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Abstract Background Relating the geographical distribution of intermediate freshwater snail hosts (viz. vectors of schistosomes) to local environmental attributes offers value for understanding the epidemiological landscape of schistosomiasis transmission in a changing aquatic environment. Schistosomiasis—both urogenital and intestinal—causes significant human suffering, affecting approximately 240 million people globally and grouped within the neglected tropical disease (NTD) umbrella. This study addresses the following questions: 1. Where are the most suitable habitats for intermediate host snails in the Lower Shire Valley (LSV) in Malawi? 2. Which environmental factors are strongly associated with the geographical distribution of such snails in the LSV? Methods This paper presents the first species distribution models (SDMs) for intermediate snail hosts for urogenital and intestinal schistosomiasis in Chikwawa and Nsanje Districts, which together form the LSV). The SDMs developed for this study are ensemble machine learning approaches based on Random Forest (RF), Support Vector Machines (SVM), and multilayer perceptron (MLP) and are specific to the Bulinus africanus group and Biomphalaria pfeifferi . The former transmits urogenital schistosomiasis ( Schistosoma haematobium ), while the latter transmits intestinal schistosomiasis ( Schistosoma mansoni ). Results The SDMs reveal the following: 1) currently, Bu. africanus group not only has a wide distribution across central Chikwawa and eastern Nsanje but is also concentrated in floodplains, and the LSV has few habitats that can support Bi. pfeifferi , and 2) vegetation cover is the most important predictor of Bu. africanus group distribution, whereas precipitation variables are most important for Bi. pfeifferi in the LSV. Thus, Bu. africanus group habitat is the most dominant and abundant, while Bi. pfeifferi suitable habitat is patchy and scarce. Conclusion The distribution of suitable habitats for potential urogenital and intestinal schistosomiasis transmission across LSV is not uniform and typically non-overlapping. Understanding the spatial and temporal distributions of these snails is important for controlling and eliminating schistosomiasis. Graphical Abstract

Urban soil sealing and anthropogenic activities, combined with the increasing intensity of rainfall due to climate change, is a threat to urban environments, exacerbating flood risks. To assess these challenges, Low Impact Development strategies, based on Nature-based solutions, are a key solution to mitigate urban flooding. To enhance the hydrological performance of LID infrastructure, and to meet the guideline requirements related to emptying time, specifically in low hydraulic conductivity soils, earthworm activity and vegetation dynamics can play a major role. The ETAGEP experimental site was built to study to address those challenges. 12 swales (10 m2 infiltration area for each swale) were monitored to evaluate the impact of earthworm activity (A. caliginosa and L. terrestris) and vegetation dynamics (Rye Grass, Petasites hybridus and Salix alba) to enhance the hydrological performance. The infiltration rate of the swales evolved in a differentiated manner, with an increase of 16.1 % to 310.8 % and draining times decrease of 13.9 % to 75.7, depending on initial soil hydro-physical properties and the impervious areas of the catchment which influence runoff volumes. The simulations on SWMM software showed similar results, with an enhancement of the hydraulic conductivity of N6 swales (60 m2 total catchment area) increasing from 18 mm h−1 to 25 mm h−1, and a reduction of drawdown time by 24.4 % (N6) and 20.8 % (N11–110 m2 active surface). A simulated storm event of 44.8 mm resulted in an overflow of 2.12 m3 for the N11 swale configuration, while no overflow was observed for N6. These results highlight the ecosystem services of earthworms for a sustainable stormwater management in urban environments, enhancing the hydrological performance of LID infrastructures and reducing therefore flood risks and limiting pressure on drainage network. © 2025 The Author(s)

This study introduces a novel methodology for assessing ice-jam flood hazards along river channels. It employs empirical equations that relate non-dimensional ice-jam stage to discharge, enabling the generation of an ensemble of longitudinal profiles of ice-jam backwater levels through Monte-Carlo simulations. These simulations produce non-exceedance probability profiles, which indicate the likelihood of various flood levels occurring due to ice jams. The flood levels associated with specific return periods were validated using historical gauge records. The empirical equations require input parameters such as channel width, slope, and thalweg elevation, which were obtained from bathymetric surveys. This approach is applied to assess ice-jam flood hazards by extrapolating data from a gauged reach at Fort Simpson to an ungauged reach at Jean Marie River along the Mackenzie River in Canada’s Northwest Territories. The analysis further suggests that climate change is likely to increase the severity of ice-jam flood hazards in both reaches by the end of the century. This methodology is applicable to other cold-region rivers in Canada and northern Europe, provided similar fluvial geomorphological and hydro-meteorological data are available, making it a valuable tool for ice-jam flood risk assessment in other ungauged areas. © 2025 by the authors.

