More frequent and intense drought and heat events imply increased multi-risks for urban green infrastructure (UGI) and their ecosystem services. To tackle this challenge, a conceptual drought and heat risk assessment framework has been developed. This study operationalizes the framework by providing a methodology that supports decision makers in their assessment, and selection of risk reduction alternatives. The methodology overlays two main procedures of the assessment: risk analysis and risk evaluation. Within the risk analysis, the risk system is delineated, from the drought and heat hazards, to the vulnerabilities of UGI entities, ecosystem functions (EF), and ecosystem services (ES). Urban parks, creeks, and lakes are used as exemplary UGI to derive biophysical system variables as so-called endpoints. A multi-layer approach is applied to translate the endpoints into an information system comprising descriptor, attribute, and indicator layers. The assignment of attributes and indicators to descriptors is based on a literature search. Hazard attributes are then linked with vulnerability indicators to derive risk indicators. A lane-based approach is adopted to interrelate indicators, and to identify the key indicators of the cascading nature of the system. The indicators “Net leaf-air temperature” and “Leaf net CO2 assimilation” are determined as key indicators with 10 linkages each. As for the risk evaluation, a guideline is set to support the selection of methods for the multi-criteria evaluation. Based upon, methods such as the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are deemed especially applicable. Finally, the role of decision makers as end-users of the methodology and its local adoption is described together with principles for selecting these decision makers. A tool is designed to offer a simple and adaptive way to organize the calculation steps of the risk assessment, making it transferable and effective to use for researchers and practitioners of environmental risk management. Overall, the proposed methodology supports decision-making on drought and heat risks of UGI through systematic risk analysis and risk evaluation.

Urban green infrastructure (UGI) is a prominent concept toward climate adaptation and urban resilience, but it is also affected by droughts and heat. Hence, this study aims to advance the multi-assessment of drought and heat risks (DHRs) for UGI through the DHR assessment framework with conceptual and methodological features, paving the way toward knowledge creation and decision support. The framework was systematically developed, starting with defining the situation, analyzing concepts, and finally, constructing the framework. The situation is interpreted as a coupled human and natural system to represent the biophysical and immaterial elements, processes, and interrelations. Further, the concepts of risk, UGI, and ecosystem services lead to a risk system showing the compound hazards, the exposure, and the cascading vulnerabilities of the UGI. The DHR assessment framework distinguishes two stages, multi-risk analysis and multi-criteria risk evaluation. The analysis includes the definition and interpretation of the UGI situation under drought and heat conditions, analyzing the hazards, exposures, and vulnerabilities of the system, and translating the risk system into an indicator-based information system. Hereby, the vulnerability analysis of the biophysical UGI aspects comprises the susceptibility and resilience of UGI entities, as well as the degree to which providing ecosystem functions and services can be affected. The multi-criteria risk evaluation covers the assignment of thresholds and weights for indicators, in addition to the aggregation methods. The resulting framework intends to support local actors in the risk assessment of current and future conditions, fostering evidence-based decisions and interventions to deal with compound DHRs.

The projected increase in ‘water scarcity – water reuse’ situations, the associated risks and sustainability challenges, and trends towards holistic approaches motivate the development of integrated assessment for decision-making. The integrated Risk and Sustainability Assessment (RSA) Framework combines the analysis and evaluation of both risk and sustainability of ‘water scarcity – water reuse’ situations. This work aims to test the RSA Framework in a case study in Chile. The analysis uses a multi-layer approach and lane-based approach to translate the real-world system into an information system and to determine interlinkages between indicators. The evaluation involves thresholds and weights to calculate risk and sustainability sub-indices and an RSA index applying TOPSIS. The results indicate low interlinkage between risk and sustainability indicators, visibilising the importance of which and how indicators are considered and what they measure. They show a higher than tolerable degree of risk but an acceptable degree of sustainability. The relevance of spatial and temporal scales for the assessment becomes evident. Spatial aspects are key in determining the degree of water scarcity and how the impact of water reuse can be included in its calculation. Temporal aspects complicate the integration of risk (scenario-based) and sustainability (snapshot mode) assessments. The TOPSIS method appears to be suitable for the aggregation of risk and sustainability performance indicators. Altogether, the results show the potential of the RSA Framework for organising and processing information required to support decision-makers addressing ‘water scarcity – water reuse’ situations from the perspectives of risk and sustainability.

‘Environmental non-migration’ refers to the spatial continuity of an individual’s residence at the same place despite environmental risk. Moreover, this is a largely under-researched topic, especially within the climate change adaptation discourse, but is increasingly coming to the attention of scientists and policymakers for sustainable adaptation planning. So far, there exists hardly any conceptual and methodical guidelines to study environmental non-migration. Considering this research gap, this paper explores environmental non-migration based on the notion that factors of livelihood resilience can partly explain the decision to non-migration. Here, livelihood resilience is seen as an outcome of the interactions between societal and environmental conditions of an individual household. These conditions inform the decisions (to stay or to migrate) taken in case of a hazard or creeping environmental change. Their influence generalises the spectrum of migration decision-making (to stay or to migrate), which is conceptualised by four broad outcomes categorised into voluntary and involuntary, and non-migrants and migrants. This analytical concept is operationalised through an empirical example in southwest coastal Bangladesh. The results suggest that the Livelihood Resilience Index (LRI) relates to the voluntary nature of migration decisions once they are made. Still, only a household’s resilience cannot predict the decisions the household makes to stay or migrate. The paper concludes that the proposed analytical concept, with its exemplary factors, maybe an initial means to holistically explore migration decisions in the context of natural hazards and climate and environmental change. However, environmental non-migration remains complex and multi-faceted, and its assessment requires deeper examination at various scales.

Given the significance of urban green infrastructure (UGI) and their ecosystem services (ES) towards urban climate resilience and sustainable development, a practical method to assess the drought and heat risks for UGI is needed for understanding the risks, selecting reduction alternatives and protecting the benefits of UGI. Hence, this study develops a spatiotemporal indicator-based method, based on a conceptual drought and heat risk assessment framework, which supports decision makers in analyzing and evaluating risks under changing conditions, and selecting risk-reduction alternatives. The UGI types of parks, creeks, and lakes are selected as representative UGI for this study for developing the assessment method. Subsequently, endpoints as variables of the biophysical risk system are derived considering the processes of drought and heat hazards, exposed UGI entities, ecosystem functions and ES. The biophysical endpoints such as biota, soil-water dynamics, and UGI’s cultural uses, are then translated into information with descriptors explaining their vulnerability aspects following a multi-layer approach and interpreted over three dimensions of provisioning, regulating, and cultural. The multi-layer approach states that the layers of descriptors are accompanied with layers of indicators as a mean to operationalize these characteristics. A two-stage literature review is applied to identify vulnerability indicators for the defined descriptors, whereas a lane-based approach is followed to interrelate these indicators based on their qualities we refer to as attributes. Using the attributes of the drought and heat hazards, the vulnerability indicators are linked with the hazards to derive risk indicators. By introducing these vulnerability and risk indicators, we pave the road for the analysis and evaluation of compound risks to support the decision makers in planning and managing UGI and protecting their ES under these risks.

