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In the last few years, some regions of the Mediterranean area have witnessed a progressive increase in extreme events, such as urban and flash floods, as a response to the increasingly frequent and severe extreme rainfall events, which are often exacerbated by the ever-growing urbanization. In such a context, the urban drainage systems may not be sufficient to convey the rainwater, thus increasing the risk deriving from the occurrence of such events. This study focuses on a particularly intense urban flood that occurred in Palermo (Italy) on 15 July 2020; it represents a typical pluvial flood due to extreme rainfall on a complex urban area that many cities have experienced in recent years, especially in the Mediterranean region. A conceptual hydrological model and a 2D hydraulic model, particularly suitable for simulations in a very complex urban context, have been used to simulate the event. Results have been qualitatively validated by means of crowdsourced information and satellite images. The experience of Palermo, which has highlighted the urgent need for a shift in the way stormwater in urban settlements is managed, can be assumed to be a paradigm for modeling pluvial floods in complex urban areas under extreme rainfall conditions. Although the approaches and the related policies cannot be identical for all cities, the modeling framework used here to assess the impacts of the event under study and some conclusive remarks could be easily transferred to other, different urban contexts.

The changing climate and anthropogenic activities raise the likelihood of damage due to compound flood hazards, triggered by the combined occurrence of extreme precipitation and storm surge during high tides and exacerbated by sea-level rise (SLR). Risk estimates associated with these extreme event scenarios are expected to be significantly higher than estimates derived from a standard evaluation of individual hazards. In this study, we present case studies of compound flood hazards affecting critical infrastructure (CI) in coastal Connecticut (USA). We based the analysis on actual and synthetic (considering future climate conditions for atmospheric forcing, sea-level rise, and forecasted hurricane tracks) hurricane events, represented by heavy precipitation and surge combined with tides and SLR conditions. We used the Hydrologic Engineering Center's River Analysis System (HEC-RAS), a two-dimensional hydrodynamic model, to simulate the combined coastal and riverine flooding of selected CI sites. We forced a distributed hydrological model (CREST-SVAS) with weather analysis data from the Weather Research and Forecasting (WRF) model for the synthetic events and from the National Land Data Assimilation System (NLDAS) for the actual events, to derive the upstream boundary condition (flood wave) of HEC-RAS. We extracted coastal tide and surge time series for each event from the National Oceanic and Atmospheric Administration (NOAA) to use as the downstream boundary condition of HEC-RAS. The significant outcome of this study represents the evaluation of changes in flood risk for the CI sites for the various compound scenarios (under current and future climate conditions). This approach offers an estimate of the potential impact of compound hazards relative to the 100-year flood maps produced by the Federal Emergency Management Agency (FEMA), which is vital to developing mitigation strategies. In a broader sense, this study provides a framework for assessing the risk factors of our modern infrastructure located in vulnerable coastal areas throughout the world.

Transition from endorheic alluvial fan environments to well-channelized fluvial systems in natural conditions may occur in response to base-level fluctuations. However, human-induced changes in semi-arid regions can also be responsible for similar unforeseen modifications. Our results confirm that in-channel gravel mining and aquifer overexploitation over the last 50 years in the case study area have changed the natural stability of the Nogalte stream and, as a result, its geomorphic parameters including channel depth and longitudinal profile have begun to adapt to the new situation. Using interferometric synthetic aperture radar (InSAR) data we obtain maximum values for ground subsidence in the Upper Guadalentín Basin of 10 cm yr􀀀1 for the period 2003–2010. In this context of a lowered base level, the river is changing its natural flood model to a more powerful one. A comparison of the 1973 flood event, the most dramatic flood event ever recorded in the area, with the 2012 event, where there was a similar discharge but a sediment load deficit, reveals greater changes and a new flooding pattern and extension. In-channel gravel mining may be responsible for significant local changes in channel incision and profile. This, together with the collateral effects of aquifer overexploitation, can favour increased river velocity and stream power, which intensify the consequences of the flooding. The results obtained here clearly demonstrate an existing transition from the former alluvial pattern to a confined fluvial trend, which may become more pronounced in the future due to the time lag between the drop in aquifer level and ground subsidence, and introduce a new scenario to be taken into consideration in future natural hazard planning in this area., Departamento de Geología y Geoquímica, Universidad Autónoma de Madrid, España, Departamento de Geodinámica, Universidad Complutense de Madrid, España, Geohazards InSAR Laboratory and Modeling Group, Instituto Geológico y Minero de España, España, Instituto de Geociencias, Universidad Complutense de Madrid, España, Instituto de Geociencias, Consejo Superior de Investigaciones Científicas, España