The flood disasters are prevalent in the Ganga–Brahmaputra (GB) basin with recurrent occurrences and severe impacts across the major watersheds. The present study analyses the vulnerability of 44 watersheds to flood inundation and its impact on cropland, urban areas, and population. The Sentinel-1 dataset was utilised to analyse flood extent and frequency from 2015 to 2022, enabling the identification of flood-prone watersheds in the Ganga–Brahmaputra basin. The analysis revealed that 7 watersheds in the Ganga basin and 12 watersheds in the Brahmaputra basin are particularly vulnerable to flooding. The flood hazard analysis was performed using fuzzy-AHP (Analytic Hierarchy Process), focusing on six parameters, including topographic wetness index (TWI), elevation, precipitation, drainage density, distance from river, and NDVI for the selected 19 watersheds. The inundation analysis from 2015 to 2022 revealed that the maximum flood extent was observed in 2020, with an affected area of 33,537.6 km2 and 34,937.9 km2 in the Ganga–Brahmaputra basin, respectively. The flood hazard analysis identified Upper Ganga (8877.52 km2), Ghaghara (18573.9 km2) and Teesta (1543.06 km2) as having the highest proportion of their geographical area under very high-hazard zone and the highest percentage in the very low hazard zones were observed in Jamuneshwary (1093.55 km2), Atreyee (4410.42 km2), and Kulsi (1273.89 km2). By first mapping these watersheds with precision and then using various parameters for flood hazard analysis, it ensures accurate identification of flood-prone areas, offering valuable insights for flood management and mitigation in a critical region. © Indian Academy of Sciences 2025.

Les événements météorologiques extrêmes (EME) et les désastres qu’ils entrainent provoquent des conséquences psychosociales qui sont modulées en fonction de différents facteurs sociaux. On constate aussi que les récits médiatiques et culturels qui circulent au sujet des EME ne sont pas représentatifs de l’ensemble des expériences de personnes sinistrées : celles qui en subissent les conséquences les plus sévères tendent aussi à être celles qu’on « entend » le moins dans l’espace public. Ces personnes sont ainsi susceptibles de vivre de l’injustice épistémique, ce qui a des effets délétères sur le soutien qu’elles reçoivent. Face à ces constats s’impose la nécessité de mieux comprendre la diversité des expériences d’EME et d’explorer des stratégies pour soutenir l’ensemble des personnes sinistrées dans leur rétablissement psychosocial. Cet article soutient que la recherche narrative peut contribuer à répondre à ces objectifs. En dépeignant des réalités multiples, la recherche narrative centrée sur les récits de personnes sinistrées présente aussi un intérêt significatif pour l’amélioration des pratiques d’intervention en contexte de désastre. , Extreme weather events (EWE) and their resulting disasters cause psychosocial consequences that are moderated by different social factors. Media and cultural accounts of EWEs do not represent the full range of disaster survivor experiences, that is, those who experienced the most severe consequences also tend to be those least “heard” in the public arena. These people are therefore most likely to experience forms of epistemic injustice that negatively impact the support offered to cope with disaster. Considering these findings, there is a need to better understand the diversity of EWE experiences and explore strategies for supporting all disaster survivors in their psychosocial recovery. This article argues that narrative research can help meet these needs. By portraying the multiple realities of people affected by EWEs, narrative research focusing on the stories of disaster survivors is also of significant interest for improving intervention practices in this context.

