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Societal awareness is a crucial factor driving floodplain dynamics. When modelling these dynamics, flood awareness decay is considered constant. However, empirical studies have shown that the intensity of an experienced event can influence awareness decay. Here we explore and model the influence of variable flood awareness decay on flood losses for two types of societies that cope with flooding by adopting structural (techno society) or nonstructural (green society) protection measures. We modified an established socio-hydrological model and performed three synthetic experiments with multiple scenarios of flood awareness decay, flood intensity, and frequency. We found that, when modelling techno societies, assuming a constant awareness decay leads to underestimating societal flood awareness after severe flood events. In contrast, overestimation of flood awareness occurs when using constant awareness decay for green societies. This might lead to overestimating the effects of human–flood dynamics, such as the levee effect and adaptation effects. QC 20230420

Climate services are expected to deliver better climate adaptation by providing decision-makers with timely, salient, credible, legitimate, and accessible climate information. Nonetheless, climate services’ impact on long-term adaptation remains poorly understood due to their ambiguous protocols, quality standards, and inadequate monitoring and evaluation processes.The aim of this study is to present the underpinnings of a framework representing the causal mechanisms and feedback interactions between adaptation to hydrometeorological extremes, i.e. floods and droughts, and climate services among the partner living labs of the I-CISK project (https://icisk.eu). To this end, a qualitative investigation based on interviews and surveys of the living labs’ stakeholders is performed. Following, the findings from the qualitative analysis are iteratively discussed with the stakeholders and presented as a causal loop diagram, highlighting feedback loops in the coupled human-climate system. Finally, the emerging dynamics are described using system archetypes.This research offers a systemic tool for evaluating the long-term dynamics of adaptation to hydrometeorological extremes while building the bases for further research in the living labs. Moreover, it shows the efficacy of system dynamics tools for informing adaptive policy-making.

Economic inequality is rising within many countries globally, and this can significantly influence the social vulnerability to natural hazards. We analysed income inequality and flood disasters in 67 middle- and high-income countries between 1990 and 2018 and found that unequal countries tend to suffer more flood fatalities. This study integrates geocoded mortality records from 573 major flood disasters with population and economic data to perform generalized linear mixed regression modelling. Our results show that the significant association between income inequality and flood mortality persists after accounting for the per-capita real gross domestic product, population size in flood-affected regions and other potentially confounding variables. The protective effect of increasing gross domestic product disappeared when accounting for income inequality and population size in flood-affected regions. On the basis of our results, we argue that the increasingly uneven distribution of wealth deserves more attention within international disaster-risk research and policy arenas.

Economic inequality is a reality in many countries and is also increasing in many contexts. The consequences of economic inequality are multifaceted and, for instance, relate to issues of justice, access to welfare, long-term health and human well-being. Economic inequality within countries can also affect how susceptible populations are to flood hazards, both directly and indirectly. A large body of research has shown that the pre-disaster economic distribution within a society can affect the disaster outcomes. One example is that unequal societies tend to exhibit physical marginalization, and if these areas are burdened with malfunctioning infrastructure it affects the ability to withstand an extreme weather event.In this work, we highlight the role of economic inequality in explaining flood losses worldwide. We conduct a statistical cross-country comparison and show that the distribution of income matters for reducing human flood losses, and that this applies at all levels of economic development. We then discuss how our results stand in contrast to some of the most common disaster reduction recommendations from flood management studies, particularly from studies conducted at large scales.

Two-way interactions and feedback between hydrological and social processes in settled floodplains determine the complex human-flood system and change vulnerability over time. To focus on the dynamic role of individual and governmental decision making on flood-risk management, we developed and implemented a coupled agent-based and hydraulic modelling framework. Within this framework, household agents are located in a floodplain protected by a levee system. Individual behaviour is based on Protection Motivation Theory and includes the options to (1) not react to flood risk; (2) implement individual flood protection measures; or (3) file a complaint to the government. The government decides about reinforcing the levee system, compromising between a cost-benefit analysis and filed complaints from households. We found that individual decision making can significantly influence flood risk. In addition, the coupled agent-based and hydraulic modelling framework approach captures commonly observed socio-hydrological dynamics, namely levee and adaptation effects. It provides an explanatory tool for assessing spatial and temporal dynamics of flood risk in a socio-hydrological system.

The past few years have seen the raise of unmanned aerial vehicles (UAV) in geosciences for generating highly accurate digital elevation models (DEM) at low costs, which promises to be an interesting alternative to satellite data for small river basins. The reliability of UAV-derived topography as input to hydraulic modelling is still under investigation: here, we analyse potentialities and highlight challenges of employing UAV-derived topography in hydraulic modelling in a tropical environment, where weather conditions and remoteness of the study area might affect the quality of the retrieved data. We focused on a stretch of the Limpopo River in Mozambique, where detailed ground survey and airborne data were available. First, we tested and compared topographic data derived by UAV (25 cm), RTK-GPS (50 cm DEM), LiDAR (1 m DEM) and SRTM (30 m DEM); then, we used each DEM as input data to a hydraulic model and compared the performance of each DEM-based model against the LiDAR based model, currently used as benchmark by practitioners in the area. Despite the challenges experienced during the field campaign—and described here—, the degree of accuracy in terrain modelling produced errors in water depth calculations within the tolerances adopted in this typology of studies and comparable in magnitude to the ones obtained from high-precision topography models. This suggests that UAV is a promising source of geometric data even in natural environments with extreme weather conditions.

