Enhancing resilience: Understanding the impact of flood hazard and vulnerability on business interruption and losses

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

Flood Vulnerability Models and Household Flood Damage Mitigation Measures: An Econometric Analysis of Survey Data

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

A look into our future under climate change?: Adaptation and migration intentions following extreme flooding in the Netherlands

Worldwide, increased flood risk from climate change prompts adaptive behavior of households in situ or through migration. Both can be sensible adaptation responses involving tradeoffs, and understanding their drivers is important for effective climate policy. However, in-situ adaptation and migration are rarely studied in combination and research on how extreme events trigger adaptive behavior in originally low-risk areas is lacking. We analyze survey data from residents affected by the extreme summer floods of 2021 in the Netherlands to contribute to fill this research gap. Our results indicate that current low levels of flood-related migration are likely to increase under higher flood risk. Undertaken in-situ adaptation may act as a barrier for further insitu adaptation or migration behavior. Where in-situ adaptation is mostly related to cognitive factors including risk perceptions, response efficacy and self-efficacy, migration seems to be driven by flood-related emotions. Personal flood experience, mediated by worry, is strongly associated with both types of adaptive behavior. We discuss how policymakers can use these insights to guide and anticipate household adaptation behavior

Adaptation to flood risk: Results of international paired flood event studies

As flood impacts are increasing in large parts of the world, understanding the primary drivers of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical case studies, we analyze eight paired floods, that is, consecutive flood events that occurred in the same region, with the second flood causing significantly lower damage. These success stories of risk reduction were selected across different socioeconomic and hydro-climatic contexts. The potential of societies to adapt is uncovered by describing triggered societal changes, as well as formal measures and spontaneous processes that reduced flood risk. This novel approach has the potential to build the basis for an international data collection and analysis effort to better understand and attribute changes in risk due to hydrological extremes in the framework of the IAHSs Panta Rhei initiative. Across all case studies, we find that lower damage caused by the second event was mainly due to significant reductions in vulnerability, for example, via raised risk awareness, preparedness, and improvements of organizational emergency management. Thus, vulnerability reduction plays an essential role for successful adaptation. Our work shows that there is a high potential to adapt, but there remains the challenge to stimulate measures that reduce vulnerability and risk in periods in which extreme events do not occur

Adaptation to flood risk - results of international paired flood event studies

As flood impacts are increasing in large parts of the world, understanding the primary drivers of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical case studies, we analyze eight paired floods, that is, consecutive flood events that occurred in the same region, with the second flood causing significantly lower damage. These success stories of risk reduction were selected across different socioeconomic and hydro‐climatic contexts. The potential of societies to adapt is uncovered by describing triggered societal changes, as well as formal measures and spontaneous processes that reduced flood risk. This novel approach has the potential to build the basis for an international data collection and analysis effort to better understand and attribute changes in risk due to hydrological extremes in the framework of the IAHSs Panta Rhei initiative. Across all case studies, we find that lower damage caused by the second event was mainly due to significant reductions in vulnerability, for example, via raised risk awareness, preparedness, and improvements of organizational emergency management. Thus, vulnerability reduction plays an essential role for successful adaptation. Our work shows that there is a high potential to adapt, but there remains the challenge to stimulate measures that reduce vulnerability and risk in periods in which extreme events do not occur

Delft-FIAT: An open-source flood impact analysis tool

Flood impacts, such as damage and casualties are increasingly important in flood risk management. Estimation of flood impacts enables policy makers to decide on the type of measures to reduce flood risk, and how much investment is warranted. A flexible, generic tool (Delft-FIAT) has been developed using Python, NumPy and GDAL to enable the quick set up a flood impact model in conjunction with the OGC WMS to visualize the results in maps. Delft-FIAT uses the unit loss method, which requires a combination of different data layers: (i) Flood hazard variables; (ii) land-use or objects information (location, type and maximum damage); and (iii) impact functions (usually relating some hazard variable e.g. water depth to an impact or damage fraction). The main advantage of this open-source tool is that it is flexible, as it can take up many different types of impact categories and these can be easily adjusted by the user. Moreover, it is efficient because the calculation engine can handle very large and high resolution input maps thanks to block division techniques in the input/output rasters and vector files. The presented tool is a good example of how open source geospatial software can contribute to environmental monitoring and in particular to flood risk simulations. The tool has already been applied in more than 10 flood risk studies around the world on different spatial scales. These studies show that Delft-FIAT enables researchers to focus on the data and impact knowledge rather than the calculation technology

Generation of User-defined Landscapes for Multi-actor Plan-making

In this paper the functioning of the landscape generator is presented. The landscape generator is developed as part of the planning support system called Simlandscape. Using real-world spatial data and a user-defined intended landscape typology, the landscape generator progresses for satisfying an overall fitness function. This fitness function is compiled of a set of criterion functions describing configurational characteristics of a landscape typology. When the overall fitness function is satisfied a landscape configuration is generated. Discerning technical characteristics with respect to other optimisation techniques, are the use of straightforward design input rules (criterion functions) and its ability to produce acceptable results in considerable time

Methodology to generate landscape configurations for use in multi-actor plan-making processes

In this paper, we investigate an approach to generate landscape configurations for use in multi-actor plan-making processes. Using the information from predefined lot typologies, a heuristic allocation method, consisting of a suitability function and an allocation mechanism of lot components is explained. The suitability function is primarily based on adjacency and distance parameters as found in landscape design literature. The allocation mechanism starts from a random but constrained initial situation, and generates a plausible lot configuration by orderly swapping pairs of cells thereby increasing the overall suitability of the plan . From the results, the limitations of this approach are concluded and the concepts are presented for an improved landscape generation algorithm

Creating 3D models from sketch plans for spatial landscape evaluation

2D sketch plans are hard to interpret for non-professionals and do not contain enough information for plan evaluation. Simple extrusion of 2D sketch plans into 3D will not suffice. This problem is faced by stakeholders in the early stages of the plan design process. Landscape types play an important role in bridging the gap between abstract 2D plans and 3D physical models. A landscape type consists of pictures from an existing landscape, a 3D model and additional attributes providing quantitative data. Through a matching algorithm, 2D landscape components in the sketch plan are replaced by 3D objects. Multiple 3D plans can be created from a specific area with different landscape types. These 3D plans are visualized with a high level of realism and they can be evaluated using the additional data. In this paper examples are shown for an apartment district and a villa district under different energy scenarios. The visual consequences of strategic energy decisions become apparent in the 3D model