Abstract Real-time precipitation data are essential for weather forecasting, flood prediction, drought monitoring, irrigation, fire prevention, and hydroelectric management. To optimize these activities, reliable precipitation estimates are crucial. Environment and Climate Change Canada (ECCC) leads the Canadian Precipitation Analysis (CaPA) project, providing near-real-time precipitation estimates across North America. However, during winter, CaPA’s 6-hourly accuracy is limited because many automatic surface observations are not assimilated due to wind-induced gauge undercatch. The objective of this study is to evaluate the added value of adjusted hourly precipitation amounts for gauge undercatch due to wind speed in CaPA. A recent ECCC dataset of hourly precipitation measurements from automatic precipitation gauges across Canada is included in CaPA as part of this study. Precipitation amounts are adjusted based on several types of transfer functions, which convert measured precipitation into what high-quality equipment would have measured with reduced undercatch. First, there are no notable differences in CaPA when comparing the performance of the universal transfer function with that of several climate-specific transfer functions based on wind speed and air temperature. However, increasing solid precipitation amounts using a specific type of transfer function that depends on snowfall intensity rather than near-surface air temperature is more likely to improve CaPA’s precipitation estimates during the winter season. This improvement is more evident when the objective evaluation is performed with direct comparison with the Adjusted Daily Rainfall and Snowfall (AdjDlyRS) dataset.

AbstractThe frequency and severity of floods has increased in different regions of the world due to climate change. Although the impact of floods on human health has been extensively studied, the increase in the segments of the population that are likely to be impacted by floods in the future makes it necessary to examine how adaptation measures impact the mental health of individuals affected by these natural disasters. The goal of this scoping review is to document the existing studies on flood adaptation measures and their impact on the mental health of affected populations, in order to identify the best preventive strategies as well as limitations that deserve further exploration. This study employed the methodology of the PRISMA-ScR extension for scoping reviews to systematically search the databases Medline and Web of Science to identify studies that examined the impact of adaptation measures on the mental health of flood victims. The database queries resulted in a total of 857 records from both databases. Following two rounds of screening, 9 studies were included for full-text analysis. Most of the analyzed studies sought to identify the factors that drive resilience in flood victims, particularly in the context of social capital (6 studies), whereas the remaining studies analyzed the impact of external interventions on the mental health of flood victims, either from preventive or post-disaster measures (3 studies). There is a very limited number of studies that analyze the impact of adaptation measures on the mental health of populations and individuals affected by floods, which complicates the generalizability of their findings. There is a need for public health policies and guidelines for the development of flood adaptation measures that adequately consider a social component that can be used to support the mental health of flood victims.

Combined sewer surcharges in densely urbanized areas have become more frequent due to the expansion of impervious surfaces and intensified precipitation caused by climate change. These surcharges can generate system overflows, causing urban flooding and pollution of urban areas. This paper presents a novel methodology to mitigate sewer system surcharges and control surface water. In this methodology, flow control devices and urban landscape retrofitting are proposed as strategies to reduce water inflow into the sewer network and manage excess water on the surface during extreme rainfall events. For this purpose, a 1D/2D dual drainage model was developed for two case studies located in Montreal, Canada. Applying the proposed methodology to these two sites led to a reduction of the volume of wastewater overflows by 100% and 86%, and a decrease in the number of surface overflows by 100% and 71%, respectively, at the two sites for a 100-year return period 3-h Chicago design rainfall. It also controlled the extent of flooding, reduced the volume of uncontrolled surface floods by 78% and 80% and decreased flooded areas by 68% and 42%, respectively, at the two sites for the same design rainfall.

This paper presents a new framework for floodplain inundation modeling in an ungauged basin using unmanned aerial vehicles (UAVs) imagery. This method is based on the integrated analysis of high-resolution ortho-images and elevation data produced by the structure from motion (SfM) technology. To this end, the Flood-Level Marks (FLMs) were created from high-resolution UAV ortho-images and compared to the flood inundated areas simulated using the HEC-RAS hydraulic model. The flood quantiles for 25, 50, 100, and 200 return periods were then estimated by synthetic hydrographs using the Natural Resources Conservation Service (NRCS). The proposed method was applied to UAV image data collected from the Khosban village, in Taleghan County, Iran, in the ungauged sub-basin of the Khosban River. The study area is located along one kilometre of the river in the middle of the village. The results showed that the flood inundation areas modeled by the HEC-RAS were 33%, 19%, and 8% less than those estimated from the UAV’s FLMs for 25, 50, and 100 years return periods, respectively. For return periods of 200 years, this difference was overestimated by more than 6%, compared to the UAV’s FLM. The maximum flood depth in our four proposed scenarios of hydraulic models varied between 2.33 to 2.83 meters. These analyses showed that this method, based on the UAV imagery, is well suited to improve the hydraulic modeling for seasonal inundation in ungauged rivers, thus providing reliable support to flood mitigation strategies

Geohazards associated with the dynamics of the liquid and solid water of the Earth’s hydrosphere, such as floods and glacial processes, may pose significant risks to populations, activities and properties [...]

