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Abstract Fluvial hazards of river mobility and flooding are often problematic for road infrastructure and need to be considered in the planning process. The extent of river and road infrastructure networks and their tendency to be close to each other creates a need to be able to identify the most dangerous areas quickly and cost‐effectively. In this study, we propose a novel methodology using random forest (RF) machine learning methods to provide easily interpretable fine‐scale fluvial hazard predictions for large river systems. The tools developed provide predictions for three models: presence of flooding (PFM), presence of mobility (PMM) and type of erosion model (TEM, lateral migration, or incision) at reference points every 100 m along the fluvial network of three watersheds within the province of Quebec, Canada. The RF models use variables focused on river conditions and hydrogeomorphological processes such as confinement, sinuosity, and upstream slope. Training/validation data included field observations, results from hydraulic and erosion models, government infrastructure databases, and hydro‐ geomorphological assessments using 1‐m DEM and satellite/historical imagery. A total of 1807 reference points were classified for flooding, 1542 for mobility, and 847 for the type of erosion out of the 11,452 reference points for the 1145 km of rivers included in the study. These were divided into training (75%) and validation (25%) datasets, with the training dataset used to train supervised RF models. The validation dataset indicated the models were capable of accurately predicting the potential for fluvial hazards to occur, with precision results for the three models ranging from 83% to 94% of points accurately predicted. The results of this study suggest that RF models are a cost‐effective tool to quickly evaluate the potential for fluvial hazards to occur at the watershed scale.

Abstract High-resolution global flood risk maps are increasingly used to inform disaster risk planning and response, particularly in lower income countries with limited data or capacity. However, current approaches do not adequately account for spatial variation in social vulnerability, which is a key determinant of variation in outcomes for exposed populations. Here we integrate annual average exceedance probability estimates from a high-resolution fluvial flood model with gridded population and poverty data to create a global vulnerability-adjusted risk index for flooding (VARI Flood) at 90-meter resolution. The index provides estimates of relative risk within or between countries and changes how we understand the geography of risk by identifying ‘hotspots’ characterised by high population density and high levels of social vulnerability. This approach, which emphasises risks to human well-being, could be used as a complement to traditional population or asset-centred approaches.

IntroductionCaribbean Small island developing states (SIDS) are generally qualified as disproportionately vulnerable to climate change, including extreme weather events like hurricanes. While many studies already documented the impacts of climate change on health in the wealthiest countries, there is little knowledge in this field in Caribbean SIDS. Our study aims to discuss health risks and vulnerabilities in a Caribbean context to inform future adaptation measures to climate change.MethodsOur paper is based on a qualitative study that was conducted in Dominica, a Caribbean SIDS. The data come from semi-structured interviews organized between March 2020 and January 2021 with people internally displaced following an extreme climate event, either tropical storm Erika (2015) or Hurricane Maria (2017), and with some people who migrated to Guadeloupe after Hurricane Maria. Interview guides were based on conceptual frameworks on climate change, migration and health, and vulnerability to climate change. Data were analyzed deductively based on frameworks and inductively to allow new codes to emerge.ResultsOur findings suggest that current knowledge of climate change by those who have been displaced by an extreme climate event varied greatly depending on the education level, class, and socioeconomic condition of the participant. Participants experienced various negative consequences from a storm or hurricane such as increased risk of relocation, lack of access to healthcare, and food, job, and water insecurities – all circumstances know to correlate with mental health issues. Participants suggested stronger dwellings, community preparedness committees to act sooner, and climate change sensitization and awareness campaigns to foster community unity and solidarity.ConclusionThese findings contribute to the perspectives and knowledge of climate change, highlighting that existing extreme climate event committees and government officials need to address structural and social barriers that can potentially increase social inequalities and lead to maladaptation to climate change with potential consequences on public health.

