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.

Monitoring of geomorphic changes affecting sea cliffs poses a difficult challenge from a logistical point of view. Nevertheless, this activity is fundamental for the evaluation of cliff recession rates and the assessment of risk conditions affecting coastal settlements. Innovative geomatics techniques provide a valid contribution to detect cliff topographic modifications induced by erosion or landslide processes. This study presents a photogrammetric approach based on structure from motion (SfM) aimed at monitoring the geomorphic evolution of a coastal landslide that displaced about 40 000 m³ of material in southern Italy. The landslide was monitored for more than two years, comparing multitemporal 3D point clouds derived from SfM. The results of change detection analysis allowed quantifying the volumes of rocks and unconsolidated sediments mobilised by erosion processes after the main failure, and developing a sediment budget. The study highlighted the high erodibility of collapsed material, as well as the suitability of the adopted techniques for 3D change detection analyses.

Systematic and timely documentation of triggered (i.e. event) landslides is fundamental to build extensive datasets worldwide that may help define and/or validate trends in response to climate change. More in general, preparation of landslide inventories is a crucial activity since it provides the basic data for any subsequent analysis. In this work we present an event landslide inventory map (E-LIM) that was prepared through a systematic reconnaissance field survey in about 1 month after an extreme rainfall event hit an area of about 5000 km² in the Marche-Umbria regions (central Italy). The inventory reports evidence of 1687 triggered landslides in an area of ~550 km². All slope failures were classified according to type of movement and involved material, and documented with field pictures, wherever possible. The database of the inventory described in this paper as well as the collection of selected field pictures associated with each feature is publicly available at figshare.

Timely and systematic collection of landslide information after a triggering event is pivotal for the definition of landslide trends in response to climate change. On September 15, 2022, a large part of central Italy, particularly Marche and Umbria regions, was struck by an anomalous rainfall event that showed characteristics of a persistent convective system. An extraordinary cumulated rainfall of 419 mm was recorded by a rain gauge in the area in only 9 h. The rainfall triggered 1687 landslides in the area affected by the peak rainfall intensity and caused widespread flash floods and floods in the central and lower parts of the catchments. In this work, we describe the characteristics of the landslides identified during a field survey started immediately after the event. Most of the mass movements are shallow, and many are rapid (i.e., debris flows, earth flows) and widely affecting the road network. Landslide area spans from a few tens of square meters to 10⁵ m², with a median value of 87 m². Field evidence revealed diffuse residual risk conditions, being a large proportion of landslides located in the immediate vicinity of infrastructures. Besides reporting the spatial distribution of landslides triggered by an extreme rainfall event, the data collected on landslides can be used to make comparisons with the distribution of landslides in the past, validation of landslide susceptibility models, and definition of the general interaction between landslides and structures/infrastructures.

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).