Les inondations de 2017 et 2019 au Québec ont affecté respectivement 293 et 240 municipalités. Ces inondations ont généré une cascade d’évènements stressants (stresseurs primaires et secondaires) qui ont eu des effets sur la santé mentale de la population et retardé le processus de rétablissement des individus. Cette période de rétablissement peut s’échelonner sur plusieurs mois voire plusieurs années. Cette étude s’inscrit dans la spécificité de la recherche mixte mise de l’avant à travers trois stratégies de recherche, réalisées de façon séquentielle : 1) sondage populationnelle réalisé auprès de 680 personnes, 2) analyse de documents produits par les organisations participant au processus de rétablissement social des sinistrés, ou sur des analyses externes portant sur ces interventions de rétablissement et 3) entrevues semi-dirigées auprès de 15 propriétaires occupants ayant complété une demande d’indemnisation à la suite des inondations de 2019 et auprès de 11 professionnels et gestionnaires participant au processus de rétablissement social. Les entrevues semi-dirigées et les questionnaires complétés par les personnes sinistrées lors des inondations de 2019 démontrent que les principales sources de stress ayant des impacts sur la santé et le bien-être des répondants sont : 1) l’absence d’avertissement et la vitesse de la montée des eaux; 2) l’obligation de se relocaliser et la peur d’être victime de pillage; 3) le manque de solidarité et d’empathie de la part de certains employés du MSP; 4) la gestion des conflits familiaux; 5) la gestion de problèmes de santé nouveaux ou préexistants; 6) la complexité des demandes d’indemnisation; 7) la lourdeur et les délais des travaux de nettoyage ou de restauration; 8) les indemnités inférieures aux coûts engendrés par l’inondation; 9) les pertes matérielles subies, particulièrement ceux d’une valeur de plus de 50 000 $; et 10) la diminution anticipée de la valeur de sa résidence. À cela s’ajoute l’insatisfaction à l’égard du programme d’indemnisation du gouvernement du Québec (PGIAF) qui fait plus que doubler la prévalence des symptômes de stress post-traumatique. Les inondations entraînent également une perte de satisfaction ou de bien-être statistiquement significative. La valeur monétaire de cette perte de jouissance peut être exprimée en équivalent salaires. En moyenne, cette diminution du bien-être équivaut à une baisse de salaire de 60 000$ pour les individus ayant vécu une première inondation et à 100 000$ pour les individus ayant vécu de multiples inondations. Ces résultats suggèrent que les coûts indirects et intangibles représentent une part importante des dommages découlant des inondations. Ce projet de recherche vise également à analyser l’application du PGIAF et son influence sur les stresseurs vécus par les sinistrés dans le contexte de la pandémie de COVID-19. La principale recommandation de cette étude repose sur une analyse de documents, un sondage populationnel et des entrevues semi-dirigées. Ainsi, s’attaquer à la réduction de principaux stresseurs nécessite 1) d’améliorer la gouvernance du risque d’inondation, 2) d’intensifier la communication et le support aux sinistrés, et 3) de revoir les mécanismes d’indemnisation existants.