This paper explores the risk approach, considering both the physical and human dimensions of the phenomenon in order to produce a more realistic and spatial analysis of risk. Exposure and vulnerability were combined and evaluated multidimensionally, considering individual, socio-economic, and structural (building-related) aspects. These risk factors were then integrated in a multi-criteria analysis in order to produce a comprehensive risk index that could be visualized at the building scale. The relative importance of the indicators was determined through a participatory process involving local and national experts on civil security and flooding. Particular attention was paid to individual vulnerability, including perception and preparedness for flood risk, which were explored directly with local people using a questionnaire. Qualitative and quantitative analyses of the responses allowed for a better understanding of the perception and preparedness of populations exposed to flooding. These data should help to improve risk communication between the authorities concerned and the populations at risk, as well as encouraging implementation of appropriate measures and a bottom-up participatory management approach. The integration of data in a geographic information system enables the visualization and spatialization of risk, but also each of its components.

Abstract The impacts of climatic disasters have been rising globally. Several studies argue that this upward trend is due to rapid growth in the population and wealth exposed to disasters. Others argue that rising extreme weather events due to anthropogenic climate change are responsible for the increase. Hence, the causes of the increase in disaster impacts remain elusive. Disaster impacts relative to income are higher in low-income countries, but existing studies are mostly from developed countries or at the cross-country level. Here we assess the spatiotemporal trends of climatic disaster impacts and vulnerability and their attribution to climatic and socioeconomic factors at the subnational scale in a low-income country, using Nepal as a case study. Loss of life is the most extreme consequence of disasters. Therefore, we employed human mortality as a measure of disaster impacts, and mortality normalized by exposed population as a measure of human vulnerability. We found that climatic disaster frequency and mortality increased in Nepal from 1992 to 2021. However, vulnerability decreased, most likely due to economic growth and progress in disaster risk reduction and climate change adaptation. Disaster mortality is positively correlated with disaster frequency and negatively correlated with per capita income but is not correlated with the exposed population. Hence, population growth may not have caused the rise in disaster mortality in Nepal. The strong rise in disaster incidence, potentially due to climate change, has overcome the effect of decreasing vulnerability and caused the rise in disaster mortality.

Abstract This study integrates novel data on 100-year flood hazard extents, exposure of residential properties, and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions. National-scale exposure of residential properties to fluvial, pluvial, and coastal flooding was estimated at the 100-year return period. A social vulnerability index (SVI) was developed and included 49 variables from the national census that represent demographic, social, economic, cultural, and infrastructure/community indicators of vulnerability. Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk. We found that about 81% of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties. Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities, but socioeconomic vulnerability is higher on reserve lands, which confirms that the overall risk of Indigenous communities is higher. Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis.

This paper finds that social differentiation in flood impacts is relatively small soon after a flood, with some surprising results such as professionals and homeowners badly affected in the short‐term – but widens over time, with socially disadvantaged groups displaying less recovery. The paper concludes that vulnerability and resilience to flooding are sensitive to financial resources, institutional support (chiefly from a landlord), and capacity to deal with disruption (chiefly time availability, which is low among professionals and high among retired people). An implication of these findings is that existing indices of flood vulnerability that use multiple measures of social deprivation should be used with caution, as not all conventional aspects of social deprivation are necessarily associated with greater vulnerability to flood impacts. , This paper reports household questionnaire survey results on vulnerability and resilience to flooding from one of the largest and most representative samples ( n  = 593) of households up to 12 years after they were flooded, and is one of the first to provide detailed analysis of social differentiation in long‐term flood impacts. A novel finding is that social differentiation in flood impacts is relatively small soon after a flood, but widens over time, with socially disadvantaged groups displaying less recovery. The patterns of social differentiation in vulnerability and resilience to flooding differ markedly according to the type and timescale of the impact, with some normally socially advantaged groups (e.g., professionals and homeowners) being most vulnerable to short‐term impacts. Consistent with some existing studies, we found that older residents (age 70+) have greater resilience to flood impacts, although our sample may not capture the frailest individuals. As in previous research, low income is linked to lower resilience, particularly in the long term. We find that prior experience of flooding, despite enhancing preparedness, overall erodes rather than enhances resilience to flooding. Flood warnings are effective at reducing vulnerability to short‐term impacts. Underlying influences on resilience to natural disasters are complex and may only be revealed by multivariate analysis and not always be evident in simple observed patterns. The paper concludes that vulnerability and resilience to flooding are sensitive to financial resources, institutional support (chiefly from a landlord), and capacity to deal with disruption (chiefly time availability, which is low among professionals and high among retired people). An implication of these findings is that existing indices of flood vulnerability that use multiple measures of social deprivation should be used with caution, as not all conventional aspects of social deprivation are necessarily associated with greater vulnerability to flood impacts.

