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Despite being recognized as a key component of shallow-water ecosystems, submerged aquatic vegetation (SAV) remains difficult to monitor over large spatial scales. Because of SAV’s structuring capabilities, high-resolution monitoring of submerged landscapes could generate highly valuable ecological data. Until now, high-resolution remote sensing of SAV has been largely limited to applications within costly image analysis software. In this paper, we propose an example of an adaptable open-sourced object-based image analysis (OBIA) workflow to generate SAV cover maps in complex aquatic environments. Using the R software, QGIS and Orfeo Toolbox, we apply radiometric calibration, atmospheric correction, a de-striping correction, and a hierarchical iterative OBIA random forest classification to generate SAV cover maps based on raw DigitalGlobe multispectral imagery. The workflow is applied to images taken over two spatially complex fluvial lakes in Quebec, Canada, using Quickbird-02 and Worldview-03 satellites. Classification performance based on training sets reveals conservative SAV cover estimates with less than 10% error across all classes except for lower SAV growth forms in the most turbid waters. In light of these results, we conclude that it is possible to monitor SAV distribution using high-resolution remote sensing within an open-sourced environment with a flexible and functional workflow.
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Au Québec, chaque année, les inondations printanières présentent un défi majeur pour les autorités québécoises. Ainsi, l'élaboration de nouveaux outils et de nouvelles méthodes pour diffuser et visualiser des données massives spatiotemporelles 3D dynamiques d'inondation est très important afin de mieux comprendre et gérer les risques reliés aux inondations. Cette recherche s'intéresse à la diffusion de données géospatiales massives 3D (modèles de bâtiments 3D, arbres, modèles numériques d'élévation de terrain (MNE), données LiDAR, imageries aériennes, etc.) en relation avec les inondations. Le problème est qu'il n'existe pas, à travers la littérature, des systèmes de diffusion efficaces des données massives 3D adaptées aux besoins de cette recherche. En ce sens, notre objectif général consiste à développer un outil de diffusion des données géospatiales massives 3D qui sont des bâtiments 3D et des modèles de terrains de haute résolution à l'échelle de la province du Québec. Les défis de diffusion du flux de données massives, nous ramènent à considérer la technique de tuilage 3D pour convertir les données brutes en formats et structures vectoriels plus légers et adaptés à la diffusion comme la spécification "3D Tiles" pour tuiler les bâtiments 3D, les nuages de points LiDAR et d'autres modèles géoréférencés 3D et le maillage irrégulier, notamment les TIN, pour tuiler les modèles numériques de terrain. Aussi, l'utilisation des techniques de traitement parallèle permet de gérer efficacement les flux massifs de données et d'améliorer le temps de traitement permettant ainsi la scalabilité et la flexibilité des systèmes existants. A cet effet, deux pipelines de tuilage ont été développés. Le premier pipeline concerne la création des tuiles de bâtiments 3D selon la spécification "3D Tiles". Le deuxième est pour créer des tuiles de terrain basées sur des maillages irréguliers. Ces pipelines sont ensuite intégrés dans un système de traitement distribué basé sur des conteneurs Docker afin de paralléliser les processus de traitements. Afin de tester l'efficacité et la validité du système développé, nous avons testé ce système sur un jeux de données massif d'environ 2.5 millions bâtiments 3D situés au Québec. Ces expérimentations ont permis de valider et de mesurer l'efficacité du système proposé par rapport à sa capacité de se mettre à l'échelle (Scalabilité) pour prendre en charge, efficacement, les flux massifs de données 3D. Ces expérimentations ont aussi permis de mettre en place des démarches d'optimisation permettant une meilleure performance dans la production et la diffusion des tuiles 3D.
