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ABSTRACTTwo modelling approaches are presented in this article for spatial and temporal analysis of water resources risk. Major sources of uncertainty in water resources management are spatial and temporal variability. Spatial variability occurs when values fluctuate with the location of an area and temporal variability occurs when values fluctuate with time. System dynamics (SD) simulation and hydrodynamic modelling are presented in this article as tools for modelling the dynamic characteristics of flood risk and its spatial variability. The first modelling framework presents SD simulation coupled with 3D fuzzy set theory. Whereas the second modelling framework presents hydrodynamic modelling coupled with 3D fuzzy set theory. The two integrated modelling frameworks are illustrated and compared using the Red River flood of 1997 (Manitoba, Canada) as a case study. For the 1997 Red River case study, SD simulation proved to be efficient modelling approach for capturing the feedback-based dynamic processes oc...

La gestion intégrée des risques d’inondation (GIRI) fait appel à la coordination de tous les niveaux et secteurs du gouvernement et de la société civile. Afin de favoriser la responsabilisation et l’appropriation des plans de GIRI par les communautés, l’implication des acteurs non gouvernementaux et des citoyens est de plus en plus valorisée. D’abord, l’émergence des approches participatives est exacerbée par l’optimisme face à la possibilité d’améliorer substantiellement la qualité et la portée des décisions, de gérer les conflits, de faciliter l'implantation des mesures non structurelles et de renforcer les capacités sociales au sein des communautés. Toutefois, certains avancent que l'intégration des non-experts dans le processus décisionnel brime l'impartialité de la procédure technocratique et que leur manque d’intérêt et de compétences limite la portée des démarches participatives. Des lacunes dans la représentativité des parties prenantes affectées et concernées au sein des instances peuvent aussi biaiser les aboutissants de la participation. De plus, la réticence des autorités à partager le pouvoir décisionnel limite l’institutionnalisation des approches participatives, tandis que la rigidité de l’appareil gouvernemental freine les élans participatifs des collectivités. Considérant l’intérêt grandissant des chercheurs, des décideurs et de la société civile envers les approches participatives dans le contexte de la gestion des inondations, cet article propose une synthèse de la littérature pour démêler les principales retombées et les limites de la participation. , In order to promote community accountability for flood risks, the involvement of non-governmental actors and citizens is increasingly valued. The emergence of participatory approaches is consolidated by optimism about the possibility of improving the quality and scope of decisions, managing conflicts, facilitating the implementation of non-structural measures and strengthening social capacity within communities. However, some argue that the integration of non-experts undermines the impartiality of the decision-making process and that their lack of interest and expertise limits the scope of participatory approaches. Moreover, the authorities’ reluctance to share decision-making power limits the institutionalization of participatory approaches, whereas the rigidity of the governmental framework hampers participatory impulses within communities. Lack of stakeholder representativeness within the decision-making framework may also bias the outcome of participation. In addition, the reluctance of the authorities to share decision-making power limits the institutionalization of participatory approaches, while the rigidity of the government apparatus hinders the participatory momentum of communities. Considering the growing interest of researchers, policymakers and civil society in participatory approaches in the context of flood management, this article provides a synthesis of the literature to unravel the major benefits and limitations of participation.

A la suite de la tragedie ferroviaire de Lac-Megantic de 2013, des enquetes populationnelles ont permis de dresser un portrait de la sante des adultes vivant sur le territoire de la MRC du Granit, sans toutefois repertorier le vecu specifique des jeunes. Le present document vise a combler cette lacune en offrant un bilan de la realite et des besoins des jeunes âges de 10 a 25 ans demeurant au sein de la communaute de Lac-Megantic. Il presente les resultats d'une etude mixte realisee a l'hiver 2017 aupres d'eleves de second cycle de quatre ecoles primaires (5e et 6e annees), de la polyvalente Montignac, ainsi que d'etudiants frequentant le Centre de formation professionnelle Le Granit, le centre d'etudes collegiales de Lac-Megantic et le Centre d'education des adultes de la Commission scolaire des Hauts-Cantons, secteur Lac-Megantic. Cet ouvrage s'adresse aux chercheurs, aux etudiants ainsi qu'aux professionnels des milieux scolaires et du reseau de la sante et des services sociaux qui s'interessent au vecu des jeunes a la suite d'une catastrophe. Plus precisement, il permet de mieux connaitre les caracteristiques personnelles, familiales, scolaires et sociales des jeunes de la commmunaute de Lac-Megantic, tout en leur donnant la parole sur leurs attentes, leurs desirs et leurs besoins.