Anthropogenic greenhouse gas emissions are leading to accelerating climate change, forcing politicians and administrations to take actions to mitigate climate change and adapt to its impacts, such as changes in flood regimes. For European countries, an increasing frequency and severity of extreme rainfall and flood events is expected. However, studies on future flood risks caused by climate change are associated with various uncertainties. The risk simulations are elaborate as they consider (i) climate data ensembles (temperature, precipitation), (ii) hydrological modeling (flood generation), (iii) hydrodynamic modeling (flood conveyance), and (iv) vulnerability modeling (damage assessment) involving a huge amount of data and their handling with Big Data methods. The results are difficult to understand for decision makers. Therefore, FloodVis offers a means of visualizing possible future flood risks in Virtual Reality (VR). The presentation of the results in a VR especially supports the user in understanding the complexity of the dynamics of the risk system enabling the feeling of presence. In FloodVis the user enters into a virtual surrounding to interact with the data, examine the temporal evolution, and compare alternative development pathways. Critical structures that require improved protection can be identified. The user can follow the inundation process in hourly resolution. We evaluated FloodVis through an online and offline user study on the context of whether VR can provide a better visualization of ensemble flood risk data and whether the sense of presence in VR

Urbanization induces spatial and environmental changes. Monitoring and understanding the nature of these changes is crucial to achieving sustainable urban development imperatives. To this end, this paper examines the evolution and spatio-environmental impacts of rapid urbanization in two major metropolitan regions of Ghana-Accra-City Region and the Greater Kumasi Sub-Region. The analysis uses Landsat satellite data and landscape metrics to examine land use transitions and to characterize the emergent landscapes over the last three decades. The results show that built-up land has increased significantly in these metropolitan regions largely at the expense of environmental land cover classes. The expansion process follows a general trend where the historical-core zones were initially sites of rapid land cover conversion to built-up, with settlements in the suburban and peripheral zones expanding in recent years and becoming integrated into the conterminous urban areas of the metropolitan regions. The analysis also uncovered a unique, dynamic and complex process whereby the urban-open-space class, being in a permanent state of flux, mediates transitions between built-up land and vegetation and vice versa. The metric-based land use transformation analysis shows that the landscape of the metropolitan regions has fragmented because of an increased expansion and aggregation of patches of built-up land in the core areas and leapfrog, sprawling expansion in the outlying suburban and peripheral zones. The paper concludes on the need for integrative urban growth management strategies that brings together spatial planning and environmental resource governance to avert the negative consequences on the natural environment of unfettered urban expansion.

Decision-makers face major challenges when trying to reduce risks of water scarcity sustainably through measures of water reuse. One of these challenges is the lack of interconnectedness between risk assessment for water scarcity and sustainability assessment for water reuse. Therefore, this paper aims to explore the conceptual integration of risk and sustainability assessments (RSA) in a framework for decision support in ‘water scarcity – water reuse’ situations. This article follows a three steps approach: (i) defining and interpreting the ‘water scarcity – water reuse’ situation as a coupled human and natural system; (ii) identifying and defining key concepts relevant for risk and sustainability assessment, and (iii) constructing the integrated RSA Framework for decision support. As a result, the latter provides a conceptualisation of a simultaneous assessment of water scarcity as a risk and the sustainability of water reuse measures according to the social, economic, and environmental dimensions. It contemplates an analysis phase and an evaluation phase to provide unified information on the level of water scarcity risk and water reuse sustainability. The resulting indicates that the integration of risk and sustainability in one joint assessment for decision support is conceptually feasible. It hence paves the way towards a comprehensive and consistent methodological operationalisation and empirical application.

Millions of people impacted by climate change actually want to remain in place; these aspirations and respective capabilities need more attention in migration research and climate adaptation policies. Residents at risk may voluntarily stay put, as opposed to being involuntarily trapped, and understanding such subjectivity is empirically challenging. This comment elaborates on "voluntary non-migration" to call attention to a neglected population within the ongoing discourses on climate-induced migration, social equality and human rights. A roadmap for action outlines specific research and policy goals.

Systemic risks are characterized by high complexity, multiple uncertainties, major ambiguities, and transgressive effects on other systems outside of the system of origin. Due to these characteristics, systemic risks are overextending established risk management and create new, unsolved challenges for policymaking in risk assessment and risk governance. Their negative effects are often pervasive, impacting fields beyond the obvious primary areas of harm. This article addresses these challenges of systemic risks from different disciplinary and sectorial perspectives. It highlights the special contributions of these perspectives and approaches and provides a synthesis for an interdisciplinary understanding of systemic risks and effective governance. The main argument is that understanding systemic risks and providing good governance advice relies on an approach that integrates novel modeling tools from complexity sciences with empirical data from observations, experiments, or simulations and evidence-based insights about social and cultural response patterns revealed by quantitative (e.g., surveys) or qualitative (e.g., participatory appraisals) investigations. Systemic risks cannot be easily characterized by single numerical estimations but can be assessed by using multiple indicators and including several dynamic gradients that can be aggregated into diverse but coherent scenarios. Lastly, governance of systemic risks requires interdisciplinary and cross-sectoral cooperation, a close monitoring system, and the engagement of scientists, regulators, and stakeholders to be effective as well as socially acceptable.