In addition to precautionary or technical flood protection measures, short-term strategies of the operational management, i.e. the initiation and co-ordination of preventive measures during and/or before a flood event are crucially for the reduction of the flood damages. This applies especially for extreme flood events. These events are rare, but may cause a protection measure to be overtopped or even to fail and be destroyed. In such extreme cases, reliable decisions must be made and emergency measures need to be carried out to prevent even larger damages from occurring. Based on improved methods for meteorological and hydrological modelling a range of (physically based) extreme flood scenarios can be derived from historical events by modification of air temperature and humidity, shifting of weather fields and recombination of flood relevant event characteristics. By coupling the large scale models with hydraulic and geotechnical models, the whole flood-process-chain can be analysed right down to the local scale. With the developed GIS-based tools for hydraulic modelling FlowGIS and the Dike-Information-System, (IS-dikes) it is possible to quantify the endangering shortly before or even during a flood event, so the decision makers can evaluate possible options for action in operational mode.

The objective is to present a reservoir management system which is capable of determining optimal operating rules both for flood event based and normal operation while at the same time attempting to achieve ecologically oriented operation. In order to maintain the variability of the natural flow regime, a new dynamic operating policy is introduced for normal operation. Flood event based operation is managed by a two-part step function. Both operating policies are optimized using a state-of-the-art multi-objective evolution strategy algorithm.

Flood events cause significant damage not only on the surface but also underground. Infiltration of surface water into soil, flooding through the urban sewer system and, in consequence, rising groundwater are the main causes of subsurface damage. The modelling of flooding events is an important part of flood risk assessment. The processes of subsurface discharge of infiltrated water necessitate coupled modelling tools of both, surface and subsurface water fluxes. Therefore, codes for surface flooding, for discharge in the sewerage system and for groundwater flow were coupled with each other. A coupling software was used to amalgamate the individual programs in terms of mapping between the different model geometries, time synchronization and data exchange. The coupling of the models was realized on two scales in the Saxon capital of Dresden (Germany). As a result of the coupled modelling it could be shown that surface flooding dominates processes of any flood event. Compared to flood simulations without coupled modelling no substantial changes of the surface inundation area could be determined. Regarding sewerage, the comparison between the influx of groundwater into sewerage and the loading due to infiltration by flood water showed infiltration of surface flood water to be the main reason for sewerage overloading. Concurrent rainfalls can intensify the problem. The infiltration of the sewerage system by rising groundwater contributes only marginally to the loading of the sewerage and the distribution of water by sewerage has only local impacts on groundwater rise. However, the localization of risk areas due to rising groundwater requires the consideration of all components of the subsurface water fluxes. The coupled modelling has shown that high groundwater levels are the result of a multi-causal process that occurs before and during the flood event.

This paper presents a hydrometeorological reconstruction of the flood triggering meteorological situation and the simulation of discharges of the flood event of December 1882 in the Neckar catchment in Baden-Württemberg (southwest Germany). The course of the 1882 flood event in the Neckar catchment in southwest Germany and the weather conditions which led to this flood were reconstructed by evaluating the information from various historical sources. From these historical data, daily input data sets were derived for run-off modeling. For the determination of the precipitation pattern at the end of December 1882, the sparse historical data were modified by using a similar modern day precipitation pattern with a higher station density. The results of this run-off simulation are compared with contemporary historical data and also with 1-D hydraulic simulations using the HEC-RAS model.

Appropriate precautions in the case of flood occurrence often require long lead times (several days) in hydrological forecasting. This in turn implies large uncertainties that are mainly inherited from the meteorological precipitation forecast. Here we present a case study of the extreme flood event of August 2005 in the Swiss part of the Rhine catchment (total area 34 550 km2). This event caused tremendous damage and was associated with precipitation amounts and flood peaks with return periods beyond 10 to 100 years. To deal with the underlying intrinsic predictability limitations, a probabilistic forecasting system is tested, which is based on a hydrological-meteorological ensemble prediction system. The meteorological component of the system is the operational limited-area COSMO-LEPS that downscales the ECMWF ensemble prediction system to a horizontal resolution of 10 km, while the hydrological component is based on the semi-distributed hydrological model PREVAH with a spatial resolution of 500 m. We document the setup of the coupled system and assess its performance for the flood event under consideration. We show that the probabilistic meteorological-hydrological ensemble prediction chain is quite effective and provides additional guidance for extreme event forecasting, in comparison to a purely deterministic forecasting system. For the case studied, it is also shown that most of the benefits of the probabilistic approach may be realized with a comparatively small ensemble size of 10 members.

