Without taking additional measures, flooding is becoming more likely and intense in a changing climate, which causes large economic damage. Households and firms are directly impacted by physical flood damage, but further ripple effects on society occur through business disruptions. By using post-disaster survey data from the 2021 flood event in the Netherlands, this study adds to the literature on business interruption duration and losses after flooding. The current empirical literature on flood impacts on firms is often unable to distinguish separate effects for flooded and non-flooded firms and does not incorporate flood severity and the influence of risk reduction measures. Here, we use multivariate regression models to determine depth-duration functions that describe the relationship between flood hazard characteristics and business interruption duration. This relationship can be used to calibrate flood damage models that capture indirect firm impacts. The prediction of business interruption after flooding allows for differentiation in business interruption between firms within a flooded area, reducing the reliance of these macroeconomic models on restrictive assumptions. Our results indicate that a day of business interruption duration costs a firm on average 0.5 % of their annual revenue; an effect that is stronger for firms with a weaker connection to their region. Flood damage mitigation (FDM) measures taken at the building level do not significantly affect business interruption duration, although further research on this is required. Finally, quick damage compensation is found to reduce business interruption duration and thus revenue losses, calling for higher insurance uptake and rapid and streamlined post-disaster insurance and government compensation.@en

This study provides an overview of the impact of the 2021 Summer floods in the Netherlands and the assessment of the effectiveness of various adaptation measures, evacuation strategies, and their impact on society. The floods were characterized by record rainfall in the cross-border region of the Meuse and Rhine basins and resulted in devastating losses in the Netherlands, Germany and Belgium. The study reports on a household survey conducted with 1,509 households in the wake of the 2021 flood event in the southern part of the Netherlands (province of Limburg). Using a descriptive approach, we present household experiences during several stages of the disaster management cycle, reporting on experienced flood hazard and impacts, evacuation, flood damage mitigation measures, the compensation progress, risk perceptions, and stress. Our findings highlight the role of early warnings and flood risk information provision in flood risk management. Risk perceptions influence both adaptation and evacuation behavior, as respondents who were aware of flood risks beforehand took significantly more flood damage mitigation measures compared with those who were not aware. Flood damage mitigation measures, such as building with water-resistant materials and elevating valuables, reduced flood damage by 20% to 50%. Our survey shows that of those who received warnings, the majority actually evacuated. However, residents not aware of any evacuation advice evacuated significantly less. Additionally, the majority (75%) of respondents experienced high or very high stress during and after the flood, which is most likely related to the destructive flood impacts and the slow and uncertain compensation experienced by many respondents. This paper describes the flood event and its consequences to provide insights into Dutch disaster management and what can be learned for potential future disasters in other contexts.@en

The floods in the Netherlands in the summer of 2021 led to severe economic damage and losses in the affected area. A first estimate in September 2021 showed that more than 2,500 houses, more than 5,000 inhabitants and around 600 businesses were affected. Using the Dutch standard Flood Damage and Loss Model (SSM2017), and based on figures from international literature, the total damage in the Netherlands is estimated in the order of € 350 – 600 million. Physical damage to houses and businesses, business interruption, damage to infrastructure and crop losses were the most substantial. The differences in damage to individual structures (residential and commercial) were large. The estimated damage in the affected area clearly exceeds the damage of the Meuse River floods in 1993 and 1995 which occurred in the same region (converted to 2021 prices: around € 200 million and € 125 million, respectively, excluding damage due to business interruption). It is important to note that the largest damages and losses in 2021 occurred in the smaller regional rivers, mainly in the Geul floodplain, while in 1993 and 1995 most damage and losses were recorded in the Meuse floodplain.@en