Economic inequality is today increasing in many contexts. Its consequences are multifaceted and relate to questions of justice, welfare, human well-being and health. Economic inequality also affects (directly or indirectly) society’s vulnerability to flood disasters. Research has previously shown that the ex-ante economic distribution within a country may affect the disaster outcomes. For instance, unequal societies also tend to exhibit spatial marginalization. If these marginalized areas are burdened with neglected infrastructure they also have a lower ability to divert flood water.Our work highlights the role that economic inequality plays in explaining human flood losses, worldwide. We perform a statistical analysis using data for over a hundred countries and illustrate the importance of considering income distribution when building flood resilient societies. We also show how our results vary between different levels of economic development and discuss implications of our results on disaster research and risk reduction.

The success of climate adaptation actions relies on the availability and quality of information, especially in climate-sensitive sectors such as tourism, agriculture, and river management. Over the years, researchers have highlighted how climate services providing such key information should focus on end-user needs to bridge the usefulness-usability gap. Thus, overcoming this dichotomy will enable the effective use of climate services in adaptation initiatives, especially at the local scale. In this study, we present the basis for a conceptual framework identifying the balancing and reinforcing feedbacks in a coupled human-climate system, with a focus on hydrological risks, i.e. floods and droughts. The analysis is based on system dynamics conceptualization and builds upon data from various living labs (i.e. case studies) across Europe. The framework is presented as a causal-loop diagram and emerging behaviors of the system are described using system archetypes. The proposed framework highlights the importance of understanding feedbacks between climate information and adaptation options when designing user-centered climate services. Moreover, it sheds a light on usefulness of system dynamics as a tool for informing the planning of effective adaptation actions while building resilience.

We present here a unique experiment that crosses borders of disciplines to stimulate active learning and to challenge students’ learning process.The joint pedagogical activity involved third year engineering students attending the AE1601/AE1603 Fluid mechanics course at the Royal Institute of Technology (KTH) and first year students from the Bachelor of circus programme at Stockholm School of Circus (SKH).The experiment took place in September 2021, over five days, as closing assignment for the fluid mechanics course. To KTH students, this was offered as an extra curriculum option and forty of the registered ninety students volunteered to take part in the pedagogical activity; students were divided in two groups of twenty students each (Group A and Group B). To the sixteen SKH students it was a required part of their Performance and Interpretation course where they learn performance techniques beyond their primary circus disciplines.The learning objectives where different for the three sets of students:Group A Fluid mechanics students: practice transferring of knowledge; adapt form of communication. Circus students: receive input unrelated to circus techniques; interpret with movement that both captured the essence of the scientific concepts while also attending to aesthetic and compositional presentation. Group B Fluid mechanics students: exercise critical thinking, practice assessment in an out-of-context situation. On the first day of the activity, Group A fluid mechanics students met with the sixteen circus students and formed ten randomly mixed groups: the task for fluid mechanics students was to teach selected topics recently learned from the fluid mechanics course to the circus colleagues. This became the input for the circus students’ task: they had three days to prepare a physical presentation representing the concepts learned from their paired fluid mechanics colleagues.On the last day of the activity, Group B fluid mechanics students were randomly allocated to a circus performance and their task was to interpret the performance and understand which fluid mechanic concept had inspired it.Fluid mechanics students had two types of assessment, each of which reflected their task. Group A students were indirectly assessed: the fluid mechanics lecturer interviewed circus students on what they had learned from their colleagues. For Group B students the assessment was based on a report where they first discussed which topics they perceived in the presentations, then they interviewed the circus performer and wrote about what the circus student intended to represent.The essence of the pedagogical task for the circus students was the process: receiving, interpreting, composing and presenting. Circus students engaged in reflective self-assessment in dialogue with the instructors and course leader, including discussion of how their presentations were received and understood by the fluid mechanics students. We believe this activity had high pedagogic value for the students in both courses as supported by students´ evaluations. By engaging with the course contents in a fun, creative and a-typical manner, all participants gained experiences that enriched knowledge in their own domain as well as their ability to communicate with people from other domains.

The effects of land use alteration, migration and urbanization are key aspects in flood management, as human activities can strongly influence the capacity of ecosystems to provide flood regulating ecosystem services and determine their demand. This study analyzes spatio–temporal dynamics of flood regulating ecosystem services to support watershed management planning. A methodology for mapping the supply and demand of flood regulation is proposed and applied to the Arno River basin, in central Italy. The spatial explicit analysis of flood regulating ecosystem services supply is carried out with SWAT - Soil and Water Assessment Tool, whose outputs are synthetized by two indicators to evaluate the retention capacity of each land use class originating from CORINE data sets. Quantification of demand for flood regulating ecosystem services is based on flood hazard classes derived from the existing local flood management plans (i.e., PAI-Piano per l’Assetto Idrogeologico and PGRA-Piano di Gestione del Rischio Alluvioni). Supply and demand data are then combined to obtain budget maps of flood regulating ecosystem services and their evolution, between 1990 and 2018. The results show how both demand and supply of ecosystem services have changed in the last decades, highlighting the main hotspots at the catchment and sub-catchment scales. With the increasing urbanization, the demand values have grown in the Arno floodplains, where residential, industrial and commercial zones are located. At the same time, land use changes have altered the water regulation supply, resulting in a generalized decrease of the basin capacity to provide flood regulation services. The maps and tables obtained show the fundamental role of forest and other vegetated areas whose protection is a priority to assure future flood regulation and associated co-benefits (e.g., regulation of air quality, reduction of erosion, improvement of water quality, wood fuel). The assessment of flood regulating here proposed is a powerful tool for decision makers to improve flood regulation and provides a sound base of knowledge to identify and locate flood prevention and mitigation measures.

