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Abstract A timely and cost-effective method of creating inundation maps could assist first responders in allocating resources and personnel in the event of a flood or in preparation of a future disaster. The Height Above Nearest Drainage (HAND) model could be implemented into an on-the-fly flood mapping application for a Canada-wide service. The HAND model requires water level (m) data inputs while many sources of hydrological data in Canada only provide discharge (m 3 /sec) data. Synthetic rating curves (SRCs), created using river geometry/characteristics and the Manning’s formula, could be utilized to provide an approximate water level given a discharge input. A challenge with creating SRCs includes representing how multiple different land covers will slow impact flow due to texture and bulky features (i.e., smooth asphalt versus rocky river channel); this relates to the roughness coefficient ( n ). In our study, two methods of representing multiple n values were experimented with (a weighted method and a minimum-median method) and were compared to using a fixed n method. A custom ArcGIS tool, Canadian Estimator of Ratings Curves using HAND and Discharge (CERC-HAND-D), was developed to create SRCs using all three methods. Control data were sourced from gauge stations across Canada in the form of rating curves. Results indicate that in areas with medium to medium–high river gradients (S > 0.002 m/m) or with river reaches under 5 km, the CERC-HAND-D tool creates more accurate SRCs (NRMSE = 3.7–8.8%, Percent Bias = −7.8%—9.4%), with the minimum-median method being the preferred n method.

River floods usually do not stop at administrative borders. The respective location of municipalities along a river creates different options and dependencies, commonly referred to as upstream–downstream relations. This regional dimension of flood risk calls for catchment‐based approaches in flood risk management as advocated by the EU Flood Directive. In this article, we present and assess the case of an intermunicipal cooperation in Austria which aims to alleviate flood risk and coordinate planning activities based on a catchment approach. The authors apply an established model of water governance to characterise the governance features and to assess the governance qualities and governance capacities of the intermunicipal cooperation. Findings show that the selected case qualifies as a suitable governance instrument to address the main policy objectives. Existing functional ties, shared (flooding) experiences, and mutual trust mark key success factors, indicating that proximity – in its many different forms – is crucial to overcome power asymmetries and spatial misfits in catchment‐based flood risk management. However, intermunicipal cooperation is weak when it comes to ensuring binding land use regulations, showing the need for a complementary use of governance arrangements and formal instruments of regional land use planning in flood risk management.

In June 2005, the headwater tributaries of the Saskatchewan River Basin in the western Canadian province of Alberta were struck by four heavy rain events. Runoff from the rainfalls resulted in three floods which extended from Alberta through the provinces of Saskatchewan and Manitoba, causing at least four deaths and property damages of CAD $400 million.

Numerous government and non-governmental agencies are increasing their efforts to better quantify the disproportionate effects of climate risk on vulnerable populations with the goal of creating more resilient communities. Sociodemographic based indices have been the primary source of vulnerability information the past few decades. However, using these indices fails to capture other facets of vulnerability, such as the ability to access critical resources (e.g., grocery stores, hospitals, pharmacies, etc.). Furthermore, methods to estimate resource accessibility as storms occur (i.e., in near-real time) are not readily available to local stakeholders. We address this gap by creating a model built on strictly open-source data to solve the user equilibrium traffic assignment problem to calculate how an individual's access to critical resources changes during and immediately after a flood event. Redundancy, reliability, and recoverability metrics at the household and network scales reveal the inequitable distribution of the flood's impact. In our case-study for Austin, Texas we found that the most vulnerable households are the least resilient to the impacts of floods and experience the most volatile shifts in metric values. Concurrently, the least vulnerable quarter of the population often carries the smallest burdens. We show that small and moderate inequalities become large inequities when accounting for more vulnerable communities' lower ability to cope with the loss of accessibility, with the most vulnerable quarter of the population carrying four times as much of the burden as the least vulnerable quarter. The near-real time and open-source model we developed can benefit emergency planning stakeholders by helping identify households that require specific resources during and immediately after hazard events.

