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Atmospheric methane (CH4) concentrations have increased to 2.5 times their pre-industrial levels, with a marked acceleration in recent decades. CH4 is responsible for approximately 30% of the global temperature rise since the Industrial Revolution. This growing concentration contributes to environmental degradation, including ocean acidification, accelerated climate change, and a rise in natural disasters. The column-averaged dry-air mole fraction of methane (XCH4) is a crucial indicator for assessing atmospheric CH4 levels. In this study, the Sentinel-5P TROPOMI instrument was employed to monitor, map, and estimate CH4 concentrations on both regional and global scales. However, TROPOMI data exhibits limitations such as spatial gaps and relatively coarse resolution, particularly at regional scales or over small areas. To mitigate these limitations, a novel Convolutional Neural Network Autoencoder (CNN-AE) model was developed. Validation was performed using the Total Carbon Column Observing Network (TCCON), providing a benchmark for evaluating the accuracy of various interpolation and prediction models. The CNN-AE model demonstrated the highest accuracy in regional-scale analysis, achieving a Mean Absolute Error (MAE) of 28.48 ppb and a Root Mean Square Error (RMSE) of 30.07 ppb. This was followed by the Random Forest (RF) regressor (MAE: 29.07 ppb; RMSE: 36.89 ppb), GridData Nearest Neighbor Interpolator (NNI) (MAE: 30.06 ppb; RMSE: 32.14 ppb), and the Radial Basis Function (RBF) Interpolator (MAE: 80.23 ppb; RMSE: 90.54 ppb). On a global scale, the CNN-AE again outperformed other methods, yielding the lowest MAE and RMSE (19.78 and 24.7 ppb, respectively), followed by RF (21.46 and 27.23 ppb), GridData NNI (25.3 and 32.62 ppb), and RBF (43.08 and 54.93 ppb).

ABSTRACT Urbanization is leading to more frequent flooding as cities have more impervious surfaces and runoff exceeds the capacity of combined sewer systems. In heavy rainfall, contaminated excess water is discharged into the natural environment, damaging ecosystems and threatening drinking water sources. To address these challenges aggravated by climate change, urban blue-green water management systems, such as bioretention cells, are increasingly being adopted. Bioretention cells use substrate and plants adapted to the climate to manage rainwater. They form shallow depressions, allowing infiltration, storage, and gradual evacuation of runoff. In 2018, the City of Trois-Rivières (Québec, Canada) installed 54 bioretention cells along a residential street, several of which were equipped with access points to monitor performance. Groundwater quality was monitored through the installation of piezometers to detect potential contamination. This large-scale project aimed to improve stormwater quality and reduce sewer flows. The studied bioretention cells reduced the flow and generally improved water quality entering the sewer system, as well as the quality of stormwater, with some exceptions. Higher outflow concentrations were observed for contaminants such as manganese and nitrate. The results of this initiative provide useful recommendations for similar projects for urban climate change adaptation.

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.

Questions have been raised about the correctness of water quality models with complete mixing assumptions in cross junctions of water distribution systems. Recent developments in the mixing phenomenon within cross junctions of water distribution networks (WDNs) have heightened the need for evaluating the existing incomplete mixing models under real-world conditions. Therefore, in this study, two cross junctions with pipe diameters of 100 Â 100 Â 100 Â 100 mm and 150 Â 150 Â 150 Â 150 mm were employed in laboratory experiments to evaluate six existing incomplete mixing models for 25 flow rate scenarios ranging between 1.5 and 3.0 L/s. It was observed that within the same flow rate scenario, the degree of mixing in a cross junction with a pipe relative roughness of 6.00 Â 10À5 (pipe diameter of 25 mm) was higher than that in a cross junction with a pipe relative roughness of 3.00 Â 10À5 (pipe diameter of 50 mm) and smaller. Considering the real-world size of pipes in evaluating the incomplete mixing models showed that two incomplete mixing models, AZRED and the one by Shao et al., had the best accordance with the results of the laboratory experiments.