Flooding causes serious impacts on the old town of Venice, its residents, and its cultural heritage. Despite this existence-defining condition, limited scientific knowledge on flood risk of the old town of Venice is available to support decisions to mitigate existing and future flood impacts. Therefore, this study proposes a risk assessment framework to provide a methodical and flexible instrument for decision-making for flood risk management in Venice. We first use a state-of-the-art hydrodynamic urban model to identify the hazard characteristics inside the city of Venice. Exposure, vulnerability, and corresponding damage are then modeled by a multi-parametric, micro-scale damage model which is adapted to the specific context of Venice with its dense urban structure and high risk awareness. Furthermore, a set of individual protection scenarios are implemented to account for possible variability in flood preparedness of the residents. This developed risk assessment framework was tested for the flood event of 12 November 2019 and proved able to reproduce flood characteristics and resulting damage well. A scenario analysis based on a meteorological event like 12 November 2019 was conducted to derive flood damage estimates for the year 2060 for a set of sea level rise scenarios in combination with a (partially) functioning storm surge barrier, the Modulo Sperimentale Elettromeccanico (MOSE). The analysis suggests that a functioning MOSE barrier could prevent flood damage for the considered storm event and sea level scenarios almost entirely. A partially closed MOSE barrier (open Lido inlet) could reduce the damage by up to 34 % for optimistic sea level rise prognoses. However, damage could be 10 % to 600 % higher in 2060 compared to 2019 for a partial closure of the storm surge barrier, depending on different levels of individual protection.

Levee-breach-induced flooding occurs occasionally but always causes considerable losses. A serious flood event occurred due to the collapse of a 15 m long levee section in Qianbujing Creek, Shanghai, China, during Typhoon Fitow in October 2013. Heavy rainfall associated with the typhoon intensified the flood severity (extent and depth). This study investigates the flood evolution to understand the dynamic nature of flooding and the compound effect using a well-established 2D hydro-inundation model (FloodMap) to reconstruct this typical event. This model coupled urban hydrological processes with flood inundation for high-resolution flood modeling, which has been applied in a number of different environments, and FloodMap is now the mainstream numerical simulation model used for flood scenarios. Our simulation results provide a comprehensive view of the spatial patterns of the flood evolution. The worst-hit areas are predicted to be low-lying settlements and farmland. Temporal evaluations suggest that the most critical time for flooding prevention is in the early 1–3 h after dike failure. In low-elevation areas, temporary drainage measures and flood defenses are equally important. The validation of the model demonstrates the reliability of the approach.

Current methods used to estimate people's evacuation times during a natural disaster assume that human responses across different social groups are similar. However, individuals respond differently based on their socioeconomic and demographic characteristics and previous knowledge. This article develops the Response Time by Social Vulnerability Index (ReTSVI), which is a methodology to estimate how human response time to evacuation warnings during a natural hazard is affected by considering characteristics related to both physical and social vulnerability. ReTSVI is a three-step methodology: first we calculate a population's evacuation curves considering social vulnerability level, certain demographic information and a model that describes an inundation hazard. Then, we use a mobilization model to generate evacuation maps per level of vulnerability and we also estimate the social vulnerability index for the area of study. In the third step, we combine the results from the second step to generate a map that indicates the percentage of people that could evacuate a hazard zone according to their social vulnerability level. Finally, we provide an example of the application of ReTSVI in a potential case of a severe flood event in Huaraz, Peru. The results show that during the first 5 minutes of the evacuation, the population that lives in neighborhoods with high social vulnerability evacuate 15 % and 22 % fewer people than the neighborhoods with medium and low social vulnerability. These differences gradually decrease over time after the evacuation warning and social vulnerability becomes less relevant after 30 minutes. Using a methodology such as ReTSVI allows first responders to identify areas where the same level of physical vulnerability affects distinct groups differently, providing them with a tool to quantify the differences in time to evacuate and where the resources before and during an evacuation should be preferentially allocated.

Flash floods are caused by intense rainfall events and represent an insufficiently understood phenomenon in Germany. As a result of higher precipitation intensities, flash floods might occur more frequently in future. In combination with changing land use patterns and urbanisation, damage mitigation, insurance and risk management in flash-flood-prone regions are becoming increasingly important. However, a better understanding of damage caused by flash floods requires ex post collection of relevant but yet sparsely available information for research. At the end of May 2016, very high and concentrated rainfall intensities led to severe flash floods in several southern German municipalities. The small town of Braunsbach stood as a prime example of the devastating potential of such events. Eight to ten days after the flash flood event, damage assessment and data collection were conducted in Braunsbach by investigating all affected buildings and their surroundings. To record and store the data on site, the open-source software bundle KoBoCollect was used as an efficient and easy way to gather information. Since the damage driving factors of flash floods are expected to differ from those of riverine flooding, a post-hoc data analysis was performed, aiming to identify the influence of flood processes and building attributes on damage grades, which reflect the extent of structural damage. Data analyses include the application of random forest, a random general linear model and multinomial logistic regression as well as the construction of a local impact map to reveal influences on the damage grades. Further, a Spearman's Rho correlation matrix was calculated. The results reveal that the damage driving factors of flash floods differ from those of riverine floods to a certain extent. The exposition of a building in flow direction shows an especially strong correlation with the damage grade and has a high predictive power within the constructed damage models. Additionally, the results suggest that building materials as well as various building aspects, such as the existence of a shop window and the surroundings, might have an effect on the resulting damage. To verify and confirm the outcomes as well as to support future mitigation strategies, risk management and planning, more comprehensive and systematic data collection is necessary.