In Eastern Dhaka, perennial flood remains a constant threat to people and livelihoods. Learning from the micro-level experiences of the poor in the peri-urban areas of Dhaka provides insights on the intersections between physical vulnerability, flood response strategies, and adaptive capacity. Through a convergent mixed method, this study examines the physical vulnerability of residential buildings, flood damages, and local physical responses in three neighborhoods of Eastern Dhaka. Results show that the level of damage to buildings is the most important predictor of physical vulnerability to floods. Buildings that are older than 20 years old and built with natural materials are likely to experience high flood damages compared to buildings that are less than 10 years and constructed with durable materials. The study concludes that in addition to socio-economic interventions, a targeted and people-centered flood management regime that pays attention to age, material composition, and structural quality of houses is necessary to build residents’ adaptive capacities and long-term resilience to flooding. This study contributes to the emerging work on grassroots responses to flood vulnerabilities with practical insights for urban planners and disaster management professionals on particular interventions needed to improve the performance of local responses to flood risks and vulnerabilities.

La province du Nouveau-Brunswick, situee dans l’est du Canada, est tres affectee par les inondations. Bien que moins documentee que l’alea, la dimension humaine du risque que represente la vulnerabilite est importante pour l’adaptation des populations. Cet article fait un survol des principaux concepts lies a la vulnerabilite et presente leur application a l’echelle d’un bassin versant de taille moyenne. Les resultats montrent la necessite de considerer simultanement la perception et la preparation au risque d’inondation. En effet, si certains residents dans les zones a risque ont une bonne connaissance des inondations et une perception realiste du risque, cela ne se traduit pas necessairement par une preparation adaptee et adequate face au risque. La reduction du risque passe indeniablement par une meilleure sensibilisation et education de la population.

Climate change has induced considerable changes in the dynamics of key hydro-climatic variables across Canada, including floods. In this study, runoff projections made by 21 General Climate Models (GCMs) under four Representative Concentration Pathways (RCPs) are used to generate 25 km resolution streamflow estimates across Canada for historical (1961–2005) and future (2061–2100) time-periods. These estimates are used to calculate future projected changes in flood magnitudes and timings across Canada. Results obtained indicate that flood frequencies in the northernmost regions of Canada, and south-western Ontario can be expected to increase in the future. As an example, the historical 100-year return period events in these regions are expected to become 10–60 year return period events. On the other hand, northern prairies and north-central Ontario can be expected to experience decreases in flooding frequencies in future. The historical 100-year return period flood events in these regions are expected to become 160–200 year return period events in future. Furthermore, prairies, parts of Quebec, Ontario, Nunavut, and Yukon territories can be expected to experience earlier snowmelt-driven floods in the future. The results from this study will help decision-makers to effectively manage and design municipal and civil infrastructure in Canada under a changing climate.

Abstract The database of the Quebec Ministry of Transport allowed us to analyze the occurrence of ice-block falls and snow avalanches for the past decades along national road 132. The results show that ice structure collapse may be categorized into three distinct phases by using daily temperatures (minimum, maximum, and average) and the cumulative degree day (temperatures above 0°C) since the March 1 st , corresponding to the beginning of the ice wall melting period: 1) a short and intense period of ice-block falls from the mid-April to the beginning of May; 2) a period of constant activity, mainly during the two first weeks of May; and 3) isolated residual activity, with a low frequency of ice-block falls until the month of June. The snow avalanche days were mainly characterized by significant snowfalls or rain-on-snow events with temperature>0°C. The multi-hazard probability was then evaluated based on the timing and relative frequency of ice-block fall and the modeling of sufficient snowpack for avalanching. This simple method to assess the synergistic effect of hillslope processes allows a better understanding of the spring avalanche regime related to the collapse of ice structures. These findings are expected to assist in the management of natural hazards and to improve our knowledge of spatiotemporal dynamics of mass-wasting events on highways.

