Adaptive flood risk management planning based on a comprehensive flood risk conceptualisation

Evaluation of deep learning computer vision for water level measurements in rivers

Image-based gauging stations offer the potential for substantial enhancement in the monitoring networks of river water levels. Nonetheless, the majority of camera gauges fall short in delivering reliable and precise measurements because of the fluctuating appearance of water in the rivers over the course of the year. In this study, we introduce a method for measuring water levels in rivers using both the traditional continuous image subtraction (CIS) approach and a SegNet neural network based on deep learning computer vision. The historical images collected from on-site investigations were employed to train three neural networks (SegNet, U-Net, and FCN) in order to evaluate their effectiveness, overall performance, and reliability. The research findings demonstrated that the SegNet neural network outperformed the CIS method in accurately measuring water levels. The root mean square error (RMSE) between the water level measurements obtained by the SegNet neural network and the gauge station's readings ranged from 0.013 m to 0.066 m, with a high correlation coefficient of 0.998. Furthermore, the study revealed that the performance of the SegNet neural network in analyzing water levels in rivers improved with the inclusion of a larger number of images, diverse image categories, and higher image resolutions in the training dataset. These promising results emphasize the potential of deep learning computer vision technology, particularly the SegNet neural network, to enhance water level measurement in rivers. Notably, the quality and diversity of the training dataset play a crucial role in optimizing the network's performance. Overall, the application of this advanced technology holds great promise for advancing water level monitoring and management in river systems.

Economic assessment of nature-based solutions to reduce flood risk and enhance co-benefits

Flooding is expected to increase due to climate change, urbanisation, and land use change. To address this issue, Nature-Based Solutions (NBSs) are often adopted as innovative and sustainable flood risk management methods. Besides the flood risk reduction benefits, NBSs offer co-benefits for the environment and society. However, these co-benefits are rarely considered in flood risk management due to the inherent complexities of incorporating them into economic assessments. This research addresses this gap by developing a comprehensive methodology that integrates the monetary analysis of co-benefits with flood risk reduction in economic assessments. In doing so, it aspires to provide a more holistic view of the impact of NBS in flood risk management. The assessment employs a framework based on life-cycle cost-benefit analysis, offering a systematic and transparent assessment of both costs and benefits over time supported by key indicators like net present value and benefit cost ratio. The methodology has been applied to the Tamnava basin in Serbia, where significant flooding occurred in 2014 and 2020. The methodology offers valuable insights for practitioners, researchers, and planners seeking to assess the co-benefits of NBS and integrate them into economic assessments. The results show that when considering flood risk reduction alone, all considered measures have higher costs than the benefits derived from avoiding flood damage. However, when incorporating co-benefits, several NBS have a net positive economic impact, including afforestation/reforestation and retention ponds with cost-benefit ratios of 3.5 and 5.6 respectively. This suggests that incorporating co-benefits into economic assessments can significantly increase the overall economic efficiency and viability of NBS.

Feasibility of Traditional Open Levee System for River Flood Mitigation in Japan

An open levee system is a traditional flood mitigation system for reducing the expansion of inland flooding and decreasing the peak flow. However, there have been few quantitative studies on its feasibility. Furthermore, the differences in applicability depending on the topography and the construction of continuous levees have not been fully examined. We studied its feasibility based on simulations in the Kuji River area, where the vast Typhoon Hagibis occurred. Morphological models representing the past (the 1940s) and the present (2019), obtained by modifying the highly accurate digital elevation models (DEM) via the tracing of aerial photos, were applied to a 2D unsteady flow simulation model to reveal the effects of the levee system on river hydrography and overland flood behavior. The results indicated that inundation flow through an open area decreased both inundation duration and depth, while the reduction of peak discharge is relatively insignificant at approximately 10%. The sub levees are not adequate under the current conditions and floodwater volume, and their effectiveness depends on the surrounding conditions, such as the development of continuous levees.

The application of an environmental performance framework for climate adaptation innovations on two nature-based adaptations

In this paper, we introduce and test a framework to qualitatively assess the environmental impact of climate adaptation innovations with the ambition to facilitate the implementation of these adaptations. The framework was designed to enable continuous environmentally conscious benchmarking based on three environmental performance indicators: sustainable design, environmental impact and ecological impact. It was pilot tested by uninvolved experts and key-persons for two large-scale nature-based flood adaptation innovations in the Netherlands and discussed with environmental assessment professionals. Our findings indicate how the inclusion of our framework helps to identify important knowledge gaps regarding environmental co-benefits and trade-offs, and can be beneficial to both those developing the innovation and the local authorities charged with assessing the suitability of innovations. We conclude by noting how the incorporation of environmental impact assessment from the design stage of adaptations could supplement existing environmental assessment regulations pre-empting concerns rather than reacting to them.