In recent decades, advances in methodology have enabled increasing detail in flood risk assessments. In particular, resolution in the location and quantification of risk have significantly increased due to the improved spatio-temporal availability of climate, weather, and land-cover data as well as enhanced modelling capabilities. High-resolution information supports flood risk management practice in the design and implementation of locally specified and efficient risk reduction strategies. Observations of flood events with their impacts have proved the added value of these efforts. However, not all flood events seem to be addressed by the tailored risk reduction. An analysis of the EM-DAT data for the period 1960–2013, for example, shows an overall slight decrease of the loss rate only with negative trends for countries with lower-middle income levels and positive trends for countries with high income levels (Tanoue, Hirabayashi, & Ikeuchi, 2016). In a similar way, data published by the insurance industry indicate an ongoing increase of flood impacts (e.g., Munich Re, 2017). This means that the success of previous efforts on high-resolution information is limited. An obvious immediate explanation of those observations could be that the state of the art in flood risk management research is not considered sufficiently in flood risk management practice. Of course, real-world societal conditions provide so many obstacles to implementation such as budget constraints, property rights, and public acceptance which mostly do not allow for realisation of the best possible technical solution. Another explanation could be to assign the responsibility for the observed limited risk reduction to climate change or the change of exposure and vulnerability of people and assets. This is supported by evidence for influences of environmental and societal drivers of change from various studies (e.g., Zischg et al., 2018). But, even in close-to-design risk-reduction implementation cases or under minor environmental and societal change, post-event observations can reveal findings that need particular reflection. Events can occur in a way that had not been anticipated in the earlier risk assessment (e.g., Di Baldassarre, Schumann, Bates, Freer, & Beven, 2010); for instance, water arising from the hinterland of the dikes can cause inundation of “protected” settlements behind the dikes. Taking the differences between risk assessments and observations after the events into account, a more provocative explanation of the above data could be as follows: The current risk assessment approaches do not sufficiently represent all processes relevant for flood risk generation and the approaches applied are maybe too narrow. This is why a more comprehensive and dynamic “nature” of environmental and societal processes needs to be recognised. To date, various disciplines have developed tools for the description of floods with their impacts such as hydrological models, hydrodynamic models, and more recently also damage models. Calculation of flood risks is based on loosely coupling of these tools with their individual input data. Those tool boxes seem to be science driven since representation of the real-world follows the combined capabilities of the disciplines involved. Risk assessment on this basis enables representation of the core processes of flood risk generation. Furthermore, dynamics of risks are addressed by scenarios of medium- and long-term climate change with their influence on either the occurrence frequencies of events or the severity. A couple of studies even include societal change in the mostly scenario-based foresight approaches (e.g., Winsemius et al., 2016). The selected discrete scenarios determine the range of possible developments considered as aleatory uncertainty. They exceed the aleatory uncertainty already covered by the occurrence frequency of events (e.g., Hall & Solomatine, 2010). In essence, the state of the art is the result of a methodological evolution with its path dependency on the evolution of the disciplines involved and their cooperation. Taking the comprehensive and dynamic “nature” of the flood risk into account can lead to a completely different perspective on the description of flood risks. Notably, the rising application of systems concepts in the environmental sciences as they are now used in the earth system sciences (e.g., Donges et al., 2018) seems to be promising. These concepts take a holistic view from the beginning onwards. They can maybe only partly be realised since fully (bio-)physical-based descriptions are not always feasible, especially for multi-faceted open systems. Flood risks also occur in those kinds of systems and hence very likely do not allow for a fully (bio-)physical-based approach. However, systems approaches in more general terms focus on the inclusion of all relevant elements with their interrelations and dynamics. They intend to provide the prerequisites for identification of emergent system features and behaviours. The proposed principal view seems to be justified for flood risk assessment at least as a complementary attempt. The underlying hypothesis is that simulation of a flood risk system with its wide spectrum of boundary conditions can enhance the description of the possible system behaviour. It involves the expectation that post-event observations are more likely to be covered by system-based pre-event simulations. Hereby, the latter are not misunderstood as a means of better predictions. Instead, they are supposed to facilitate learning about the system behaviour for more appropriate responses. The potential of the resulting knowledge lies in the scope of risks under dynamic boundary conditions. This is assumed to facilitate a more realistic understanding of the full range of possible events. Following the lines of the general system theory, the starting point of flood risk assessment is the conceptualisation of the “flood risk system.” Conceptualisation comprises contextual, spatial and temporal system delineation, identification of relevant system elements (e.g., people, assets, infrastructure) and mapping of system interdependencies. Representation of interdependencies bears on a selection of major cause–effect interrelations with their network probably including the display with software tools such as the Unified Modelling Language (UML). As already stated, construction of a fully (bio-)physical-based system will very likely remain unfeasible. The core processes of flood risk generation for fluvial flood risks are related to the cascade from rainfall-runoff generation and concentration, flood wave propagation and impact generation. Other processes, for instance, are cascading and consequential effects on the infrastructure network. Processes influencing system elements are triggered by autonomous external or internal drivers of variability or change and targeted interventions (Schanze, Trümper, Burmeister, Pavlik, & Kruhlov, 2012). They lead to the dynamics of the system's boundary conditions. Conceptualisation of the system in this way can reach an “intermediate” complex and dynamic system representation with mimicking key system features although it does not meet the requirement for a systems approach in a narrow sense. It supports a more epistemological perspective rather than the current predominant methodological framing. Simulation of the “intermediate” system requires a set of models and methods. On the one hand, it depends on the availability of tools for representing the network of cause–effect interrelations. On the other hand, it needs to be created according to the systems concept and not initially restricted to the availability of tools. For the core processes of flood risk generation, the established hydrological, hydrodynamic, and damage models again play an essential role. However, these models require hard coupling as a model “pipeline” to allow for whole system simulations. To do so, specific software is required to run the entire “pipeline” on a High Performance Computing (HPC) facility such as the so-called Simple Linux Utility for Resource Management (SLURM). Furthermore, auto-calibration and parallelised algorithms of individual models become key to enhance the model performance within the pipeline. Other parts of the cause–effect interrelations network can be simulated with additional pipelines or using, for example, Agent-Based Models (ABM). As a result, the conceptualised “intermediate” flood risk system is intended to be simulated with high performance, considering optimisation of the HPC facility in terms of, for example, number of nodes and CPUs/GPUs for the calculation time. Mimicking the system dynamics depends on projections of autonomous environmental and societal change as well as targeted system interventions for the elements prone to alteration. Especially for the drivers of change, ensembles are now widely established at least in the climate research community. They reflect inherent and epistemic uncertainties through the inclusion of a multitude of scenarios and projection methods. Combined environmental and societal ensembles may consider the full range of changing boundary conditions. Moreover, they can support consistency of scenarios and projections for all drivers (Winsemius et al., 2016). Simulations of the “intermediate” system under those ensembles lead to a huge number of model runs exceeding current risk assessment in research and practice. They result in a very wide range of risks which in the best case covers most possible risks. Interpretation of these results is not straight forward. It necessitates most recent methods from data analytics such as deep learning using artificial intelligence to identify pattern in the data that uncover spatial and temporal variabilities, uncertainties and development trends (e.g., Najafabadi et al., 2015). This means that the additional efforts of the systems approach are not dedicated to specifying the geographical space and time where risks are expected to be precise. In contrast, its strength lies in the exploration of the entire possible future development even distinguishing the influences of autonomous change and targeted interventions to identify the decision space within the full range of possible developments. The potentials of the systemic understanding of flood risks are not yet fully explored and hence still require more attention in future research. The challenges range from data integration and harmonisation to performance optimisation and digital analytics of the results, which is now a focus in Big Data research. Typical issues are heterogeneity, velocity, veracity and volume of data (see Gaidomi & Haider, 2015). Accordingly, a direct application of the systems approach in flood risk management practice will not be feasible in the short term. Nevertheless, in the long run risk assessment, risk evaluation and risk reduction with the whole spectrum from emergency management to long-term planning are expected to profit from capabilities to better consider the interdependencies and dynamic boundary conditions of the flood risk system as well as the identification of most possible risks. This will require methodological and interpretation guidelines for practical application. Beyond this, the systems approach also has a direct implication for flood risk management practice from a societal perspective. It asks for a close cross-sectoral cooperation to create the systems concept, to adjust consistent ensembles, to build a common database and to agree on the interpretation and use of the outcomes. The latter among others mainly refers to the consideration of various uncertainties and their patterns in the risk reduction strategies. Complementing the current paradigm of anticipating the future, it facilitates resilience of the responses, for example, through flexibility of measures and instruments (Schanze, 2016). This will improve elasticity of the flood risk system. Although this approach might lower efficiency of spending resources for both risk assessment and risk reduction, it is likely to advance overall capacity to deal with unpredictable dynamics and accelerations of the Anthropocene.