Abstract A disproportionate share of the global economic and human losses caused by environmental shocks is borne by people in the developing nations. The mountain region of Hindu-Kush Himalaya (HKH) in South Asia is threatened by numerous flooding events annually. An efficient disaster risk reduction often needs to rest upon location-based synoptic view of vulnerability. Resolving this deficit improves the ability to take risk reduction measures in a cost-effective way, and in doing so, strengthens the resilience of societies to flooding disasters. The central aim of this research is to identify the vulnerable locations across HKH boundary from the perspective of reported history of economic and human impacts due to occurrence of flooding disasters. A detailed analysis indicates a very high spatial heterogeneity in flooding disaster occurrence in the past 6 decades. The most recent decade reported highest number of disasters and greater spatial coverage as compared to the earlier decades. The data indicates that, in general, economic impacts of flooding disasters were notably higher in Pakistan, Afghanistan and Nepal. On the other hand, vulnerability scenarios with respect to human impacts were diverse for different countries. In terms of morbidity and mortality, Bangladesh, Pakistan, Bhutan and India were detected to be most susceptible to human impacts. Although Bhutan had seen lesser number of flooding disasters, higher population living within disaster prone region make them vulnerable. In summary, complex interactions between natural and socio-economic conditions play a dominant role to define and characterize the type and magnitude of vulnerability of HKH countries to disaster occurrence and their economic and human impacts.

The global impacts of river floods are substantial and rising. Effective adaptation to the increasing risks requires an in-depth understanding of the physical and socioeconomic drivers of risk. Whereas the modeling of flood hazard and exposure has improved greatly, compelling evidence on spatiotemporal patterns in vulnerability of societies around the world is still lacking. Due to this knowledge gap, the effects of vulnerability on global flood risk are not fully understood, and future projections of fatalities and losses available today are based on simplistic assumptions or do not include vulnerability. We show for the first time (to our knowledge) that trends and fluctuations in vulnerability to river floods around the world can be estimated by dynamic high-resolution modeling of flood hazard and exposure. We find that rising per-capita income coincided with a global decline in vulnerability between 1980 and 2010, which is reflected in decreasing mortality and losses as a share of the people and gross domestic product exposed to inundation. The results also demonstrate that vulnerability levels in low- and high-income countries have been converging, due to a relatively strong trend of vulnerability reduction in developing countries. Finally, we present projections of flood losses and fatalities under 100 individual scenario and model combinations, and three possible global vulnerability scenarios. The projections emphasize that materialized flood risk largely results from human behavior and that future risk increases can be largely contained using effective disaster risk reduction strategies.

Flood risk assessments provide inputs for the evaluation of flood risk management (FRM) strategies. Traditionally, such risk assessments provide estimates of loss of life and economic damage. However, the effect of policy measures aimed at reducing risk also depends on the capacity of households to adapt and respond to floods, which in turn largely depends on their social vulnerability. This study shows how a joint assessment of hazard, exposure and social vulnerability provides valuable information for the evaluation of FRM strategies. The adopted methodology uses data on hazard and exposure combined with a social vulnerability index. The relevance of this state-of-the-art approach taken is exemplified in a case-study of Rotterdam, the Netherlands. The results show that not only a substantial share of the population can be defined as socially vulnerable, but also that the population is very heterogeneous, which is often ignored in traditional flood risk management studies. It is concluded that FRM measures, such as individual mitigation, evacuation or flood insurance coverage should not be applied homogenously across large areas, but instead should be tailored to local characteristics based on the socioeconomic characteristics of individual households and neighborhoods.