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Flood-related damage has increased dramatically in recent decades with direct and indirect economic impacts accounting for a large share of gross national products. Therefore, there is an urgent need to acquire more quantitative knowledge about flood damage to mitigate economic losses and reduce exposure to flood risk.Firms are especially affected in case of flood. Still, flood damage assessment to businesses is hindered by the paucity of available data to characterize the enterprises, the lack of high-quality damage data to derive new models or validate existing ones, and the high variability of activity types which hampers generalization. This study contributes at improving knowledge about types and extent of damage of flood events on economic activities through the analysis of empirical data, focusing on direct damage and with specific reference to the Italian context.In detail, the investigated dataset is composed by around a thousand of observed damage records collected after four flood events in Italy, along with additional information on the dimension (i.e., surface and number of employees) and the typology of the affected firms (i.e., NACE category) as well as on local water depth levels. Damage data are further classified in damage to the building structure, the stock, and the equipment.Several econometric models have been implemented to better understand the links among the damage, the characteristics of the economic activities and the water depth. Since the heterogeneity of the affected firms is very high, in terms of surface, water depth levels, and number of employees and this might have had influence on the firm’s damage reporting, data has been analyzed with Heckman's selection bias model.Obtained results show the absence of a constant return scale relationship, therefore, the total damage increases less than proportionally to the firm’s surface; the water depth plays an important role to explain the damage to the stock that results the more vulnerable asset. Information on the NACE category made it possible to quantify the differences in damage by economic sector. The results reveal as the most vulnerable sectors for building structure, stock and equipment, respectively, human health, commercial, and manufacture. The accuracy of the prediction models represented by adjusted R2 varies between 0.25, 0.36 depending on the damage component.Despite characterized by significant uncertainty, obtained results supply a first model for the prediction of flood damage to firms for the Italian context, in the support of more effective risk mitigation actions. In fact, the model identifies the more vulnerable elements within the business sectors orienting modelers and decision-makers choices.Acknowledgements: Authors acknowledge with gratitude: Francesca Carisi, Alessio Domeneghetti and Armando Brath (from University of Bologna), Giovanni Menduni, Giulia Pesaro and Guido Minucci (from Politecnico di Milano), Simone Sterlacchini and Marco Zazzeri (from the Italian National Research Council) for their collaboration in collecting the observed damage records analysed in the research. A special thanks to Marta Galliani (from Politecnico di Milano) for providing the refined dataset used in this study.

The purpose of the study is to define how the models available for flood damage assessment in the Italian context can support cost-benefit or multi-criteria analyses of risk mitigation measures, in accordance with current laws and regulations on the subject. On the basis of the present situation in which risk mitigation measures are evaluated mostly according to their capability of reducing the hazard and by considering few simple exposure factors, the study aims at identifying more robust indicators to assess measures effectiveness based on results from flood damage modelling. State of the art flood damage models developed within the context of the project MOVIDA (MOdello per la Valutazione Integrata del Danno Alluvionale – Model for integrated evaluation of flood damage, https://sites.google.com/view/movida-project) were applied to evaluate the expected damage in several flood prone areas within the Lombardia Region (northern Italy), where mitigation actions are planned by the Regional Authority. Then, obtained results for these areas were analysed to define effectiveness indicators as well as their range of values. Finally, specific indicators were developed to evaluate the environmental impact of each intervention according to present policies to promote sustainable investments in the field of soil protection as well as contribute to achieve Green Deal goals. Results show that developed indicators increase the ability of local authorities in the definition of priorities of intervention, leading to a reduction of institutional and legislative inefficiencies and increasing the efficiency of disaster risk reduction policies.

The motion state of a particle is a crucial aspect in sediment transport problems. In this paper, we conceptualized three states: stillness, ‘transport’ and ‘non-transport’. Starting from a data set of bed-load particle tracks obtained from Particle-Tracking-Velocimetry, we removed the bias from experimental uncertainty and applied one-dimensional, instantaneous and non-parametric criteria for distinguishing the different states. We present the distributions of particle velocity for all the moving states and separating the transport and non-transport states, fitting a literature model to them. The transport state is related to isotropic particle vibrations and does not significantly contribute to the bed-load rate. Vice-versa, the choice of accounting or not accounting for the non-transport state has major quantitative impact on the mean number of moving particles and mean particle velocity. Finally, the non-transport state has non-negligible contribution to the total kinetic energy of the bed-load particles.