Extratropical Cyclone (EC) characteristics depend on a combination of large-scale factors and regional processes. However, the latter are considered to be poorly represented in global climate models (GCMs), partly because their resolution is too coarse. This paper describes a framework using possibilities given by regional climate models (RCMs) to gain insight into storm activity during winter over North America (NA). Recent past climate period (1981–2005) is considered to assess EC activity over NA using the NCEP regional reanalysis (NARR) as a reference, along with the European reanalysis ERA-Interim (ERAI) and two CMIP5 GCMs used to drive the Canadian Regional Climate Model—version 5 (CRCM5) and the corresponding regional-scale simulations. While ERAI and GCM simulations show basic agreement with NARR in terms of climatological storm track patterns, detailed bias analyses show that, on the one hand, ERAI presents statistically significant positive biases in terms of EC genesis and therefore occurrence while capturing their intensity fairly well. On the other hand, GCMs present large negative intensity biases in the overall NA domain and particularly over NA eastern coast. In addition, storm occurrence over the northwestern topographic regions is highly overestimated. When the CRCM5 is driven by ERAI, no significant skill deterioration arises and, more importantly, all storm characteristics near areas with marked relief and over regions with large water masses are significantly improved with respect to ERAI. Conversely, in GCM-driven simulations, the added value contributed by CRCM5 is less prominent and systematic, except over western NA areas with high topography and over the Western Atlantic coastlines where the most frequent and intense ECs are located. Despite this significant added-value on seasonal-mean characteristics, a caveat is raised on the RCM ability to handle storm temporal ‘seriality’, as a measure of their temporal variability at a given location. In fact, the driving models induce some significant footprints on the RCM skill to reproduce the intra-seasonal pattern of storm activity.

The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water—PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately.

Empirical relationships are derived for the expected sampling error of quantile estimations using Monte Carlo experiments for two frequency distributions frequently encountered in climate sciences. The relationships found are expressed as a scaling factor times the standard error of the mean; these give a quick tool to estimate the uncertainty of quantiles for a given finite sample size.

An urban heat island (UHI) is a relative measure defined as a metropolitan area that is warmer than the surrounding suburban or rural areas. The UHI nomenclature includes a surface urban heat island (SUHI) definition that describes the land surface temperature (LST) differences between urban and suburban areas. The complexity involved in selecting an urban core and external thermal reference for estimating the magnitude of a UHI led us to develop a new definition of SUHIs that excludes any rural comparison. The thermal reference of these newly defined surface intra-urban heat islands (SIUHIs) is based on various temperature thresholds above the spatial average of LSTs within the city’s administrative limits. A time series of images from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) from 1984 to 2011 was used to estimate the LST over the warm season in Montreal, Québec, Canada. Different SIUHI categories were analyzed in consideration of the global solar radiation (GSR) conditions that prevailed before each acquisition date of the Landsat images. The results show that the cumulative GSR observed 24 to 48 h prior to the satellite overpass is significantly linked with the occurrence of the highest SIUHI categories (thresholds of +3 to +7 °C above the mean spatial LST within Montreal city). The highest correlation (≈0.8) is obtained between a pixel-based temperature that is 6 °C hotter than the city’s mean LST (SIUHI + 6) after only 24 h of cumulative GSR. SIUHI + 6 can then be used as a thermal threshold that characterizes hotspots within the city. This identification approach can be viewed as a useful criterion or as an initial step toward the development of heat health watch and warning system (HHWWS), especially during the occurrence of severe heat spells across urban areas.

Since the 1980s, populations of the Asian tiger mosquito Aedes albopictus have become established in south-eastern, eastern and central United States, extending to approximately 40°N. Ae. albopictus is a vector of a wide range of human pathogens including dengue and chikungunya viruses, which are currently emerging in the Caribbean and Central America and posing a threat to North America.

Changes in extreme precipitation should be one of the primary impacts of climate change (CC) in urban areas. To assess these impacts, rainfall data from climate models are commonly used. The main goal of this paper is to report on the state of knowledge and recent works on the study of CC impacts with a focus on urban areas, in order to produce an integrated review of various approaches to which future studies can then be compared or constructed. Model output statistics (MOS) methods are increasingly used in the literature to study the impacts of CC in urban settings. A review of previous works highlights the non-stationarity nature of future climate data, underscoring the need to revise urban drainage system design criteria. A comparison of these studies is made difficult, however, by the numerous sources of uncertainty arising from a plethora of assumptions, scenarios, and modeling options. All the methods used do, however, predict increased extreme precipitation in the future, suggesting potential risks of combined sewer overflow frequencies, flooding, and back-up in existing sewer systems in urban areas. Future studies must quantify more accurately the different sources of uncertainty by improving downscaling and correction methods. New research is necessary to improve the data validation process, an aspect that is seldom reported in the literature. Finally, the potential application of non-stationarity conditions into generalized extreme value (GEV) distribution should be assessed more closely, which will require close collaboration between engineers, hydrologists, statisticians, and climatologists, thus contributing to the ongoing reflection on this issue of social concern.