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.

In recent years, understanding and improving the perception of flood risk has become an important aspect of flood risk management and flood risk reduction policies. The aim of this study was to explore perceptions of flood risk in the Petite Nation River watershed, located in southern Quebec, Canada. A survey was conducted with 130 residents living on a floodplain in this river watershed, which had been affected by floods in the spring of 2017. Participants were asked about different aspects related to flood risk, such as the flood hazard experience, the physical changes occurring in the environment, climate change, information accessibility, flood risk governance, adaptation measures, and finally the perception of losses. An analysis of these factors provided perspectives for improving flood risk communication and increasing the public awareness of flood risk. The results indicated that the analyzed aspects are potentially important in terms of risk perception and showed that the flood risk perceptions varied for each aspect analyzed. In general, the information regarding flood risk management is available and generally understandable, and the level of confidence was good towards most authorities. However, the experiences of flood risk and the consequences of climate change on floods were not clear among the respondents. Regarding the adaptation measures, the majority of participants tended to consider non-structural adaptation measures as being more relevant than structural ones. Moreover, the long-term consequences of flooding on property values are of highest concern. These results provide a snapshot of citizens’ risk perceptions and their opinions on topics that are directly related to such risks.

In Canada, flooding is the most common and costly natural hazard. Flooding events significantly impact communities, damage infrastructures and threaten public security. Communication, as part of a flood risk management strategy, is an essential means of countering these threats. It is therefore important to develop new and innovative tools to communicate the flood risk with citizens. From this perspective, the use of story maps can be very effectively implemented for a broad audience, particularly to stakeholders. This paper details how an interactive web-based story map was set up to communicate current and future flood risks in the Petite-Nation River watershed, Quebec (Canada). This web technology application combines informative texts and interactive maps on current and future flood risks in the Petite-Nation River watershed. Flood risk and climate maps were generated using the GARI tool, implemented using a geographic information system (GIS) supported by ArcGIS Online (Esri). Three climate change scenarios developed by the Hydroclimatic Atlas of Southern Quebec were used to visualize potential future impacts. This study concluded that our story map is an efficient flood hazard communication tool. The assets of this interactive web mapping tool are numerous, namely user-friendly mapping, use and interaction, and customizable displays.

Floods are the most common natural hazard worldwide. GARI is a flood risk management and analysis tool that is being developed by the Environmental and Nordic Remote Sensing Group (TENOR) of INRS in Quebec City (Canada). Beyond mapping the flooded areas and water levels, GARI allows for the estimation, analysis and visualization of flood risks for individuals, residential buildings, and population. Information can therefore be used during the different phases of flood risk management. In the operational phase, GARI can use satellite radar images to map in near real-time the flooded areas and water levels. It uses an innovative approach that combines Radarsat-2 and hydraulic data, specifically flood return period data. Information from the GARI enable municipalities and individuals to anticipate the impacts of a flood in a given area, to mitigate these impacts, to prepare, and to better coordinate their actions during a flood.

Abstract Measuring freshwater submerged aquatic vegetation (SAV) biomass at large spatial scales is challenging, and no single technique can cost effectively accomplish this while maintaining accuracy. We propose to combine and intercalibrate accurate quadrat‐scuba diver technique, fast rake sampling, and large‐scale echosounding. We found that the overall relationship between quadrat and rake biomass is moderately strong (pseudo R 2  = 0.61) and varies with substrate type and SAV growth form. Rake biomass was also successfully estimated from biovolume (pseudo R 2  = 0.57), a biomass proxy derived from echosounding. In addition, the relationship was affected, in decreasing relevance, by SAV growth form, flow velocity, acoustic data quality, depth, and wind conditions. Sequential application of calibrations yielded predictions in agreement with quadrat observations, but echosounding predictions underestimated biomass in shallow areas (< 1 m) while outperforming point estimation in deep areas (> 3 m). Whole‐system quadrat‐equivalent biomass from echosounding differed by a factor of two from point survey estimates, suggesting echosounding is more accurate at larger scales owing to the increased sample size and better representation of spatial heterogeneity. To decide when an individual or a combination of techniques is profitable, we developed a step‐by‐step guideline. Given the risks of quadrat‐scuba diver technique, we recommend developing a one‐time quadrat–rake calibration, followed by the use of rake and echosounding when sampling at larger spatial and temporal scales. In this case, rake sampling becomes a valid ground truthing method for echosounding, also providing valuable species information and estimates in shallow waters where echosounding is inappropriate.