With the intent to be compliant with the European Floods Directive (2007/60/EC) duties, the Po River District Authority gathered the expertise of 20 Italian Universities and the Italian National Research Council (CNR) active on hydrology (including climate change effects), hydraulics and damage modelling. Within this research framework, the MOVIDA project is developed by a consortium dedicated to flood damage modelling (8 Universities and CNR) and intends to provide an Information System capable to perform an analytical evaluation and mapping of expected damage, overcoming the limitations of present maps where the evaluation of risk remains highly qualitative and subjective. Proper damage assessment tools were identified for all the five categories of exposed elements foreseen by the EU Directive: population, infrastructures, economic activities, environmental and cultural heritage, and na-tech sites. A dedicated Open Source Geographic Information System (i.e. QGIS plugin) was developed and transferred to Regional Authorities for flood damage evaluation and mapping to all areas at significant risk in the Po District. In particular, the methodology defined for road and railway infrastructures qualitatively estimates the potential damage impacts of a flood event for those infrastructures. Different impact classes (High, Medium, Low and Null) are assigned in relation to roads category (i.e., Highways, Main, Secondary, Service, Other) and railways type (high-speed train or not), taking into account both the importance of the infrastructure itself (as well as its topographic characteristics: e.g. tunnel, bridge, etc.) and the magnitude of the expected event (i.e., hazard). The results enable to spatially identify the extent of the impacted infrastructures, as to drive the evaluation of potential mitigation measures and to support the competent bodies in the organization of the rescue.

In degraded landscapes, recolonization by pioneer vegetation is often halted by the presence of persistent environmental stress. When natural expansion does occur, it is commonly due to the momentary alleviation of a key environmental variable previously limiting new growth. Thus, studying the circumstances in which expansion occurs can inspire new restoration techniques, wherein vegetation establishment is provoked by emulating natural events through artificial means. Using the salt‐marsh pioneer zone on tidal flats as a biogeomorphic model system, we explore how locally raised sediment bed forms, which are the result of natural (bio)geomorphic processes, enhance seedling establishment in an observational study. We then conduct a manipulative experiment designed to emulate these facilitative conditions in order to enable establishment on an uncolonized tidal flat. Here, we attempt to generate raised growth‐promoting sediment bed forms using porous artificial structures. Flume experiments demonstrate how these structures produce a sheltered hydrodynamic environment in which suspended sediment and seeds preferentially settle. The application of these structures in the field led to the formation of stable, raised sediment platforms and the spontaneous recruitment of salt‐marsh pioneers in the following growing season. These recruits were composed primarily of the annual pioneering Salicornia genus, with densities of up to 140 individuals/m2 within the structures, a 60‐fold increase over ambient densities. Lower abundances of five other perennial species were found within structures that did not appear elsewhere in the pioneer zone. Furthermore, recruits grew to be on average three times greater in mass inside of the structures than in the neighboring ambient environment. The success of this restoration design may be attributed to the combination of three factors: (1) enhanced seed retention, (2) suppressed mortality, and (3) accelerated growth rates on the elevated surfaces generated by the artificial structures. We argue that restoration approaches similar to the one shown here, wherein the conditions for natural establishment are actively mimicked to promote vegetation development, may serve as promising tools in many biogeomorphic ecosystems, ranging from coastal to arid ecosystems.

The Po River District Authority has recently signed a research agreement with 20 Italian Universities and the Italian National Research Council (CNR) for updating the Flood Risk Management Plan, in compliance with the European Floods Directive (2007/60/EC). Specifically, the MOVIDA project envisages the efforts of a research consortium dedicated to flood damage modelling (8 Universities and CNR) to provide an Information System capable to perform an analytical evaluation and mapping of expected damage, overcoming the limitations of present maps where the evaluation of risk remains highly qualitative and subjective. Proper damage assessment tools were identified for all the five categories of exposed elements foreseen by the EU Directive: population, infrastructures, economic activities, environmental and cultural heritage, and na-tech sites. A dedicated Open Source Geographic Information System (i.e. QGIS plugin) was developed and transferred to Regional Authorities for flood damage evaluation and mapping to all areas at significant risk in the Po District. Focusing on road and railway infrastructures, the methodology proposed adopts information coming from different data sources (Regional Geoportals, Open Street Map, etc.) and allows to qualitatively estimate the potential damage impacts of a flood event. Different impact classes (High, Medium, Low and Null) are assigned in relation to the roads category (i.e., Highways, Main, Secondary, Service, Other) or railways type (high-speed train or not), taking into account both the importance of the infrastructure itself (as well as its topographical characteristics: e.g. tunnel, bridge, etc.) and the magnitude of the expected event (i.e., hazard).The results enable to spatially identify the extent of the impacted infrastructures and the locations of the flooded railway stations, information necessary to identify potential mitigation and support measures to the competent bodies in the organization of the rescue.