Scour (localised erosion) during flood events is one of the most significant threats to bridges over rivers and estuaries, and has been the cause of numerous bridge failures, with damaging consequences. Mitigation of the risk of bridges being damaged by scour is therefore important to many infrastructure owners, and is supported by industry guidance. Even after mitigation, some residual risk remains, though its extent is difficult to quantify because of the uncertainties inherent in the prediction of scour and the assessment of the scour risk. This paper summarises findings from an international expert workshop on bridge scour risk assessment that explores uncertainties about the vulnerability of bridges to scour. Two specialised structured elicitation methods were applied to explore the factors that experts in the field consider important when assessing scour risk and to derive pooled expert judgements of bridge failure probabilities that are conditional on a range of assumed scenarios describing flood event severity, bridge and watercourse types and risk mitigation protocols. The experts' judgements broadly align with industry good practice, but indicate significant uncertainty about quantitative estimates of bridge failure probabilities, reflecting the difficulty in assessing the residual risk of failure. The data and findings presented here could provide a useful context for the development of generic scour fragility models and their associated uncertainties.

The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth–damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.

River floods generate a large share of the socio-economic impact of weather-driven hazards worldwide. Accurate assessment of their impact is a key priority for governments, international organization, reinsurance companies and emergency responders. Yet, available databases of flood losses over large domains are often affected by gaps and inconsistencies in reported figures. In this work, a framework to reconstruct the economic damage and population affected by river floods at continental scale is applied. Pan-European river flow simulations are coupled with a high-resolution impact assessment framework based on 2-D inundation modelling. Two complementary methods are compared in their ability to estimate the climatological average flood impact and the impact of each flood event in Europe between 1990 and 2013. The event-based method reveals key features, such as the ability to include changes in time of all three components of risk, namely hazard, exposure and vulnerability. Furthermore, it skilfully reproduces the socio-economic impact of major flood events in the past two decades, including the severe flooding hitting central Europe in June 2013. On the other hand, the integral method is capable of reproducing the average flood losses which occurred in Europe between 1998 and 2009. Strengths and limitations of the proposed model are discussed to stress the large potential for filling in the gaps of current datasets of flood impact.

Rapid urbanisation, climate change and unsustainable developments are increasing the risk of floods. Flood is a frequent natural hazard that has significant financial consequences for Australia. The emergency response system in Australia is very successful and has saved many lives over the years. However, the preparedness for natural disaster impacts in terms of loss reduction and damage mitigation has been less successful. In this paper, a newly derived flood loss function for Australian residential structures (FLFArs) has been presented and calibrated by using historic data collected from an extreme event in Queensland, Australia, that occurred in 2013. Afterwards, the performance of the method developed in this work (contrasted to one Australian model and one model from USA) has been compared with the observed damage data collected from a 2012 flood event in Maranoa, Queensland. Based on this analysis, validation of the selected methodologies has been performed in terms of Australian geographical conditions. Results obtained from the new empirically based function (FLFArs) and the other models indicate that it is apparent that the precision of flood damage models is strongly dependent on selected stage damage curves, and flood damage estimation without model calibration might result in inaccurate predictions of losses. Therefore, it is very important to be aware of the associated uncertainties in flood risk assessment, especially if models have not been calibrated with real damage data.

The paper presents a review of structural measures that were taken to cope with floods in some cities along the Danube River, such as Vienna, Bratislava, and Belgrade. These cities were also considered as case studies within the KULTURisk project. The structural measures are reviewed and compared to each other according to the type, duration of application, the return period of the design flood event, how the project measures are integrated into spatial planning and the problems that occur in the flood defences today. Based on this review, some suggestions are given on how to improve the flood risk management in flood-prone areas.

Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied – even in different geographical regions – without further validation, mainly due to the lack of real damage data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions from different geographical regions in Central Europe for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated with official damage data. The analysis reveals that flood loss functions derived from related and more similar regions perform considerably better than those from more heterogeneous data sets of different regions and flood events. While former loss functions estimate the observed damage well, the latter overestimate the reported loss clearly. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was calculated. In the case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, our results reveal evidently that a carefree model transfer in other geographical regions might be critical. Therefore, we conclude that loss models should at least be selected or derived from related regions with similar flood and building characteristics, as far as no model validation is possible. To further increase the general reliability of flood loss assessment in the future, more loss data and more comprehensive loss data for model development and validation are needed.

