Risk management has reduced vulnerability to floods and droughts globally^1,2, yet their impacts are still increasing³. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data^4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change³.

Effective flood risk management requires a realistic estimation of flood losses. However, available flood damage estimates are still characterized 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, in a blind-validation test, the performances of different models for the assessment of the direct flood damage to the residential sector at the building level (i.e. microscale). The test consisted of a common flood case study characterized by high availability of hazard and building data but with undisclosed information on observed losses in the implementation stage of the models. The nine selected 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 multivariable models. From another perspective, the exercise allowed us to increase awareness of strengths and limits of flood damage modelling, which are summarized in the paper in the form of take-home messages from a modeller's perspective.

Several severe flood events hit Germany in recent years, with events in 2013 and 2016 being the most destructive ones, although dynamics and flood processes were very different. While the 2013 event was a slowly rising widespread fluvial flood accompanied by some severe dike breaches, the events in 2016 were fast-onset pluvial floods, which resulted in surface water flooding in some places due to limited capacities of the drainage systems and in destructive flash floods with high sediment loads and clogging in others, particularly in small steep catchments. Hence, different pathways, i.e. different routes that the water takes to reach (and potentially damage) receptors, in our case private households, can be identified in both events. They can thus be regarded as spatially compound flood events or compound inland floods. This paper analyses how differently affected residents coped with these different flood types (fluvial and pluvial) and their impacts while accounting for the different pathways (river flood, dike breach, surface water flooding and flash flood) within the compound events. The analyses are based on two data sets with 1652 (for the 2013 flood) and 601 (for the 2016 flood) affected residents who were surveyed around 9 months after each flood, revealing little socio-economic differences – except for income – between the two samples. The four pathways showed significant differences with regard to their hydraulic and financial impacts, recovery, warning processes, and coping and adaptive behaviour. There are just small differences with regard to perceived self-efficacy and responsibility, offering entry points for tailored risk communication and support to improve property-level adaptation.

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, https://doi.org/10.5880/GFZ.4.4.2023.001).

Flood loss data collection and modeling are not standardized, and previous work has indicated that losses from different flood types (e.g., riverine and groundwater) may follow different driving forces. However, different flood types may occur within a single flood event, which is known as a compound flood event. Therefore, we aimed to identify statistical similarities between loss‐driving factors across flood types and test whether the corresponding losses should be modeled separately. In this study, we used empirical data from 4,418 respondents from four survey campaigns studying households in Germany that experienced flooding. These surveys sought to investigate several features of the impact process (hazard, socioeconomic, preparedness, and building characteristics, as well as flood type). While the level of most of these features differed across flood type subsamples (e.g., degree of preparedness), they did so in a nonregular pattern. A variable selection process indicates that besides hazard and building characteristics, information on property‐level preparedness was also selected as a relevant predictor of the loss ratio. These variables represent information, which is rarely adopted in loss modeling. Models shall be refined with further data collection and other statistical methods. To save costs, data collection efforts should be steered toward the most relevant predictors to enhance data availability and increase the statistical power of results. Understanding that losses from different flood types are driven by different factors is a crucial step toward targeted data collection and model development and will finally clarify conditions that allow us to transfer loss models in space and time.

Study regionThe Tapajós Basin is an important Amazon tributary affected by human activities with great potential for water conflicts. The basin, as others within the Amazon region, is receiving a number of hydropower plants, among them the Teles Pires plant, projected to operate in 2015.Study focusHydrological impacts due to climate change affect human activities, such as hydroelectric generation, and should be carefully studied for better planning of water management. In this study, we assess climate change impacts by applying the MHD-INPE hydrological model using several climate models projections as inputs. The impact assessment consisted of statistical shifts of precipitation and discharge. Energy production in a projected hydropower plant was assessed through the development of annual power duration curves for each projection, also considering its design and structural limitations.New hydrological insights for the regionThe high inter-model variability in the climate projections drives a high variability in the projected hydrological impacts. Results indicate an increase of basin's sensitivity to climate change and vulnerability of water exploitation. Uncertainties prevent the identification of a singular optimal solution for impacts assessment. However, exploratory analysis of the plant design robustness for hydropower generation show a reduction in the energy production even under projections of increased discharge, due to plant capacity limitations. This is valuable information for stakeholders to decide about energy production strategies