Paraglacial Timescale and Sediment Fluxes for Hillslope Land Systems in the Northern Appalachian Mountains of Eastern Canada - Germain, Daniel; Stabile-Caillé (2022)
The Appalachian Mountains of Eastern Canada are prone to several mass-wasting processes related to the geology and the nearby presence of large water bodies that influence the climate. Superimposed on this rugged terrain is the impacts of ongoing climate change, which may increase the magnitude, frequency, and duration of an array of hillslope phenomena. In this regard, the quantification of sediment fluxes at various spatiotemporal scales is prerequisite to reducing the exposure of infrastructure and communities, as well as to better understanding the mountain landscape evolution. Here, we report the quantitative modeling of sediment fluxes of several hillslope processes, mainly based on radiocarbon dating, which in turn improves understanding of how sediment has been eroded and transported through these mountain catchments since deglaciation. The results show a variable pattern of paraglacial effects at local and regional scales, highlighting the importance of ecological and hydroclimatic conditions in controlling the duration of glacially conditioned sedimentary stock exhaustion, and therefore the delay of paraglacial responses by geomorphic land systems. Current active scree slopes under the cold-temperate climate are characterized by sedimentation rates slightly lower than those calculated for the periglacial period following deglaciation, and even the sporadic remobilization of the primary stock by alluvial fan dynamics appears to be significant, testifying to a duration of paraglacial processes of more than 10,000 years.
MAG ID: 3209185843

Ice-block fall and snow avalanche hazards in northern Gaspésie (eastern Canada): Triggering weather scenarios and process interactions - Graveline, Marie-Hélène; Germain, Daniel (Cold Regions Science and Technology, 2016)
Abstract The database of the Quebec Ministry of Transport allowed us to analyze the occurrence of ice-block falls and snow avalanches for the past decades along national road 132. The results show that ice structure collapse may be categorized into three distinct phases by using daily temperatures (minimum, maximum, and average) and the cumulative degree day (temperatures above 0°C) since the March 1 st , corresponding to the beginning of the ice wall melting period: 1) a short and intense period of ice-block falls from the mid-April to the beginning of May; 2) a period of constant activity, mainly during the two first weeks of May; and 3) isolated residual activity, with a low frequency of ice-block falls until the month of June. The snow avalanche days were mainly characterized by significant snowfalls or rain-on-snow events with temperature>0°C. The multi-hazard probability was then evaluated based on the timing and relative frequency of ice-block fall and the modeling of sufficient snowpack for avalanching. This simple method to assess the synergistic effect of hillslope processes allows a better understanding of the spring avalanche regime related to the collapse of ice structures. These findings are expected to assist in the management of natural hazards and to improve our knowledge of spatiotemporal dynamics of mass-wasting events on highways.
MAG ID: 2205881108

Logistic models as a forecasting tool for snow avalanches in a cold maritime climate: northern Gaspésie, Québec, Canada - Gauthier, F.; Germain, Daniel; Hétu, Bernard (Natural Hazards, 2017)
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.
MAG ID: 2625362830

Extreme weather events in northeastern New Brunswick (Canada) for the period 1950–2012: Comparison of newspaper archive and weather station data - Mallet, Julie; Fortin, Guillaume; Germain, Daniel (Canadian Geographer, 2018)
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.
MAG ID: 2762324269