Résumé L'hydrogéomorphologie étudie la dynamique des rivières en se concentrant sur les interactions liant la structure des écoulements, la mobilisation et le transport des sédiments et les morphologies qui caractérisent les cours d'eau et leur bassin‐versant. Elle offre un cadre d'analyse et des outils pour une meilleure intégration des connaissances sur la dynamique des rivières pour la gestion des cours d'eau au sens large, et plus spécifiquement, pour leur restauration, leur aménagement et pour l'évaluation et la prévention des risques liés aux aléas fluviaux. Au Québec, l'hydrogéomorphologie émerge comme contribution significative dans les approches de gestion et d'évaluation du risque et se trouve au cœur d'un changement de paradigme dans la gestion des cours d'eau par lequel la restauration des processus vise à augmenter la résilience des systèmes et des sociétés et à améliorer la qualité des environnements fluviaux. Cette contribution expose la trajectoire de l'hydrogéomorphologie au Québec à partir des publications scientifiques de géographes du Québec et discute des visées de la discipline en recherche et en intégration des connaissances pour la gestion des cours d'eau . , Abstract Hydrogeomorphology studies river dynamics, focusing on the interactions between flow structure, sediment transport, and the morphologies that characterize rivers and their watersheds. It provides an analytical framework and tools for better integrating knowledge of river dynamics into river management in the broadest sense, and more specifically, into river restoration as well as into the assessment and prevention of risks associated with fluvial hazards. In Quebec, hydrogeomorphology is emerging as a significant contribution to risk assessment and management approaches, and is at the heart of a paradigm shift in river management whereby process restoration aims to increase the resilience of fluvial systems and societies, and improve the quality of fluvial environments. This contribution outlines the trajectory of hydrogeomorphology in Quebec, based on scientific publications by Quebec geographers, and discusses the discipline's aims in research and knowledge integration for river management . , Messages clés Les géographes du Québec ont contribué fortement au développement des connaissances et outils de l'hydrogéomorphologie. L'hydrogéomorphologie a évolué d'une science fondamentale à une science où les connaissances fondamentales sont au service de la gestion des cours d'eau. L'hydrogéomorphologie et le cortège de connaissances et d'outils qu'elle promeut font de cette discipline une partenaire clé pour une gestion holistique des cours d'eau.

Dans le bassin-versant de la rivière Chaudière, les inondations sont partie intégrante de la réalité territoriale. En effet, de nombreuses études ont été réalisées dans les dernières années concernant les inondations en eau libre et par embâcle. Néanmoins, on observe que les inondations torrentielles, ou crues torrentielles, bien qu’omniprésentes dans la région, sont très peu documentées à ce jour. Le présent mémoire s’intéresse à la dynamique spatio-temporelle de ces évènements et aux facteurs aggravants présents sur le territoire qui tendent à amplifier le phénomène. Par une double approche qualitative et quantitative, qui combine une recension historique, la caractérisation des sous-bassins-versants et la modélisation des facteurs de vulnérabilité environnementale, nous avons dressé un premier portrait de l’aléa torrentiel à l’échelle du bassin-versant de la rivière Chaudière. Ainsi, nous avons pu répertorier 53 évènements à caractère torrentiel pour la période de 1900 à aujourd’hui. La collecte des informations liées aux crues torrentielles, soit les facteurs météorologiques, anthropiques et géomorphologiques ont permis d’établir des constats généraux quant à l’occurrence de celles-ci. L’occurrence des évènements à caractère torrentiel semble premièrement liée aux passages d’évènements météorologiques extrêmes. Les facteurs aggravants consistent en un aménagement du territoire qui accroît le ruissellement (augmentation des surfaces minéralisées et diminution des forêts, prairies et milieux humides) et une disposition géomorphologique des tributaires (forte pente et compacité) qui provoque une amplification du ruissellement lors de fortes précipitations. L’analyse multicritère repose sur l’addition d’indices amplifiant le ruissellement lors de fortes précipitations (pente, occupation du sol et potentiel de ruissellement). La comparaison entre les sous-bassins-versants présentant les valeurs les plus élevées et ceux ayant connu le plus d'événements d'inondation selon la recension historique a démontré la pertinence de cette méthode pour identifier, de manière préliminaire, les sous-bassins-versants potentiellement vulnérables à l’aléa torrentiel. Cette étude se veut donc un premier jalon dans l’acquisition de connaissances sur la dynamique torrentielle dans le bassin-versant de la rivière Chaudière. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : inondation, torrents, crues torrentielles, pluies torrentielles, aléas torrentiels, bassin-versant de la rivière Chaudière, facteurs aggravants, conditions hydrométéorologiques