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.

Abstract Integrating hydrogeomorphological (HGM) principles into the restoration of degraded rivers can achieve sustainable results and provide various human benefits. HGM principles mainly involve understanding the context and processes that shape a fluvial system before any intervention, in order to support its dynamism and to align with its potential functioning and uses. Despite recent management approaches inspired by HGM principles, most restoration projects carried out in Quebec (Canada) are not process‐based and target specific one‐dimensional objectives. Although there is an overall lack of post‐project monitoring, several projects appear to have failed or had mixed success. This research aims to shed light on the diversity of societal drivers behind river restoration projects and to examine how they influence the integration of HGM principles and human benefits. Four restoration projects were characterized through participant observation and interviews with the organizations running them. Representatives of two ministries involved in river restoration and management were also interviewed. The results show that projects were mainly shaped by public acceptance disregarding HGM principles, which can lead to poorly‐informed action. Project funding and stakeholders' expertise have also challenged project implementation and played a key role in defining their objectives. The addition of these components improve the current analytical frameworks for identifying river restoration objectives. Depending on specific sociocultural, political and legislative contexts, funding programs and stakeholders' expertise may either facilitate or restrict the integration of HGM principles and human benefits in the projects. Recognizing these key drivers reframes river restoration as a fundamentally social activity and enlightens how they could impel innovative approaches towards more sustainable results.

&lt;p&gt;Spring floods have generated colossal damages to residential areas in the Province of Quebec, Canada, in 2017 and 2019. Government authorities need accurate modelling of the impact of theoretical floods in order to prioritize pre-disaster mitigation projects to reduce vulnerability. They also need accurate modelling of forecasted floods in order to direct emergency responses.&amp;#160;&lt;/p&gt;&lt;p&gt;We present a governmental-academic collaboration that aims at modelling flood impact for both theoretical and forecasted flooding events over all populated river reaches of meridional Quebec. The project, funded by the minist&amp;#232;re de la S&amp;#233;curit&amp;#233; publique du Qu&amp;#233;bec (Quebec ministry in charge of public security), consists in developing a diagnostic tool and methods to assess the risk and impacts of flooding. Tools under development are intended to be used primarily by policy makers.&amp;#160;&lt;/p&gt;&lt;p&gt;The project relies on water level data based on the hydrological regimes of nearly 25,000 km of rivers, on high-precision digital terrain models, and on a detailed database of building footprints and characterizations. It also relies on 24h and 48h forecasts of maximum flow for the subject rivers. The developed tools integrate large data sets and heterogeneous data sources and produce insightful metrics on the physical extent and costs of floods and on their impact on the population. The software also provides precise information about each building affected by rising water, including an estimated cost of the damages and impact on inhabitants.&amp;#160;&amp;#160;&lt;/p&gt;

The goal of this study is to compare the seasonal variability of 12 physicochemical characteristics of waters in the Ottawa and St. Lawrence Rivers (SLR). Water samples were collected on board the research vessel Lampsillis in the spring (May), summer (August), and fall (October) of 2006 at four stations located downstream from the confluence of the two rivers. Temperature and total nitrogen values varied significantly for the three seasons. In contrast, seasonal values of light extinction coefficient and turbidity do not show any significant variation. The values of the other characteristics varied significantly only for one season. Comparison of these data with those measured in 1994–1996 reveals a net warming of the waters and a significant increase in nitrite-nitrate concentrations due to the increasing use of nitrogen-bearing fertilizers by farmers in Quebec. Concentrations of these two substances are higher than the limits set by the government of Quebec for water quality in rivers.