A spatially distributed hydrological model, dedicated to flood simulation, is developed on the basis of physical process representation (infiltration, overland flow, channel routing). Estimation of model parameters requires data concerning topography, soil properties, vegetation and land use. Four parameters are calibrated for the entire catchment using one flood event. Model sensitivity to individual parameters is assessed using Monte-Carlo simulations. Results of this sensitivity analysis with a criterion based on the Nash efficiency coefficient and the error of peak time and runoff are used to calibrate the model. This procedure is tested on the Gardon d'Anduze catchment, located in the Mediterranean zone of southern France. A first validation is conducted using three flood events with different hydrometeorological characteristics. This sensitivity analysis along with validation tests illustrates the predictive capability of the model and points out the possible improvements on the model's structure and parameterization for flash flood forecasting, especially in ungauged basins. Concerning the model structure, results show that water transfer through the subsurface zone also contributes to the hydrograph response to an extreme event, especially during the recession period. Maps of soil saturation emphasize the impact of rainfall and soil properties variability on these dynamics. Adding a subsurface flow component in the simulation also greatly impacts the spatial distribution of soil saturation and shows the importance of the drainage network. Measures of such distributed variables would help discriminating between different possible model structures.

Estimating flood risks and managing disasters combines knowledge in climatology, meteorology, hydrology, hydraulic engineering, statistics, planning and geography – thus a complex multi-faceted problem. This study focuses on the capabilities of multi-source remote sensing data to support decision-making before, during and after a flood event. With our focus on urbanized areas, sample methods and applications show multi-scale products from the hazard and vulnerability perspective of the risk framework. From the hazard side, we present capabilities with which to assess flood-prone areas before an expected disaster. Then we map the spatial impact during or after a flood and finally, we analyze damage grades after a flood disaster. From the vulnerability side, we monitor urbanization over time on an urban footprint level, classify urban structures on an individual building level, assess building stability and quantify probably affected people. The results show a large database for sustainable development and for developing mitigation strategies, ad-hoc coordination of relief measures and organizing rehabilitation.

To date, in Austria no empirical assessment of absolute damage curves has been realized on the basis of detailed information on flooded buildings due to a dam breach, presumably because of the lack of data. This paper tries to fill this gap by estimating an absolute flood-damage curve, based on data of a recent flood event in Austria in 2006. First, a concise analysis of the case study area is conducted, i.e., the maximum damage potential is identified by using raster-based GIS. Thereafter, previous literature findings on existing flood-damage functions are considered in order to determine a volume-water damage function that can be used for further flood damage assessment. Finally, the flood damage function is cross validated and applied in prediction of damage potential in the study area. For future development of the estimated flood damage curve, and to aid more general use, we propose verification against field data on damage caused by natural waves in rivers.

We assessed societal landslide and flood risk to the population of Italy. The assessment was conducted at the national (synoptic) and at the regional scales. For the assessment, we used an improved version of the catalogue of historical landslide and flood events that have resulted in loss of life, missing persons, injuries and homelessness in Italy, from 1850 to 2008. This is the recent portion of a larger catalogue spanning the 1941-year period from 68 to 2008. We started by discussing uncertainty and completeness in the historical catalogue, and we performed an analysis of the temporal and geographical pattern of harmful landslide and flood events, in Italy. We found that sites affected by harmful landslides or floods are not distributed evenly in Italy, and we attributed the differences to different physiographical settings. To determine societal risk, we investigated the distribution of the number of landslide and flood casualties (deaths, missing persons, and injured people) in Italy, and in the 20 Italian Regions. Using order statistics, we found that the intensity of a landslide or flood event – measured by the total number of casualties in the event – follows a general negative power law trend. Next, we modelled the empirical distributions of the frequency of landslide and flood events with casualties in Italy and in each Region using a Zipf distribution. We used the scaling exponent s of the probability mass function (PMF) of the intensity of the events, which controls the proportion of small, medium, and large events, to compare societal risk levels in different geographical areas and for different periods. Lastly, to consider the frequency of the events with casualties, we scaled the PMF obtained for the individual Regions to the total number of events in each Region, in the period 1950–2008, and we used the results to rank societal landslide and flood risk in Italy. We found that in the considered period societal landslide risk is largest in Trentino-Alto Adige and Campania, and societal flood risk is highest in Piedmont and Sicily.

