In a recent editorial in the journal Nature Sustainability, the editors raised the concern that journal submissions on water studies appear too similar. The gist of the editorial: “too many publications and not enough ideas.” In this response, we contest this notion, and point to the numerous new ideas that result from taking a broader view of the water science field. Drawing inspiration from a recently hosted conference geared at transcending traditional disciplinary silos and forging new paradigms for water research, we are, in fact, enthusiastic and optimistic about the ways scientists are investigating political, economic, historical, and cultural intersections toward more just and sustainable human-water relations and ways of knowing.

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Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model’s ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model’s performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework.

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Commercial assets comprise buildings, machinery and equipment, which are susceptible to floods. Existing damage models and exposure estimation methods for this sector have limited transferability between flood events and therefore limited potential for pan-European applications. In this study we introduce two methodologies aiming at improving commercial flood damage modelling: (1) disaggregation of economic statistics to obtain detailed building-level estimates of replacement costs of commercial assets; (2) a Bayesian Network (BN) damage model based primarily on post-disaster company surveys carried out in Germany. The BN model is probabilistic and provides probability distributions of estimated losses, and as such quantitative uncertainty information. The BN shows good accuracy of predictions of building losses, though overestimates machinery/equipment loss. To test its suitability for pan-European flood modelling, the BN was applied to three case studies, comprising a coastal flood in France (2010) and fluvial floods in Saxony (2013) and Italy (2014). Overall difference between modelled and reported average loss per company was only 2–19% depending on the case study. Additionally, the BN model achieved better results than six alternative damage models in those case studies (except for one model in the Italian case study). Further, our exposure estimates mostly resulted in better predictions of the damage models compared to previously published pan-European exposure data, which tend to overestimate exposure. All in all, the methods allow easy modelling of commercial flood losses in the whole of Europe, since they are applicable even if only publicly-available datasets are obtainable. The methods achieve a higher accuracy than alternative approaches, and inherently provide confidence intervals, which is particularly valuable for decision making under high uncertainty.@en

Natural hazards affect many types of tangible assets, the most valuable of which are often residential assets, comprising buildings and household contents. Yet, information necessary to derive exposure in terms of monetary value at the level of individual houses is often not available. This includes building type, size, quality, or age. In this study, we provide a universal method for estimating exposure of residential assets using only publicly available or open data. Using building footprints (polygons) from OpenStreetMap as a starting point, we utilized high-resolution elevation models of 30 European capitals and pan-European raster datasets to construct a Bayesian-network-based model that is able to predict building height. The model was then validated with a dataset of (1) buildings in Poland endangered by sea level rise, for which the number of floors is known, and (2) a sample of Dutch and German houses affected in the past by fluvial and pluvial floods, for which usable floor space area is known. Floor space of buildings is an important basis for approximating their economic value, including household contents. Here, we provide average national-level gross replacement costs of the stock of residential assets in 30 European countries, in nominal and real prices, covering the years 2000-2017. We either relied on existing estimates of the total stock of assets or made new calculations using the perpetual inventory method, which were then translated into exposure per square metre of floor space using data on countries' dwelling stocks. The study shows that the resulting standardized residential exposure values provide much better coverage and consistency compared to previous studies.@en

The Sustainable Development Goals (SDGs) of the United Nations Agenda 2030 represent an ambitious blueprint to reduce inequalities globally and achieve a sustainable future for all mankind. Meeting the SDGs for water requires an integrated approach to managing and allocating water resources, by involving all actors and stakeholders, and considering how water resources link different sectors of society. To date, water management practice is dominated by technocratic, scenario-based approaches that may work well in the short term but can result in unintended consequences in the long term due to limited accounting of dynamic feedbacks between the natural, technical, and social dimensions of human-water systems. The discipline of sociohydrology has an important role to play in informing policy by developing a generalizable understanding of phenomena that arise from interactions between water and human systems. To explain these phenomena, sociohydrology must address several scientific challenges to strengthen the field and broaden its scope. These include engagement with social scientists to accommodate social heterogeneity, power relations, trust, cultural beliefs, and cognitive biases, which strongly influence the way in which people alter, and adapt to, changing hydrological regimes. It also requires development of new methods to formulate and test alternative hypotheses for the explanation of emergent phenomena generated by feedbacks between water and society. Advancing sociohydrology in these ways therefore represents a major contribution toward meeting the targets set by the SDGs, the societal grand challenge of our time.

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Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Münster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Münster and Amsterdam, in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend the inclusion of cell phones in a CATI survey to avoid biased sampling towards certain age groups.

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In 2013, the International Association of Hydrological Sciences (lAHS) launched the hydrological decade 2013-2022 with the theme "Panta Rhei; Change in Hydrology and Society". The decade recognizes the urgency of hydrological research to understand and predict the interactions of society and water, to support sustainable water resource use under changing climatic and environmental conditions. This paper reports on the first Panta Rhei biennium 2013-2015, providing a comprehensive resource that describes the scope and direction of Panta Rhei. We bring together the knowledge of all the Panta Rhei working groups, to summarize the most pressing research questions and how the hydrological community is progressing towards those goals. We draw out interconnections between different strands of research, and reflect on the need to take a global view on hydrology in the current era of human impacts and environmental change. Finally, we look back to the six driving science questions identified at the outset of Panta Rhei, to quantify progress towards those aims. @en

We explore how to address the challenges of adaptation of water resources systems under changing conditions by supporting flexible, resilient and low-regret solutions, coupled with on-going monitoring and evaluation. This will require improved understanding of the linkages between biophysical and social aspects in order to better anticipate the possible future co-evolution of water systems and society. We also present a call to enhance the dialogue and foster the actions of governments, the international scientific community, research funding agencies and additional stakeholders in order to develop effective solutions to support water resources systems adaptation. Finally, we call the scientific community to a renewed and unified effort to deliver an innovative message to stakeholders. Water science is essential to resolve the water crisis, but the effectiveness of solutions depends, inter alia, on the capability of scientists to deliver a new, coherent and technical vision for the future development of water systems.

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Pluvial floods have caused severe damages to urban dwellings in Europe and elsewhere in recent years. With a predicted increase in extreme weather events as well as an ongoing urbanization, pluvial flood damage is expected to increase in the future. These type of flood events, caused by stormwater being unable to enter urban drainage systems or flowing out of urban drainage systems when capacity is exceeded, often happen with little warning and in areas which are often not obviously prone to flooding. Up to now little research was done on the adverse consequences of pluvial floods, as empirical damage data of pluvial flooding is scarce. In this study, results of two telephone surveys are discussed. The surveys comprise interviews with more than 500 flood-affected households in Germany (Münster and Greven) and the Netherlands (Amsterdam), related to the severe rain event of July 28th 2014. Respondents were asked a series of questions about the damage to their building structure and contents, as well as on topics such as early warning, emergency and precautionary measures, building properties and hazard characteristics. The questionnaire was developed with the aim to create a harmonized transnational pluvial flood damage survey that can potentially be extended to other European countries. New indicator variables have been developed to account for different national and regional standards in building structure, early warning, socio-economic data and recovery. The survey data from the German and Dutch case studies are compared with the goal to identify similarities and differences in damage reducing factors and recovery. Water level data and other hazard characteristics are used to form comparable groups out of the German and Dutch sample. Within these groups, regional distinctions in building topology and use are expected to have the strongest impact on differences between reported damage amounts of the two case studies. The newly collected data will be used in future studies to develop pluvial flood damage models. @en