River floods are currently among the most devastating natural hazards. In the last two decades, much research has been conducted in the field of flood risk management, but the role of land has received little attention explicitly; important questions are: How do different kinds of land use and land management influence flood risk generation? Whose land should be used to retain water or mitigate vulnerability? Which policy instruments allow for accessing and governing the land? This special issue is an endeavour to explore the various meanings of land for flood risk management with the specific lenses of relevant disciplines ranging from natural sciences to policy science and economics. In general, flood hazard generation mainly depends on the retention capacity of the land, where vulnerability and risk result from exposure of receptors as well as from their susceptibility, value or function, and coping capacity (e.g., Blanco-Vogt & Schanze, 2014). Accordingly, there are three primary risk reduction options for river floods: first, to retain runoff in the headwaters of catchments through decentralised water retention before it reaches the river network; second, to slow the flood propagation down and cut the peak discharge in the river network upstream of areas prone to flood impacts through modifying flood conveyance, centralised water retention, and flood defence; and third, to foster resilient settlements through mitigation of their exposure and vulnerability. Each of these options has specific effects on flood risks also depending on the size of a catchment and the nature of the flood. Moreover, it may involve various side-effects and interdependencies. Hence, the relevance of land for these options significantly varies. The three options are not entirely new. However, their appropriate combination and effective implementation on the catchment scale seem still to be hampered by a lack of knowledge on the site-specific multifunctionality of land, catchment-wide interrelations, and coordinated land governance (Hartmann & Juepner, 2014; Klijn, Samuels, & van Os, 2008). Many existing studies on flood risk management focus on selected hydro-meteorological aspects, vulnerability with resilience of constructions, or management strategies and the governance context. A catchment-wide and consistent view on land from the biophysical processes to the institutional arrangements is lacking and thus likely to remain a major hurdle for effective risk reduction. This special issue frames the respective field with key contributions from relevant disciplines ranging from hydrology to planning science and economics. It starts with articles on the three options and then provides contributions on crosscutting topics.

Projections of future land-cover (LC) change are challenging because of the multitude of spatial and dynamic drivers involved, such as politics, economics, demographics, and the environment. This paper presents a combined qualitative and quantitative scenario approach for giving consistent projections of urban and rural land-cover change (LCC), considering both the demands of certain LC types, and their allocation. The approach has been implemented in the Upper Western Bug River catchment in Ukraine in the context of integrated water resource management. Special attention is paid to the identification of spatial and dynamic drivers of LCC, the scenario formulation and projection of the identified drivers, and the projections of alternative plausible LCC. The identification of spatial and dynamic drivers is based on the detection of retrospective LCC, statistical analysis of interrelations between LCC and drivers, and expert validation of transition rules. The scenario formulation and projection of the drivers involve storylines with inputs from expert interviews. The creation of future LC change projections followed four steps: suitability maps from retrospective LCC detection, expert validation, the future development of drivers, and the allocation of LCC. Results indicate demographic change and GDP development as dynamic drivers mainly influencing the LCC, as other studies have implied. Furthermore, there are spatial drivers influencing the local allocation such as the regional capital of Lviv, and they are shaped by, for example, environmental laws, distances to roads and settlements, slope, and soil fertility.

