A Flood Risk Management Model to Identify Optimal Defence Policies in Coastal Areas Considering Uncertainties in Climate Projections - Cioffi, Francesco; De Bonis Trapella, Alessandro; Giannini, Mario; Lall, Upmanu (Water, 2022)
Coastal areas are particularly vulnerable to flooding from heavy rainfall, sea storm surge, or a combination of the two. Recent studies project higher intensity and frequency of heavy rains, and progressive sea level rise continuing over the next decades. Pre-emptive and optimal flood defense policies that adaptively address climate change are needed. However, future climate projections have significant uncertainty due to multiple factors: (a) future CO2 emission scenarios; (b) uncertainties in climate modelling; (c) discount factor changes due to market fluctuations; (d) uncertain migration and population growth dynamics. Here, a methodology is proposed to identify the optimal design and timing of flood defense structures in which uncertainties in 21st century climate projections are explicitly considered probabilistically. A multi-objective optimization model is developed to minimize both the cost of the flood defence infrastructure system and the flooding hydraulic risk expressed by Expected Annual Damage (EAD). The decision variables of the multi-objective optimization problem are the size of defence system and the timing of implementation. The model accounts for the joint probability density functions of extreme rainfall, storm surge and sea level rise, as well as the damages, which are determined dynamically by the defence system state considering the probability and consequences of system failure, using a water depth–damage curve related to the land use (Corine Land Cover); water depth due to flooding are calculated by hydraulic model. A new dominant sorting genetic algorithm (NSGAII) is used to solve the multi-objective problem optimization. A case study is presented for the Pontina Plain (Lazio Italy), a coastal region, originally a swamp reclaimed about a hundred years ago, that is rich in urban centers and farms. A set of optimal adaptation policies, quantifying size and timing of flood defence constructions for different climate scenarios and belonging to the Pareto curve obtained by the NSGAII are identified for such a case study to mitigate the risk of flooding and to aid decision makers.

The Roles of Climate Risk Dynamics and Adaptation Limits in Adaptation Assessment - Bouwer, Laurens M. (Springer climate, 2022)
Abstract The performance of adaptation measures depends on their robustness against various possible futures, with varying climate change impacts. Such impacts are driven by both climatic as well as non-climatic drivers. Risk dynamics are then important, as the avoided risk will determine the benefits of adaptation actions. It is argued that the integration of information on changing exposure and vulnerability is needed to make projections of future climate risk more realistic. In addition, many impact and vulnerability studies have used a top-down rather a technical approach. Whether adaptation action is feasible is determined by technical and physical possibilities on the ground, as well as local capacities, governance and preference. These determine the hard and soft limits of adaptation. Therefore, it is argued that the risk metrics outputs alone are not sufficient to predict adaptation outcomes, or predict where adaptation is feasible or not; they must be placed in the local context. Several of the current climate risk products would fall short of their promise to inform adaptation decision-making on the ground. Some steps are proposed to improve adaptation modelling in order to better incorporate these aspects.

Déterminants de l'intention d'adoption d'un nouvel outil prévisionnel des crues dans le cadre du projet info-crue - Mutabazi, Jean-Paul (Université du Québec à Rimouski, 2022)
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.

Empirical Rainfall Thresholds for Landslide Occurrence in Serra do Mar, Angra dos Reis, Brazil - Germain, Daniel; Roy, Sébastien; Jose Teixera Guerra, Antonio (Landslides, 2022)
In the tropical environment such as Brazil, the frequency of rainfall-induced landslides is particularly high because of the rugged terrain, heavy rainfall, increasing urbanization, and the orographic effect of mountain ranges. Since such landslides repeatedly interfere with human activities and infrastructures, improved knowledge related to spatial and temporal prediction of the phenomenon is of interest for risk management. This study is an analysis of empirical rainfall thresholds, which aims to establish local and regional scale correlations between rainfall and the triggering of landslides in Angra dos Reis in the State of Rio de Janeiro. A statistical analysis combining quantile regression and binary logistic regression was performed on 1640 and 526 landslides triggered by daily rainfall over a 6-year period in the municipality and the urban center of Angra dos Reis, in order to establish probabilistic rainfall duration thresholds and assess the role of antecedent rainfall. The results show that the frequency of landslides is highly correlated with rainfall events, and surprisingly the thresholds in dry season are lower than those in wet season. The aspect of the slopes also seems to play an important role as demonstrated by the different thresholds between the southern and northern regions. Finally, the results presented in this study provide new insight into the spatial and temporal dynamics of landslides and rainfall conditions leading to their activation in this tropical and mountainous environment.