Understanding the NEEDS for ACTING: An integrated framework for applying nature-based solutions in Brazil

Nature-based solutions (NBS) support the provision of multiple benefits for the environment and society. First idealised in 2008, NBS are recommended by worldwide reports and guidelines as strategies to protect, sustainably manage and restore ecosystems. However, their operationalisation is still in the early stages, especially in developing countries, and only a few studies consider their full potential. This article contributes to this context by developing an integrated framework, with spatial and participatory tools, for analysing flood risk mitigation in Brazil. The approach enables a deep understanding of the societal challenges and vulnerabilities of the area (i.e., NEEDS) for subsequently planning the appropriate NBS (i.e., ACTIONS), with the participation of 255 stakeholders of Campina Grande municipality. Results show mappings of flood-prone areas, in which approximately 52% of the flooded areas will see an increase in the future. Hotspots (i.e., hazard, vulnerability, and exposure) are shown and discussed with four application cases. Finally, multiple benefits of seven NBS alternatives are analysed in 53 scenarios of application, in which the higher rates of reductions are found to combined alternatives. The discussion emphasizes the importance of spatially assessing the 'needs' and 'multiple benefits' of NBS, including reducing vulnerabilities and increment of resilience.

Flood Vulnerability Analysis in Urban Context: A Socioeconomic Sub-Indicators Overview

Despite indicators-based assessment models for flood vulnerability being a well-established methodology, a specific set of indicators that are universally or widely accepted has not been recognized yet. This work aims to review previous studies in the field of vulnerability analysis in order to overcome this knowledge gap identifying the most accepted sub-indicators of exposure, sensitivity and adaptive capacity. Moreover, this review aims to clarify the use of the terms of vulnerability and risk in vulnerability assessment. Throughout a three-phase process, a matrix containing all the sub-indicators encountered during the review process was constructed. Then, based on an adaptation of the Pareto diagram, a set of the most relevant sub-indicators was identified. According to the citation count of each sub-indicator, indeed, 33 sub-indicators were chosen to represent the most universally or widely accepted sub-indicators.

A Critical Review of Flood Risk Management and the Selection of Suitable Measures

Modern-day flood management has evolved into a variety of flood management alternatives. The selection of appropriate flood measures is crucial under a variety of flood management practices, approaches, and assessment criteria. Many leading countries appraise the significance of risk-based flood management, but the fixed return period is still the de facto standard of flood management practices. Several measures, approaches, and design criteria have been developed over time. Understanding their role, significance, and correlation toward risk-based flood management is crucial for integrating them into a plan for a floodplain. The direct impacts of a flood are caused by direct contact with the flood, while indirect impacts occur as a result of the interruptions and disruptions of the socio-economical aspects. To proceed with a risk-based flood management approach, the fundamental requirement is to understand the risk dynamics of a floodplain and to identify the principal parameter that should primarily be addressed so as to reduce the risk. Risk is a potential loss that may arise from a hazard. On the one hand, exposure and susceptibility of the vulnerable system, and on the other, the intensity and probability of the hazard, are the parameters that can be used to quantitatively determine risk. The selection of suitable measures for a flood management scheme requires a firm apprehension of the risk mechanism. Under socio-economic and environmental constraints, several measures can be employed at the catchments, channels, and floodplains. The effectiveness of flood measures depends on the floodplain characteristics and supporting measures.

Realising the potential of cultural heritage to achieve climate change actions in the Netherlands

Climate change impacts on diverse cultural heritage is gaining scholarly and policy attention, yet little research has been conducted on how can diverse cultural heritage inform decisionmakers and policymakers in achieving climate change actions (i.e., climate change adaptation and mitigation). For this study, we conducted semi-structured interviews with Dutch cultural heritage and environmental or climate change experts (n = 52) and participant observations across the Netherlands to explore the importance of cultural heritage benefits and their relation to climate change actions. We also explored the perceptions of cultural heritage management over time, including the influence of climate policy on heritage practice in the Netherlands. Our findings show that experts perceived a multiplicity of heritage benefits as important in supporting and informing present and future climate change actions. The most salient benefits were informational benefits where diverse cultural heritage is perceived as an important source of knowledge about past societal, economic and environmental developments and changes. Further, heritage management was perceived as constantly changing over time, reflecting the transformative nature of diverse heritage types. Experts agreed that climate policy has already influenced cultural heritage practice in the Netherlands. Lastly, the interrelationships between heritage benefits and management were identified and characterised. This study informs both cultural heritage and climate change research agendas and helps leverage diverse cultural heritage into climate change adaptation and mitigation policies.