There are currently several large-scale gridded archives available for the study of flood exposure, and the results will inevitably depend on the datasets included in the analysis. The purpose of this work is to demonstrate how country flood exposure, here represented as the presence of population within floodplains, is influenced by dataset choices.We conduct this geographical analysis in two parts. First, we conduct a global analysis showing how different flood exposure metrics influence comparisons between countries. Second, we overlay five commonly used gridded archives (three population archives and two floodplain archives) for 32 countries. The purpose is to quantify the influence of data choices, while also giving an overview of the various dataset methodologies. We finally zoom in on areas where the five datasets yield very dissimilar results, to exemplify typical differences among the datasets.

Human activities can strongly influence the capacity of ecosystems to provide flood regulating ecosystem services (ES). Therefore, the effects of land use alteration, population migration and urbanization are key aspects to be considered when dealing with flood management. This study aims at analyzing the spatio‑temporal dynamics of flood regulating ES to support watershed management planning. The spatial explicit analysis of flood regulating ES is carried out with SWAT - Soil and Water Assessment Tool, using daily meteorological data between 2000 and 2014. Two indicators are elaborated in order to evaluate the retention capacity of each land use setting and to map the ES supply. Demand quantification is obtained from the information derived by the existing flood management plans (i.e. PAI-Piano per l’Assetto Idrogeologico and PGRA-Piano di Gestione del Rischio Alluvioni) which contain the identification and the perimeter of hydraulic hazard classes. Supply and demand data are then merged in order to obtain budget maps of flood regulating ES and their evolution from 1960 up to 2012 (1960, 1990, 2000 and 2012). The results show that both the demand and the supply of ecosystem services change during the time. With the increasing urbanization, the demand values have grown in the Arno floodplains, where residential, industrial and commercial zones are located. At the same time, land use changes (e.g. intensive agriculture) have caused negative effects on water regulation supply. This work shows the advantages of assessing flood regulating ES to improve flood regulation in the Arno river basin and provide a sound base of knowledge to identify floods prevention and mitigation measures.

Hydropower accounts for almost half of all electricity production in Sweden, while also being the most important energy balancing resource. Nuclear power plants are gradually being decommissioned up to 2045 in Sweden according to the government’s plans. It means there is a need for a dramatic expansion of renewable energy production, especially for hydropower as a balancing resource. The availability of renewable energy fluctuates with the weather, seasons, and between years, which is an important factor for the coordination of renewable energy production.The aim of this research is to investigate how runoff forecasts affect hydropower production planning when the account is taken to hydro-climatic variations. This problem is studied by using production planning models fed by runoff forecasts that exhibit climate-driven periodicity. Statistical ensemble predictions and receding horizon control are implemented to reveal the effect on the production. Further, we utilize half-a-century long daily hydro-climatological data to runoff forecasts that are aggregated in ensembles particularly reflecting the bi-annual climate periodicity apparent from spectral analysis of the data.Dalälven River Basin is used as a study case, which is a watershed stretching from western Sweden to the Baltic in the east and which has more than 30 hydropower stations. Four forecast ensemble scenarios have been analyzed out by studying the periodicity of discharge data in Dalälven River Basin. According to the seasonal and two-year periodicity, the four scenario ensembles are defined as: a) Odd year, wet month; b) Even year, dry month; c) Odd year, dry month; d) Even year, wet month. [A1] A large-scale optimal hydropower production model was built in MATLAB, in order to simulate hydropower production in Dalälven River Basin. It includes 13 reservoirs and 36 hydropower plants, and applies the sequential-quadratic-programming (SQP ) as the optimization method. Receding horizon control is embedded into the optimal production programming, which can correct the systematic error. The historical data shows that the one-year-long sampling has a consistent biannual periodicity, with wet and dry years of different strength depending on the start month of the data selection in the year. It indicates the discharge data selection start from November and December gives the most dramatic effect on periodicity, while starting from May and July have a lower impact. Dynamic programming of hydropower production shows for both dry and wet runoff conditions that matching the forecast ensemble with the right phase of the actual climate conditions has a significant effect on the production profit.

The viability of a renewable electricity system depends on long-term climate variations, uneven spatiotemporal distribution of renewable energy, and technical constraints. A major problem is to achieve a sustainable balance of water usage and consumption, as well as adequate energy and water distribution and storage capacities. In particular, hydropower offers a large capacity for energy storage and production flexibility, but only stands for a minor part of the total energy potential. In this study we explored the spatial and temporal variance of hydropower availability for a 35-year period based on historical hydro-meteorological data from large parts of Europe. A spectral analysis of these historical time-series shows that spatiotemporal coordination of the hydropower system covered in the Global Reservoir and Dam Database (GRanD) can potentially contribute with a “virtual” energy storage capacity that is up to four times the actual energy storage capacity contained in the existing hydropower reservoirs. Such virtual energy storage capacity implies reduced water storage demand, hence, indirectly contributes to reduced constraints of the food-water-energy nexus also in a wider system perspective. We found that the most significant benefits from a spatiotemporal management arise at distances of 1,200 – 3,000 km, i.e. on the continental scale, which can have implications for a future renewable energy system at large. The analysis also covers what we denote “energy-domain-specific drought”, which implies a shortage of energy storage capacity to avoid a deficit of energy for a given time period, and which may be reduced by the spatiotemporal coordination of power production.

The availability of planetary-scale geospatial datasets that can support the study of water-related disasters in the Anthropocene is rapidly growing. We review over hundred global and free datasets allowing spatiotemporal analyses of floods, droughts and their interactions with human societies. The purpose of structuring a data collection for a broad range of variables is to foster data exchange and illustrate research opportunities across scientific disciplines.Our collection of datasets confirms that the availability of geospatial data capturing hydrological hazards and exposure is far more mature than those capturing vulnerability aspects. We do not only highlight data applications by listing a selection of recent studies exploiting these global datasets, but also discuss challenges associated with using these datasets in comparative studies. Specific discussion points include spatiotemporal resolution and coverage, inequalities of geographic representation, omission of detailed information at large scales, data consistency and accessibility, and dependencies between the datasets prohibiting interaction studies.

