, and against those parts of the East End that were unserviced or close to lakefront industry. The evidence for Hamilton confirms that in Canada redlining originated in the suburbs. The same may also be true for US metropolitan areas, although the institutional context was different and relevant data are lacking.

The KnnCAD Version 4 weather generator algorithm for nonparametric, multisite simulations of temperature and precipitation data is presented. The K-nearest neighbor weather generator essentially reshuffles the historical data, with replacement. In KnnCAD Version 4, a block resampling scheme is introduced to preserve the temporal correlation structure in temperature data. Perturbation of the reshuffled variable data is also added to enhance the generation of extreme values. The Upper Thames River Basin in Ontario, Canada isused as a case study and the model is shown to simulate effectively the historical characteristics at the site. The KnnCAD Version 4 approach is shown to improve on the previous versions of the model and offers a major advantage over many parametric and semiparametric weather generators in that multisite use can be easily achieved without making statistical assumptions dealing with the spatial correlations and probability distributions of each variable.

Changes in society's vulnerability to natural hazards are important to understand, as they determine current and future risks, and the need to improve protection. Very large impacts including high numbers of fatalities occur due to single storm surge flood events. Here, we report on impacts of global coastal storm surge events since the year 1900, based on a compilation of events and data on loss of life. We find that over the past, more than eight thousand people are killed and 1.5 million people are affected annually by storm surges. The occurrence of very substantial loss of life (g10000 persons) from single events has however decreased over time. Moreover, there is a consistent decrease in event mortality, measured by the fraction of exposed people that are killed, for all global regions, except South East Asia. Average mortality for storm surges is slightly higher than for river floods, but lower than for flash floods. We also find that for the same coastal surge water level, mortality has decreased over time. This indicates that risk reduction efforts have been successful, but need to be continued with projected climate change, increased rates of sea-level rise and urbanisation in coastal zones.

As Hurricane Katrina revealed, coastal communities have become far more vulnerable to tropical storms and the long-term displacement of residents. Yet, because the emergency management model presumes that recovery quickly follows response, governments focus only on short-term, localized displacement. However, long-term and long-distance displacement exposes a gray area between immediate shelter and permanent housing, along with concerns about vulnerability, housing availability, and land development. We begin this article by discussing the transition between response and recovery. We then review literature regarding social vulnerability, displacement, provision of temporary housing, households' return decisions, and disaster-driven land development and housing construction processes. We close with thoughts on future research to increase planners' understanding of the issues involved and to help them craft effective policies.

Abstract. Model intercomparison studies are carried out to test and compare the simulated outputs of various model setups over the same study domain. The Great Lakes region is such a domain of high public interest as it not only resembles a challenging region to model with its transboundary location, strong lake effects, and regions of strong human impact but is also one of the most densely populated areas in the USA and Canada. This study brought together a wide range of researchers setting up their models of choice in a highly standardized experimental setup using the same geophysical datasets, forcings, common routing product, and locations of performance evaluation across the 1×106 km2 study domain. The study comprises 13 models covering a wide range of model types from machine-learning-based, basin-wise, subbasin-based, and gridded models that are either locally or globally calibrated or calibrated for one of each of the six predefined regions of the watershed. Unlike most hydrologically focused model intercomparisons, this study not only compares models regarding their capability to simulate streamflow (Q) but also evaluates the quality of simulated actual evapotranspiration (AET), surface soil moisture (SSM), and snow water equivalent (SWE). The latter three outputs are compared against gridded reference datasets. The comparisons are performed in two ways – either by aggregating model outputs and the reference to basin level or by regridding all model outputs to the reference grid and comparing the model simulations at each grid-cell. The main results of this study are as follows: The comparison of models regarding streamflow reveals the superior quality of the machine-learning-based model in the performance of all experiments; even for the most challenging spatiotemporal validation, the machine learning (ML) model outperforms any other physically based model. While the locally calibrated models lead to good performance in calibration and temporal validation (even outperforming several regionally calibrated models), they lose performance when they are transferred to locations that the model has not been calibrated on. This is likely to be improved with more advanced strategies to transfer these models in space. The regionally calibrated models – while losing less performance in spatial and spatiotemporal validation than locally calibrated models – exhibit low performances in highly regulated and urban areas and agricultural regions in the USA. Comparisons of additional model outputs (AET, SSM, and SWE) against gridded reference datasets show that aggregating model outputs and the reference dataset to the basin scale can lead to different conclusions than a comparison at the native grid scale. The latter is deemed preferable, especially for variables with large spatial variability such as SWE. A multi-objective-based analysis of the model performances across all variables (Q, AET, SSM, and SWE) reveals overall well-performing locally calibrated models (i.e., HYMOD2-lumped) and regionally calibrated models (i.e., MESH-SVS-Raven and GEM-Hydro-Watroute) due to varying reasons. The machine-learning-based model was not included here as it is not set up to simulate AET, SSM, and SWE. All basin-aggregated model outputs and observations for the model variables evaluated in this study are available on an interactive website that enables users to visualize results and download the data and model outputs.