In the framework of AMPHORE, an INTERREG III B EU project devoted to the hydrometeorological modeling study of heavy precipitation episodes resulting in flood events and the improvement of the operational hydrometeorological forecasts for the prediction and prevention of flood risks in the Western Mediterranean area, a hydrometeorological model intercomparison has been carried out, in order to estimate the uncertainties associated with the discharge predictions. The analysis is performed for an intense precipitation event selected as a case study within the project, which affected northern Italy and caused a flood event in the upper Reno river basin, a medium size catchment in the Emilia-Romagna Region. Two different hydrological models have been implemented over the basin: HEC-HMS and TOPKAPI which are driven in two ways. Firstly, stream-flow simulations obtained by using precipitation observations as input data are evaluated, in order to be aware of the performance of the two hydrological models. Secondly, the rainfall-runoff models have been forced with rainfall forecast fields provided by mesoscale atmospheric model simulations in order to evaluate the reliability of the discharge forecasts resulting by the one-way coupling. The quantitative precipitation forecasts (QPFs) are provided by the numerical mesoscale models COSMO and MM5. Furthermore, different configurations of COSMO and MM5 have been adopted, trying to improve the description of the phenomena determining the precipitation amounts. In particular, the impacts of using different initial and boundary conditions, different mesoscale models and of increasing the horizontal model resolutions are investigated. The accuracy of QPFs is assessed in a threefold procedure. First, these are checked against the observed spatial rainfall accumulations over northern Italy. Second, the spatial and temporal simulated distributions are also examined over the catchment of interest. And finally, the discharge simulations resulting from the one-way coupling with HEC-HMS and TOPKAPI are evaluated against the rain-gauge driven simulated flows, thus employing the hydrological models as a validation tool. The different scenarios of the simulated river flows – provided by an independent implementation of the two hydrological models each one forced with both COSMO and MM5 – enable a quantification of the uncertainties of the precipitation outputs, and therefore, of the discharge simulations. Results permit to highlight some hydrological and meteorological modeling factors which could help to enhance the hydrometeorological modeling of such hazardous events. Main conclusions are: (1) deficiencies in precipitation forecasts have a major impact on flood forecasts; (2) large-scale shift errors in precipitation patterns are not improved by only enhancing the mesoscale model resolution; and (3) weak differences in flood forecasting performance are found by using either a distributed continuous or a semi-distributed event-based hydrological model for this catchment.

The British coast is not considered at particular risk from tsunami, a view that is supported by a number of recent government reports. However, these reports largely ignore some written historic records that suggest southern Britain has experienced a number of events over the past 1000 yrs. This study briefly assesses these records and recognises four groups of events: 1) sea disturbance and coastal floods in southeast England linked to earthquakes in the Dover Straits (e.g. 1382 and 1580), 2) far-field tsunami reaching the coast of the British Isles, for example, from earthquakes along the Azores-Gibraltar Fault Zone offshore Portugal (e.g. 1755), 3) tsunami associated with near-coastal low magnitude earthquakes (e.g. 1884 and 1892), and 4) a flood event in AD 1014 that has been linked to comet debris impact. The seismogenic events range from minor water disturbance, through seismic seiching, to small and "giant" waves, suggesting near-coastal, low-magnitude, shallow earthquakes may be capable of triggering disturbance in relatively shallow water, as supported by similar occurrences elsewhere, and that the British tsunami risk requires a more careful evaluation.

Written sources that aim at documenting and analysing a particular natural hazard event in the recent past are published at vast majority as grey literature (e.g. as technical reports) and therefore outside of the scholarly publication routes. In consequence, the application of event-specific documentation in natural hazard research has been constrained by barriers in accessibility, concerns of credibility towards these sources and by limited awareness of their content and its usefulness for research questions. In this study we address the concerns of credibility for the first time and present a quality assessment framework for written sources from a user's perspective, i.e. we assess the documents' fitness for use to enhance the understanding of trans-basin floods in Germany in the period 1952–2002. The framework is designed to be generally applicable for any natural hazard event documentation and assesses the quality of a document, addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. We introduce an ordinal scaling scheme to grade the quality in the individual quality dimensions and the Pedigree score which serves as a measure for the overall document quality. We present results of an application of the framework to a set of 133 cases of event-specific documentation relevant for understanding trans-basin floods in Germany. Our results show that the majority of flood event-specific reports are of good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The validation of our results against assessments of two independent peers confirms the objectivity and transparency of the quality assessment framework. Using an example flood event that occurred in October/November 1998 we demonstrate how the information from multiple reports can be synthesised.