Our understanding of the advantages and limitations of satellite derived precipitation datasets as a forcing to hydrological models has made tremendous progress over the past decade. However, most studies have only analysed the performance of one or few datasets, have used global precipitation datasets to force lumped models on regional/large-scale basins, or have adopted more complex distributed models but applied them to small basin scales.We aimed at addressing these gaps in the literature: in particular, we compared the performance of 18 different precipitation datasets used as input in a grid-based distributed hydrological model to assess streamflow in large-scale river basins. These datasets are classified as Uncorrected Satellites, Corrected Satellites, and Reanalysis-Gauges based datasets. The hydrological model is applied to 8 large scale river basins (Amazon, Brahmaputra, Congo, Danube, Godavari, Mississippi, Rhine and Volga) with different sizes, presence of hydraulic structures, human footprint, hydrometeorological characteristics, and precipitation gauge network density were selected.The results of this study showed that there is not a unique best performing precipitation dataset for all basins and results are very sensitive to the basin characteristics. However, there are few datasets which persistently outperform the others: SM2RAIN-ASCAT for Class 1, CHIRPS V2.0, MSWEP V2.1, and CMORPH-CRTV1.0 for Class 2, GPCC and WFEDEI GPCC for Class 3. The use of a distributed modelling approach rather than lumped is supported by the fact that precipitation datasets showing the highest model result at the basin outlet do not show the same high performance at internal locations of the basin. In addition, precipitation datasets belonging to Class 2 outperform the other datasets in basins with Tropical and Temperate-Arid climate (e.g. Congo, Mississippi and Godavari), while Class 3 datasets show the highest NSE values in Temperate and Temperate-Cold basins (e.g. Danube, Rhine and Volga).

Levees protect floodplain areas from frequent flooding, but they can paradoxically contribute to more severe flood losses. The construction or reinforcement of levees can attract more assets and people in flood-prone area, thereby increasing the potential flood damage when levees eventually fail. Moreover, structural protection measures can generate a sense of complacency, which can reduce preparedness, thereby increasing flood mortality rates. We explore these phenomena in the Jamuna River floodplain in Bangladesh. In this study area, different levels of flood protection have co-existed alongside each other since the 1960s, with a levee being constructed only on the right bank and its maintenance being assured only in certain places. Primary and secondary data on population density, human settlements, and flood fatalities were collected to carry out a comparative analysis of two urban areas and two rural areas with different flood protection levels. We found that the higher the level of flood protection, the higher the increase of population density over the past decades as well as the number of assets exposed to flooding. Our results also show that flood mortality rates associated with the 2017 flooding in Bangladesh were lower in the areas with lower protection level. This empirical analysis of the unintended consequences of structural flood protection is relevant for the making of sustainable policies of disaster risk reduction and adaptation to climate change in rapidly changing environments.

The availability of planetary-scale geospatial datasets that can support the study of water-related disasters in the Anthropocene is rapidly growing. We review 124 global and free datasets allowing spatial (and temporal) analyses of floods, droughts and their interactions with human societies. Our collection of datasets is available in a descriptive list for download at . The purpose of providing an overview of datasets across a wide range of hydrological and socioeconomic variables is to highlight research opportunities across scientific disciplines for the study of the water-society interplay. Our collection of datasets confirms that the availability of geospatial data capturing hydrological hazards and exposure is far more mature than those capturing vulnerability aspects. We do not only highlight the unprecedented opportunities associated with these global datasets for the study of water-related disasters in the Anthropocene, but also discuss the challenges associated with their exploitation. These challenges include: (a) time varying datasets advised not to be used in time series analyses; (b) fine spatial resolution datasets advised not to be used in local scale studies; (c), datasets built by a wide variety of data sources prohibiting systematic uncertainty assessments; and (d) datasets built by covariate variables preventing interaction studies.

The reliability of a levee system is a crucial factor in flood risk management. In this study we present a probabilistic methodology to assess the effects of levee cover strength on levee failure probability, triggering time, flood propagation and consequent impacts on population and assets. A method for determining fragility curves is used in combination with the results of a one-dimensional hydrodynamic model to estimate the conditional probability of levee failure in each river section. Then, a levee breach model is applied to calculate the possible flood hydrographs, and for each breach scenario a two-dimensional hydrodynamic model is used to estimate flood hazard (flood extent and timing, maximum water depths) and flood impacts (economic damage and affected population) in the areas at risk along the river reach. We show an application for levee overtopping and different flood scenarios for a 98 km reach of the lower Po River in Italy. The results show how different design solutions for the le...