Journal of Flood Risk ManagementVolume 11, Issue 3 p. 227-229 EditorialFree Access Pluvial flood risk management: an evolving and specific field Jochen Schanze, Jochen Schanze Associate EditorSearch for more papers by this author Jochen Schanze, Jochen Schanze Associate EditorSearch for more papers by this author First published: 21 August 2018 https://doi.org/10.1111/jfr3.12487Citations: 13AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat River and coastal floods with their related risks are well-established topics in international flood risk management research and practice. They continue to have relevance due to on-going high damage in some regions of the world, climate change impacts, and, the need for effective, resilient and sustainable solutions (c.f. e.g. Temmerman et al., 2013; Tanoue et al., 2016). In addition, since the end of the 1970s, flash floods have gained attention following catastrophic events around the globe (e.g. Big Thomson Flood 1976). Whilst heavy rainfall and flash flooding are closely related phenomena (c.f. Schumacher, 2017), recent publications differentiate more strictly between flash floods (e.g. Javelle et al., 2016) and pluvial floods (e.g. Szewranski et al., 2018). Although both are − with a few exceptions such as dam breaks − triggered by convective storms, each has their own characteristics. Flash floods are usually associated with the headwaters of a river network ranging in catchment size from a few square kilometres up to some hundred square kilometres together with steep slopes in mountainous areas or impermeable surfaces in desert wadis. They involve runoff concentration and lead to high flow velocities and tractive forces that cause significant sediment transport and creation of debris flows with a high space–time variability (Szewranski et al., 2018). Flash floods can also affect land and communities remote from the causative rainfall. The onset of this flood type has been observed to appear within a couple of hours (c.f. Javelle et al., 2016). Impacts exceed the damage due to static inundation and comprise erosion or sedimentation even of assets. Flash flooding may cause numerous fatalities (c.f. Schumacher, 2017). In contrast, pluvial floods occur on a much smaller spatial scale without any direct relation to the main river network. They depend strongly upon the micro topography and the drainage pathways. The possible role of the sewer capacity has led to the use of the term 'sewer flood' as a synonym. Although this would be appropriate for urban areas and drainage systems consisting only of sewers, urban water management practice has now broadened using a combination of grey and green infrastructure for sustainable stormwater drainage (commonly known as SuDS). Moreover, pluvial floods also occur in rural areas with surface flow across agricultural land, accumulating on lower lying land and in settlements according to the natural or artificial drainage conditions. The onset of this flood type can occur within a couple of minutes to a few hours of the rainfall. The resulting floods are shaped by a rapid rise in water level and highly turbulent conditions at outflows or manholes. The impacts in urban areas include the inundation of basements and ground floors of buildings as well as the infrastructure systems, for example public and private transport. In rural areas, such floods cause waterlogging of soils and damaging of crops, leading to loss of livelihood and income from agriculture. This very brief characterisation of the two flood types not only illustrates the principal differences in the generation of the flood risks, it also indicates the particular factors needed in their investigation and management. In the remainder of this editorial, the focus is on pluvial floods as a more recent and hitherto hidden topic of flood risk management research and practice. Major challenges are derived from the state of the art published in the academic literature and current practice documented in reports. A common structure for the description of the flood risk system is applied, starting with the source of flooding, proceeding with the pathways and ending with the receptors and consequences. Finally, the implications of these challenges for the management of the flood risks are considered. Rainfall events are not only the source of pluvial flood risks but also the key triggering component. The state of the respective research is summarised by Schumacher (2017, p. 1): 'Although scientific understanding of the processes responsible for heavy rainfall continues to advance, there are still many challenges associated with predicting where, when, and how much precipitation will occur'. Of course, the issues of analysing, simulating and predicting storm-scale atmospheric processes also matter for flash floods. However, the prediction of extreme rainfall causing pluvial floods needs a particular high degree of detail in the observation and explanation of the deep atmospheric convection with an appropriate spatial and temporal resolution, coupled with consideration of influences from the local land surface and landscape patterns. Based on the current knowledge and methodologies, any prediction of amounts of extreme rainfall for a defined grid involves significant uncertainties (e.g. Apel et al., 2016). In line with that, climate change impacts on the triggering atmospheric processes are difficult to project. This is a major problem given the very high confidence referring to the increase of extreme precipitation in the AR5 (IPCC, 2014). Thus, there is at least a demand for long-term, small-scale observations of rainfall events causing pluvial floods. Furthermore, studies try to calculate the change of the frequency of events with a defined intensity (e.g. DeGaetano and Castellano, 2017). The requirements for specific fine-scale resolution also apply to the description of the pathways of pluvial floods. First, propagation of those floods is shaped by the natural and anthropogenic topographic micro relief (c.f. Palla et al., 2016). Detection of this relief may use most recent very high resolution (VHR) methods such as space-borne optical satellites (e.g. GeoEye, WorldView and Pléiades; Barbarella et al., 2017) and terrestrial LiDAR (e.g. Hancock et al., 2017), in addition to air-borne and terrestrial laser scanning. Currently, vertical resolutions of the order of up to 0.1–0.2 m can be achieved. Digital elevation models (DEM), as commonly used for other flood types (including flash floods), normally are insufficient. And even the most recent DEM products reach their limitation of vertical accuracy in a spatial resolution that is still relevant for analysing pluvial floods. Second, the flood conveyance depends highly on the location of natural or artificial flow obstacles and drainage structures such as manholes. Therefore, detailed data on drainage infrastructure in urban areas are required which might be provided from the urban water management organisation. In contrast to the urban situation, obstructions and drainage structures in rural areas are much more difficult to identify and may involve resource-intensive fieldwork. Third, hydrodynamic modelling of pluvial flooding requires suitable tools. Similar to the previous aspects of the sources and pathways of pluvial floods, the core challenges relate to parameterisation and processing. Crowd-sourcing of data and the application of model tools in high-performance computing (HPC) environments most recently have led to technological advance, especially in real-time forecasting (c.f. e.g. Liang et al., 2017). A closer look at the impacts of pluvial floods indicates that the receptors should also be considered from a particular view since the predominately low water levels and depths of this flood type do not affect large parts of buildings but mainly the basements and ground floors. Damage assessment, derivation of depth-damage functions and damage modelling all require higher accuracy for pluvial flood assessments beyond the identification of structures from topographic maps as in the common approach of risk mapping for river floods. Currently there is little specific research available on pluvial flood vulnerability but some physical-based knowledge has been gained on surface and groundwater flood vulnerability (e.g. Schinke et al., 2012) which can be customised and further specified for pluvial flooding. It is also necessary to take into account the small scale retention function of inundated basements. In addition to characterising the vulnerability, risk assessment for pluvial floods needs high accuracy in the location of buildings to determine their exposure. Advances in remote-sensing techniques have paved the way towards a use of these techniques for exposure and even vulnerability assessment (e.g. Geiß et al., 2016). Satellite images not only provide large-scale, high resolution observation, but also facilitate detection of changes in the built environment and enable updating of databases. Innovation can currently be seen in the collection and validation of crowd-sourced data, for example, on lateral view especially from street view imagery or social networks (c.f. Hecht et al., 2017). The assessment of pluvial flood risks from the individual components of the risk system also involves a couple of particular issues. The most important one is the high degree of uncertainty in the intensity and related frequency of the spatially distributed risk. These uncertainties stem from both the understanding of the risk system and the data and methods representing its components. Thus, these uncertainties are both aleatory and epistemic (c.f. Apel et al., 2016). Because of the very high resolution needed from the risk modelling, uncertainties may often only be estimated instead of quantified. For example, sensitivity runs may assist in exploring their impacts on the results. Probability calculation as in other flood types can cover both hazard and risk, leading to well-established risk metrics such as expected annual damage (EAD). There are various methods to calculate these metrics such as simulated time series, numerical solution and analytical solution (c.f. Olsen et al., 2015). Beyond these traditional approaches, new methods are evolving to tackle the fact that pluvial floods may cause impacts significantly higher than the direct damage due to interruption of key functions of urban areas such as transport. Mapping of pluvial flood hazards and particularly flood risks mainly focuses on the asset values and is still in its infancy as an information tool (c.f. e.g. EC (2015) for national approaches within the EU). The high degree of uncertainty has implications for risk management and governance. Whilst river floods in intensively gauged catchments justify an anticipation of probable future events, the mostly unexpected nature of pluvial floods demands more emphasis on a resilience approach (c.f. Schanze, 2016). Resilience in this case refers to organisational capacities in dealing with the unexpected based on, for instance, the diversity of responses and the redundancy of response resources. Experience from previous events may be a means of continuous, albeit slow learning about uncertainties in a wider decision-making context (c.f. Penning-Rowsell and Korndewal, 2018). Overall, pluvial flood risk management is an emerging and rather specific field that needs further development in research and practice. Up to now, no database exists documenting the share of all impacts from pluvial flooding compared to other flood types. Reports from a few countries indicate a possible ratio of approximately 30% to 50%. Against this background, the likely increase of the frequency and severity of pluvial flood risks, due to climate change and even societal change, demands greater urgency and attention to this type of flooding. Further research and development of practice should address both the specific character of pluvial floods and their role in multi-hazard and multi-risk situations alongside other flood types and flood vulnerabilities. References Apel H., Martínez Trepat O., Hung N.N., Chinh D.T., Merz B. & Dung N.V. Combined fluvial and pluvial urban flood hazard analysis: concept development and application to Can Tho city, Mekong Delta, Vietnam. Nat Hazards Earth Syst Sci 2016, 16, 941– 961. Barbarella M., Fiani M. & Zollo C. Assessment of DEM derived from very high-resolution stereo satellite imagery for geomorphometric analysis. Eur J Remote Sens 2017, 50, (1), 534– 549. DeGaetano A.T. & Castellano C.M. Future projections of extreme precipitation intensity-duration-frequency curves for climate adaptation planning in New York state. Clim Serv 2017, 2017, (5), 23– 35. EC – European Commission EU overview of methodologies used in preparation of flood hazard and flood risk maps. 2015. http://ec.europa.eu/environment/water/flood_risk/pdf/fhrm_reports/EU%20FHRM%20Overview%20Report.pdf (accessed 18 July 2018). Geiß C., Jilge M., Lakes T. & Taubenböck H. Estimation of seismic vulnerability levels of urban structures with multisensor remote sensing. IEEE J Sel Top Appl Earth Obs Remote Sens 2016, 9, (5), 1913– 1936. Hancock S., Anderson A., Disney M. & Gaston K.J. Measurement of fine-spatial-resolution 3D vegetation structure with airborne waveform lidar: Calibration and validation with voxelised terrestrial lidar. Remote Sens Environ 2017, 2017, (188), 37– 50. Hecht R., Kalla M. & Krüger T. Crowd-sourced data collection to support automatic classification of building footprint data. In: Proceedings of the 28th International Cartographic Conference (ICC2017), July 1-8th. Washington DC: Copernicus Publications, 2017, 1– 10. IPCC – Intergovernmental Panel on Climate Change Climate change 2014: impacts, adaptation, and vulnerability. Part A: Global and Sectoral Aspects. Cambridge, UK and New York: Cambridge University Press, 2014. Javelle P., Braud I., Saint-Martin C., Payrastre O., Gaume E., et al.. Improving flash flood forecasting and warning capabilities. The Mediterranean region under climate change. A scientific update, IRD editions, 978-2-7099-2219-7, 2016. Liang Q., Xing Y., Ming X., Xia X., Chen H., Tong X. & Wang G. An open-source modelling and data system for near real-time flood forecasting. In: Q. Liang, Y. Xing, X. Ming, X. Xia, H. Chen, X. Tong & G. Wang, eds. E-proceedings of the 37th IAHR World Congress August 13–18, 2017. Kuala Lumpur, Malaysia: IAHR, 2017, 1– 10. Olsen A.S., Zhou Q., Linde J.J. & Arnbjerg-Nielsen K. Comparing methods of calculating expected annual damage in urban pluvial flood risk assessments. Water 2015, 7, 255– 270. Palla A., Colli M., Candela A., Aronica G.T. & Lanza L.G. Pluvial flooding in urban areas: the role of surface drainage efficiency. J Flood Risk Manag 2016, 2018, (11), S663– S676. Penning-Rowsell E. & Korndewal M. The realities of managing uncertainties surrounding pluvial urban flood risk: an ex post analysis in three European cities. J Flood Risk Manag 2018, 2018, 1– 12. Schanze J. Resilience in flood risk management – Exploring its added value for science and practice. E3S Web Conferences 2016, 7, (08003), 1– 9. Schinke R., Neubert M., Hennersdorf J., Stodolny U., Sommer T. & Naumann T. Damage estimation of subterranean building constructions due to groundwater inundation – the GIS-based model approach GRUWAD. Nat Hazards Earth Syst Sci 2012, 12, (9), 2865– 2877. Schumacher R.S. Heavy rainfall and flash flooding. In: Oxford Research Encyclopedia, Natural Hazard Science, Oxford University Press, 2017, 1– 41. Szewranski S., Chruscinski J., Kazak J., Swiader M., Tokarczyk-Dorociak K. & Zmuda R. Pluvial flood risk assessment tool (PFRA) for rainwater management and adaptation to climate change in newly urbanised areas. Water 2018, 10, (386), 1– 20. Tanoue M., Hirabayashi Y. & Ikeuchi H. Global-scale river flood vulnerability in the last 50 years. Sci Rep 2016, 6, 36021. Temmerman S., Meire P., Bouma T.J., Herman P.M.J., Ysebaert T. & De Vried H.J. Ecosystem-based coastal defence in the face of global change. Nature 2013, 504, 79– 83. Citing Literature Volume11, Issue3September 2018Pages 227-229 ReferencesRelatedInformation