Vulnerability is a complex concept involving a variety of disciplines from both the physical and socio-economic sciences. Currently, two opposite trends exist: the physical approach in which vulnerability is analysed as a sum of potential impacts on elements at risk and the social approach in which vulnerability is mostly viewed as a combination of socio-economic variables determining people's ability to anticipate, cope with and recover from a catastrophic event. Finding a way to combine these two approaches is a key issue for a global vulnerability assessment. In this paper we propose to combine elements from these two approaches through the analysis of the potential consequences of a high-magnitude flood event (recurrence interval (RI) > 100 years) on human and material stakeholders. To perform our analysis, we choose to upgrade an existing index, the Potential Damage Index (PDI; Puissant et al., 2013), by including social criteria. The PDI was originally developed to assess the physical consequences of hazards on the elements at risk (people, building and lands). It is based on the calculation of three sub-indices representing different types of direct and indirect consequences: physical injury consequences (PIC), structural and functional consequences (SFC), indirect functional consequences (IC). Here, we propose to add a fourth sub-index representing the social consequences. This new sub-index, called social consequences (SC) is obtained by combining criteria derived from INSEE French census data and a risk-perception survey conducted in the field. By combining the four indices (PIC, SFC, IC and SC), we managed to create a new index called the Potential Consequences Index (PCI). The new PCI was tested on the Upper Guil catchment to assess the consequences of a high-magnitude flood event (RI > 100 years). Results of the PDI were compared with the PCI and show significant differences. The upgrade to the PDI method provided us with many inputs. The introduction of elements from social vulnerability added an extra dimension to the total consequence map. It allowed us to qualify the potential physical consequences (physical injury, structural and functional consequences) on elements at risk by considering the global resilience of local communities.

The increasing number of extreme natural phenomena, which are related to the climate variability and are mainly caused by anthropogenic factors, escalate the frequency and severity of natural disasters. Operational monitoring of natural hazards and assessment of the affected area impose quick and efficient methods based on large-scale data, readily available to the agencies. The growing number of satellite systems and their capabilities give rise to remote sensing applications to all types of natural disasters, including forest fires and floods. Remote sensing techniques can be used in all three aspects of disaster management viz: forecasting, monitoring and damage assessment. The purpose of this paper is to highlight the importance of satellite remote sensing for monitoring and near-real time assessment of the affected by forest fires and floods areas. As a tool, two satellite indices are presented, namely the Normalized Difference Vegetation Index (NDVI) and the Surface Temperature (ST), extracted by the meteorological satellite NOAA/AVHRR. In the first part of the paper, a review of utilized techniques using NDVI and ST is given. In the second part, the application of various methodologies to three case studies are presented: the forest fire of 21–24 July 1995 in Penteli Mountain near Athens and 16 September 1994 in Pelion Mountain in Thessaly region, central Greece, and finally the flood of 17–23 October 1994 in Thessaly region, central Greece. For all studies the NDVI has been utilized for hazard assessment. The method of ST has been applied to the flood event in Thessaly, for the estimation of the areal extent of the floods. As emerged from the studies, remote sensing data can be decisive for monitoring and damage assessment, caused by forest fires and floods.

Interdisciplinary frameworks for studying natural hazards and their temporal trends have an important potential in data generation for risk assessment, land use planning, and therefore the sustainable management of resources. This paper focuses on the adjustments required because of the wide variety of scientific fields involved in the reconstruction and characterisation of flood events for the past 1000 years. The aim of this paper is to describe various methodological aspects of the study of flood events in their historical dimension, including the critical evaluation of old documentary and instrumental sources, flood-event classification and hydraulic modelling, and homogeneity and quality control tests. Standardized criteria for flood classification have been defined and applied to the Isère and Drac floods in France, from 1600 to 1950, and to the Ter, the Llobregat and the Segre floods, in Spain, from 1300 to 1980. The analysis on the Drac and Isère data series from 1600 to the present day showed that extraordinary and catastrophic floods were not distributed uniformly in time. However, the largest floods (general catastrophic floods) were homogeneously distributed in time within the period 1600-1900. No major flood occurred during the 20th century in these rivers. From 1300 to the present day, no homogeneous behaviour was observed for extraordinary floods in the Spanish rivers. The largest floods were uniformly distributed in time within the period 1300-1900, for the Segre and Ter rivers., Une approche interdisciplinaire sur l`étude des phénomènes climatiques et de leur variabilité temporelle présente un intérêt certain pour l`analyse des risques naturels, de l`aménagement du territoire et de la gestion durable des ressources en eau. Cet article traite des aspects méthodologiques liés à la reconstitution et l`analyse d`événements de crue sur le dernier millénaire. Il aborde les questions de la critique des sources documentaires historiques, de la classification des crues et de la modélisation hydraulique des crues anciennes, des tests statistiques sur l`homogénéité des valeurs. Une échelle standardisée de classification des crues a été définie et appliquée aux crues de l`Isère et du Drac en France, de 1600 à 1950, et du Ter, du Llobregat et du Segre en Espagne, de 1300 à 1980.L`analyse des séries chronologiques du Drac et de l`Isère, de 1600 à aujourd`hui, montre que les crues fortes à exceptionnelles ne sont pas réparties de façon homogène dans le temps. Aucune tendance n`est décelable pour les crues exceptionnelles de 1600 à 1900. Aucune crue majeure de ce type n`a été observé sur ces deux rivières au cours du XXe siècle. En Espagne, de 1300 à aujourd`hui, l`occurrence des crues n`est pas stationnaire pour les crues fortes à exceptionnelles. Les crues exceptionnelles, de 1300 à 1900, sont par contre réparties de façon homogène pour le Segre et le Ter.