Over the past decades, a variety of valuable research studies has helped to advance our understanding of the advantages and limitations of satellite derived precipitation datasets as a forcing to hydrological models, in combination with or as an alternative to gauge data. However, most studies have assessed the performance of only one single dataset (or a few), have used global precipitation datasets to force lumped models on regional/large-scale basins or have tested more complex distributed models only at small-scale basins. In addition, only few studies have re-calibrated the model for each precipitation dataset or have investigated reanalysis-based precipitation datasets. We aimed at addressing these gaps in the literature: in particular, we compared the performance of 18 different precipitation datasets when used as main forcing in a grid-based distributed hydrological model to assess streamflow in medium to large-scale river basins. These datasets are classified as Uncorrected Satellites (Class 1), Corrected Satellites (Class 2) and Reanalysis - Gauges based datasets (Class 3). To provide a broad-based analysis, 8 large-scale river basins (Amazon, Brahmaputra, Congo, Danube, Godavari, Mississippi, Rhine and Volga) having different sizes, hydrometeorological characteristics, and human influence were selected. The distributed hydrological model was recalibrated for each precipitation dataset individually. We found that there is not a unique best performing precipitation dataset for all basins and that results are very sensitive to the basin characteristics. However, a few datasets persistently outperform the others: SM2RAIN-ASCAT for Class 1, CHIRPS V2.0, MSWEP V2.1, and CMORPH-CRTV1.0 for Class 2, GPCC and WFEDEI GPCC for Class 3. Surprisingly, precipitation datasets showing the highest model accuracy at basin outlets do not show the same high performance in internal locations, supporting the use of distributed modelling approach rather than lumped.

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790&ndash, 2010&mdash, i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

The viability of a renewable electricity system depends on a relatively small share of hydropower storage resources to regulate climate variations and the spatially uneven distribution of renewable energy. By spatio-temporal coordination of hydropower production over larger regions, the energy storage demand will be reduced and contribute to a “virtual” energy storage gain that in Europe was found to be almost twice the actual energy storage capacity of hydropower reservoirs. In an attempt to quantify this gain, hydropower availability was simulated for most parts of the European continent for a 35-year period based on historical hydrometeorological data. The most significant benefits from spatio-temporal management arise at distances between 1200 and 3000 km, i.e., on the continental scale, which can have implications for a future renewable energy system at large. Furthermore, we discuss a condition termed “energy-domain-specific drought”, which is a risk that can be reduced by the spatio-temporal management of power production. Virtual energy storage gain is not explicitly considered in the management models of hydropower production systems but could in principle complement existing management incentives.

This paper offers a conceptual approach to explore the complex dynamics of floodplains as fully coupled human-water systems. A number of hydrologists have recently investigated the impact of human activities (such as flood control measures, land-use changes, and settlement patterns) on the frequency and severity of floods. Meanwhile, social scientists have shown how interactions between society and waters in deltas and floodplain areas, including the frequency and severity of floods, have an impact on the ways in which social relations unfold (in terms of governance processes, policies, and institutions) and societies are organised (spatially, politically, and socially). However, we argue that the interactions and associated feedback mechanisms between hydrological and social processes remain largely unexplored and poorly understood. Thus, there is a need to better understand how the institutions and governance processes interact with hydrological processes in deltas and floodplains to influence the frequency and severity of floods, while (in turn) hydrological processes co-constitute the social realm and make a difference for how social relations unfold to shape governance processes and institutions. Our research goal, therefore, is not in identifying one or the other side of the cycle (hydrological or social), but in explaining the relationship between them: how, when, where, and why they interact, and to what result for both social relations and hydrological processes? We argue that long time series of hydrological and social data, along with remote sensing data, can be used to observe floodplain dynamics from unconventional approaches, and understand the complex interactions between water and human systems taking place in floodplain areas, across scales and levels of human impacts, and within different hydro-climatic conditions, socio-cultural settings, and modes of governance.

In Bangladesh, socio-economic and hydrological processes are both extremely dynamic and inter-related. Human population patterns are often explained as a response, or adaptation strategy, to physical events, e.g. flooding, salt-water intrusion, and erosion. Meanwhile, these physical processes are exacerbated, or mitigated, by diverse human interventions, e.g. river diversion, levees and polders. In this context, this paper describes an attempt to explore the complex interplay between floods and societies in Bangladeshi floodplains. In particular, we performed a spatially-distributed analysis of the interactions between the dynamics of human settlements and flood inundation patterns. To this end, we used flooding simulation results from inundation modelling, LISFLOOD-FP, as well as global datasets of population distribution data, such as the Gridded Population of the World (20 years, from 1990 to 2010) and HYDE datasets (310 years, from 1700 to 2010). The outcomes of this work highlight the behaviour of Bangladeshi floodplains as complex human–water systems and indicate the need to go beyond the traditional narratives based on one-way cause–effects, e.g. climate change leading to migrations.

This study compares model averaging and model selection methods to estimate design floods, while accounting for the observation error that is typically associated with annual maximum flow data. Model selection refers to methods where a single distribution function is chosen based on prior knowledge or by means of selection criteria. Model averaging refers to methods where the results of multiple distribution functions are combined. Numerical experiments were carried out by generating synthetic data using the Wakeby distribution function as the parent distribution. For this study, comparisons were made in terms of relative error and root mean square error (RMSE) referring to the 1-in-100 year flood. The experiments show that model averaging and model selection methods lead to similar results, especially when short samples are drawn from a highly asymmetric parent. Also, taking an arithmetic average of all design flood estimates gives estimated variances similar to those obtained with more complex weighted model averaging.

In flood risk assessment, there remains a lack of analytical frameworks capturing the dynamics emerging from two-way feedbacks between physical and social processes, such as adaptation and levee effect. The former, “adaptation effect”, relates to the observation that the occurrence of more frequent flooding is often associated with decreasing vulnerability. The latter, “levee effect”, relates to the observation that the non-occurrence of frequent flooding (possibly caused by flood protection structures, e.g. levees) is often associated to increasing vulnerability. As current analytical frameworks do not capture these dynamics, projections of future flood risk are not realistic. In this paper, we develop a new approach whereby the mutual interactions and continuous feedbacks between floods and societies are explicitly accounted for. Moreover, we show an application of this approach by using a socio-hydrological model to simulate the behavior of two main prototypes of societies: green societies, which cope with flooding by resettling out of flood-prone areas; and technological societies, which deal with flooding also by building levees or dikes. This application shows that the proposed approach is able to capture and explain the aforementioned dynamics (i.e. adaptation and levee effect) and therefore contribute to a better understanding of changes in flood risk, within an iterative process of theory development and empirical research.