Forecasting of Future Flooding and Risk Assessment under CMIP6 Climate Projection in Neuse River, North Carolina

Hydrological extremes associated with climate change are becoming an increasing concern all over the world. Frequent flooding, one of the extremes, needs to be analyzed while considering climate change to mitigate flood risk. This study forecast streamflow and evaluate risk of flooding in the Neuse River, North Carolina considering future climatic scenarios, and comparing them with an existing Federal Emergency Management Agency study. The cumulative distribution function transformation method was adopted for bias correction to reduce the uncertainty present in the Coupled Model Intercomparison Project Phase 6 (CMIP6) streamflow data. To calculate 100-year and 500-year flood discharges, the Generalized Extreme Value (L-Moment) was utilized on bias-corrected multimodel ensemble data with different climate projections. Out of all projections, shared socio-economic pathways (SSP5-8.5) exhibited the maximum design streamflow, which was routed through a hydraulic model, the Hydrological Engineering Center’s River Analysis System (HEC-RAS), to generate flood inundation and risk maps. The result indicates an increase in flood inundation extent compared to the existing study, depicting a higher flood hazard and risk in the future. This study highlights the importance of forecasting future flood risk and utilizing the projected climate data to obtain essential information to determine effective strategic plans for future floodplain management.

A framework for comparing permanent and forecast-based flood risk-reduction strategies

Flood risk can be reduced at various stages of the disaster management cycle. Traditionally, permanent infrastructure is used for flood prevention, while residual risk is managed with emergency measures that are triggered by forecasts. Advances in flood forecasting hold promise for a more prominent role to forecast-based measures. In this study, we present a methodology that compares permanent with forecast-based flood-prevention measures. On the basis of this methodology, we demonstrate how operational decision-makers can select between acting against frequent low-impact, and rare high-impact events. Through a hypothetical example, we describe a number of decision scenarios using flood risk indicators for Chikwawa, Malawi, and modelled and forecasted discharge data from 1997 to 2018. The results indicate that the choice between permanent and temporary measures is affected by the cost of measures, climatological flood risk, and forecast ability to produce accurate flood warnings. Temporary measures are likely to be more cost-effective than permanent measures when the probability of flooding is low. Furthermore, a combination of the two types of measures can be the most cost-effective solution, particularly when the forecast is more skillful in capturing low-frequency events. Finally, we show that action against frequent low-impact events could more cost-effective than action against rare high-impact ones. We conclude that forecast-based measures could be used as an alternative to some of the permanent measures rather than being used only to cover the residual risk, and thus, should be taken into consideration when identifying the optimal flood risk strategy.

Fine-Scale Coastal Storm Surge Disaster Vulnerability and Risk Assessment Model: A Case Study of Laizhou Bay, China

In the assessment of storm surge vulnerability, existing studies have often selected several types of disaster-bearing bodies and assessed their exposure. In reality, however, storm surges impact all types of disaster-bearing bodies in coastal and estuarine areas. Therefore, all types of disaster-bearing bodies exposed to storm surges should be considered when assessing exposure. In addition, geographical factors will also have an impact on the exposure of the affected bodies, and thus need to be fully considered. Hence, we propose a fine-scale coastal storm surge disaster vulnerability and risk assessment model. First, fine-scale land-use data were obtained based on high-resolution remote sensing images. Combined with natural geographic factors, such as the digital elevation model (DEM), slope, and distance to water, the exposure of the disaster-bearing bodies in each geographic unit of the coastal zone was comprehensively determined. A total of five indicators, such as the percentage of females and ratio of fishery products to the gross domestic product (GDP), were then selected to assess sensitivity. In addition, six indicators, including GDP and general public budget expenditure, were selected to assess adaptability. Utilizing the indicators constructed from exposure, sensitivity, and adaptability, a vulnerability assessment was performed in the coastal area of Laizhou Bay, China, which is at high risk from storm surges. Furthermore, the storm surge risk assessment was achieved in combination with storm water statistics. The results revealed that the Kenli District, Changyi City, and the Hanting District have a higher risk of storm surge and require more attention during storm surges. The storm surge vulnerability and risk assessment model proposed in this experiment fully considers the impact of the natural environment on the exposure indicators of the coastal zone’s disaster-bearing bodies, and combines sensitivity, adaptability indicators, and storm water record data to conduct vulnerability and risk assessment. At the same time, the model proposed in this study can also realize multi-scale assessment of storm surge vulnerability and risk based on different scales of socioeconomic statistical data, which has the advantages of flexibility and ease of operation.