Natural hazards are a leading driver of power outages worldwide. Although flooding has lower impact compared to other natural hazards, it may still have a significant impact on power grids functionality in terms of frequency, magnitude, and duration of power outage. Maintaining the security of power supply under emergency conditions triggered by natural hazards, such as floods, is a challenging task because of the inherent structural and dynamic complexity of the system. In such a context, this paper presents a new model for the estimation of direct, indirect, and systemic flood damage to power grids. The key objective of the model is to be an operational tool able to: (i) consider the magnitude, probability of occurrence, and spatiotemporal variability of flood hazard, (ii) identify the vulnerable components of power grids and evaluate their probability of failure in case of flood, (iii) analyze the cascading effects of individual or multiple failure states on the power transmission and distribution networks, (iv) and assess the impacts of power outages on the power-dependent economic activities and infrastructures. To achieve this goal, the model combines deterministic flood hazard scenarios, a spatially distributed power flow model, fragility curves of power grid components for different voltage levels, and a social model, describing the various users connected to the power grid. For quantitative illustration purposes, a synthetic model has been developed by referring to the IEEE 14 bus system benchmark, to which a spatial dimension has been allocated. Furthermore, to account for differentiated social impacts, the power flow model has been linked to a synthetic social model including several communities (hubs) with different social and economic characteristics.The development of the synthetic model constitutes a preliminary step in understanding and quantifying the impacts that sustained power interruptions caused by floods can have on the customers of power grids. Next research efforts will be devoted, on the one hand, to the adoption of a probabilistic approach, by substituting deterministic hazard scenarios with spatial dependent, probabilistic ones; on the other hand, to the sensitivity analysis of the different modeling phases to identify the components of the model on which the final damage scenario depends mostly. The final aim is to provide a modeling and simulation tool for risk analysis, so as to enable stakeholders, authorities, and policy makers to formulate effective strategies to guarantee public security and ensure financial well-being.

The evaluation of flood impacts to economic activities is characterized by obstacles like the paucity of available data to characterise the enterprises, the lack of high-quality data to derive new models or validate existing ones, and the high variability of activity types which hampers generalisation. This study contributes at improving knowledge about types and extent of impacts of flood events on economic activities through the analysis of empirical data, focusing on direct damage and with specific reference to the Italian context. The collaboration among different research groups allowed to collect around a thousand of observed damage records after four flood events in Italy: the inundations that occurred in the town of Lodi (Lombardia Region) in 2002, in Sardegna Region in 2013, and in the Emilia-Romagna Region caused by the Secchia (2014) and Enza (2017) Rivers. The analysis of these data lead to a better knowledge of the types of losses suffered by economic activities, to a representation of damage composition and to the computation of reference damage values. Such a result supports the identification of the more vulnerable elements within the business sector as well as the estimation of the order of magnitude of potential damage, orienting modellers’ and decision-makers’ choices.

The study of flood impacts on the different sectors that compose the built environment and the society is crucial to implement actions of prevention, mitigation, and cautious planning. In such a context, the sector of businesses assumes a critical role, both for its importance for the wellbeing of the society and because of the high losses it suffers in case of inundations. Nevertheless, flood damage modelling to businesses is still a challenging task: the large number of different commercial activities, their specific geographical and economic contexts and the few observed damage data are just some of the reasons for that. In Italy, for example, a shared methodology to assess damage to enterprises is not present; building knowledge about types and dimensions of impacts of flood events to economic activities is then even more impelling. This contribution presents the analysis of about a thousand observed damage records regarding industrial and commercial activities, collected by four research groups after different flood events in Italy: the inundation occurred in the town of Lodi (Lombardia Region) in 2002, the one in Sardegna Region in 2013, and the floods caused in the Emilia-Romagna Region by Secchia (2014) and Enza (2017) Rivers. Data retrieved from the local and regional authorities responsible for damage compensation present different levels of detail and aggregation, according to the case study investigated. In all cases, they refer to the direct damage only and, for each case study, they have been first organised according to the activity types (e.g. trade, manufacturing, construction, finance) and per affected components: i.e. structure, equipment and stock. Data analysis has been led by some questions, we identified as key to start developing knowledge for damage modelling: are there similarities in the different case studies? Which are the more affected business sectors in case of flood? Which component suffers the highest damage among structure, equipment, and stock? Is there an empirical trend of damage with hazard parameters? Results were first compared with the socio-economic context of the affected area, to have a first confirmation of data quality and reliability; then, the analysis focused on searching information and relationships between damage and activity type, activity dimension and water level. Results support the identification of the more vulnerable elements within the business sector, orienting modellers’ and decision-makers’ choices.

