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With the record breaking flood experienced in Canada’s capital region in 2017 and 2019, there is an urgent need to update and harmonize existing flood hazard maps and fill in the spatial gaps between them to improve flood mitigation strategies. To achieve this goal, we aim to develop a novel approach using machine learning classification (i.e., random forest). We used existing fragmented flood hazard maps along the Ottawa River to train a random forest classification model using a range of flood conditioning factors. We then applied this classification across the Capital Region to fill in the spatial gaps between existing flood hazard maps and generate a harmonized high-resolution (1 m) 100 year flood susceptibility map. When validated against recently produced 100 year flood hazard maps across the capital region, we find that this random forest classification approach yields a highly accurate flood susceptibility map. We argue that the machine learning classification approach is a promising technique to fill in the spatial gaps between existing flood hazard maps and create harmonized high-resolution flood susceptibility maps across flood-vulnerable areas. However, caution must be taken in selecting suitable flood conditioning factors and extrapolating classification to areas with similar characteristics to the training sites. The resulted harmonized and spatially continuous flood susceptibility map has wide-reaching relevance for flood mitigation planning in the capital region. The machine learning approach and flood classification optimization method developed in this study is also a first step toward Natural Resources Canada’s aim of creating a spatially continuous flood susceptibility map across the Ottawa River watershed. Our modeling approach is transferable to harmonize flood maps and fill in spatial gaps in other regions of the world and will help mitigate flood disasters by providing accurate flood data for urban planning.

Semantic Scholar extracted view of "CLIMATE VARIABILITY AND CHANGE IN CANADA" by E. Barrow et al.

Rivers are sensitive to natural climate change as well as to human impacts such as flow modification and land-use change. Climate change could cause changes to precipitation amounts, the intensity of cyclonic storms, the proportion of precipitation falling as rain, glacier mass balance, and the extent of permafrost; all of which affect the hydrology and morphology of river systems. Changes to the frequency and magnitude of flood flows present the greatest threat. Historically, wetter periods are associated with significantly higher flood frequency and magnitude. These effects are reduced in drainage basins with large lakes or glacier storage. Alluvial rivers with fine-grained sediments are most sensitive, but all rivers will respond, except those flowing through resistant bedrock. The consequences of changes in flow include changes in channel dimensions, gradient, channel pattern, sedimentation, bank erosion rates, and channel migration rates. The most sensitive and vulnerable regions are in southern Canada, particularly those regions at risk of substantial increases in rainfall intensity and duration. In northern rivers, thawing of permafrost and changes to river-ice conditions are important concerns. The type and magnitude of effects will be different between regions, as well as between small and large river basins. Time scales of change will range from years to centuries. These changes will affect the use that we make of rivers and their floodplains, and may require mitigative measures. Radical change is also possible. Climatic impacts will be ubiquitous and will be in addition to existing and future direct human impact on streamflow and rivers.

This paper presents an integrated assessment model for use with climate policy decision making in Canada. The feedback based integrated assessment model ANEMI_CDN represents Canada within the global society-biosphere-climate-economy-energy system. The model uses a system dynamics simulation approach to investigate the impacts of climate change in Canada and policy options for adapting to changing global conditions. The disaggregation techniques allow ANEMI_CDN to show results with various temporal resolutions. Two Canadian policy scenarios are presented as illustrative examples to map policy impacts on key model variables, including population, water-stress, food production, energy consumption, and emissions under changing climate over this century. The main finding is a significant impact of a carbon tax on energy consumption. Two policy scenario simulations provide additional insights to policy makers regarding the choice of adaptation/mitigation options along with their implementation time.

