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Abstract. One of the key priorities for disaster risk reduction is to ensure decision makers, stakeholders, and the public understand their exposure to disaster risk, so that they can take protective action. Flood maps are a potentially valuable tool for facilitating this understanding of flood risk, but previous research has found that they vary considerably in availability and quality. Using an evaluation framework comprising nine criteria grounded in existing scholarship, this study assessed the quality of flood maps available to the public in Canadian communities located in designated flood risk areas. It found that flood maps in most municipalities (62 %) are low quality (meeting less than 50 % of the criteria) and the highest score was 78 % (seven of nine criteria met). The findings suggest that a more concerted effort to produce high-quality, publicly accessible flood maps is required to support Canada's international commitment to disaster risk reduction. Further questions surround possible weighting of quality assessment criteria, whether and how individuals seek out flood maps, and how flood risk information could be better communicated using modern technology.

The potential impacts of floods are of significant concern to our modern society raising the need to identify and quantify all the uncertainties that can impact their simulations. Climate simulations at finer spatial resolutions are expected to bring more confidence in these hydrological simulations. However, the impact of the increasing spatial resolutions of climate simulations on floods simulations has to be evaluated. To address this issue, this paper assesses the sensitivity of summer–fall flood simulations to the Canadian Regional Climate Model (CRCM) grid resolution. Three climate simulations issued from the fifth version of the CRCM (CRCM5) driven by the ERA-Interim reanalysis at 0.44°, 0.22° and 0.11° resolutions are analysed at a daily time step for the 1981–2010 period. Raw CRCM5 precipitation and temperature outputs are used as inputs in the simple lumped conceptual hydrological model MOHYSE to simulate streamflows over 50 Quebec (Canada) basins. Summer–fall flooding is analysed by estimating four flood indicators: the 2-year, 5-year, 10-year and 20-year return periods from the CRCM5-driven streamflows. The results show systematic impacts of spatial resolution on CRCM5 outputs and seasonal flood simulations. Floods simulated with coarser climate datasets present smaller peak discharges than those simulated with the finer climate outputs. Smaller catchments show larger sensitivity to spatial resolution as more detail can be obtained from the finer grids. Overall, this work contributes to understanding the sensitivity of streamflow modelling to the climate model’s resolution, highlighting yet another uncertainty source to consider in hydrological climate change impact studies.

Soil moisture is a key variable in Earth systems, controlling the exchange of water and energy between land and atmosphere. Thus, understanding its spatiotemporal distribution and variability is important. Environment and Climate Change Canada (ECCC) has developed a new land surface parameterization, named the Soil, Vegetation, and Snow (SVS) scheme. The SVS land surface scheme features sophisticated parameterizations of hydrological processes, including water transport through the soil. It has been shown to provide more accurate simulations of the temporal and spatial distribution of soil moisture compared to the current operational land surface scheme. Simulation of high resolution soil moisture at the field scale remains a challenge. In this study, we simulate soil moisture maps at a spatial resolution of 100 m using the SVS land surface scheme over an experimental site located in Manitoba, Canada. Hourly high resolution soil moisture maps were produced between May and November 2015. Simulated soil moisture values were compared with estimated soil moisture values using a hybrid retrieval algorithm developed at Agriculture and Agri-Food Canada (AAFC) for soil moisture estimation using RADARSAT-2 Synthetic Aperture Radar (SAR) imagery. Statistical analysis of the results showed an overall promising performance of the SVS land surface scheme in simulating soil moisture values at high resolution scale. Investigation of the SVS output was conducted both independently of the soil texture, and as a function of the soil texture. The SVS model tends to perform slightly better over coarser textured soils (sandy loam, fine sand) than finer textured soils (clays). Correlation values of the simulated SVS soil moisture and the retrieved SAR soil moisture lie between 0.753–0.860 over sand and 0.676-0.865 over clay, with goodness of fit values between 0.567–0.739 and 0.457–0.748, respectively. The Root Mean Square Difference (RMSD) values range between 0.058–0.062 over sand and 0.055–0.113 over clay, with a maximum absolute bias of 0.049 and 0.094 over sand and clay, respectively. The unbiased RMSD values lie between 0.038–0.057 over sand and 0.039–0.064 over clay. Furthermore, results show an Index of Agreement (IA) between the simulated and the derived soil moisture always higher than 0.90.