The risk coping culture of a community plays a major role in the development of urban floodplains. In this paper we analyse, in a conceptual way, the interplay of community risk coping culture, flooding damage and economic growth. We particularly focus on three aspects: (i) collective memory, i.e., the capacity of the community to keep risk awareness high; (ii) risk-taking attitude, i.e., the amount of risk the community is collectively willing to be exposed to; and (iii) trust of the community in risk reduction measures. To this end, we use a dynamic model that represents the feedback between the hydrological and social system components. Model results indicate that, on the one hand, by under perceiving the risk of flooding (because of short collective memory and too much trust in flood protection structures) in combination with a high risk-taking attitude, community development is severely limited because of high damages caused by flooding. On the other hand, overestimation of risk (long memory and lack of trust in flood protection structures) leads to lost economic opportunities and recession. There are many scenarios of favourable development resulting from a trade-off between collective memory and trust in risk reduction measures combined with a low to moderate risk-taking attitude. Interestingly, the model gives rise to situations in which the development of the community in the floodplain is path dependent, i.e., the history of flooding may lead to community growth or recession.

High social, environmental and financial costs of dam construction during the past century provide valuable lessons for improving large infrastructure governance and enhancing dam safety. The Italian Vajont dam tragedy in 1963, for example, where the urgency to boost post-war economic development overruled cautionary site selection and reservoir filling, led to improved safety regulations. Today, Afghanistan is facing similar pressure to spur economic development. Revisiting Afghanistan’s own dam history may inform decision-making over large scale dam development. For this, we refer to dam development in Afghanistan during the Cold War institutional constellation, which combined with the discourse on the role of dams in state formation, modernisation and development, profoundly shaped Afghanistan’s landscape. Current dam development shows little evidence that any historic reflection is taking place; instead the discourse of infrastructure-as-prerequisite-for-development is consistently repeated. We argue that four factors compromise dam development in Afghanistan today: (1) lack of security; (2) an institutional context under transition; (3) absence of transboundary dialogue and agreements and (4) uncertain and fragmented aid provision. The complexity of dam development and operation is exacerbated by the extended temporal and spatial scale of their impact, thus placing a heavy burden on management- and planning capacity. Given these conditions, these dam development plans are built on fragile institutional foundations. To address their feasibility under such circumstances this paper links lessons from the past with the criticalities in future Afghan dam development.

The population growth and the economic development that the five Countries (Argentina, Bolivia, Brazil, Paraguay and Uruguay) located in La Plata Basin (LPB) have gone through over the last decades have risen the necessity to assess the current and future electricity demand and compare it to the energy production. In this region, the water resources of LPB are one of the most important sources of energy. In this context, the CLARIS EU (European Union) FP7 project has carried out an extensive research work which, in terms of investigating hydropower potential and vulnerability, has produced the following outcomes: assessment of current hydropower production and electricity demand; calculation of the maximum potential hydropower in order to establish whether and when shortage in terms of hydropower generation is to be expected; analysis of potential residual hydropower taking into account future user demands and analysis of hydropower production taking into account climate change scenarios, in order to iden...

Isla Hispaniola, the island shared by Haiti and the Dominican Republic, has repeatedly witnessed catastrophic disasters that caused dramatic economic losses and killed thousands of people over the last decades. One striking example is the disastrous flood event that hit the transnational basin of River Soliette on 24 May 2004. The event resulted from a severe tropical storm and killed over 1000 Haitian and 400 Dominican people. In the context of an International Cooperation Initiative, the University of Bologna led several activities in the fields of flood risk assessment, management and mitigation, and sustainable development planning for the Soliette river basin. This paper presents new techniques for a timely assessment of flood risk in data-scarce and remote areas in developing countries showing in particular: (1) Global Navigation Satellite System (GNSS)-based topographic survey of the Soliette riverbed, carried out under urgent temporal, logistical and technical constraints, and (2) some possible utilisations of the collected topographic data for the identification of structural and non-structural flood risk mitigation measures. The analysis enabled us to set and test a GNSS-based technique for fast, reliable and detailed topographic surveys in remote regions, which represents a valid option for similar areas with limited accessibility in emerging and developing countries.

This opinion article posits that the current lack of understanding of the dynamic interactions among the different components of risk (e.g., hazard, exposure, vulnerability, or resilience) is one of the main obstacles for the implementation of effective risk prevention measures. In state-of-the-art methods for risk assessment, natural and social systems are typically treated separately by using different approaches. In flood risk studies, for instance, hydrological scientists typically focus on flood hazard, whereas socioeconomic scientists mainly examine the exposure, vulnerability, or resilience to flood events. However, we argue that these different components are deeply interconnected: for example, changes in flood hazard often trigger changes in vulnerability, and vice versa. These interconnections between the different components of risk remain largely unexplored and poorly understood. This lack of knowledge is of serious concern as it limits our ability to plan appropriate risk prevention measures. To design flood protection structures, for example, current methods can indeed provide quantitative assessments of the corresponding risk reduction associated to the reduced flood hazard. Nevertheless, traditional methods cannot estimate how, and to what extent, the reduced frequency or magnitude of floods might trigger increases of exposure or vulnerability to flooding (e.g., ‘levee effect’). Thus, while many progresses have been made in the static assessment of flood risk, the dynamics of risk are still poorly investigated. We think that this is a major issue in a rapidly changing world, and we therefore propose a transdisciplinary research agenda as a possible way out. Conflict of interest: The authors have declared no conflicts of interest for this article.