An interdisciplinary and catchment approach to enhancing urban flood resilience: a Melbourne case

This paper presents a novel interdisciplinary and catchment-based approach for exploring urban flood resilience. Our research identified and developed a diverse set of adaptation measures for Elwood, a suburb in Melbourne, Australia, that is vulnerable to pluvial and coastal flooding. We drew on methods from social science, urban design and environmental engineering to gain integrated insights into the opportunities for Elwood to increase its flood resilience and urban liveability. Results showed that an appropriate balance of social, infrastructural and urban design responses would be required to retreat from, accommodate and protect against flood risk. These would also deliver broader benefits such as securing water supplies through harvested stormwater and mitigating extreme heat through greener landscapes. Our interdisciplinary approach demonstrated the value of (i) engaging with the community to understand their concerns, aspirations and adaptation ideas, (ii) exploring design measures that densify and use urban forms in ways that implement adaptation measures while responding to local context, (iii) adopting modelling techniques to test the performance, robustness and economic viability of possible adaptation solutions, and (iv) innovating governance arrangements and principles needed to improve flood resilience in the Elster Creek catchment. Our research also provided valuable insight on how to operationalize interdisciplinary work in practice, highlighting the importance of sharing an impact agenda, taking a place-based approach, developing a common conceptual framework, and fostering a constructive team culture. This article is part of the theme issue 'Urban flood resilience'.

Application of Reliability Analysis for Risk Ranking in a Levee Reconstruction Project

Levees are embankments designed for passive flood protection. In order to reduce the potential of climate-induced flooding risks, it is necessary to reconstruct or upgrade the existing levees. Flood risk management aims to reduce the probability of floods and their potential adverse effects on the population, economy, and environment. This paper presents the novel application of reliability analysis for risk ranking in the Otok Virje-Brezje levee reconstruction project in the Republic of Croatia. To identify, verify and analyse key risks, a group of 35 experts, who were directly involved in the levee reconstruction project or have extensive experience in similar projects, was selected. An Analytic network process (ANP) was used for group multi criteria decision-making. Quantitative and qualitative approaches to risk analysis were combined. Different experts from the various organisations may have diverse interests and goals. The geometric mean method was chosen to reach group consensus. The resources that will be allocated to the risk responses are proportional to the risk exposures. To analyse the reliability of the group consensus-reaching method a determination of the risk ranking probability matrix is proposed by using the Monte Carlo simulation method. Different decision-making approaches are proposed for cases in which consensus is not reached with satisfactory reliability.

Social Learning in Multilevel Flood Risk Governance: Lessons from the Dutch Room for the River Program

Although social learning is a key element of multilevel flood risk governance, it is hardly studied. This paper addresses this knowledge gap. The paper aims to identify enabling conditions for social learning in multilevel flood risks governance arrangements. We first conceptualize social learning and draw up a conceptual framework consisting of enabling conditions for social learning, using the literature on adaptive co-management, sustainable land and water management, and integrated flood risk management. Next, we apply this framework to analyze social learning in the context of the Dutch Room for the River program. Our interview results reveal that social learning about integrated flood protection measures took place at multiple levels. We found that a strong personal commitment to learning and mutual interpersonal trust in working groups are key conditions for successful social learning. Based on our analysis, we conclude with some recommendations for enhancing social learning processes in future flood protection programs.