In the context of global warming, changes in extreme weather and climate events are expected, particularly those associated with changes in temperature and precipitation regimes and those that will affect coastal areas. The main objectives of this study were to establish the number of extreme events that have occurred in northeastern New Brunswick, Canada in recent history, and to determine whether their occurrence has increased. By using archived regional newspapers and data from three meteorological stations in a national network, the frequency of extreme events in the study area was established for the time period 1950–2012. Of the 282 extreme weather events recorded in the newspaper archives, 70% were also identified in the meteorological time series analysis. The discrepancy might be explained by the synergistic effect of co-occurring non-extreme events, and increased vulnerability over time, resulting from more people and infrastructure being located in coastal hazard zones. The Mann Kendall and Pettitt statistical tests were used to identify trends and the presence of break points in the weather data time series. Results indicate a statistically significant increase in average temperatures and in the number of extreme events, such as extreme hot days, as well as an increase in total annual and extreme precipitation. A significant decrease in the number of frost-free days and extreme cold days was also found, in addition to a decline in the number of dry days.

Abstract During spring 2011, an extreme flood occurred along the Richelieu River located in southern Quebec, Canada. The Richelieu River is the last section of the complex Richelieu basin, which is composed of the large Lake Champlain located in a valley between two large mountains. Previous attempts in reproducing the Richelieu River flow relied on the use of simplified lumped models and showed mixed results. In order to prepare a tool to assess accurately the change of flood recurrences in the future, a state‐of‐the‐art distributed hydrological model was applied over the Richelieu basin. The model setup comprises several novel methods and data sets such as a very high resolution river network, a modern calibration technique considering the net basin supply of Lake Champlain, a new optimization algorithm, and the use of an up‐to‐date meteorological data set to force the model. The results show that the hydrological model is able to satisfactorily reproduce the multiyear mean annual hydrograph and the 2011 flow time series when compared with the observed river flow and an estimation of the Lake Champlain net basin supply. Many factors, such as the quality of the meteorological forcing data, that are affected by the low density of the station network, the steep terrain, and the lake storage effect challenged the simulation of the river flow. Overall, the satisfactory validation of the hydrological model allows to move to the next step, which consists in assessing the impacts of climate change on the recurrence of Richelieu River floods. , Plain Language Summary In order to study the 2011 Richelieu flood and prepare a tool capable of estimating the effects of climate change on the recurrence of floods, a hydrological model is applied over the Richelieu basin. The application of a distributed hydrological model is useful to simulate the flow of all the tributaries of the Richelieu basin. This new model setup stands out from past models due to its distribution in several hydrological units, its high‐resolution river network, the calibration technique, and the high‐resolution weather forcing data set used to drive the model. The model successfully reproduced the 2011 Richelieu River flood and the annual hydrograph. The simulation of the Richelieu flow was challenging due to the contrasted elevation of the Richelieu basin and the presence of the large Lake Champlain that acts as a reservoir and attenuates short‐term fluctuations. Overall, the application was deemed satisfactory, and the tool is ready to assess the impacts of climate change on the recurrence of Richelieu River floods. , Key Points An advanced high‐resolution distributed hydrological model is applied over a U.S.‐Canada transboundary basin The simulated net basin supply of Lake Champlain and the Richelieu River discharge are in good agreement with observations of the 2011 flood The flow simulation is challenging due to the topographic and meteorological complexities of the basin and uncertainties in the observations

In recent years, geospatial data (e.g. remote sensing imagery), and other relevant ancillary datasets (e.g. land use land cover, climate conditions) have been utilized through sophisticated algorithms to produce global population datasets. With a handful of such datasets, their performances and skill in flood exposure assessment have not been explored. This study proposes a comprehensive framework to understand the dynamics and differences in population flood exposure over Canada by employing four global population datasets alongside the census data from Statistics Canada as the reference. The flood exposure is quantified based on a set of floodplain maps (for 2015, 1 in 100-yr and 1 in 200-yr event) for Canada derived from the CaMa-Flood global flood model. To obtain further insights at the regional level, the methodology is implemented over six flood-prone River Basins in Canada. We find that about 9% (3.31 million) and 11% (3.90 million) of the Canadian population resides within 1 in 100-yr and 1 in 200-yr floodplains. We notice an excellent performance of WorldPop, and LandScan in most of the cases, which is unaffected by the representation of flood hazard, while Global Human Settlement and Gridded Population of the World showed large deviations. At last, we determined the long-term dynamics of population flood exposure and vulnerability from 2006 to 2019. Through this analysis, we also identify the regions that contain a significantly larger population exposed to floods. The relevant conclusions derived from the study highlight the need for careful selection of population datasets for preventing further amplification of uncertainties in flood risk. We recommend a detailed assessment of the severely exposed regions by including precise ground-level information. The results derived from this study may be useful not only for flood risk management but also contribute to understanding other disaster impacts on human-environment interrelationships. • Five population datasets are considered for quantifying flood exposure over Canada. • WorldPop and LandScan provide the closest estimates when compared with census data. • Skill of population datasets is tested over six flood-prone River Basins of Canada. • Long-term changes in degree of exposure is characterized at census-division level. • Highly exposed divisions are identified for ensuring detailed flood-risk assessment

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.