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Les politiques québécoises de prévention des risques liés aux inondations ont été sujettes à débat ces dernières années, avec une remise en cause du modèle centralisé et uniforme à travers le Québec, pour une approche plus intégrée. Celle-ci fait notamment la promotion de mesures axées sur la vulnérabilité et d’une participation plus active des acteurs territoriaux. On en sait toutefois très peu sur les déclinaisons locales de l’approche intégrée dans le contexte québécois. Ce mémoire propose d’interroger les différentes approches locales de la prévention et de soulever les enjeux qu’elles posent du point de vue des autorités qui y participent. L’étude se penche sur le cas des territoires concernés par les inondations du lac des Deux Montagnes (Région hydrographique de l'Outaouais et de Montréal). Le cadre d’analyse met de l’avant l’approche des instruments d’action publique pour comprendre leur appropriation par les acteurs locaux et une approche pragmatique qui consiste à centrer notre regard sur les pratiques et les stratégies de réduction des risques d’inondation. La recherche s’appuie sur trois sources de données : une analyse documentaire des régimes provinciaux de régulation des risques d’inondation, un recensement des pratiques de prévention déployées par les autorités locales concernées par les inondations du lac des Deux Montagnes et une série de 15 entretiens réalisés avec les personnes travaillant au sein de ces différentes autorités. Le cas illustre la difficulté et le faible engagement de prévenir les risques autrement que par l’approche de réduction de l’exposition aux risques imposée par la Politique de protection des rives, du littoral et des plaines inondables (PPRLPI). Toutefois, après les inondations de 2017 et de 2019, des approches alternatives propres aux contextes territoriaux ont été envisagées par différentes organisations. Celles-ci devraient davantage être documentées et mises en débat afin d’envisager un régime provincial de la gestion des risques plus flexible et ouvert à leur coexistence. <br /><br /> Uniformed and centralized model of Quebec's flood prevention policies have been recently debated. Integrated approach to flood risk prevention is now put forward, which focus more on vulnerability and foster an active participation of local authorities. Local declinations of the approach are relatively unknown in Quebec. This study presents different local approaches to flood risk prevention and raise issues they pose from the perspective of local authorities involved. It is based on the authority’s concerns by Lac des Deux Montagnes flooding (Outaouais and Montreal hydrographic region). Combining a political sociology approach to policy instruments and a pragmatic approach, we focus on risk regulation regimes, practices and risk reduction strategies. Three sources of data were used: an analysis of flood risk regulation regimes, an inventory of prevention practices deployed by local authorities and 15 interviews conducted with professionals among these authorities. Results show the difficulty and low commitment to implement local distinct approaches apart from prohibiting and discouraging exposure to flood risk enforced by the Protection Policy for Lakeshores, Riverbanks, Littoral Zones and Floodplains. However, after the floods of 2017 and 2019, alternative strategies specific to different territorial contexts were considered. These should be better documented and debated in order to consider a more flexible and coexistence provincial policy.
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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.
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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.
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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
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Abstract The analysis across spatial, temporal and governance scales shows an inequitable distribution of risk across Canada’s Metro Vancouver region. For First Nation communities in this region, this risk is rooted in the colonial history of land dispossession. This article makes a contribution by expanding our understanding of historic creation of riskscapes and a discussion of its implications as a multiscale governance issue that persists across space and time. This article also situates the impacts of projected sea level rise on Indigenous communities in the context of regional, provincial and federal settler-colonial flood risk management regime.
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ABSTRACT Large-scale disasters can disproportionately impact different population groups, causing prominent disparity and inequality, especially for the vulnerable and marginalized. Here, we investigate the resilience of human mobility under the disturbance of the unprecedented ‘720’ Zhengzhou flood in China in 2021 using records of 1.32 billion mobile phone signaling generated by 4.35 million people. We find that although pluvial floods can trigger mobility reductions, the overall structural dynamics of mobility networks remain relatively stable. We also find that the low levels of mobility resilience in female, adolescent and older adult groups are mainly due to their insufficient capabilities to maintain business-as-usual travel frequency during the flood. Most importantly, we reveal three types of counter-intuitive, yet widely existing, resilience patterns of human mobility (namely, ‘reverse bathtub’, ‘ever-increasing’ and ‘ever-decreasing’ patterns), and demonstrate a universal mechanism of disaster-avoidance response by further corroborating that those abnormal resilience patterns are not associated with people’s gender or age. In view of the common association between travel behaviors and travelers’ socio-demographic characteristics, our findings provide a caveat for scholars when disclosing disparities in human travel behaviors during flood-induced emergencies.
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Flood risk management requires to comprehensively assess how policy strategies may affect individuals and communities. However, policy development and implementation often downplay or even increase social inequality. Analysis of the social and societal implications of strategies and implementation projects to manage flood hazards is still in its infancy. To close this gap, this chapter critically questions the roles of social justice and their political implications for flood risk management with regard to resilience. The chapter discusses and argues how different theoretical concepts as well as different perspectives on justice (e.g. social, environmental and climate justice) and resilience in flood risk management are related. There is a strong need to have a broader and more in-depth discussion about the role of justice in the current resilience debate. Finally, the chapter presents the outline of a future research agenda.
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Government employees, municipal officials, and communities in South Africa have grappled with post-apartheid environmental challenges, such as floods, droughts, severe storms, and wildfires. These disasters are a result of both natural and human activities. The government implemented different policies and strategies after 1994 to address these issues. While acknowledging some success in managing these disasters with the current adaptive measures, the frequency and intensity of disasters have increased, causing significant damage to life and property, particularly among the vulnerable population. This paper uses qualitative and quantitative data collection approaches to explore possible systematic and structural weaknesses in addressing post-disaster situations in South Africa. Floods appear to be the most frequent natural disaster in South Africa. The paper uncovered the fact that disaster management is a multi-sectoral and multidisciplinary field. Although various institutional arrangements exist, they do not seem appropriate for assisting vulnerable groups. While officials have made some progress in implementing post-disaster projects, challenges still hinder sustainability. Furthermore, regrettably, despite the level of success in addressing disasters, most measures have failed to achieve the intended results for a variety of reasons. The consolidated long-term measures suggested by the participants yielded a proposed ‘South African Floods Post-Disaster Checklist or Model’, which was non-existent in South Africa. By implementing more effective and efficient post-disaster measures, the proposed tool can help policymakers and strategic partners standardise post-disaster resilience and adaptive capacity in various sectors’ sustainability contexts.