Extreme Coastal Water Levels Exacerbate Fluvial Flood Hazards in Northwestern Europe

Compound flooding, such as the co-occurrence of fluvial floods and extreme coastal water levels (CWL), may lead to significant impacts in densely-populated Low Elevation Coastal Zones. They may overstrain disaster management owing to the co-occurrence of inundation from rivers and the sea. Recent studies are limited by analyzing joint dependence between river discharge and either CWL or storm surges, and little is known about return levels of compound flooding, accounting for the covariance between drivers. Here, we assess the compound flood severity and identify hotspots for northwestern Europe during 1970–2014, using a newly developed Compound Hazard Ratio (CHR) that compares the severity of compound flooding associated with extreme CWL with the unconditional T-year fluvial peak discharge. We show that extreme CWL and stronger storms greatly amplify fluvial flood hazards. Our results, based on frequency analyses of observational records during 2013/2014’s winter storm Xaver, reveal that the river discharge of the 50-year compound flood is up to 70% larger, conditioned on the occurrence of extreme CWL, than that of the at-site peak discharge. For this event, nearly half of the stream gauges show increased flood hazards, demonstrating the importance of including the compounding effect of extreme CWL in river flood risk management.

Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification

Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.

Flash Flood Risk Analysis Based on Machine Learning Techniques in the Yunnan Province, China

Flash flood, one of the most devastating weather-related hazards in the world, has become more and more frequent in past decades. For the purpose of flood mitigation, it is necessary to understand the distribution of flash flood risk. In this study, artificial intelligence (Least squares support vector machine: LSSVM) and classical canonical method (Logistic regression: LR) are used to assess the flash flood risk in the Yunnan Province based on historical flash flood records and 13 meteorological, topographical, hydrological and anthropological factors. Results indicate that: (1) the LSSVM with Radial basis function (RBF) Kernel works the best (Accuracy = 0.79) and the LR is the worst (Accuracy = 0.75) in testing; (2) flash flood risk distribution identified by the LSSVM in Yunnan province is near normal distribution; (3) the high-risk areas are mainly concentrated in the central and southeastern regions, where with a large curve number; and (4) the impact factors contributing the flash flood risk map from higher to low are: Curve number > Digital elevation > Slope > River density > Flash Flood preventions > Topographic Wetness Index > annual maximum 24 h precipitation > annual maximum 3 h precipitation.

Mediterranean UNESCO World Heritage at risk from coastal flooding and erosion due to sea-level rise

UNESCO World Heritage sites (WHS) located in coastal areas are increasingly at risk from coastal hazards due to sea-level rise. In this study, we assess Mediterranean cultural WHS at risk from coastal flooding and erosion under four sea-level rise scenarios until 2100. Based on the analysis of spatially explicit WHS data, we develop an index-based approach that allows for ranking WHS at risk from both coastal hazards. Here we show that of 49 cultural WHS located in low-lying coastal areas of the Mediterranean, 37 are at risk from a 100-year flood and 42 from coastal erosion, already today. Until 2100, flood risk may increase by 50% and erosion risk by 13% across the region, with considerably higher increases at individual WHS. Our results provide a first-order assessment of where adaptation is most urgently needed and can support policymakers in steering local-scale research to devise suitable adaptation strategies for each WHS.

UNESCO World Heritage located in low-lying coastal areas is increasingly at risk from flooding and erosion due to sea-level rise. This study shows that up to 82% of cultural World Heritage sites located in the Mediterranean will be at risk from coastal flooding and over 93% from coastal erosion by 2100 under high-end sea-level rise.

Transitioning to Sponge Cities: Challenges and Opportunities to Address Urban Water Problems in China

At present, the Sponge City Concept (SCC) is gaining ground, Sponge Cities technologies are becoming more and more accepted by Chinese city governments, and the first best practices are being shared. However, there are still many challenges ahead which hamper effective implementation and upscaling. This paper presents an overview of some opportunities and constraints for the take up of this approach and has drawn upon international experiences. In China at the national level, the State Council has set a progressive target for the SCC initiative to be achieved in 2030. This target seems to be ambitious as the time needed for integrative planning and design and implementation is much longer than traditional sectoral approaches often omitting to address social well-being, the (local) economy, and ecosystem health. This particularly holds true for the existing building stock. Transforming the existing building stock requires a long-term planning horizon, with urban restoration, regeneration, and modernization being key drivers for adapting the city to become a sponge city. A key challenge will be to align the sponge city initiative (SCI) projects with infrastructure and urban renovation portfolios. Moreover, substantial investment needs and a lack of reliable financing schemes and experience also provide a huge challenge for China. This calls for an integrative opportunistic strategy that creates enabling conditions for linking the SCI investment agenda with those from other sectors. These transformations cannot be made overnight: completing the transformation process will typically take a life time of one generation. The progress in sustainable urban water management is also impacted by innovations in technologies as well as in management strategies. These technological innovations create fertile ground for businesses to adapt state-of-the-art developments from around the world and contextualize them into fit-for-purpose products. China is well-placed to play a leading role in this process in the coming decade.