The introduction of a risk-based approach for the management of floods has particularly triggered a stronger involvement of flood vulnerability with its exposure as element of risk generation complementary to the flood hazard as well as a focus on the probabilities of flood events with their impacts as a means of determining the reliability of flood defences and tolerability of risk. With risk defined as the likelihood of negative consequences, areas with a (potential) risk, such as settlements, moved to the fore (cf. EU Floods Directive). Risk reduction strategies accordingly concentrate on the control and conveyance of discharge from upstream of these areas at risk and the protection of the vulnerable elements. These strategies involve a high degree of grey infrastructure, such as upstream dams and local defences, in combination with technologies for flood proofing of constructions. Recently, experts from nature conservation emphasised the meaning of natural processes for nature conservation and natural resources management (International Union for Conservation of Nature (IUCN), 2012). This led to the concept of so-called nature-based solutions (NBSs) which in the meantime has been also set on the politically agenda (e.g. Nesshöver et al., 2016) not least since it fits well the broader context of the 2030 Agenda for Sustainable Development. NBSs have been defined by the European Expert Group on ‘Nature-Based Solutions and Re-Naturing Cities’ as ‘… actions inspired by, supported by or copied from nature; both using and enhancing existing solutions to challenges, as well as exploring more novel solutions, for example, mimicking how non-human organisms and communities cope with environmental extremes. nature-based solutions use the features and complex system processes of nature, such as its ability to store carbon and regulate water flows …’ (European Commission (EC), 2015, p. 24). Additional criteria for the definition of NBSs have been proposed by Albert et al. (2017). In principle, the concept seems to have a relation to water and flood issues and hence asks for consideration in the disaster risk community in general and the flood risk management community in particular. Both observations and model-based analyses carried out at catchment scale indicate that the larger the catchment and the higher the severity of an event, the lower are effects of the land surface on the discharge and resulting floods (e.g. Rogger et al., 2017). However, it is also expected that NBSs may exceed the influence of land cover and could have more significant hydrological or hydrodynamic effects, especially if realised in a spatially densely distributed manner. Direct effects are supposed to be complemented by indirect effects on other ecosystem services and landscape functions and hence require comprehensive assessment disclosing co-benefits. Therefore, it is crucial to examine carefully the potential of NBSs as a contribution to flood risk management rather than adopting the term as a buzzword only. Exploration of this potential seems to be additionally justified given the remaining high flood risks in many regions of the world (e.g. Tanoue et al., 2016) and the limitations of existing design levels of grey infrastructures under the conditions of climate and societal change. Advancements of understanding could be grounded in a few guiding questions for flood risk management science and practice and their joint efforts with nature conservation and natural resources management. First, what do NBSs actually mean in terms of flood risk reduction? Its answer is likely to need a closer look at the mechanisms of nature retaining, infiltrating, storing, and dissipating water flows. This closer look should involve analysis with high spatial and temporal resolution, on different scales and for the diversity of environmental conditions. Second, how to design NBSs in an ecosystem-based and sustainable manner? Its answer comprises a wide scope of alternative design principles from nature conservation to soft-engineering and necessitates experiments for standardisation, performance control, and replicability. Third, how to allocate NBSs on a large scale under specific natural and societal conditions? Its answer demands the upscaling of NBSs from experiments to the scale of river networks and catchments and of coastlines including the combination of NBS portfolios. Furthermore, it necessitates comprehensive impact assessment with a component of comparison with traditional risk reduction measures and instruments, also considering co-benefits. Fourth, how to participatory design and implement NBS portfolios? Its answer calls on pre-requisites for cultural and social acceptance and economic feasibility as well as on uncovering barriers and enablers resulting from the governance context, such as property rights and market mechanisms. Fifth, how to mainstream NBSs? Its answer is closely related to the potential contributions of advanced planning and management practices, institutional contexts, market uptake with possible financial instruments, and capacity development. Moreover, it calls for an incremental development based on learning from performance control and societal experience. From the aforementioned questions and the proposed focus for their answers, it is obvious that innovation regarding NBSs requires the involvement of flood risk management science and practice, but also of stakeholders from a multitude of sectors relevant for NBS implementation, local communities, and landowners. Science is supposed to focus on advancement of NBS design principles, standardisation, upscaling, and impact assessment with the respective methods and modelling strategies. Flood risk management practitioners may contribute with their local knowledge and comprehensive experience and establish links to nature conservation practice. Stakeholders are key for cultural and social acceptance, economic feasibility, and handling of institutional barriers and enablers. Thus, collaboration of these parties should build on co-design, co-deployment, and co-evaluation of NBSs and include mutual learning (e.g. Mauser et al., 2013). There is a long tradition of observation of natural processes in view of flood risk reduction and in water management in general. This led to multiple attempts to build with nature in the recent past. However, these attempts have often been carried out with the sectoral focus on water. Moreover, findings from certain sites, small field plots or water laboratories are not always upscalable to river networks and catchments and to coastlines. Field studies are especially challenging in terms of standardisation and thus cause limitations referring to replicability and transferability to other regions. Performance of NBSs in laboratory experiments cannot be easily upscaled and comprehensively assessed under real-world conditions. Therefore, the effectiveness and acceptance of NBSs for flood risk reduction on a large scale to a certain degree are still unknown and lack well-documented experience. As a consequence, NBSs so far can hardly be sufficiently considered in flood risk management and compared with other technical solutions. Against this background, there is an urgent demand to enhance efforts on advancing knowledge on and practical experience in NBS implementation in flood risk management. To do so, the following key tasks should be of high priority: (1) to strengthen documentation and standardisation of NBSs through experiments; (2) to develop and test methods and tools for upscaling and combining NBSs, participatory planning and comparison with hard-engineering works; (3) to analyse and advance the institutional context including planning systems, market mechanisms, and capacities to facilitate mainstreaming of NBSs for flood risk reduction. Findings and experiences from that should be treated in an unprepossessed way to avoid misinterpretation and underperformance during real events. Based on the previous studies on NBS experiments, it may be expected that they are likely to play complementary, integral roles in flood risk reduction strategies. These roles need to be more clearly understood, measureable, and implementable considering regional natural and societal conditions. In addition, co-benefits should be made tangible, such as effects on the reduction of risks from other natural hazards, but also on nature conservation and natural resources management. All in all, the brief look at NBSs from the viewpoint of flood risk management suggests that the relatively new concept seems to be worthwhile for further consideration in both science and practice. Not at least as the need for a close cooperation between various scientific disciplines and multiple sectoral and local stakeholders seems to open up some room for joint innovation.