&lt;p&gt;In snow-prone regions, snowmelt is one of the main drivers of runoff. For operational flood forecasting and mitigation, the spatial distribution of snow water equivalent (SWE) in near real time is necessary. In this context, in situ observations of SWE provide a valuable information. Nonetheless, the high spatial variability of snowpack characteristics makes it necessary to implement some kind of snow modelling to get a spatially continuous estimation. Data assimilation is thus a useful approach to combine information from both observation and modeling in near real-time. &lt;/p&gt;&lt;p&gt;For example, at the provincial government of Quebec (eastern Canada), the HYDROTEL Snowpack Model is applied on a daily basis over a 0.1 degree resolution mesh covering the whole province. The modelled SWE is corrected in real time by in situ manual snow survey which are assimilated using a spatial particles filter (Cantet et al., 2019). This assimilation method improves the reliability of SWE estimation at ungauged sites.&lt;/p&gt;&lt;p&gt;The availability of manual snow surveys is however limited both in space and time. These measurements are conducted on a bi-weekly basis in a limited number of sites. In order to further improve the temporal and spatial observation coverage, alternative sources of data should be considered.&lt;/p&gt;&lt;p&gt;In this research, it is hypothesized that data gathered by SR50 sonic sensors can be assimilated in the spatial particle filter to improve the SWE estimation. These automatic sensors provide hourly measurements of snow depth and have been deployed in Quebec since 2005. Beforehand, probabilistic SWE estimations were derived from the SR50 snow depth measurements using an ensemble of artificial neural networks (Odry et al. 2019). Considering the nature of the data and the conversion process, the uncertainty associated with this dataset is supposed larger than for the manual snow surveys. The objective of the research is to evaluate the potential interest of adding this lower-quality information in the assimilation framework.&lt;/p&gt;&lt;p&gt;The addition of frequent but uncertain data in the spatial particle filter required some adjustments in term of assimilation frequency and particle resampling. A reordering of the particles was implemented to maintain the spatial coherence between the different particles. With these changes, the consideration of both manual snow surveys and SR50 data in the spatial particle filter reached performances that are comparable to the initial particle filter that combines only the model and manual snow survey for estimating SWE in ungauged sites. However, the addition of SR50 data in the particle filter allows for continuous information in time, between manual snow surveys.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Cantet, P., Boucher, M.-A., Lachance-Coutier, S., Turcotte, R., Fortin, V. (2019). Using a particle filter to estimate the spatial distribution of the snowpack water equivalent. J. Hydrometeorol, 20.&lt;/p&gt;&lt;p&gt;Odry, J., Boucher, M.-A., Cantet,P., Lachance-Cloutier, S., Turcotte, R., St-Louis, P.-Y. (2019). Using artificial neural networks to estimate snow water equivalent from snow depth. Canadian water ressources journal (under review)&lt;/p&gt;

Abstract Flood quantile estimation at sites with little or no data is important for the adequate planning and management of water resources. Regional Hydrological Frequency Analysis (RFA) deals with the estimation of hydrological variables at ungauged sites. Random Forest (RF) is an ensemble learning technique which uses multiple Classification and Regression Trees (CART) for classification, regression, and other tasks. The RF technique is gaining popularity in a number of fields because of its powerful non-linear and non-parametric nature. In the present study, we investigate the use of Random Forest Regression (RFR) in the estimation step of RFA based on a case study represented by data collected from 151 hydrometric stations from the province of Quebec, Canada. RFR is applied to the whole data set and to homogeneous regions of stations delineated by canonical correlation analysis (CCA). Using the Out-of-bag error rate feature of RF, the optimal number of trees for the dataset is calculated. The results of the application of the CCA based RFR model (CCA-RFR) are compared to results obtained with a number of other linear and non-linear RFA models. CCA-RFR leads to the best performance in terms of root mean squared error. The use of CCA to delineate neighborhoods improves considerably the performance of RFR. RFR is found to be simple to apply and more efficient than more complex models such as Artificial Neural Network-based models.