Since 2010, a national method is available in France for multi-criteria analysis of flood prevention projects. The method uses national damage functions to estimate losses to the different exposed items, including economic activities. Despite the business sector suffers significant losses in case of flood, flood damage modelling to businesses is less advanced than for other exposed sectors, as e.g. residential buildings. Reasons are many and include: the high variability of activities types composing this sector and then the difficulty of standardisation (above all when contents are considered), and the lack of data to understand and quantify damage and validate existing modelling tools. The collection of damage data in two case studies, in France and in Italy, and the collaboration between two research groups in the two countries allowed to study the applicability, the validity, and the transferability of the French damage functions for economic activities to Italy. Firstly, the functions were tested and validated in a French case study, i.e. the flood that affected the Île-de-France Region in 2016. This validation exercise faced the problem of working with few information about the identity of the activities, and propose a solution; moreover, it allowed to verify the actual availability of input data to implement the functions in France and pointed out the paucity of information to validate the methodology. Testing the functions in a foreign case study, i.e. the flood occurred in 2002 in Italy in the city of Lodi, allowed instead to verify the transferability of the method.

Flood damage assessment is a crucial component of any decision-making process on flood risk management and mitigation; for this reason, reliable tools for flood damage estimation are required, for all the categories of exposed elements. Despite networks can suffer high losses in case of flood, and in comparison with other exposed items, flood damage modelling to infrastructures is still a challenging task. This is due, on the one hand, to the complexity of networks as well as of their interconnections; on the other hand, to the lack of knowledge and data to investigate damage mechanisms and to calibrate and validate damage models. Grounding on the investigation of the state of art, this contribution presents a conceptualization of flood damage to power grids. The ultimate objective of the conceptual model is to be an operative tool in support of more comprehensive and reliable flood damage assessments to power grids, highlighting: (i) the different components of the damage (i.e. direct, indirect, and systemic, meaning damage due to the interdependencies among power grids and residential, commercial, industrial and other infrastructure sectors), (ii) their interconnections, (iii) the hazard, exposure and vulnerability variables on which they depend, (iv) the temporal and spatial scales for their assessment. The development of the model highlighted, on the one hand, the importance of dividing damage assessment in two steps: the estimation of damage in quantitative/physical units and the estimation of the consequent economic losses. On the other hand, the variety of damage mechanisms and cascading effects shaping the final damage figure arises, asking for an interdisciplinary and multi-scale evaluation approach. The development of the conceptual model is the first step of a PhD research on the development of flood damage models for infrastructures. Next steps will validate the model in real case studies and evaluate how the different damage components could be investigated in the Italian context.

The European Floods Directive (2007/60/EC) requires that Member States develop flood hazard and risk maps, to be used as the information basis for the development of Flood Risk Management Plans, and to update them every 6 years. To support such a process, the Po River District Authority signed in May 2020 an agreement with 20 Italian Universities and the Italian National Research Council (CNR) with the aim of transferring the state of the art about hydrology (including climate change), hydraulics and damage modelling into the production of the new maps, to be delivered by December 2021. This contribution describes the activities done so far by the damage modelling group, composed by 8 Universities and CNR. The objective of the group is to provide an Information System able to perform a quantitative estimation of flood damage, overcoming the limitations of present maps where the evaluation of risk remains highly qualitative and subjective. Proper damage assessment tools were identified for all the five categories of exposed elements included in the Directive: population, infrastructures, economic activities, environmental and cultural heritage, and na-tech sites. These tools are thought to address specific requirements: (i) being valid/applicable for the whole area of the District, (ii) being based on standardised and institutional data, available at national level, (iii) being calibrated (and possibly validated) in the Italian context. A dedicated Geographical Information System is currently under development to support technicians in the application of proposed tools and in the visualisation and processing of damage assessment results. The work done so far suggests that a quantitative estimation of damage is not yet possible for all the categories, rather three different levels of damage knowledge can be reached depending on the category and available data: quantitative, qualitative or descriptive (the latter being based on a deep investigation of historical data). Therefore, in order to get a total damage figure, the need arises of (i) comparing damage data with different metrics and (ii) comparing and weighting damage to different exposed categories, whose values may depend on objectives at stakes. A participatory process with final users will be then set up in the next year, to guarantee the usability and applicability of developed tools.