Abstract Objective Despite Canada being an important energy producer, not all Canadians can access or afford adequate levels of energy services at home to meet their needs, maintain healthy indoor temperatures, and live a decent life—a situation known as energy poverty. Depending on the measure, 6–19% of Canadian households face energy poverty. Health risks associated with energy poverty are documented in countries with milder climates. This study explores, for the first time in the Canadian context, the association between energy poverty and health. Methods Cross-sectional data are from the 2018 Canadian Housing Survey. Analyses are conducted on a sample weighted to represent 14 million Canadian households. The associations between expenditure-based and self-reported measures of energy poverty and self-rated general and mental health were assessed using logistic regression models, adjusted for potential confounding variables. Results The odds of rating one’s general (OR: 1.48; 95%CI: 1.29, 1.70) and mental (OR: 1.21; 1.04, 1.41) health as poor are significantly higher for Canadian adults in households with a high share of energy expenditure to income. The likelihood of poor general and mental health was significantly higher for those dissatisfied with the energy efficiency of their dwelling, and with their ability to maintain a comfortable temperature both in the winter and in the summer. Conclusion Exposure to energy poverty is associated with significantly increased likelihood of poor general and mental health. Given the high proportion of Canadian households facing energy poverty, with demonstrated implications for population health, tackling energy poverty is essential for an equitable energy transition and for climate resilience. , Résumé Objectif Bien que le Canada soit un important producteur d’énergie, entre 6 % et 19 % des ménages canadiens, selon la mesure retenue, sont en précarité énergétique, une situation qui survient lorsqu’un ménage n’a pas les moyens ou l’accès à des services énergétiques résidentiels adéquats pour maintenir une température ambiante confortable, répondre à ses besoins et vivre dans la dignité. Les risques socio-sanitaires associés à la précarité énergétique sont documentés dans des pays au climat tempéré. Cette étude explore, pour la première fois dans le contexte canadien, l’association entre la précarité énergétique et la santé. Méthodes Les données transversales proviennent de l’Enquête canadienne sur le logement de 2018. Les associations entre différentes mesures de précarité énergétique (mesures basées sur les dépenses des ménages et auto-rapportées) et la santé générale et mentale perçue sont estimées à l’aide de modèles de régression logistique ajustés pour des variables de confusion potentielles. Les analyses sont réalisées sur un échantillon pondéré pour représenter 14 millions de ménages. Résultats Les probabilités de déclarer une mauvaise santé générale (OR : 1,48; IC95% : 1,29-1,70) et mentale (OR : 1,21; 1,04-1,41) sont significativement plus élevées pour les adultes canadiens dont le ménage consacre une part importante de son revenu aux coûts énergétiques. Elles sont aussi significativement plus élevées pour ceux qui déclarent être insatisfaits avec l’efficacité énergétique de leur logement et de leur capacité à maintenir une température confortable en hiver et en été. Conclusion Vivre en situation de précarité énergétique est associée à des probabilités accrues de déclarer une mauvaise santé générale et mentale chez les adultes canadiens. En raison de la proportion élevée de ménages canadiens confrontés à la précarité énergétique et des effets socio-sanitaires que cette situation engendre, lutter contre la précarité énergétique est essentiel pour une transition énergétique équitable et pour la résilience climatique.

Social participation is a modifiable health determinant influenced by physical and social aspects of the environment. Little is known about aging women’s and men’s community activities and barriers according to region and population size. This study compared social participation, desire to participate more, and perceived barriers of aging women and men by Canadian region and population size.