The paper presents the approach and empirical findings of a study on systematic land-cover change in the upper Western Bug River catchment in Ukraine. Landsat and SPOT images as remote sensing data are used for land-cover classification for the time steps 1989, 2000 and 2010. Thereby, three inner-annual scenes represent the vegetation development for each time step and facilitate classification with the Maximum Likelihood Classifier. Six classes are detected: artificial surface, broad-leaved and coniferous forests, arable land, grassland and water bodies. After this step, land-cover change detection over two decades is conducted. The observed against the expected gross loss and gross gain are statistically analyzed to identify the systematic and random land-cover changes in the study region. Results show that arable land changes not into artificial surface. Arable land changes into grassland and vice versa. This systematic change is very strong. The forest classes interchange whereat broad-leaved forest gains more from coniferous forest in the last decade.

The concept of resilience has become more prominent in the disaster risk sciences and policy documents on disaster risk reduction such as the United Nations Sendai Framework of Action 2015-2030. Originating from physics, psychology and ecology, it currently gains interest in a number of other fields. In line with that, it has been adopted in flood risk management from different disciplinary perspectives. Therefore, the question about the meaning of the resilience concept for flood risk management occurs. The paper derives a core concept of resilience for flood risk management from an extensive literature review. Hereby, it reflects the scope and characteristics of elements and (sub-)systems relevant to governing flood risks. It then integrates this concept in a comprehensive framework of risk management and differentiates it from similar concepts such as resistance, adaptability and transformability. Thereafter, the core concept is related to disciplinary views on resilience and particularly their operationalisation. The focus is on two examples of building constructions and risk management strategies. Interdependencies between application of resilience in these examples are discussed as well as similarities and distinctions of the disciplinary views are indicated. This leads to conclusions on the added value of the resilience concept for science and practice of flood risk management and to identification of questions for future research and implementation.