The paper presents the results from the multidisciplinary investigations performed on Baghetto Bridge. The structure, built in 1966, crosses the Adda river between the Municipalities of Castello dell'Acqua and Chiuro. It consists of three steel–concrete composite girders of different lengths supported by stone-masonry piers. The research program involved several investigations: (i) documentary research, (ii) ambient vibration testing, (iii) hydraulic study, and (iv) FE modelling and updating. After a concise review of the bridge history and a brief description of the structure, the hydraulic study based on existing topographic surveys is presented. This latter analyses allowed the estimation of hydraulic actions as well as the evaluation of possible hydro-geomorphologic scenarios. Subsequently, the complete results of the experimental tests are described and discussed. The modal parameters identified from the dynamic survey allowed validation of the numerical model, together with a more in-depth interpretation of the actual behaviour of the bridge. Moreover, the overall investigation allows to sound the presented multidisciplinary approach for the structural assessment of existing bridges.

In the last 20 years, SAR sensors installed on satellites have been increasingly used to monitor large scale phenomena such as subsidence, uplifting, or landslides. Recently several research groups started to investigate the use of remote sensing for damage detection in civil infrastructures. This technique presents in principle several advantages, not least the possibility to monitor a network of structures using the same sensor. However, its implementation for civil engineering projects is still at its infancy and a limited number of applications can be found in literature. The goal of this paper is to investigate the feasibility of using InSAR data for structural health monitoring of bridges with reference to a number of case studies. Data measured by radar satellites with different spatial and temporal resolutions and different frequency bands are processed to extract bridge displacement data and analyzed to identify possible structural damages. The SqueeSAR technique is used to extract displacement time histories from SAR images acquired by radar sensors with different spatial and temporal resolution (TerraSAR-X and RADARSAT 1–2). Displacements are then processed to identify anomalies possibly related to damage. Results show that high-resolution radar data enable the detection of very small structural displacements due to environmental changes, such as temperature variation.

INSYDE is a multi-variable, synthetic model for flood damage assessment to dwellings. The analysis and use of this model highlighted some weaknesses, linked to its complexity, that can undermine its usability and correct implementation. This study proposes a simplified version of INSYDE which maintains its multi-variable and synthetic nature, but has simpler mathematical formulations permitting an easier use and a direct analysis of the relation between damage and its explanatory variables.

Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterised by significant levels of uncertainty, questioning the capacity of flood damage models to depict real damages. With a joint effort of eight international research groups, the objective of this study was to compare the performances of different damage models for the estimation of the direct flood damage to the residential sector at the building level (i.e. micro scale) in a blind validation test. The test consisted in a common flood case study characterised by high availability of hazard and building data, but with undisclosed information on observed losses in the implementation stage of the models. The selected nine models were chosen in order to guarantee a good mastery of the models by the research teams, variety of the modelling approaches and heterogeneity of the original calibration context, in relation to both hazard and vulnerability features. By avoiding possible biases in model implementation, this blind comparison provided more objective insights on the transferability of the models and on the reliability of their estimations, especially regarding the potentials of local and multi-variable models. From another perspective, the exercise allowed to increase authors’ awareness on strengths and limits of flood damage modelling, which are summarised in the paper in the form of take-home messages from a modeller's perspective.

