Mapping the Sensitivity of Population Exposure to Changes in Flood Magnitude: Prospective Application From Local to Global Scale

The floodplains of rivers are relevant living spaces for population globally and provide favorable locations for economic development. However, these areas are commonly exposed to floods, and the increasing population together with the changes in storminess as a result of global warming mean that the risks from flooding are expected to rise. Most studies investigating the impact that climatic change has on flood risk are based on a cascade of global climate model simulations coupled with regional climate models, hydrologic models, inundation models, and flood impact models. However, this approach is subject to uncertainties. Model results are found to be sensitive to climate forcing, the structure of the underlying models, the choice of methods used for downscaling and bias correction, and the use of extreme value analysis for both current and future climate conditions. Moreover, uncertainties are expected to propagate through the model cascade. To overcome these problems, we propose a method for analyzing and mapping the sensitivity of population exposure in floodplains to changes in flood magnitude. The method is based on downward counterfactuals, namely perturbations of a selected flood scenario by increasing its magnitude, interpreted in this case as the worsening of a today’s design flood event as a result of climatic changes. The increase in the impact of a current design flood compared to its counterfactual illustrates the sensitivity to changes in hazard. We calculate the normalized gradients of the flood exposure curves, that is, the increase in the exposure and magnitude of the perturbed event relative to the exposure and magnitude of the current scenario. We test the applicability of the method on local, national, and global scale by using existing data sets, including flood hazard maps, flood protection standards, floodplain delineation, river network definition, and spatial population distribution. The gradients were found to vary remarkably across the globe and are overall smaller in the upper range of flood magnitudes that in the lower range. Based on these results, we compare the drivers of the sensitivity in different parts of the world and identify river reaches with the highest relative gradients. These river reaches might be the most affected by climate change and thus deserve an indepth investigation of the underlying characteristics of the floodplains and the need for climate change adaptation.Mobiliar Lab for Natural Risks, Oeschger Centre for Climate Change Research, University of BernEuropean Union (EU) 754446UGR Research and Knowledge Transfer Fund-AtheneaUniversity of Granad

Participatory development of storymaps to visualize the spatiotemporal dynamics and impacts of extreme flood events for disaster preparedness

Floods are one of the costliest natural hazards in Switzerland and worldwide. Therefore, society is confronted with questions about protecting people and assets from flood risks. Key instruments are protective measures, land use regulations, spatial planning, and the interventions by civil protection units if flood magnitudes exceed the protection standards. Both prevention and preparedness require risk awareness from professionals, politicians, and the public. Risk awareness is generally high after an event and low after a period without major events. However, the rarity of extreme flood events limits learning from flood events. The training of intervention forces who should manage flood events with magnitudes beyond hitherto observed flood events requires a comprehensive description and visualization of the flood processes and their impacts. To address this, together with stakeholders and civil protection and intervention planning experts, we co-developed a new way to visualize the spatiotemporal dynamics of extreme flood events and thereby communicate their impacts using dynamical flood storymaps. We selected physically plausible precipitation scenarios from reforecasts to develop storylines of extreme river flood events and their socioeconomic impacts in Switzerland. The co-development process revealed which information is relevant to potential users and how it must be presented. It is shown that storylines of extreme events presented as storymaps are a valuable tool to communicate scientific results in a way that allows practitioners to gain relevant information for their work. Therefore, we built an interactive online tool (www.flooddynamics.ch), enabling the user to analyze the spatiotemporal unfolding of flood events in Switzerland from the start of precipitation to the recession of the flood. The visualization includes maps of inundated areas at hourly timesteps and the related impacts in terms of affected persons, buildings, roads, and infrastructure. Such a temporally explicit (dynamic) representation of extreme events in storymaps, in contrast to static hazard maps, which are commonly used today, is favorable for emergency intervention planning and training and thus for awareness creation and better disaster preparedness

Short communication: A model to predict flood loss in mountain areas

Because effects of climate change and an increase in elements at risk, mountain hazard loss increased throughout Europe. Yet, factors influencing loss, i.e. vulnerability, have gained less attention to date. Vulnerability is defined as the degree of loss resulting from the hazard impact on buildings. Recent studies have focused on evaluating vulnerability to dynamic flooding using proxies from case studies and based on empirical ex-post approaches. However, the transferability to other case studies and, therefore, the ability of such models to actually predict future losses is limited. To overcome this gap, we present a beta model based on loss data from the European Alps, which clearly shows that a single vulnerability function is sufficient to predict losses resulting from different types of torrential hazards and to provide probabilities of destruction under specific scenarios. As a result, the curves are transferable and may significantly increase the predictive power of risk analyses