Floods, intensified by climate change, pose major challenges for flood zone management in Quebec. This report addresses these issues through two complementary aspects: a historical analysis of the evolution of flood zone management in Quebec and the projected impact of the cartographic and regulatory overhaul, as well as an exploration of the imaginary surrounding the flood-prone territory of the city of Lachute, which has faced recurrent floods for decades and yet continues to be inhabited. The historical analysis reveals that the major floods of 1974, 1976, 2017, and 2019 marked significant turning points in Quebec’s risk management, particularly by highlighting gaps in the regulatory framework and flood zone mapping. The adoption of the Act Respecting Land Use Planning and Development (LAU) in 1979 and the Policy for the Protection of Shorelines, Littorals, and Floodplains (PPRLPI) in 1987 represented a shift toward a preventive approach. However, inconsistencies, insufficient updates to maps, and uneven enforcement of standards have hindered their effectiveness. The catastrophic floods of 2017 and 2019 triggered a regulatory overhaul, a modernization of mapping, and measures to strengthen community resilience. In 2022, a transitional regime came into effect to tighten the regulation of activities in flood zones, pending the adoption of a risk-based management framework. However, to this day, the regulatory perimeters proposed in the modernization project fail to account for the adaptive capacities deployed by communities to live with water, thus providing a biased interpretation of flood risk. The second part explores the social and cultural representations associated with Lachute’s flood-prone territory. It highlights the complex relationships that have developed between residents and the Rivière du Nord through successive flooding episodes and the adaptation strategies implemented to cope, particularly by those who have repeatedly experienced flooding. These residents have come to live with overflow events and to (co)exist with water, challenging the persistent notion that flood-prone areas are inherently dangerous. While local strategies are sometimes innovative, they remain constrained by a regulatory framework that disregards the human experience of the territory and the specific ways in which people inhabit exposed areas to learn to manage flood risks. In summary, this report underscores the urgency of a territorialized, risk-based approach to modernizing flood zone management. It also highlights the need to look beyond cartographic boundaries and better integrate human and cultural dimensions into planning policies, as illustrated in the case of Lachute, to more accurately reflect the true level of risk. These reflections aim to promote more coherent, sustainable, and acceptable management, planning, and development of exposed territories in response to the growing challenges posed by climate change.

Earthquakes pose potentially substantial risks to residents in the Western Quebec seismic zone of eastern Canada, where Ottawa and Montreal are located. In eastern Canada, the majority of houses are not constructed to modern seismic standards and most homeowners do not purchase earthquake insurance for their homes. If a devastating earthquake strikes, homeowners would be left unprotected financially. To quantify financial risks to homeowners in the Western Quebec seismic zone, regional earthquake catastrophe models are developed by incorporating up-to-date public information on hazard, exposure and vulnerability. The developed catastrophe models can quantify the expected and upper-tail financial seismic risks by considering a comprehensive list of possible seismic events as well as critical earthquake scenarios based on the latest geological data in the region. The results indicate that regional seismic losses could reach several tens of billions of dollars if a moderate-to-large earthquake occurs near urban centres in the region, such as Montreal and Ottawa. The regional seismic loss estimates produced in this study are useful for informing earthquake risk management strategies, including earthquake insurance and disaster relief policies.

