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Quebec has experienced a significant decrease in the amount of snow and an increase in temperature during the cold season. The objective of this study is to analyze the impacts of these climate changes on the spatio-temporal variability of the daily maximum flows generated by snowmelt in winter and spring using several statistical tests of correlation (spatial variability) and long-term trend (temporal variability). The study is based on the analysis of flows measured in 17 watersheds (1930–2019) grouped into three hydroclimatic regions. Regarding the spatial variability, the correlation analysis revealed that in winter, the flows are positively correlated with the agricultural area and the daily maximum winter temperature. In the spring, the flows are positively correlated with the drainage density and the snowfall but negatively correlated with the area of wetlands and the daily maximum spring temperature. As for temporal variability (long-term trend), the application of eight statistical tests revealed a generalized increase in flows in winter due to early snowmelt. In the spring, despite the decreased snow cover, no negative trend was observed due to the increase in the spring rainfall, which compensates for the decrease in the snowfall. This temporal evolution of flows in the spring does not correspond to the predictions of climate models. These predict a decrease in the magnitude of spring floods due to the decrease in the snowfall in southern Quebec.
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Snow is the main source of streamflow in temperate regions characterized by very cold and snowy winters. Due to global warming, these regions are experiencing a significant decrease in snowfall. The main objective of this study is to analyze the impacts of snowfall on the spatio-temporal variability of mean annual flows (MAFs) of 17 rivers, grouped into three hydroclimatic regions, from 1930 to 2019 in southern Quebec. In terms of spatial variability, snowfall is the variable most correlated with MAFs (positive correlation), followed by drainage density (positive correlation) and wetland surface areas (negative correlation). Due to the influence of these three factors, MAF values are generally higher in the most agricultural watersheds of the southeastern hydroclimatic region on the south shore than in the less agricultural watersheds of the southwestern hydroclimatic region on the north shore of the St. Lawrence River. As for temporal variability, the four statistical tests applied to the hydrological series detect no significant downward trend in MAFs, despite having reduced snowfall. Instead, they suggest an evolution toward an increase in mean annual flows, as a result of increased rainfall due to the increase in temperature. This evolution is more pronounced on the north shore than on the south shore, likely due to the presence of wetlands and others water bodies, whose runoff water storage capacity does not change over time to be able to store the surplus of the quantity of water brought by the increase in rain.
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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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Introduction:In July 2013, a train carrying 72 cars of crude oil derailed in the town of Lac-Mégantic (Eastern Townships, Quebec, Canada). This disaster provoked a major conflagration, explosions, 47 deaths, the destruction of 44 buildings, the evacuation of one-third of the local population, and an unparalleled oil spill. Notwithstanding the environmental impact, many citizens of this town and in surrounding areas have suffered and continue to suffer substantial losses as a direct consequence of this catastrophe.Problem:To tailor public health interventions and to meet the psychosocial needs of the community, the Public Health Department of Eastern Townships has undertaken repeated surveys to monitor health and well-being over time. This study focuses on negative psychosocial outcomes one and two years after the tragedy.Methods:Two cross-sectional surveys (2014 and 2015) were conducted among large random samples of adults in Lac-Mégantic and surrounding areas (2014: n = 811; 2015: n = 800), and elsewhere in the region (2014: n = 7,926; 2015: n = 800). A wide range of psychosocial outcomes was assessed (ie, daily stress, main source of stress, sense of insecurity, psychological distress, excessive drinking, anxiety or mood disorders, psychosocial services use, anxiolytic drug use, gambling habits, and posttraumatic stress symptoms [PSS]). Exposure to the tragedy was assessed using residential location (ie, six-digit postal code) and intensity of exposure (ie, intense, moderate, or low exposure; from nine items capturing human, material, or subjective losses). Relationships between such exposures and adverse psychosocial outcomes were examined using chi-squares and t-tests. Distribution of outcomes was also examined over time.Results:One year after the disaster, an important proportion of participants reported human, material, and subjective losses (64%, 23%, and 54%, respectively), whereas 17% of people experienced intense exposure. Participants from Lac-Mégantic, particularly those intensely exposed, were much more likely to report psychological distress, depressive episode, anxiety disorders, and anxiolytic drug use, relative to less-exposed ones. In 2015, 67% of the Lac-Mégantic participants (76% of intensely exposed) reported moderate to severe PSS. Surprisingly, the use of psychosocial services in Lac-Mégantic declined by 41% from 2014 to 2015.Conclusion:The psychosocial burden in the aftermath of the Lac-Mégantic tragedy is substantial and persistent. Public health organizations responding to large-scaling disasters should monitor long-term psychosocial consequences and advocate for community-based psychosocial support in order to help citizens in their recovery process.