The impact of climate change on the frequency distribution of spring floods in the Red River basin is investigated. Several major floods in the last couple of decades have caused major damages and inconvenience to people living in the Red River flood plain south of Winnipeg, and have raised the question of whether climate change is at least partly responsible for what appears to be more frequent occurrences of high spring runoff. To investigate whether this is the case, a regression model is used to associate spring peak flow at the US–Canada border with predictor variables that include antecedent precipitation in the previous fall (used as a proxy for soil moisture at freeze-up), winter snow accumulation and spring precipitation. Data from the Coupled Model Intercomparison Project – Phase 5 (CMIP5) are used to derive information about possible changes to the predictor variables in the future, and this information is then used to derive flood distributions for future climate conditions. While mean monthly...

In late June 2013, heavy rainfall and rapidly melting alpine snow triggered flooding throughout much of the southern half of Alberta. Heavy rainfall commenced on 19 June and continued for 3 days. When the event was over, more than 200 mm and as much as 350 mm of precipitation had fallen over the Front Ranges of the Canadian Rocky Mountains. Tributaries to the Bow River including the Ghost, Kananaskis, Elbow, Sheep and Highwood, and many of their tributaries, all reached flood levels. The storm had a large spatial extent causing flooding to the north and south in the Red Deer and Oldman Basins, and also to the west in the Elk River in British Columbia. Convergence of the nearly synchronous floodwaters downstream in the South Saskatchewan River system caused record high releases from Lake Diefenbaker through Gardiner Dam. Dam releases in Alberta and Saskatchewan attenuated the downstream flood peak such that only moderate flooding occurred in Saskatchewan and Manitoba. More than a dozen municipalities decla...

Abstract In flood frequency analysis (FFA), annual maximum (AM) model is widely adopted in practice due to its straightforward sampling process. However, AM model has been criticized for its limited flexibility. FFA using peaks-over-threshold (POT) model is an alternative to AM model, which offers several theoretical advantages; however, this model is currently underemployed internationally. This study aims to bridge the current knowledge gap by conducting a scoping review covering several aspects of the POT approach including model assumptions, independence criteria, threshold selection, parameter estimation, probability distribution, regionalization and stationarity. We have reviewed the previously published articles on POT model to investigate: (a) possible reasons for underemployment of the POT model in FFA; and (b) challenges in applying the POT model. It is highlighted that the POT model offers a greater flexibility compared to the AM model due to the nature of sampling process associated with the POT model. The POT is more capable of providing less biased flood estimates for frequent floods. The underemployment of POT model in FFA is mainly due to the complexity in selecting a threshold (e.g., physical threshold to satisfy independence criteria and statistical threshold for Generalized Pareto distribution – the most commonly applied distribution in POT modelling). It is also found that the uncertainty due to individual variable and combined effects of the variables are not well assessed in previous research, and there is a lack of established guideline to apply POT model in FFA.

In Canada, climate change is expected to increase the extreme precipitation events by magnitude and frequency, leading to more intense and frequent river flooding. In this study, we attempt to map the flood hazard and damage under projected climate scenarios (2050 and 2080). The study was performed in the two most populated municipalities of the Petite Nation River Watershed, located in southern Quebec (Canada). The methodology follows a modelling approach, in which climate projections are derived from the Hydroclimatic Atlas of Southern Quebec following two representative concentration pathways (RCPs) scenarios, i.e., RCP 4.5 and RCP 8.5. These projections are used to predict future river flows. A frequency analysis was carried out with historical data of the peak flow (period 1969–2018) to derive different return periods (2, 20, and 100 years), which were then fed into the GARI tool (Gestion et Analyse du Risque d’Inondation). This tool is used to simulate flood hazard maps and to quantify future flood risk changes. Projected flood hazard (extent and depth) and damage maps were produced for the two municipalities under current and for future scenarios. The results indicate that the flood frequencies are expected to show a minor decrease in peak flows in the basin at the time horizons, 2050 and 2080. In addition, the depth and inundation areas will not significantly change for two time horizons, but instead show a minor decrease. Similarly, the projected flood damage changes in monetary losses are projected to decrease in the future. The results of this study allow one to identify present and future flood hazards and vulnerabilities, and should help decision-makers and the public to better understand the significance of climate change on flood risk in the Petite Nation River watershed.