Abstract The snow melt from the High Atlas represents a crucial water resource for crop irrigation in the semiarid regions of Morocco. Recent studies have used assimilation of snow cover area data from high‐resolution optical sensors to compute the snow water equivalent and snow melt in other mountain regions. These techniques however require large model ensembles, and therefore it is a challenge to determine the adequate model resolution that yields accurate results with reasonable computation time. Here we study the sensitivity of an energy balance model to the resolution of the model grid for a pilot catchment in the High Atlas. We used a time series of 8‐m resolution snow cover area maps with an average revisit time of 7.5 days to evaluate the model results. The digital elevation model was generated from Pléiades stereo images and resampled from 8 to 30, 90, 250, 500, and 1,000 m. The results indicate that the model performs well from 8 to 250 m but the agreement with observations drops at 500 m. This is because significant features of the topography were too smoothed out to properly characterize the spatial variability of meteorological forcing, including solar radiation. We conclude that a resolution of 250 m might be sufficient in this area. This result is consistent with the shape of the semivariogram of the topographic slope, suggesting that this semivariogram analysis could be used to transpose our conclusion to other study regions. , Key Points A distributed energy balance snow model is applied in the High Atlas for the first time The model performance decreases at resolution coarser than 250 m This result is consistent with the semivariogram of the topographic slope

La résilience, cette capacité d’une ville ou d’un environnement à maintenir sa structure, à s’organiser, apprendre et s’adapter aux chocs et stress, participe au mouvement de responsabilisation accrue du citoyen dans la protection contre les risques naturels. Si les inondations sont un phénomène récurrent à Montréal depuis la création même de la ville, les citoyens n’y sont encore que peu préparés comme le démontre l’ampleur des dommages causés par les inondations du printemps de 2017. Depuis le début du 21e siècle, les agences internationales et les États cherchent à sensibiliser le citoyen afin de susciter une action de sa part. On suppose alors que le citoyen informé aura ainsi une perception accrue des risques, conduisant au comportement de protection. Ce lien entre information, perception et comportement n’est pourtant pas évident. En réalité, la littérature montre que le comportement dépend d’une multiplicité de facteurs tels que l’expérience, la fréquence du risque ainsi qu’une évaluation par la personne de l’efficacité des mesures de protection, de leur coût face à une évaluation de la probabilité de la menace. Le mémoire vise à répondre à la question de recherche suivante : comment inciter les individus à adopter des mesures de protection contre les inondations à Montréal ? Une enquête auprès de 237 citoyens de quatre secteurs de l’agglomération touchés par les inondations printanières de 2017 met en lumière un ensemble d’obstacles à l’adoption des mesures de protection contre les inondations aujourd’hui analysés grâce au Protective Action Decision Model de Lindell et Perry (2012). Ainsi, dans le cas de Montréal, le manque d’action relève à la fois d’un manque d’information et de connaissances sur les origines du risque et les mesures de prévention, de la perception d’inefficacité des mesures comme la trousse 72 heures, d’une perception d’incapacité à mettre en place soi-même les mesures de prévention, et d’un coût important en ressources de ces dernières. Le dernier élément est l’incertitude de ce type de risque et l’incapacité à prévoir avec précision le prochain événement de crue, qui, combiné à un sentiment de responsabilité élevé des autorités à assurer la protection, implique un manque d’urgence à agir. Face à ces constats et après une étude du cas de la Nouvelle Orléans aux États-Unis, une réflexion est proposée sur les moyens à mettre en place pour inciter les citoyens à adopter ces mesures, comprenant sensibilisation mais aussi des moyens coercitifs et incitatifs.