The interaction of water flow, ice, and structures is common in fluvial ice processes, particularly around Ice Control Structures (ICSs) that are used to manage and prevent ice jam floods. To evaluate the effectiveness of ICSs, it is essential to understand the complex interaction between water flow, ice and the structure. Numerical modeling is a valuable tool that can facilitate such understanding. Until now, classical Eulerian mesh-based methods have not been evaluated for the simulation of ice interaction with ICS. In this paper we evaluate the capability, accuracy, and efficiency of a coupled Computational Fluid Dynamic (CFD) and multi-body motion numerical model, based on the mesh-based FLOW-3D V.2023 R1 software for simulation of ice-structure interactions in several benchmark cases. The model’s performance was compared with results from meshless-based models (performed by others) for the same laboratory test cases that were used as a reference for the comparison. To this end, simulation results from a range of dam break laboratory experiments were analyzed, encompassing varying numbers of floating objects with distinct characteristics, both in the presence and absence of ICS, and under different downstream water levels. The results show that the overall accuracy of the FLOW-3D model under various experimental conditions resulted in a RMSE of 0.0534 as opposed to an overall RMSE of 0.0599 for the meshless methods. Instabilities were observed in the FLOW-3D model for more complex phenomena that involve open boundaries and a larger number of blocks. Although the FLOW-3D model exhibited a similar computational time to the GPU-accelerated meshless-based models, constraints on the processors speed and the number of cores available for use by the processors could limit the computational time.

Abstract. The amount and phase of cold season precipitation accumulating in the upper Saint John River basin are critical factors in determining spring runoff, ice-jams, and flooding in downstream communities. To study the impact of winter and spring storms on the snowpack in the upper Saint John River (SJR) basin, the Saint John River Experiment on Cold Season Storms (SAJESS) utilized meteorological instrumentation, upper air soundings, human observations, and hydrometeor macrophotography during winter/spring 2020–21. Here, we provide an overview of the SAJESS study area, field campaign, and existing data networks surrounding the upper SJR basin. Initially, meteorological instrumentation was co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick, in early December 2020. This was followed by an intensive observation period that involved manual observations, upper-air soundings, a multi-angle snowflake camera, macrophotography of solid hydrometeors, and advanced automated instrumentation throughout March and April 2021. The resulting datasets include optical disdrometer size and velocity distributions of hydrometeors, micro rain radar output, near-surface meteorological observations, and wind speed, temperature, pressure and precipitation amounts from a K63 Hotplate precipitation gauge, the first one operating in Canada. These data are publicly available from the Federated Research Data Repository at https://doi.org/10.20383/103.0591 (Thompson et al., 2022). We also include a synopsis of the data management plan and data processing, and a brief assessment of the rewards and challenges of utilizing community volunteers for hydro-meteorological citizen science.

In cold regions, ice jams frequently result in severe flooding due to a rapid rise in water levels upstream of the jam. Sudden floods resulting from ice jams threaten human safety and cause damage to properties and infrastructure. Hence, ice-jam prediction tools can give an early warning to increase response time and minimize the possible damages. However, ice-jam prediction has always been a challenge as there is no analytical method available for this purpose. Nonetheless, ice jams form when some hydro-meteorological conditions happen, a few hours to a few days before the event. Ice-jam prediction can be addressed as a binary multivariate time-series classification. Deep learning techniques have been widely used for time-series classification in many fields such as finance, engineering, weather forecasting, and medicine. In this research, we successfully applied convolutional neural networks (CNN), long short-term memory (LSTM), and combined convolutional–long short-term memory (CNN-LSTM) networks to predict the formation of ice jams in 150 rivers in the province of Quebec (Canada). We also employed machine learning methods including support vector machine (SVM), k-nearest neighbors classifier (KNN), decision tree, and multilayer perceptron (MLP) for this purpose. The hydro-meteorological variables (e.g., temperature, precipitation, and snow depth) along with the corresponding jam or no-jam events are used as model inputs. Ten percent of the data were excluded from the model and set aside for testing, and 100 reshuffling and splitting iterations were applied to 80 % of the remaining data for training and 20 % for validation. The developed deep learning models achieved improvements in performance in comparison to the developed machine learning models. The results show that the CNN-LSTM model yields the best results in the validation and testing with F1 scores of 0.82 and 0.92, respectively. This demonstrates that CNN and LSTM models are complementary, and a combination of both further improves classification.