Abstract. Groundwater contribution to river flows, generally called base flows, often accounts for a significant proportion of total flow rate, especially during the dry season. The objective of this work is to test simple approaches requiring limited data to understand groundwater contribution to river flows. The Noire river basin in southern Quebec is used as a case study. A lumped conceptual hydrological model (the MOHYSE model), a groundwater flow model (MODFLOW) and hydrograph separation are used to provide estimates of base flow for the study area. Results show that the methods are complementary. Hydrograph separation and the MOHYSE surface flow model provide similar annual estimates for the groundwater contribution to river flow, but monthly base flows can vary significantly between the two methods. Both methods have the advantage of being easily implemented. However, the distinction between aquifer contribution and shallow subsurface contribution to base flow can only be made with a groundwater flow model. The aquifer renewal rate estimated with the MODFLOW model for the Noire River is 30% of the recharge estimated from base flow values. This is a significantly difference which can be crucial for regional-scale water management.

RÉSUMÉ : Pour atténuer les risques d'inondation au Québec mais aussi partout dans le monde, plusieurs organismes gouvernementaux et des organismes privés, qui ont dans leurs attributions la gestion des risques des catastrophes naturelles, continuent d'améliorer ou d'innover en matière d'outils qui peuvent les aider efficacement à la mitigation des risques d'inondation et aider la société à mieux s'adapter aux changements climatiques, ce qui implique des nouvelles technologies pour la conception de ces outils. Après les inondations de 2017, le ministère de l'Environnement et de la Lutte contre les changements climatiques (MELCC) du gouvernement du Québec, en collaboration avec d'autres ministères et organismes et soutenu par Ouranos, a initié le projet INFO-Crue qui vise d'une part, à revoir la cartographie des zones inondables et, d'autre part, à mieux outiller les communautés et les décideurs en leur fournissant une cartographie prévisionnelle des crues de rivières. De ce fait, l'objectif de notre travail de recherche est d'analyser de façon empirique les facteurs qui influencent l'adoption d'un outil prévisionnel des crues. La revue de la littérature couvre les inondations et les prévisions, les théories et les modèles d'acceptation de la technologie de l'information (TI). Pour atteindre l'objectif de recherche, le modèle développé s'est appuyé particulièrement sur le modèle qui combine les concepts de la théorie unifiée de l'acceptation et l'utilisation des technologies (UTAUT) de Venkatesh et al. (2003) avec le concept « risque d'utilisation ». Afin de répondre à notre objectif de recherche, nous avons utilisé une méthodologie de recherche quantitative hypothético-déductive. Une collecte de données à l'aide d'une enquête par questionnaire électronique a été réalisée auprès de 106 citoyens qui habitent dans des zones inondables. L'analyse des résultats concorde avec la littérature. La nouvelle variable « risque d'utilisation » rajoutée au modèle UTAUT a engendré trois variables qui sont : « risque psychologique d'utilisation »; « risque de performance de l'outil » et « perte de confiance ». Pour expliquer l'adoption d'un nouvel outil prévisionnel des crues, notre analyse a révélé que cinq variables à savoir : « l'utilité perçue », « la facilité d'utilisation », « l'influence sociale », « la perte de confiance » et « le risque psychologique » sont des facteurs significatifs pour l'adoption du nouvel outil prévisionnel. -- Mot(s) clé(s) en français : Inondation, Prévision, UTAUT, Adoption de la technologie, Risque perçu d'utilisation, facteurs d'adoption, Projet INFO-Crue. -- ABSTRACT : With the aim of mitigating flood risks in Canada as well as around the world, several government and private organizations that have the responsibility of natural hazard risk management, are working hard to improve or innovate the flood mitigation approaches that can help effectively reducing flood risks and helping people adapt to climate change. After the 2017 floods, the Ministry of the Environment and the Fight against Climate Change (MELCC) of the Government of Quebec, in collaboration with other ministries and organizations and supported by Ouranos, initiated the INFO-Crue project which aims at reviewing the mapping of flood zones and providing communities and decision-makers with a forecast mapping of river floods. In this context, the objective of our research is to analyze the factors that may influence the adoption of a flood forecasting tool. The literature review covers flood and forecasting, as well as technology adoption models. To achieve the goal of our research, a conceptual model that combines the Unified Theory of Acceptance and Use of Technology (UTAUT) of Venkatesh et al. (2003) with perceived use risk was developed. A quantitative research methodology was used, and we administrate an electronic questionnaire survey to 106 citizens who live in flood-plain area. Results analysis show that the new variable "perceived use risk" introduced in the model generates three variables which are: "psychological risk"; "performance risk" and "loss of trust". To explain the adoption of a new forecasting tool, our analysis revealed that the following five variables which are "perceived usefulness", "ease of use­", "social influence", "loss of trust" and "psychological risk" are significant factors for the adoption of the new forecasting tool. -- Mot(s) clé(s) en anglais : Flood, Forecasting, UTAUT, Technology Adoption, perceived Risk of use, adoption factors, INFO-Crue project.