Článek popisuje přístup a empirické výsledky systematických změn v povodí horního Západního Bugu na Ukrajině. Z teledat satelitu Landsat a SPOT je určen zemský povrch v období 1989, 2000 a 2010. Každý časový úsek je přitom zastoupen třemi obrázky z různých ročních období s cílem integrovat vývoj vegetace a opravit klasifikaci pomocí metody maximální věrohodnosti. Jako výsledek bylo detektováno celkem šest tříd: zastavěná plocha (městská), listnatý les, jehličnatý les, zemědělská půda, zeleň a vodstvo. Po učení povrchu v jednotlivých časových úsecích jsou zkoumány změny vzniklé za poslední dvě desetiletí. Pozorovaný pokles a růst je statisticky analyzován, aby mohly být stanoveny systematické a náhodné změny zemského povrchu ve zkoumané oblasti. Výsledky ukazují, že orná půda není přeměněna na zastavěné plochy. Orná půda se mění v travnaté porosty a naopak. Tato systematická změna je velmi silná. V klasifikaci lesních porostů jde především o vzájemnou záměnu, přičemž více dochází k přeměně lesů jehličnatých na listnaté.

Flooding as natural hazard has led to an evolution of approaches for the mitigation of its impacts. Initially, humankind was exposed to floods as natural phenomenon without any influence during most of its history of development. An early and first paradigm of actively dealing with floods evolved in the Egyptian culture thousands of years ago. It involved flood management through flood observation and construction of minor dams and channels accompanied by adapted land use. This paradigm formed also the basis for building dikes in The Netherlands and other parts of Europe from the 9th century onwards. Until this day, it is the background for constructing major dams, straightening and relocating rivers and realising thousands of miles of flood defences worldwide. Due to emphasis on protection against inundation, this first paradigm is called ‘flood protection’. During the International Decade of Natural Disaster Reduction (IDNDR) from 1990 to 1999, a second paradigm has been proposed which bears on the recognition that absolute flood protection is unachievable and unsustainable, because of high costs and inherent uncertainties. Instead, risk as probability of negative consequences due to floods is in the centre. And this risk can only be reduced to a tolerable level. The paradigm of ‘risk management’ initiated a more comprehensive view of the generation of flood impacts. Consideration of the flood risk system ranges from the flood hazard to the flood vulnerability and its exposure. Moreover uncertainties in the risk concept, and especially uncertainty quantifiable as probability, express restriction of impact mitigation for events that do not exceed a pre-defined likelihood. This requires tolerance of residual risk. In the last decade, flood risk management has become the predominant approach in science and practice in many regions of the world as visible e.g. in the European Floods Directive. It also encompasses most elements of the first paradigm and so it is sometimes not easy to identify the degree of shift from one to another in flood risk management practice. Following the elaboration and implementation of risk management, the concept of resilience became more prominent in the disaster science literature and in policy documents such as the United Nations Hyogo Framework of Action 2005–2015. It originated from psychology of the 1950's and ecology of the 1970's and has gained more attention in the environmental sciences and other fields since the beginning of the 21st century. In line with that, it was quickly adopted in flood risk management e.g. as an engineering dimension of vulnerability in recent years. In parallel, social scientists have shown the explanatory potential of resilience for the recovery of people and communities at risk. After some efforts in this respect, the questions about the more general meaning of the resilience concept for flood impact mitigation occurs and whether it is paving the way towards a new paradigm. To try to give an initial answer to these questions, resilience needs brief explanation. Resilience has no universally accepted meaning and therefore may just be understood as ‘boundary object’. However, as a kind of key feature it can be recognised as the system's ability to retain characteristic elements, structures and processes (and capacity to re-organise while undergoing alteration) in case of sudden disturbance (e.g. hazardous event) or creeping change (e.g. climate and land-use change) of system's boundary conditions. Resilience differs from resistance as ability to withstand disturbance. Both are descriptive in the first instance; evaluation needs goals or targets. There are some areas of flood impacts and their mitigation where resilience plays a role. Human beings can be the subject of psychological and medical resilience, their neighbourhoods and networks of social resilience. Constructions such as buildings and infrastructure may be addressed from the view of engineering resilience. Ability to retain ecosystems depends on ecological resilience. Local and regional markets have an economic resilience. Lastly, risk management strategies and governance regimes may be seen from the perspective of (inter-)organisational resilience. Further areas of resilience can be identified by individual disciplines. Socio-ecological resilience not only involves all these areas but additionally puts them in complex interrelation. For instance, resilience of the built environment may affect social, economic and organisational resilience. However, numerous single areas of resilience and particularly their interrelation are not well understood so far although the number of scientific papers using the term resilience in a more or less specific way recently have begun to exceed several hundreds a year. From some of these publications it seems to be possible to derive some features going beyond flood risk management as the current flood impact mitigation approach. One of these features is the dynamic performance of receptors of flood impacts with their ability to ‘bounce back’ after an event, possibly undergoing re-organisation. Vulnerability accordingly reaches a process-related notion beyond the common surveying of people and assets at risk and contributes to overcome the static description of risk with resulting design levels for risk reduction. Beyond analysis of previous events and revision of calculations, statistics and design levels, it also requires learning aptitudes. Hereby, the intention is to gain insights from the unexpected course of events and to build capacities for future unknowns. It thus complements anticipation of probable and even possible events and focusses the abilities of retaining characteristic elements, structures and processes of the flood risk system even under unforeseeable conditions. Against this brief look on the comprehensive meaning of the resilience concept, it can be seen as candidate for a new paradigm of flood impact mitigation. This paradigm again does not replace but enhances the previous one. It introduces resilience as part of vulnerability in general and physical, social, economic and ecological coping capacity as one component of vulnerability in more particular. Hence, the meaning of vulnerability does not only become more important, it unfolds a systemic and dynamic dimension. At the same time, learning aptitudes from the unexpected course of previous events and enhancement of response capacities among others receive special relevance in risk management strategies and governance regimes. The paradigm could be designated as ‘flood resilience’ as part of comprehensive flood risk management. Further effort is required to fully uncover and operationalise all potentials of the resilience concept for flood impact mitigation and to finally answer the questions on the new paradigm. For example, there is the requirement for relating selected disciplinary resilience concepts to represent the socioecological resilience of the flood risk system. In addition, accelerating climate and societal change pose the challenge of how to combine scenario-based anticipation and capacity-oriented resilience. Moreover, investigation of (inter-)organisational resilience of local and regional flood risk management strategies and the governance regime lacks suitable theory and methodology. Last but not least, currently the concept may appears as rather academic, proper transfer and specification of its added values for flood risk management practice needs increasing attention.

Assessment of building susceptibility due to natural hazard such as floods requires information about the building construction, which cannot always be properly collected and characterised in many cities of the world due to lack of reliable data and laborious techniques and high costs involved in field work. To overcome these issues, the paper proposes an approach to infer a building's taxonomy for the investigation of settlements at the building scale. The approach combines generic methods for building feature extraction, derivation of building parameters, and classification of the parameters using fuzzy clustering. It is implemented in a case study in the city of Dresden.