The estimation of flood losses implies the use of vulnerability/exposure models for flood damage and risk assessment (Meyer et al. 2013; Zischg et al. 2018; Wagenaar et al. 2018; Molinari et al. 2019). According to Gerl et al. (2016), in central Europe there are 28 models with 652 functions to assess flood losses, whereas almost half of the functions refer to residential buildings. The main differences among damage models are: (i) spatial scale, (ii) metric (i.e. absolute or relative loss), (iii) exposure assessment (i.e. whole building or affected floors, market values or reconstruction-replacement costs), (iv) number of input variables, (v) calibration/validation with observed losses. These differences pose the issue of model transferability to other urban or environmental contexts. With a joint effort of eight research groups, the objective of this study is to test and compare damage models for residential buildings used or developed by each group, by applying them in a “blind exercise”, i.e. a common flood case study characterised by high availability of hazard and building data, with unknown information on observed losses in the implementation stage of the models. As the research groups use approaches representing many different types and characteristics of models (e.g. univariable – multivariable; absolute – relative; graduated – regression – machine learning), being calibrated based on empirical data stemming from different countries (Austria, France, Germany, Italy, Japan, Netherlands), with different landscapes, the blind exercise provides an extensive comparison of models and their transferability. The analysis of the differences in the ensemble of model outcomes aims at pointing out common patterns or divergent behaviours between model outcomes and with respect to observed losses.

Effective flood risk mitigation requires the impacts of flood events to be much better and more reliably known than is currently the case. Available post-flood damage assessments usually supply only a partial vision of the consequences of the floods as they typically respond to the specific needs of a particular stakeholder. Consequently, they generally focus (i) on particular items at risk, (ii) on a certain time window after the occurrence of the flood, (iii) on a specific scale of analysis or (iv) on the analysis of damage only, without an investigation of damage mechanisms and root causes. This paper responds to the necessity of a more integrated interpretation of flood events as the base to address the variety of needs arising after a disaster. In particular, a model is supplied to develop multipurpose complete event scenarios. The model organizes available information after the event according to five logical axes. This way post-flood damage assessments can be developed that (i) are multisectoral, (ii) consider physical as well as functional and systemic damage, (iii) address the spatial scales that are relevant for the event at stake depending on the type of damage that has to be analyzed, i.e., direct, functional and systemic, (iv) consider the temporal evolution of damage and finally (v) allow damage mechanisms and root causes to be understood. All the above features are key for the multi-usability of resulting flood scenarios. The model allows, on the one hand, the rationalization of efforts currently implemented in ex post damage assessments, also with the objective of better programming financial resources that will be needed for these types of events in the future. On the other hand, integrated interpretations of flood events are fundamental to adapting and optimizing flood mitigation strategies on the basis of thorough forensic investigation of each event, as corroborated by the implementation of the model in a case study.

This paper presents AGRIDE-c, a conceptual model for the assessment of flood damage to crops, in favour of more comprehensive flood damage assessments. Available knowledge on damage mechanisms triggered by inundation phenomena is systematised in a usable and consistent tool, with the main strength represented by the integration of physical damage assessment into the evaluation of its economic consequences on the income of the farmers. This allows AGRIDE-c to be used to guide the flood damage assessment process in different geographical and economic contexts, as demonstrated by the example provided in this study for the Po Plain (north of Italy). The development and implementation of the model highlighted that a thorough understanding and modelling of mechanisms causing damage to crops is a powerful tool to support more effective damage mitigation strategies, both at public and at private (i.e. farmers) levels.

This study's objective is to assess the sensitivity analysis' potential for application in the context of the stochastic-input based modelling of fluvial morphodynamics. The corresponding work involved (1) an analysis of the work available in the literature and (2) an independent application of sensitivity analysis for comparison. The application of sensitivity analysis was accomplished by using a numerical hydro-morphodynamic model to represent the natural morphodynamical processes' response to the uncertainty in a selected set of variables. The resulting morphodynamical sensitivities were quantified and a characterization of the relationship between the variables' effects and morphodynamics was produced. The potential generalization of the results of sensitivity analysis for the purposes of validating stochastic modelling across different case studies was assessed. Resulting sensitivities were found to be strongly case-specific with little generalization potential, indicating that sensitivity analysis in the context of fluvial morphodynamics is likely of little scientific interest.

Observation of incomplete particle hops in imaging-based experiments with bed-load transport does not just occur with hops that are longer than an area of observation. Even short hops can be in fact incompletely measured if they cross the boundaries of the focus area. Experimental censorship biases the statistical distribution and moments of bed-load particle hops. This paper presents: a theoretical quantification of an expected effect of experimental censorship; based on this quantification, a method to correct the statistical distribution of hop lengths; an application of the method to experimental data. Applying the correction leads to significantly different values of the mean hop length, compensating the biasing effect of censorship. By contrast, nothing can be done for experimental truncation that is associated with hops longer than an applied area of observation. Experimental truncation must be avoided a priori, by appropriate design of the measurement method.

The editors of a new book describe the benefits of systematic collection, storage, analysis, and sharing of damage data after flood events.