Lessons learned from applying adaptation pathways in flood risk management and challenges for the further development of this approach

Worldwide, an increase in flood damage is observed. Governments are looking for effective ways to protect lives, buildings, and infrastructure. At the same time, a large investment gap seems to exist-a big difference between what should necessarily be done to curb the increase in damage and what is actually being done. Decision-makers involved in climate adaptation are facing fundamental (so-called deep) uncertainties. In the course of time, the scientific community has developed a wide range of different approaches for dealing with these uncertainties. One of these approaches, adaptation pathways, is gaining traction as a way of framing and informing climate adaptation. But research shows that "very little work has been done to evaluate the current use of adaptation pathways and its utility to practitioners and decision makers" (Lin et al. 2017, p. 387). With this paper, the authors, as action researchers and practitioners involved in two of the world's largest real-life applications of this approach in flood risk management, aim to contribute to filling in that gap. Analysis of the experience in the United Kingdom and the Netherlands in long-term planning in flood risk management shows that the adaptation pathways approach is effective in keeping decision processes going forward, to the final approval of a long-term plan, and helps increase awareness about uncertainties. It contributes to political support for keeping long-term options open and motivates decision-makers to modify their plans to better accommodate future conditions. When it comes to implementing the plans, there are still some major challenges, yet to be addressed, amongst others: the timely detection of tipping points in situations with large natural variability, the inclusion of measures that prepare for a switch to transformational strategies, and the retention of commitment of regional and local authorities, non government organizations, and the private sector, to climate adaptation as national policies move from blueprint planning to adaptive plans. In delivering this feedback, the authors hope to motivate the scientific community to take on these challenges.

Identifying spatial clusters of flood exposure to support decision making in risk management

A sound understanding of flood risk drivers (hazard, exposure and vulnerability) is essential for the effective and efficient implementation of risk-reduction strategies. In this paper, we focus on 'exposure' and study the influence of different methods and parameters of flood exposure analyses in Switzerland. We consider two types of exposure indicators and two different spatial aggregation schemes: the density of exposed assets (exposed numbers per km²) and the ratios of exposed assets (share of exposed assets compared to total amount of assets in a specific region) per municipality and per grid cells of similar size as the municipalities. While identifying high densities of exposed assets highlights priority areas for cost-efficient strategies, high exposure ratios can suggest areas of interest for strategies focused on the most vulnerable regions, i.e. regions with a low capacity to cope with a disaster. In Switzerland, the spatial distribution of high exposure densities and exposure ratios tend to be complementary. With regards to the methods, we find that the spatial cluster analysis provides more information for the prioritization of flood protection measures than 'simple' maps of spatially aggregated data represented in quantiles. In addition, our study shows that the data aggregation scheme influences the results. It suggests that the aggregation based on grid cells supports the comparability of different regions better than aggregation based on municipalities and is, thus, more appropriate for nationwide analyses.

Flood risk assessments at different spatial scales

Managing flood risk, i.e. both the hazard and the potential consequences, is an important aspect of adapting to global change and has gained much traction in recent decades. As a result, a priori flood risk assessments have become an important part of flood management practices. Many methodologies have been set up, ranging from global risk assessments for the world as a whole, to local assessments for a particular stretch of a river/coast or small town. Most assessment frameworks generally follow a similar approach, but there are also notable differences between assessments at different spatial scales. This review article examines these differences, for instance those related to the methodology, use of assessments and uncertainties. From this review, future research needs are identified in order to improve flood risk assessments at different scales. At global/continental scale, there is a clear need for harmonised information on flood defences to improve assessments. Furthermore, inclusions of indirect economic effects at the macro-/meso-scale would give a better indication of the total effects of catastrophic flooding. At the meso-/micro-scale, there is an urgent need to improve our understanding of the effects of flooding on critical infrastructures, given their importance to society, the economy, emergency management and reconstruction. An overarching theme at all scales is the validation of flood risk assessments, which is often limited. More detailed post-disaster information would allow for improved calibration, validation and thus performance of flood risk models. Lastly, the link between spatial scales also deserves attention, for instance up- or downscaling methodologies.