Two-Phase Flow Modeling for Bed Erosion by a Plane Jet Impingement - Pham Van Bang, Damien; Uh Zapata, Miguel; Gauthier, Georges; Gondret, Philippe; Zhang, Wei; Nguyen, Kim Dan (Water, 2022)
This paper presents experimental and numerical studies on the erosion of a horizontal granular bed by a two-dimensional plane vertical impinging jet to predict the eroded craters’ size scaling (depth and width). The simulations help understand the microscopic processes that govern erosion in this complex flow. A modified jet-bed distance, accounting for the plane jet virtual origin, is successfully used to obtain a unique relationship between the crater size and a local Shields parameter. This work develops a two-phase flow numerical model to reproduce the experimental results. The numerical techniques are based on a finite volume formulation to approximate spatial derivatives, a projection technique to calculate the pressure and velocity for each phase, and a staggered grid to avoid spurious oscillations. Different options for the sediment’s solid-to-liquid transition during erosion are proposed, tested, and discussed. One model is based on unified equations of continuum mechanics, others on modified closure equations for viscosity or momentum transfer. A good agreement between the numerical solutions and the experimental measurements is obtained.
Keywords: PhamVanBang_Damien

A Novel Statistical Modeling Approach to Developing IDF Relations in the Context of Climate Change - Nguyen, Van-Thanh-Van; Nguyen, Truong-Huy (Journal of Water Management Modeling, 2022)
Extreme rainfall intensity–duration–frequency (IDF) relations have been commonly used for estimating the design storm for the design of various urban water infrastructures. In recent years, climate change has been recognized as having a profound impact on the hydrologic cycle. Hence, the derivation of IDF relations in the context of a changing climate has been recognized as one of the most challenging tasks in current engineering practice. The main challenge is how to establish the linkages between the climate projections given by climate models at the global or regional scales and the observed extreme rainfalls at a local site of interest. Therefore, our overall objective is to introduce a new statistical modeling approach to linking global or regional climate predictors to the observed daily and sub-daily rainfall extremes at a given location. Illustrative applications using climate simulations from 21 different global climate models and extreme rainfall data available from rain gauge networks located across Canada are presented to indicate the feasibility, accuracy, and robustness of the proposed modeling approach for assessing the climate change impact on IDF relations.
Keywords: Infolettre; Infolettre_Septembre_2022; Site_internet_RIISQ

Uncertainty in three dimensions: the challenges of communicating probabilistic flood forecasts maps - Jean, Valérie; Boucher, Marie-Amélie; Frini, Anissa; Roussel, Dominic (2022)
Abstract. Real time operational flood forecasting most often concentrates on issuing streamflow predictions at specific points along the rivers of a watershed. Those points often coincide with gauging stations, and the forecasts can eventually be compared with the corresponding observations for post-event analysis. We are now witnessing an increasing number of studies aimed at also including flood mapping as part of the forecasting system, by feeding the forecasted streamflow to a hydraulics model. While this additional new information (flood extent, depth, velocity, etc.) can potentially be useful for decision makers, it also has the potential to be overwhelming. This is especially true for probabilistic and ensemble forecasting systems. While ensemble streamflow forecasts for a given point in space can be visualized relatively easily, the visualization and communication of probabilistic forecasts for water depth and extent brings additional challenges. The uncertainty becomes three dimensional and it becomes difficult to convey all the important information to support decision-making, while a confusion that could arise from too much information, counter-intuitive interpretation, or simply too much complexity in the representation of the forecast. In this paper, we synthesize the results of a large-scale survey across multiple categories of users of hydrological forecasts (28 government representatives, 52 municipalities, 9 organizations, 37 citizens and farmers, for a total of 139 persons) regarding their preferences in terms of visualizing probabilistic flood forecasts over an entire river reach. Those users have different roles and realities, which influence their needs and preferences. The survey was performed through individual and group interviews during which the interviewees were asked about their needs in terms of hydrological forecasting and their preferences in terms of communication and visualization of the information. In particular, we presented the interviewees with four prototypes representing alternative visualizations of the same probabilistic forecast in order to understand their preferences in terms of colour maps, wording, and the representation of uncertainty. Our results highlight several issues related to the understanding of probabilities in the specific context of visualizing forecasted flood maps. We propose several suggestions for visualizing probabilistic flood maps in order to convey all the relevant information while limiting the confusion of decision makers, and also describe several potential adaptations for different categories of end users.
Keywords: Infolettre; Infolettre_Mars_2024