Au Québec, les conditions printanières extraordinaires de 2017 et 2019 ont incité le gouvernement provincial à commander une mise à jour des cartes des zones inondables. La plupart des cartes existantes ne reflètent pas adéquatement l’aménagement actuel du territoire, ni l’aléa associé. Généralement, pour la cartographie, les modèles hydrodynamiques tel que HEC-RAS sont utilisés, mais ces outils nécessitent une expertise significative, des données hydrométriques et des relevés bathymétriques à haute résolution. Étant donnée la nécessité de mettre à jour ces cartes tout en réduisant les coûts financiers associés, des méthodes conceptuelles simplifiées ont été développées. Ces approches, y compris l’approche géomatique HAND (Height above the nearest drainage), qui reposent uniquement sur un modèle numérique d’élévation (MNE), sont de plus en plus utilisées. HAND permet de calculer la hauteur d’eau nécessaire pour inonder chaque pixel du MNE selon la différence entre son élévation et celle du pixel du cours d’eau dans lequel il se déverse. Les informations sur la géométrie hydraulique dérivées par HAND ainsi que l’application de l’équation de Manning permettent la construction d’une courbe de tarage synthétique (CTS) pour chaque tronçon de rivière homogène. Dans la littérature, cette méthode a été appliquée pour établir une cartographie de la zone inondable de première instance de grands fleuves aux États-Unis avec un taux de correspondance de 90% par rapport à l’utilisation de HEC-RAS. Elle n’a toutefois pas été appliquée sur de petits bassins versants, car ceux-ci engendrent des défis méthodologiques substantiels. Ce projet s’attaque à ces défis sur deux bassins versants Québécois, ceux des rivières à la Raquette et Delisle. Les conditions frontières des modèles sont dérivées d’un traitement statistique empirique des séries de débits simulés avec le modèle hydrologique HYDROTEL. Étant donnée l’absence de stations météorologiques sur le territoire à l’étude, des chroniques du système Canadien d’Analyse de la précipitation (CaPA) ont été utilisées pour cette modélisation hydrologique. Les résultats de ce projet pointent vers des performances satisfaisantes de l’approche géomatique HAND-CTS en comparaison avec le modèle hydrodynamique HEC-RAS (1D/2D et 2D au complet), avec des taux de correspondance entre les étendues des inondations supérieurs à 60 % pour les bassins versants de Delisle et à la Raquette. Les comparaisons étaient effectuées sur une gamme de débit allant d’un débit de période de retour de 2 ans jusqu’à un débit de plus de 350 ans. On notera que l’application sur la rivière à la Raquette a été développée dans les règles de l’art, incluant un processus de calage développé dans le cadre d’un projet de maitrise en sciences de l’eau connexe à ce mémoire, relativement à la longueur du tronçon, le calage vertical de la CTS en considérant la hauteur d’eau présente dans le cours d’eau lors du relevé LiDAR et sa précision verticale. Les résultats ont montré que le coefficient de précision globale le plus bas était de 98 % pour un débit de 350 ans, avec une précision de plus que 99 % pour les autres périodes de retour, ce qui représente une très bonne performance du modèle. Et par ailleurs, le coefficient de Kappa conditionnel humide variait entre 58 % et 28 %. Alors, que pour la rivière Delisle, l’application se veut naïve, c’est-à-dire sans calage préalable de la méthode HANDCTS. La précision globale a varié entre 83 % et 96 %, ce qui est considéré comme "très approprié" et une variation du coefficient Kappa conditionnel humide de 35,2 à 64,3 %. Alors que pour une différence d’élévations d'eau entre les élévations de référence et simulées, la performance était quantifiée par un RMSE qui variait pour les périodes de retour de 100 ans et