Aim: The aim of the study was to investigate the health effect on and adaptation of the elderly affected by floods in the Lat Krabang District, Bangkok, Thailand in 2011.Methods: A cross-sectional descriptive study was conducted. Data were collected from 290 elderly participants who were affected by the floods using questionnaires.Results: The elderly participants had previous experience with flooding, but the massive flooding in 2011 was the most severe compared to any other experiences in the past. Physical health effects included muscle pain (35.2%), athlete’s foot (28.3%), and skin rash (23.1%). The psychological health effects (24.3%) encountered included insomnia, constant stress and tension, attention deficit, and discontentment. Most elderly (89.3%) decided not to relocate thinking they could still live at home, but they were concerned about the safety of their property. In regards to preparation for the flood, they prepared consumer goods, medication, and emergency kits. In addition, they kept abreast with news on television and public announcements in the community. They also helped clear the drainage system and prepared contact information of children, relatives, and government offices in case they needed assistance. Finally, to reduce possible damage to the property, they moved their belongings to high places, built sandbag walls, raised the house level, and prepared a water pump.Conclusion: The 2011 Thailand floods had adverse effects on physical and psychological health of the elderly people. To ensure better management for this vulnerable group, plans to respond to possible disasters need to be devised by relevant agencies to reduce flood-related health impacts.

Mapping the delineation of areas that are flooded due to water control infrastructure failure is a critical issue. Practical difficulties often present challenges to the accurate and effective analysis of dam-break hazard areas. Such studies are expensive, lengthy, and require large volumes of incoming data and refined technical skills. The creation of cost-efficient geospatial tools provides rapid and inexpensive estimates of instantaneous dam-break (due to structural failure) flooded areas that complement, but do not replace, the results of hydrodynamic simulations. The current study implements a Geographic Information System (GIS) based method that can provide useful information regarding the delineation of dam-break flood-prone areas in both data-scarce environments and transboundary regions, in the absence of detailed studies. Moreover, the proposed tool enables, without advanced technical skills, the analysis of a wide number of case studies that support the prioritization of interventions, or, in emergency situations, the simulation of numerous initial hypotheses (e.g., the modification of initial water level/volume in the case of limited dam functionality), without incurring high computational time. The proposed model is based on the commonly available data for masonry dams, i.e., dam geometry (e.g., reservoir capacity, dam height, and crest length), and a Digital Elevation Model. The model allows for rapid and cost-effective dam-break hazard mapping by evaluating three components: (i) the dam-failure discharge hydrograph, (ii) the propagation of the flood, and (iii) the delineation of flood-prone areas. The tool exhibited high accuracy and reliability in the identification of hypothetical dam-break flood-prone areas when compared to the results of traditional hydrodynamic approaches, as applied to a dam in Basilicata (Southern Italy). In particular, the over- and under-estimation rates of the proposed tool, for the San Giuliano dam, Basilicata, were evaluated by comparing its outputs with flood inundation maps that were obtained by two traditional methods whil using a one-dimensional and a two-dimensional propagation model, resulting in a specificity value of roughly 90%. These results confirm that most parts of the flood map were correctly classified as flooded by the proposed GIS model. A sensitivity value of over 75% confirms that several zones were also correctly identified as non-flooded. Moreover, the overall effectiveness and reliability of the proposed model were evaluated, for the Gleno Dam (located in the Central Italian Alps), by comparing the results of literature studies concerning the application of monodimensional numerical models and the extent of the flooded area reconstructed by the available historical information, obtaining an accuracy of around 94%. Finally, the computational efficiency of the proposed tool was tested on a demonstrative application of 250 Italian arch and gravity dams. The results, when carried out using a PC, Pentium Intel Core i5 Processor CPU 3.2 GHz, 8 GB RAM, required about 73 min, showing the potential of such a tool applied to dam-break flood mapping for a large number of dams.