Abstract Collecting data on the dynamic breakup of a river's ice cover is a notoriously difficult task. However, such data are necessary to reconstruct the events leading to the formation of ice jams and calibrate numerical ice jam models. Photogrammetry using images from remotely piloted aircraft (RPA) is a cost-effective and rapid technique to produce large-scale orthomosaics and digital elevation maps (DEMs) of an ice jam. Herein, we apply RPA photogrammetry to document an ice jam that formed on a river in southern Quebec in the winter of 2022. Composite orthomosaics of the 2-km ice jam provided evidence of overbanking flow, hinge cracks near the banks and lengthy longitudinal stress cracks in the ice jam caused by sagging as the flow abated. DEMs helped identify zones where the ice rubble was grounded to the bed, thus allowing ice jam thickness estimates to be made in these locations. The datasets were then used to calibrate a one-dimensional numerical model of the ice jam. The model will be used in subsequent work to assess the risk of ice interacting with the superstructure of a low-level bridge in the reach and assess the likelihood of ice jam flooding of nearby residences.

Abstract Ice is present during a part of the year on many rivers of cold, and even temperate, regions of the globe. Though largely ignored in hydrological literature, river ice has serious hydrologic impacts, including extreme flood events caused by ice jams, interference with transportation and energy production, low winter flows and associated ecological and water quality consequences. It is also a major factor in the life cycle of many aquatic and other species, being both beneficial and destructive, depending on location and time of year. A brief review of the hydrologic aspects of river ice shows strong climatic links and illustrates the sensitivity of the entire ice regime to changes in climatic conditions. To date, this sensitivity has only partly been documented: the vast majority of related studies have focused on the timing of freeze‐up and break‐up over the past century, and indicate trends that are consistent with concomitant changes in air temperature. It is only in the past few years that attention has been paid to the more complex, and practically more important, question of what climatic change may do to the frequency and severity of extreme ice jams, floods and low flows. The probable changes to the ice regime of rivers, and associated hydrological processes and impacts, are discussed in the light of current understanding. Copyright © 2002 John Wiley & Sons, Ltd.

Abstract. Floods resulting from river ice jams pose a great risk to many riverside municipalities in Canada. The location of an ice jam is mainly influenced by channel morphology. The goal of this work was therefore to develop a simplified geospatial model to estimate the predisposition of a river channel to ice jams. Rather than predicting the timing of river ice breakup, the main question here was to predict where the broken ice is susceptible to jam based on the river's geomorphological characteristics. Thus, six parameters referred to potential causes for ice jams in the literature were initially selected: presence of an island, narrowing of the channel, high sinuosity, presence of a bridge, confluence of rivers, and slope break. A GIS-based tool was used to generate the aforementioned factors over regular-spaced segments along the entire channel using available geospatial data. An ice jam predisposition index (IJPI) was calculated by combining the weighted optimal factors. Three Canadian rivers (province of Québec) were chosen as test sites. The resulting maps were assessed from historical observations and local knowledge. Results show that 77 % of the observed ice jam sites on record occurred in river sections that the model considered as having high or medium predisposition. This leaves 23 % of false negative errors (missed occurrence). Between 7 and 11 % of the highly predisposed river sections did not have an ice jam on record (false-positive cases). Results, limitations, and potential improvements are discussed.

QUIC is a modern transport layer internet protocol designed to be more efficient and secure than TCP. It has gained popularity quickly in recent years and has been adopted by a number of prominent tech companies. Its efficiency comes from its handshake design. The server and the client make both the transport layer acknowledgment and the TLS agreement during the same round trip. However this process makes the packets heavy and requires more processing on the server-side than TCP. This characteristic can be used as leverage by an attacker to compromise the computing resources of its victim. This thesis investigates the resilience of QUIC Protocol against handshake flood attacks and proposes a detection mechanism (QUICShield). I conducted comprehensive experiments to evaluate the resource consumptions of both the attacker and the target during incomplete handshake attacks, including CPU, memory, and bandwidth. We compared the results against TCP Syn Cookies under Syn flood attacks. The DDoS amplification factor was measured and analyzed based on the results. This work also proposes a detection mechanism based on a Bloom filter combined with Generalized Likelihood Ratio Cumulative Sum (GLR-CUSUM) to adapt to evolving attack patterns. It was implemented and deployed against real attacks to evaluate its efficiency. We showed that the QUIC Protocol design has a much larger DDoS amplification factor compared to the TCP, which means QUIC is more vulnerable to handshake DDoS attacks. However the mechanism proposed is accurate and efficient in terms of resources.