Spatio-Temporal Dynamics and Drivers of Flood Risk Change. Perspectives of Coupled Component Models

Extreme floods are one of the most damaging natural hazards, accounting for the majority of all economic losses from natural hazards worldwide. Several intertwined natural and anthropogenic drivers influence flood risk and its change: global warming, precipitation patterns, flood triggering processes, river morphology, river engineering works, population and values at risk, and flood risk reduction strategies. Sustainable flood risk management requires understanding all aspects of flood risk and its change in space and time. Thus, flood risks must be analyzed from a dynamic rather than a static perspective. However, methods to analyze and quantify environmental and socio-economic changes related to flood risk, both in space and time, are nearly not existent. Within this cumulative habilitation thesis methods are examined and developed that allow the analysis of past and future changes in both the natural and human environment with a spatially explicit perspective, and methods that allow disentangling the different drivers of change that are mostly interwoven and have opposing effects on flood risk evolution. The habilitation extends the frontiers of research on flood risk changes with three main methodological approaches: (1) data-driven analyses of environmental and socio-economic change, (2) development of models for specific aspects of flood risk, and (3) model coupling. Coupled component models provide an interesting approach for analyzing flood risk change, for modelling feedback mechanisms between human activities and the natural environment, and for the regionalization of global environmental and socio-economic changes. The habilitation thesis gives an outlook for enabling coupled model frameworks to predict and evaluate the effects of different adaptation strategies on flood risk evolution. Finally a modelling framework that couples specialist models toward whole-system models offers the potential for obtaining an universalist view and unifying several approaches in geography. Such a holistic approach is supporting the search for sustainable solutions for the complex and interconnected problems we are facing today

River corrections and long-term changes in flood risk in the Aare valley, Switzerland

Flood risk is changing over time. Beside climatic changes, key drivers for changing flood risks are the modification of the river courses by flood defence structures and the increase in properties exposed to floods due to economic development. In this study, both effects – the modification of the river courses and the increase of economic assets – on the long-term evolution of flood risk were isolated and confronted. To this aim, two states of the river network were compared, one representing the river courses of today and another representing the river courses of the early 19th century before the river corrections took place. Selected observed and well documented flood events of the last decades were modelled on the historic states of the river reaches. The documented flood events were compared with the simulations in terms of inundated area and exposed buildings. Without river corrections, the flooded areas and the number of exposed residential housings would be remarkably higher than observed in recent flood events. The examples show that the effects of the main river corrections are remarkable for today’s economic activities in the floodplains. Therefore, the maintenance of the former river correction works is an important part of today’s risk management practice

Floodplains and Complex Adaptive Systems—Perspectives on Connecting the Dots in Flood Risk Assessment with Coupled Component Models

Floodplains, as seen from the flood risk management perspective, are composed of co-evolving natural and human systems. Both flood processes (that is, the hazard) and the values at risk (that is, settlements and infrastructure built in hazardous areas) are dynamically changing over time and influence each other. These changes influence future risk pathways. The co-evolution of all of these drivers for changes in flood risk could lead to emergent behavior. Hence, complexity theory and systems science can provide a sound theoretical framework for flood risk management in the 21st century. This review aims at providing an entry point for modelers in flood risk research to consider floodplains as complex adaptive systems. For the systems science community, the actual problems and approaches in the flood risk research community are summarized. Finally, an outlook is given on potential future coupled component modeling approaches that aims at bringing together both disciplines

Sensitivity of flood loss estimates to building representation and flow depth attribution methods in micro-scale flood modelling

Thanks to modelling advances and the increase in computational resources in recent years, it is now feasible to perform 2-D urban flood simulations at very high spatial resolutions and to conduct flood risk assessments at the scale of single buildings. In this study, we explore the sensitivity of flood loss estimates obtained in such micro-scale analyses to the spatial representation of the buildings in the 2D flood inundation model and to the hazard attribution methods in the flood loss model. The results show that building representation has a limited effect on the exposure values (i.e. the number of elements at risk), but can have a significant impact on the hazard values attributed to the buildings. On the other hand, the two methods for hazard attribution tested in this work result in remarkably different flood loss estimates. The sensitivity of the predicted flood losses to the attribution method is comparable to the one associated with the vulnerability curve. The findings highlight the need for incorporating these sources of uncertainty into microscale flood risk prediction methodologies