Flood events are expected to increase in their frequency and severity, which results in higher flood risk without additional adaptation measures. The information gained from flood risk models is essential in effective disaster risk management. However, vulnerability estimations are often a large driver of uncertainty, and flood damage is rarely estimated due to a lack of empirical damage data from flood events. This study uses a unique data set with experienced damages and the implementation of flood damage mitigation (FDM) measures on the household level, collected after the flood event in the Netherlands in 2021. Flood damage models that control for several hazard, exposure, and vulnerability indicators are estimated and allow for additional input in flood risk models. Previous estimates of the effectiveness of FDM measures are prone to a selection bias, as households that do, and do not implement FDM measures systematically differ in their risk profiles. By using an instrumental variable-estimation, this study overcomes this selection bias and finds significant reductions in flood damage due to FDM measures. These reductions can be incorporated in multivariate flood vulnerability estimations, which indicate that FDM measures significantly reduce flood damage. Providing information on flood hazard, as well as implementing early warning systems, is crucial for ensuring effective flood risk management.

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Due to rising sea levels and projected socio-economic change, global coastal flood risk is expected to increase in the future. To reduce this increase in risk, one option is to reduce the probability or magnitude of the hazard through the implementation of structural, Nature-based or hybrid adaptation measures. Nature-based Solutions in coastal areas have the potential to reduce impacts of climate change and can provide a more sustainable and cost-effective alternative to structural measures. In this paper, we present the first global scale assessment of the benefits of conserving foreshore vegetation as a means of adaptation to future projections of change in coastal flood risk. In doing so, we extend the current knowledge on the economic feasibility of implementing global scale Nature-based Solutions. We show that globally foreshore vegetation can contribute to a large decrease in both absolute and relative flood risk (13% of present-day and 8.5% of future conditions in 2080 of global flood risk). Although this study gives a first proxy of the flood risk reduction benefits of conserving foreshore vegetation at the global scale, it shows promising results for including Nature-based and hybrid adaptation measures in coastal adaptation schemes.

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Coastal flood hazard and exposure are expected to increase over the course of the 21st century, leading to increased coastal flood risk. In order to limit the increase in future risk, or even reduce coastal flood risk, adaptation is necessary. Here, we present a framework to evaluate the future benefits and costs of structural protection measures at the global scale, which accounts for the influence of different flood risk drivers (namely sea-level rise, subsidence, and socioeconomic change). Globally, we find that the estimated expected annual damage (EAD) increases by a factor of 150 between 2010 and 2080 if we assume that no adaptation takes place. We find that 15 countries account for approximately 90 % of this increase. We then explore four different adaptation objectives and find that they all show high potential in cost-effectively reducing (future) coastal flood risk at the global scale. Attributing the total costs for optimal protection standards, we find that sea-level rise contributes the most to the total costs of adaptation. However, the other drivers also play an important role. The results of this study can be used to highlight potential savings through adaptation at the global scale.

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We assess the suitability of ECMWF Integrated Forecasting System (IFS) data for the global modeling of tropical cyclone (TC) storm surges. We extract meteorological forcing from the IFS at a 0.225° horizontal resolution for eight historical TCs and simulate the corresponding surges using the global tide and surge model. Maximum surge heights for Hurricanes Irma and Sandy are compared with tide gauge observations, with R ² -values of 0.86 and 0.74 respectively. Maximum surge heights for the other TCs are in line with literature. Our case studies demonstrate that a horizontal resolution of 0.225° is sufficient for the large-scale modeling of TC surges. By upscaling the meteorological forcing to coarser resolutions as low as 1.0°, we assess the effects of horizontal resolution on the performance of surge modeling. We demonstrate that coarser resolutions result in lower-modeled surges for all case studies, with modeled surges up to 1 m lower for Irma and Nargis. The largest differences in surges between the different resolutions are found for the TCs with the highest surges. We discuss possible drivers of maximum surge heights (TC size, intensity, and coastal slope and complexity), and find that coastal complexity and slope play a more profound role than TC size and intensity alone. The highest surges are found in areas with complex coastlines (fractal dimension > 1.10) and, in general, shallow coastlines. Our findings show that using high-resolution meteorological forcing is particularly beneficial for areas prone to high TC surges, since these surges are reduced the most in coarse-resolution datasets.

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