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The paper describes the development of predictive equations of windthrow for five tree species based on remote sensing of wind-affected stands in southwestern New Brunswick (NB). The data characterises forest conditions before, during and after the passing of extratropical cyclone Arthur, July 4–5, 2014. The five-variable logistic function developed for balsam fir (bF) was validated against remote-sensing-acquired windthrow data for bF-stands affected by the Christmas Mountains windthrow event of November 7, 1994. In general, the prediction of windthrow in the area agreed fairly well with the windthrow sites identified by photogrammetry. The occurrence of windthrow in the Christmas Mountains was prominent in areas with shallow soils and prone to localised accelerations in mean and turbulent airflow. The windthrow function for bF was subsequently used to examine the future impact of windthrow under two climate scenarios (RCP’s 4.5 and 8.5) and species response to local changes anticipated with global climate change, particularly with respect to growing degree-days and soil moisture. Under climate change, future windthrow in bF stands (2006–2100) is projected to be modified as the species withdraws from the high-elevation areas and NB as a whole, as the climate progressively warms and precipitation increases, causing the growing environment of bF to deteriorate.

With the record breaking flood experienced in Canada’s capital region in 2017 and 2019, there is an urgent need to update and harmonize existing flood hazard maps and fill in the spatial gaps between them to improve flood mitigation strategies. To achieve this goal, we aim to develop a novel approach using machine learning classification (i.e., random forest). We used existing fragmented flood hazard maps along the Ottawa River to train a random forest classification model using a range of flood conditioning factors. We then applied this classification across the Capital Region to fill in the spatial gaps between existing flood hazard maps and generate a harmonized high-resolution (1 m) 100 year flood susceptibility map. When validated against recently produced 100 year flood hazard maps across the capital region, we find that this random forest classification approach yields a highly accurate flood susceptibility map. We argue that the machine learning classification approach is a promising technique to fill in the spatial gaps between existing flood hazard maps and create harmonized high-resolution flood susceptibility maps across flood-vulnerable areas. However, caution must be taken in selecting suitable flood conditioning factors and extrapolating classification to areas with similar characteristics to the training sites. The resulted harmonized and spatially continuous flood susceptibility map has wide-reaching relevance for flood mitigation planning in the capital region. The machine learning approach and flood classification optimization method developed in this study is also a first step toward Natural Resources Canada’s aim of creating a spatially continuous flood susceptibility map across the Ottawa River watershed. Our modeling approach is transferable to harmonize flood maps and fill in spatial gaps in other regions of the world and will help mitigate flood disasters by providing accurate flood data for urban planning.

Ce travail de recherche a pour objectif d’évaluer le risque d’inondation printanier à Rigaud (Québec, Canada), en faisant une analyse de cas de l’inondation historique du printemps 2017. Dans la première partie de ce mémoire, une analyse des conditions météorologiques printanières dans le bassin versant de la rivière des Outaouais (BVRO) est d’abord réalisée à partir des données météorologiques sous forme de grille (DAYMET) à 1 km de résolution (1980 à 2017), mais également à partir des données météorologiques de stations d’Environnement et Changement climatique Canada (1963 à 2017). La sévérité des aléas d’inondation à Rigaud (1963 à 2019) est ensuite évaluée en termes d’ampleur de l’aléa hydrologique et des dommages potentiels associés. Dans la seconde partie de ce mémoire,l’exposition au risque d’inondation à Rigaud ainsi que les conditions socio-environnementales contribuant à exacerber le risque d’inondation à l’exutoire du bassin sont caractérisées. Une analyse multicritère qui tient compte de la pente, de la capacité de drainage des sols et de l’utilisation du sol en plus des caractéristiques de l’aléa météorologique dans le BVRO permet d’estimer la contribution des sous-bassins versants (SBV) à l’inondation printanière de 2017 à Rigaud. Au printemps 2017, le dégel brusque du début avril ainsi que le caractère exceptionnellement intense et régulier des événements de précipitation liquide aux mois d’avril et mai, généralisés sur l’ensemble du BVRO, ont contribué en partie à la sévérité de l’inondation. Ces facteurs météorologiques ont eu des conséquences importantes sur l’occurrence et l’intensité de l’inondation durant ces mois, d’autant plus que les conditions les plus extrêmes se sont produites dans les SBV les plus près de l’exutoire et les plus vulnérables, compte tenu de leurs fortes pentes et des modifications importantes au territoire engendrées par les activités humaines entre 1990 et 2010. L’indice de sévérité révèle que les inondations de 2017 et de 2019 se distinguent des autres inondations majeures en raison de l’intensité des débits journaliers enregistrés à l’exutoire du BVRO sur une durée de plus de 40 jours, alors que les dernières inondations historiques de 1974 et 1976 ont plutôt enregistré des niveaux d’eau records à l’exutoire du bassin. À Rigaud, l’exposition au risque d’inondation s’est également accrue entre 1970 et 2017, en raison du développement de l’aménagement périurbain (infrastructure et construction résidentielle) au cours de ces années, résultant en un potentiel de dommages beaucoup plus important lors des événements récents de 2017 et 2019. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : inondation, risque d’inondation, aléa, facteurs de risque, conditions socioenvironnementales, conditions hydrométéorologiques, exposition, bassin versant de la rivière des Outaouais, Rigaud