Natural catastrophic events are one of most critical aspects for health and economy all around the world. However, the impact in a poor region can impact more dramatically than in others countries. Isla Hispaniola (Haiti and the Dominican Republic), one of the poorest regions of the planet, has repeatedly been hit by catastrophic natural disasters that caused incalculable human and economic losses. After the catastrophic flood event occurred in the basin of River Soliette on May 24th, 2004, the General Direction for Development and Cooperation of the Italian Department of Foreign Affairs funded an international cooperation initiative (ICI) coordinated by the University of Bologna, that involved Haitian and Dominican institutions.Main purpose of the ICI was hydrological and hydraulic analysis of the May 2004 flood event aimed at formulating a suitable and affordable flood risk mitigation plan, consisting of structural and non-structural measures. In this contest, a topographic survey was necessary to realize the hydrological model and to improve the knowledge in some areas candidates to be site for mitigation measures.To overcome the difficulties arising from the narrowness of funds, surveyors and limited time available for the survey, only GPS technique have been used, both for framing aspects (using PPP approach), and for geometrical survey of the river by means of river cross-sections and detailed surveys in two areas (RTK technique). This allowed us to reconstruct both the river geometry and the DTM’s of two expansion areas (useful for design hydraulic solutions for mitigate flood-hazard risk).

Isla Hispaniola, the island shared by Haiti and the Dominican Republic, has repeatedly witnessed catastrophic disasters that caused dramatic economic losses and killed thousands of people over the last decades. One striking example is the disastrous flood event that hit the transnational basin of River Soliette on 24 May 2004. The event resulted from a severe tropical storm and killed over 1000 Haitian and 400 Dominican people. In the context of an International Cooperation Initiative, the University of Bologna led several activities in the fields of flood risk assessment, management and mitigation, and sustainable development planning for the Soliette river basin. This paper presents new techniques for a timely assessment of flood risk in data-scarce and remote areas in developing countries showing in particular: (1) Global Navigation Satellite System (GNSS)-based topographic survey of the Soliette riverbed, carried out under urgent temporal, logistical and technical constraints, and (2) some possible utilisations of the collected topographic data for the identification of structural and non-structural flood risk mitigation measures. The analysis enabled us to set and test a GNSS-based technique for fast, reliable and detailed topographic surveys in remote regions, which represents a valid option for similar areas with limited accessibility in emerging and developing countries.

Investigating the influence of minor hydraulic structures on modeling flood events in lowland areas

Population growth, economic development, urbanization, changes in hydrological regimes and land use are the main drivers affecting allocation and exploitation of water resources. The pressure exerted by these global changes on the five countries -Argentina, Bolivia, Brazil, Paraguay and Uruguay- located in La Plata Basin over the last decades has raised the need for assessing trends in future electricity demand and energy production in the basin. The aim of this research is to assess whether (and when) shortage and vulnerabilities in terms of hydropower generation are to be expected in La Plata basin in the next decades. The methodology proposed has focused on two aspects to reach the objectives: 1) assessment of hydropower production and electricity demand in the basin over the last twenty years (1987–2008), in order to establish growing trends for the next thirty years; 2) computation of maximum potential hydropower using the newly developed Arc-GIS based tool VAPIDRO-ASTE. The assessment and calculation have been applied to La Plata River and its main tributaries: Paranaiba, Grande River, Tiete, Paranapanema, Iguacu, Uruguay, Negro River, Paraguay and Parana. The first outcomes of this research show that La Plata Basin has high hydropower potential. About 40% of the hydropower potential is already used to produce and supply energy. Out of the remaining 60% potential, about 25% could hardly be exploited because of environmental issues or low cost/benefit ratio. Thus, the estimated residual potential hydropower is about 35% of the maximum potential hydropower calculated.

La Plata Basin is shared by five countries (Argentina, Bolivia, Brazil, Paraguay and Uruguay), which have fast growing economies in South America. These countries need energy for their sustainable development; hence, hydropower can play a very important role as a renewable clean source of energy. This paper presents an analysis of the current hydropower production and electricity demand in La Plata Basin (LPB), and it analyses the maximum and residual hydropower potential of the basin for a horizon of 30 yr (i.e. year 2040). Current hydropower production is estimated based on historical available data, while future energy production is deduced from the available water in the catchment (estimated based on measured hydrographs of the past years), whereas electricity demand is assessed by correlating existing electricity demand with the estimated population growth and economic development. The maximum and residual hydropower potential of the basin were assessed for the mean annual flows of the present hydrological regime (1970–2000) and topographical characteristics of the area. Computations were performed using an integrated GIS environment called VAPIDRO-ASTE released by the Research on Energy System (Italy). The residual hydropower potential of the basin is computed considering first that the water supply needs for population, industry and agriculture are served, and then hydropower energy is produced. The calculated hydropower production is found to be approximately half of the estimated electricity demand, which shows that there is a need to look for other sources of energy in the future.

The presence of a bridge spanning over a river and its floodplain alters the condition of flow. In subcritical conditions, which are typical in alluvial rivers, this flow alteration results in the so-called backwater effect, that is, an increase of the water surface elevation upstream of the structure as a response to increased energy losses. The extension of the expected backwater affected area and the increase in water surface elevation are highly dependent on the river morphology, bridge geometry, flow and floodplain characteristics and may originate upstream flooding. Thus, in many countries, at the stage of design a new bridge (or renovation works), a specific investigation on the backwater effect has to be undertaken to analyse its effect on the flooding of its vicinity. Bridge waterway hydraulics has been widely investigated in terms of practical research and some standard guidelines have been suggested for modelling the backwater effect at bridge crossings. Although the scientific literature has widely proven that hydraulic modelling is affected by many sources of uncertainty, the hydraulic modelling of backwater effects is still undertaken within a deterministic approach, based on the outcomes of a calibrated hydraulic model. This article aims at approaching the prediction of backwater effects at bridge crossings by accounting for the main sources of uncertainty affecting the hydraulic modelling exercise. A bridge over a highly vegetated floodplain (Tallahala Creek, Mississippi, USA) was considered for this analysis, and uncertainty in the model parameters and input data was assessed to predict backwater flood design profiles. Copyright © 2012 John Wiley & Sons, Ltd.

