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Despite the prognoses of the effects of global warming (e.g., rising sea levels, increasing river discharges), few international studies have addressed how flood preparedness should be stimulated among private citizens. This article aims to predict Dutch citizens’ flood preparedness intentions by testing a path model, including previous flood hazard experiences, trust in public flood protection, and flood risk perceptions (both affective and cognitive components). Data were collected through questionnaire surveys in two coastal communities ( n = 169, n = 244) and in one river area community ( n = 658). Causal relations were tested by means of structural equation modeling (SEM). Overall, the results indicate that both cognitive and affective mechanisms influence citizens’ preparedness intentions. First, a higher level of trust reduces citizens’ perceptions of flood likelihood, which in turn hampers their flood preparedness intentions (cognitive route). Second, trust also lessens the amount of dread evoked by flood risk, which in turn impedes flood preparedness intentions (affective route). Moreover, the affective route showed that levels of dread were especially influenced by citizens’ negative and positive emotions related to their previous flood hazard experiences. Negative emotions most often reflected fear and powerlessness, while positive emotions most frequently reflected feelings of solidarity. The results are consistent with the affect heuristic and the historical context of Dutch flood risk management. The great challenge for flood risk management is the accommodation of both cognitive and affective mechanisms in risk communications, especially when most people lack an emotional basis stemming from previous flood hazard events.

Purpose This study aims to understand the socioeconomic impact of flood events on households, especially household welfare in terms of changes in consumption and coping strategies to deal with flood risk. This study is based on Bihar, one of the most frequently flood-affected, most populous and economically backward states in India. Design/methodology/approach Primary data were collected from 700 households in the seven most frequently flood-affected districts in Bihar. A total of 100 individuals from each district were randomly selected from flood-affected villages. Based on a detailed literature review, an econometric (probit) model was developed to test the null hypothesis of the availability of consumption insurance, and the multivariate probability approach was used to analyze the various coping strategies of these households. Findings The results of this study suggest that flood-affected households maintain their consumption by overcoming various losses, including income, house damage and livestock loss. Households depend on financial transfers, borrowings and relief, and migrate to overcome losses. Borrowing could be an extra burden as the government compensates for house damage and crop loss late to the affected households. Again, there is no compensation to overcome livelihood loss and deal with occurrences of post-flood diseases, which further emphasizes the policy implications of strengthening the health infrastructure in the state and generating alternative livelihood opportunities. Originality/value This study discusses flood risk in terms of changes in household welfare, identifies the most effective risk-coping capabilities of rural communities and contributes to the shortcomings of the government insurance and relief model. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-07-2023-0569

Abstract Flood exposure has been linked to shifts in population sizes and composition. Traditionally, these changes have been observed at a local level providing insight to local dynamics but not general trends, or at a coarse resolution that does not capture localized shifts. Using historic flood data between 2000-2023 across the Contiguous United States (CONUS), we identify the relationships between flood exposure and population change. We demonstrate that observed declines in population are statistically associated with higher levels of historic flood exposure, which may be subsequently coupled with future population projections. Several locations have already begun to see population responses to observed flood exposure and are forecasted to have decreased future growth rates as a result. Finally, we find that exposure to high frequency flooding (5 and 20-year return periods) results in 2-7% lower growth rates than baseline projections. This is exacerbated in areas with relatively high exposure to frequent flooding where growth is expected to decline over the next 30 years.

Abstract Disasters worldwide tend to affect the poorest more severely and increase inequality. Brazil is one of the countries with high income‐inequality rates and has unplanned urbanization issues and an extensive disaster risk profile with little knowledge on how those disasters affect people's welfare. Thus, disasters often hit the poorest hardest, increasing the country's income inequality and poverty rates. This study proposes a method to assess the impact of floods on households spatially based on their income levels by conducting flood analysis and income analysis. The method is applied to the Itapocu River basin (IRB) located in Santa Catarina State, Brazil. The flood is assessed by conducting rainfall analysis and hydrological simulation and generating flood inundation maps. The income is evaluated using downloaded 2010 census data and a dasymetric approach. Flood and income information is combined to analyze flood‐impacted households by income level and flood return period. The results confirm the initial assumption that flood events in the IRB are more likely to affect the lowest‐income households rather than the highest‐income levels, thus, increasing the income inequality.

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.

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.