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This paper explores the risk approach, considering both the physical and human dimensions of the phenomenon in order to produce a more realistic and spatial analysis of risk. Exposure and vulnerability were combined and evaluated multidimensionally, considering individual, socio-economic, and structural (building-related) aspects. These risk factors were then integrated in a multi-criteria analysis in order to produce a comprehensive risk index that could be visualized at the building scale. The relative importance of the indicators was determined through a participatory process involving local and national experts on civil security and flooding. Particular attention was paid to individual vulnerability, including perception and preparedness for flood risk, which were explored directly with local people using a questionnaire. Qualitative and quantitative analyses of the responses allowed for a better understanding of the perception and preparedness of populations exposed to flooding. These data should help to improve risk communication between the authorities concerned and the populations at risk, as well as encouraging implementation of appropriate measures and a bottom-up participatory management approach. The integration of data in a geographic information system enables the visualization and spatialization of risk, but also each of its components.

In the context of global warming, changes in extreme weather and climate events are expected, particularly those associated with changes in temperature and precipitation regimes and those that will affect coastal areas. The main objectives of this study were to establish the number of extreme events that have occurred in northeastern New Brunswick, Canada in recent history, and to determine whether their occurrence has increased. By using archived regional newspapers and data from three meteorological stations in a national network, the frequency of extreme events in the study area was established for the time period 1950–2012. Of the 282 extreme weather events recorded in the newspaper archives, 70% were also identified in the meteorological time series analysis. The discrepancy might be explained by the synergistic effect of co-occurring non-extreme events, and increased vulnerability over time, resulting from more people and infrastructure being located in coastal hazard zones. The Mann Kendall and Pettitt statistical tests were used to identify trends and the presence of break points in the weather data time series. Results indicate a statistically significant increase in average temperatures and in the number of extreme events, such as extreme hot days, as well as an increase in total annual and extreme precipitation. A significant decrease in the number of frost-free days and extreme cold days was also found, in addition to a decline in the number of dry days.

Due to limitations in traditional concrete gravity dam (CGD) design, a new approach is necessary. In this study, the lean analysis as a novel approach for CGD design, considering the interaction between dam and reservoir was considered. Maximum and minimum stresses at the heel and displacement of the crest were obtained as crucial input values of bubble sorting based on seismic analysis using Finite element analysis (FEA), and the Fuzzy Analytic Hierarchy Process (FAHP). The fuzzy bubble sorting analytic process, aimed at developing a novel method for selecting the best CGD configuration, was developed. Required Criteria, Sub-Criteria and developed models were applied to optimize the body of CGD. The weight of each sub-criterion and models were calculated based on pairwise comparison matrices. The novel approach was designed in MATLAB with the OPT-CGD code to select the best CGD model. The best weight of the Criteria, for selecting the best CGD model, based on the lean construction principles was selected from 60 developed models under implicit dynamic analysis. Statistical analysis reveals a 20% reduction in the concrete mass of the case study’s optimal body compared to the traditionally designed dam.

In time series of essential climatological variables, many discontinuities are created not by climate factors but changes in the measuring system, including relocations, changes in instrumentation, exposure or even observation practices. Some of these changes occur due to reorganization, cost-efficiency or innovation. In the last few decades, station movements have often been accompanied by the introduction of an automatic weather station (AWS). Our study identifies the biases in daily maximum and minimum temperatures using parallel records of manual and automated observations. They are selected to minimize the differences in surrounding environment, exposition, distance and difference in elevation. Therefore, the type of instrumentation is the most important biasing factor between both measurements. The pairs of weather stations are located in Piedmont, a region of Italy, and in Gaspe Peninsula, a region of Canada. They have 6years of overlapping period on average, and 5110 daily values. The approach implemented for the comparison is divided in four main parts: a statistical characterization of the daily temperature series; a comparison between the daily series; a comparison between the types of events, heat wave, cold wave and normal events; and a verification of the homogeneity of the difference series. Our results show a higher frequency of warm (+10%) and extremely warm (+35%) days in the automated system, compared with the parallel manual record. Consequently, the use of a composite record could significantly bias the calculation of extreme events.

La province du Nouveau-Brunswick, situee dans l’est du Canada, est tres affectee par les inondations. Bien que moins documentee que l’alea, la dimension humaine du risque que represente la vulnerabilite est importante pour l’adaptation des populations. Cet article fait un survol des principaux concepts lies a la vulnerabilite et presente leur application a l’echelle d’un bassin versant de taille moyenne. Les resultats montrent la necessite de considerer simultanement la perception et la preparation au risque d’inondation. En effet, si certains residents dans les zones a risque ont une bonne connaissance des inondations et une perception realiste du risque, cela ne se traduit pas necessairement par une preparation adaptee et adequate face au risque. La reduction du risque passe indeniablement par une meilleure sensibilisation et education de la population.

Une coulee de slush (bouillie de neige fondante) est un ecoulement rapide constitue d’un melange de neige fondante, d’eau, de boue et de debris de toutes sortes. Les sept sites analyses demontrent que les coulees de slush peuvent survenir dans des contextes topographiques fort differents qui presentent toutefois des similitudes au niveau du mode d’enneigement et des conditions hydro-meteorologiques. Les coulees de slush etudiees demarrent dans des ruisseaux d’ordre 1 ou 2, etroits et peu profonds, de pente tres variable (de 1° a plus de 30°), qui sont combles par des bouchons de neige dense soufflee par le vent ou transportee par les avalanches. Parce qu’ils s’opposent a la libre circulation des eaux de fusion lors des periodes de fonte acceleree, ces bouchons de neige favorisent la saturation du manteau neigeux jusqu’a la rupture sous l’effet combine de la pression hydrostatique et de la gravite. Les onze coulees analysees, qui se sont produites entre 1936 et 2013, permettent de definir deux scenarios hydro-meteorologiques propices a leur declenchement : 1) des redoux de longue duree caracterises par des temperatures qui restent positives pendant plusieurs jours consecutifs sans apport de precipitations liquides; 2) des redoux relativement courts (moins de 48 heures) couples a des precipitations liquides abondantes. Largement meconnues au Quebec, les coulees de slush pourraient etre plus frequentes a l’avenir en reponse au rechauffement climatique en cours.

Droughts are increasingly recognized as a significant global challenge, with severe impacts observed in Canada's Prairie provinces. While less frequent in Eastern Canada, prolonged precipitation deficits, particularly during summer, can lead to severe drought conditions. This study investigates the causes and consequences of droughts in New Brunswick (NB) by employing two drought indices: the Palmer Drought Severity Index (PDSI) and Standardized Evapotranspiration Deficit Index (SEDI)– at ten weather stations across NB from 1971 to 2020. Additionally, the Canadian Gridded Temperature and Precipitation Anomalies (CANGRD) dataset (1979–2014) was utilized to examine spatial and temporal drought variability and its alignment with station-based observations. Statistical analyses, including the Mann–Kendall test and Sen's slope estimator, were applied to assess trends in drought indices on annual and seasonal timescales using both station and gridded data. The results identified the most drought-vulnerable regions in NB and revealed significant spatial and temporal variability in drought severity over the 1971–2020 period. Trend analyses further highlighted the intensification of extreme drought events during specific years. Coastal areas in southern NB were found to be particularly susceptible to severe drought conditions compared to inland regions, consistent with observed declines in both the frequency of rainy days and daily precipitation amounts in these areas. These findings underscore the need for targeted drought mitigation strategies particularly in NB’s coastal zones, to address the region’s increasing vulnerability to extreme drought events.