The scientific literature has widely shown that hydraulic modelling is affected by many sources of uncertainty (e.g. model structure, input data, model parameters). However, when hydraulic models are used for engineering purposes (e.g. flood defense design), there is still a tendency to make a deterministic use of them. More specifically, the prediction of flood design profiles is often based on the outcomes of a calibrated hydraulic model. Despite the good results in model calibration, this prediction is affected by significant uncertainty, which is commonly considered by adding a freeboard to the simulated flood profile. A more accurate approach would require an explicit analysis of the sources of uncertainty affecting hydraulic modelling and design flood estimation. This paper proposes an alternative approach, which is based on the use of uncertain flood profiles, where the most significant sources of uncertainty are explicitly analyzed. An application to the Po river reach between Cremona and Borgoforte (Italy) is used to illustrate the proposed framework and compare it to the traditional approach. This paper shows that the deterministic approach underestimates the design flood profile and questions whether the freeboard, often arbitrarily defined, might lead to a false perception of additional safety levels.

Scouring of piers and abutment has been recognized as the main cause of damage and failure of bridges over waterways. The scientific community has produced a number of studies addressing the complex characteristics of the scour process and has provided engineers with several techniques for the estimate of the maximum expected scour depth at a bridge site. Nevertheless, the prediction of scour depths is affected by many sources of uncertainty, such as observation uncertainty, parameter uncertainty, and structural uncertainty. Only a few studies have recently tried to estimate the uncertainty associated to the scour depth prediction. This paper offers a broad review of the main aspects to be taken into account when analyzing bridge pier scour: 1) processes: to better understand the dynamics triggering pier scour, an analysis of the type of scour occurring at bridge piers, the most influencing factors, failure mechanisms and local pier scour dynamics is carried out; 2) measurements: one of the main difficulties faced in the real world practice is scour data collection; this session reviews the latest techniques available for the measurements of the scour depth at bridge piers; 3) estimates: this session critically reviews different approaches the scientific literature has offered for the estimate of the maximum local scour depth and discusses the difficulty to address uncertainty in the estimates. This review is meant to be a useful reference for scientists and technicians dealing with the bridge pier scour issue.

The scouring effect of the flowing water around bridge piers may undermine the stability of the structure, leading to extremely high direct and indirect costs and, in extreme cases, the loss of human lives. The use of Artificial Neural Network (ANN) models has been recently proposed in the literature for estimating the maximum scour depth around bridge piers: this study aims at further investigating the potentiality of the ANN approach and, in particular, at analysing the influence of the experimental setting (laboratory or field data) and of the sediment transport mode (clear water or live bed) on the prediction performances. A large database of both field and laboratory observations has been collected from the literature for predicting the maximum local scour depth as a function of a parsimonious set of variables characterizing the flow, the sediments and the pier. Neural networks with an increasing degree of specialization have been implemented – using different subsets of the calibration data in the training phase – and validated over an external validation dataset. The results confirm that the ANN scour depths' predictions outperform the estimates obtained by empirical formulae conventionally used in the literature and in the current engineering practice, and demonstrate the importance of taking into account the differences in the type of available data – laboratory or field data – and the sediment transport mode – clear water or live bed conditions.

It is widely recognised that remote sensing can support flood monitoring, modelling and management. In particular, satellites carrying Synthetic Aperture Radar (SAR) sensors are valuable as radar wavelengths can penetrate cloud cover and are insensitive to daylight. However, given the strong inverse relationship between spatial resolution and revisit time, monitoring floods from space in near real time is currently only possible through low resolution (about 100 m pixel size) SAR imagery. For instance, ENVISAT-ASAR (Advanced Synthetic Aperture Radar) in WSM (wide swath mode) revisit times are of the order of 3 days and the data can be obtained within 24 h at no (or low) cost. Hence, this type of space-borne data can be used for monitoring major floods on medium-to-large rivers. This paper aims to discuss the potential for, and uncertainties of, coarse resolution SAR imagery to monitor floods and support hydraulic modelling. The paper first describes the potential of globally and freely available space-borne data to support flood inundation modelling in near real time. Then, the uncertainty of SAR-derived flood extent maps is discussed and the need to move from deterministic binary maps (wet/dry) of flood extent to uncertain flood inundation maps is highlighted.

The average risk of a bridge over water in the USA collapsing from scour during its 75 years design life is estimated at 3.7×10−3. This risk makes scour of foundations the number one cause of bridge collapse and 3 times larger than the next cause of bridge collapse, which is collisions. The current paper presents a site specific method to estimate the probability that a certain scour depth will be exceeded during the life of a bridge. The methodology is limited to some uncertainties associated with the randomness of hydrologic conditions. It does not include uncertainties associated with other input parameters, such as geometry and soil erodibility or uncertainties associated with the scour prediction model. The SRICOS–EFA method is used as the reference method to predict the scour depth. This method requires three inputs: the hydraulic parameters (e.g. velocity hydrograph), the geometry parameters (e.g. pier size) and the soil erodibility parameters (e.g. erosion function). The input is used together wit...