Abstract Flood risk may differ across income levels. In this paper, I employ unique survey data from more than 8000 households in Germany to derive an integrated flood risk indicator that accounts for local flood exposure, assets-at-risk, housing characteristics, and household coping behavior. The results suggest that low-income households, due to their smaller homes and less valuable assets, face lower monetary flood risks than wealthier households despite the former’s limited capacity to implement protection measures and purchase insurance. Relative to the available financial budget, however, expected flood damage weighs higher for low-income households.

Objectives. To understand changes in behavioral health services utilization and expenditures before and after natural disaster with an adult Medicaid population affected by the Baton Rouge, Louisiana–area flood (August 2016). Methods. We examined de-identified behavioral health claims data for Medicaid-insured adults in the affected region for 10 months before and after flooding (October 2015–June 2017). This constituted 273 233 provider claims for 22 196 individuals. Claims data included patient gender, behavioral health diagnoses, treatment dates, and costs. We made adjustments for Medicaid expansion by using monthly enrollment data. Results. Overall, most male patient behavioral health care visits were for substance use disorders (33.6%) and most female patient behavioral health care visits were for depression-related disorders (30%). Both diagnostic categories increased after the flood by 66% and 44%, respectively. Expansion accounted for a 4% increase in claims. Postflood claims reflected 8% to 10% higher costs. Conclusions. Greater amounts of behavioral health care services were sought in all 10 months of the postflood study period. We observed gender differences in use of services and diagnoses. Behavioral health care services following natural disasters must be extended longer than traditionally expected, with consideration for specific population needs.

The threat of flooding poses a considerable challenge for justice. Not only are more citizens becoming exposed to risk, but they are expected to play increasingly active roles in flood risk management. However, until recently, few efforts have charted broader understandings of disadvantage relating to flood risk exposure. Drawing upon social science scholarship that has long been sensitive to concerns related to justice, we deploy and develop the notion of flood disadvantage as a means to assess the challenges to more ‘just’ flood risk management. We contend that the concept of flood disadvantage offers a useful lens to appreciate the constraints of technical approaches to flood risk management, in particular, its limited ability to incorporate complex social elements such as how individuals have differing vulnerabilities and sensitivities to flooding and uneven abilities to engage with risk agendas. The notion highlights the compounding interactions between flooding and other social disadvantages across multiple public policy areas and scales. We argue a fuller acknowledgement of the socio-spatial-temporal dimensions of intersecting disadvantages can help sensitise technical risk analyses that tend to see people and communities as homogeneous entities in a given spatiality. In doing so we can better reveal why some individuals or communities are more vulnerable to disasters or are slower to recover than others. Finally, we outline the challenges in turning more ‘just’ flood risk management from an abstract notion into one that could inform future practice.

Abstract Flooding remains a major problem for the United States, causing numerous deaths and damaging countless properties. To reduce the impact of flooding on communities, the U.S. government established the Community Rating System (CRS) in 1990 to reduce flood damages by incentivizing communities to engage in flood risk management initiatives that surpass those required by the National Flood Insurance Program. In return, communities enjoy discounted flood insurance premiums. Despite the fact that the CRS raises concerns about the potential for unevenly distributed impacts across different income groups, no study has examined the equity implications of the CRS. This study thus investigates the possibility of unintended consequences of the CRS by answering the question: What is the effect of the CRS on poverty and income inequality? Understanding the impacts of the CRS on poverty and income inequality is useful in fully assessing the unintended consequences of the CRS. The study estimates four fixed‐effects regression models using a panel data set of neighborhood‐level observations from 1970 to 2010. The results indicate that median incomes are lower in CRS communities, but rise in floodplains. Also, the CRS attracts poor residents, but relocates them away from floodplains. Additionally, the CRS attracts top earners, including in floodplains. Finally, the CRS encourages income inequality, but discourages income inequality in floodplains. A better understanding of these unintended consequences of the CRS on poverty and income inequality can help to improve the design and performance of the CRS and, ultimately, increase community resilience to flood disasters.