Abstract This study confronts the new concept of ‘surface storage’ with the old concept of ‘sponge effect’ to explain the spatio-temporal variability of the annual daily maximum flows measured in 17 watersheds of southern Quebec during the period 1930–2019. The new concept takes into account the hydrological impacts of wetlands and other topographic components of the landscape (lakes, depressions, ditches, etc.) while that of the sponge effect only takes into account the hydrological impacts of wetlands. With regard to spatial variability, the area of wetlands and other water bodies is the variable best correlated negatively with the magnitude but positively with the duration of flows. As for the temporal variability, the application of the long-term trend tests revealed a significant increase in the magnitude and, to a lesser extent, the duration of the flows occurring in the watersheds of the north shore characterized by a greater area of wetlands and other water bodies (>5%). This increase is explained by the fact that the storage capacity of these land types, which remains unchanged over time, does not make it possible to store the surplus runoff water brought by the increase in rainfall during the snowmelt season.

Abstract Quebec is experiencing a significant increase in summer and fall temperatures and rainfall. This study compares the spatiotemporal variability of maximum daily flows generated by rainfall during the fall season (September–December) in relation to this climatic change and physiographic and land use factors. Analysis of the spatial variability of these maximum flows measured from 1930 to 2018 in 17 watersheds revealed that the magnitude of flows is approximately twice as low on the north shore as it is on the south shore south of 47° N. This difference is explained by three main factors: wetlands (negative correlation) and agricultural (positive correlation) surface area, and summer–fall total precipitation (positive correlation). As for the temporal variability of flows, the different Mann–Kendall statistical tests showed a significant increase in flows due to increased rainfall. The increase of flows was more widespread on the north shore than on the south because the storage capacity of wetlands and other water bodies does not change over time to store excess rainfall. On the south shore, the increase in flows over time is limited due to the significant reduction in agricultural areas since the modernization of agriculture. This reduction favored infiltration to the detriment of runoff.

Abstract The objective of this study is to compare the spatiotemporal variability of seasonal daily mean flows measured in 17 watersheds, grouped into three homogeneous hydroclimatic regions, during the period 1930–2023 in southern Quebec. With regard to spatial variability, unlike extreme daily flows, seasonal daily mean flows are very poorly correlated with physiographic factors and land use and land cover. In fall, they are not correlated with any physiographic or climatic factor. In winter, they are positively correlated with the rainfall and winter daily mean maximum temperatures. In spring, they are strongly correlated positively with the snowfall but negatively with the spring daily mean maximum temperatures. However, in summer, they are better correlated with forest area and, to a lesser extent, with the rainfall. As for their temporal variability, the application of six different statistical tests revealed a general increase in daily mean flows in winter due to early snowmelt and increased rainfall in fall. In summer, flows decreased significantly in the snowiest hydroclimatic region on the south shore due to the decrease in the snowfall. In spring, no significant change in flows was globally observed in the three hydroclimatic regions despite the decrease in the snowfall due to the increase in the rainfall. In fall, flows increased significantly south of 47°N on both shores due to the increase in the rainfall. This study demonstrates that, unlike extreme flows, the temporal variability of seasonal daily average flows is exclusively influenced by climatic variables in southern Quebec. Due to this influence, seasonal daily mean flows thus appear to be the best indicator for monitoring the impacts of changes in precipitation regimes and seasonal temperatures on river flows in southern Quebec.

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.

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.

Modifications to land can serve to jointly reduce risks of floods and droughts to people and to ecosystems. Whether land modifications are implemented will depend on the willingness and ability of a diversity of actors. This article reviews the state of knowledge on land modification use in areas exposed to dual hydrologic risks and the land owners, managers, and users who directly make decisions about action on lands they control. The review presents a typology of land modifications and explains how land modifications interact with the hydrological cycle to reduce risks. It then addresses the roles and perspectives of the land owners, managers, and users undertaking land modifications, summarizing theories explaining motivations for, as well as barriers to and enablers of, land modification implementation. The analysis reveals geographical differences in narratives on land modifications as well as knowledge gaps regarding variation across actors and types of land modifications.