de 350 ans respectivement de 4,5 m et de 7,1 m. Enfin, la distribution spatiale des différences d’élévations montre une distribution gaussienne avec une moyenne qui est à peu près égale à 0 où la plupart des erreurs se situent entre -0,34 m et 1,1 m La cartographie des zones inondables dérivée de HAND-CTS présente encore certains défis associés notamment à la présence d’infrastructures urbaines complexes (ex. : ponceaux, ponts et seuils) dont l’influence hydraulique n’est pas considérée. Dans le contexte où l’ensemble du Québec (529 000 km²) dispose d’une couverture LiDAR, les résultats de ce mémoire permettront de mieux comprendre les sources d’incertitude associées à la méthode HAND-CTS tout en démontrant son potentiel pour les bassins versants dépourvus de données bathymétriques et hydrométéorologiques. <br /><br />The 2017 and 2019 extraordinary spring conditions prompted the Quebec government to update flood risk maps, as most of them do not adequately reflect current land use and associated hazard. Generally, hydrodynamic models such as HEC-RAS are used for flood mapping, but they require significant expertise, hydrometric data, and high-resolution bathymetric surveys. Given the need to update these maps while reducing the associated financial costs, simplified conceptual methods have been developed over the last decade. These methods are increasingly used, including HAND (height above the nearest drainage), which relies on a Digital Elevation Model (DEM) to delineate the inundation area given the water height in a river segment. Furthermore, the river geometry derived from HAND data and the application of Manning’s equation allow for the construction of a synthetic rating curve (SRC) for each homogeneous river segment. In the scientific literature, this framework has been applied to produce first-instance floodplain mapping of large rivers. For example, in the Continental United States 90% match rates were achieved when compared to the use of HEC-RAS. However, this framework has not been validated for small watersheds, as substantial methodological challenges are anticipated. This project addresses these underlying challenges in two Quebec watersheds, the à la Raquette and Delisle watersheds. The boundary conditions of the HECRAS models were derived from an empirical statistical treatment of flow time series simulated by HYDROTEL, a hydrological model, using Canadian Precipitation Analysis Product (CaPA) time series. The results of this project point towards satisfactory performances, with match rates greater than 60 % for both watersheds. It should be noted that the application on the Delisle River is naive, that is without prior calibration of the HAND-SRC method. The overall accuracy ranged from 83.4 % to 96.2 % while the water surface elevation difference was quantified by an RMSE that was for the 100-year and 350-year return periods of 4.5 m and 7.1 m respectively and where most errors are between -0.34 m and 1.1 m representing a very good model comparing to similar studies. For à la Raquette, the application showed an overall accuracy coefficient of 98 % for a 350-year flow, with an accuracy of over 99 % for other return periods. The mapping of flood risk areas using HAND-SRC still faces certain challenges, notably the presence of complex urban infrastructures (e.g., culverts, bridges, and weirs) whose hydraulic influences are not considered by this geomatic approach. Given that most of Quebec (529,000 km²) topography has been digitized using LiDAR data, the results conveyed in this MSc thesis will allow for a better understanding of the sources of uncertainty associated with the application of the HAND-SRC method while demonstrating its potential for watersheds lacking hydrometeorological and high-resolution bathymetric data.