Flood loss models are one important source of uncertainty in flood risk assessments. Many countries experience sparseness or absence of comprehensive high-quality flood loss data, which is often rooted in a lack of protocols and reference procedures for compiling loss datasets after flood events. Such data are an important reference for developing and validating flood loss models. We consider the Secchia River flood event of January 2014, when a sudden levee breach caused the inundation of nearly 52 km2 in northern Italy. After this event local authorities collected a comprehensive flood loss dataset of affected private households including building footprints and structures and damages to buildings and contents. The dataset was enriched with further information compiled by us, including economic building values, maximum water depths, velocities and flood durations for each building. By analyzing this dataset we tackle the problem of flood damage estimation in Emilia-Romagna (Italy) by identifying empirical uni- and multivariable loss models for residential buildings and contents. The accuracy of the proposed models is compared with that of several flood damage models reported in the literature, providing additional insights into the transferability of the models among different contexts. Our results show that (1) even simple univariable damage models based on local data are significantly more accurate than literature models derived for different contexts; (2) multivariable models that consider several explanatory variables outperform univariable models, which use only water depth. However, multivariable models can only be effectively developed and applied if sufficient and detailed information is available.

Scholars have unravelled the complexities and underlying uncertainties in coupled human and water systems in various fields and disciplines. These complexities, however, are not always reflected in the way in which the dynamics of human–water systems are modelled. One reason is the lack of social data time series, which may be provided by longitudinal surveys. Here, we show the value of collecting longitudinal survey data to enrich sociohydrological modelling of flood risk. To illustrate, we compare and contrast two different approaches (repeated cross-sectional and panel) for collecting longitudinal data and explore changes in flood risk awareness and preparedness in a municipality hit by a flash flood in 2018. We found that risk awareness has not changed significantly in the timeframe under study (1 year). Perceived preparedness increased only among those respondents who suffered low damage during the flood event. We also found gender differences across both approaches for most of the variables explored. Lastly, we argue that results that are consistent across the two approaches can be used for the parametrisation of sociohydrological models. We posit that there is a need to enhance the representation of socio-demographic heterogeneity in modelling human–water systems in order to better support risk management.

On 18 June 2013, a damaging flood of the Garona River (Val d'Aran, Central Pyrenees, Spain) caused losses exceeding EUR 100 million. Few studies have related flood events to the geologic, tectonic and geomorphologic context. This study deals with both short- and long-term processes by studying the upper reach of the Garona River on different timescales and space scales. There has been a clear entrenchment tendency of the drainage network since the Miocene. Post-orogenic exhumation and uplift of the Axial Pyrenees determines the recent and active tectonics of the area and leads to fluvial incision. The last Upper Pleistocene glaciation affected Val d'Aran and gave rise to a destabilization period during the glacial–interglacial transition, marked by a postglacial incision tendency. Mean entrenchment rates between 0.68 and 1.56 mm yr−1 since deglaciation have been estimated. The assessment of the 2013 flood, characterized by the predominance of vertical incision and bank erosion, suggests that the long-term tendency of the fluvial system is reflected in short-term processes. The study of the geologic and geomorphologic evolution, combined with the analysis of this 30–50-year return period flood event, helps to improve flood risk management by providing contextual information that can constrain predictions and help guide choices and decisions. In fact, the millennial entrenchment tendency is shown at the human scale, which is considered useful for river management, but could be imperceptible in detailed hydrodynamic and channel morphology studies that describe river dynamics mostly at the 10–15-year timescale.

This article presents a novel methodology to assess flood risk to people by integrating people's vulnerability and ability to cushion hazards through coping and adapting. The proposed approach extends traditional risk assessments beyond material damages; complements quantitative and semi-quantitative data with subjective and local knowledge, improving the use of commonly available information; produces estimates of model uncertainty by providing probability distributions for all of its outputs. Flood risk to people is modeled using a spatially explicit Bayesian network model calibrated on expert opinion. Risk is assessed in terms of: (1) likelihood of non-fatal physical injury; (2) likelihood of post-traumatic stress disorder; (3) likelihood of death. The study area covers the lower part of the Sihl valley (Switzerland) including the city of Zurich. The model is used to estimate the benefits of improving an existing Early Warning System, taking into account the reliability, lead-time and scope (i.e. coverage of people reached by the warning). Model results indicate that the potential benefits of an improved early warning in terms of avoided human impacts are particularly relevant in case of a major flood event: about 75 % of fatalities, 25 % of injuries and 18 % of post-traumatic stress disorders could be avoided.