In volcanic fields, the location of an eruptive vent controls the hazards, their intensities, and ultimately the impact of the eruption. Estimates of where future eruptions are likely to occur inform evacuation plans, the (re)location of vital infrastructure, and the placement of early-warning monitoring equipment. Current estimates assume that locations with more past-vents are more likely to produce future-vents. We provide the formulae for an alternative hypothesis of magma depletion.

This study constructs an indicator-based composite framework and assesses urban resilience to typhoons in China's seven major river basins. The results verified the spatial heterogeneity, and the calculated resilience score in certain circumstances did not match the strength of city economy. The analysis is helpful for the government to enhance capability of comprehensive resilience in specific dimensions and provides a reference in probing resilience assessment confronting typhoon disasters.

The Mediterranean Sea has been warming rapidly since 1980, and its basic thermodynamic effect acts to boost hail in the higher-risk parts of Europe. Climate model experiments indicate the Mediterranean warming is mainly caused by rising greenhouse gases, with reduced anthropogenic aerosols contributing too. A review of research and data revealed hail losses rising at around 2 % per year over the same period. Moreover, the trajectory of anthropogenic forcings suggests hail risk will keep rising.

Between 17 and 20 September 2024, the Lamone River basin in northern Italy was hit by extreme precipitation. This study adopts the hydrological model Rhyme and the hydrodynamic model PARFLOOD to simulate the hydrological processes in the watershed and the levee-breach-induced inundation affecting the village of Traversara. The close match between the resulting flooded areas and the observed ones shows the capability of these numerical models to support the preparedness for at-risk populations.

On 2 April 2024, a M_w 7.4 earthquake hit Taiwan's eastern coast, causing extensive landslides and damage. We used automated methods combining Earth observation (EO) data with AI to quickly inventory the landslides. This approach identified 7090 landslides over 75 km² within 3 h of acquiring the EO imagery. The study highlights AI's role in improving landslide detection efforts in disaster response.

Understanding coastal flood protection is vital for assessing risks from natural disasters and climate change. However, current global data on coastal flood protection are limited and based on simplified assumptions, leading to potential uncertainties in risk estimates. As a step in this direction, we propose a comprehensive dataset, COASTtal flood PROtection Standards within EUrope (COASTPROS-EU), which compiles coastal flood protection standards in Europe.

Mapping exposure to landslides is necessary to mitigate risk and reduce vulnerability. In this study, we show that there is a poor correlation between building damage and deaths from landslides, such that the deadliest landslides do not always destroy the most buildings and vice versa. This has important implications for our management of landslide risk.

Communicating uncertainties is a crucial yet challenging aspect of spatial modelling – especially in applied research, where results inform decisions. In disaster risk reduction, susceptibility maps for natural hazards guide planning and risk assessment, yet their uncertainties are often overlooked. We present a new type of landslide susceptibility map that visualizes both susceptibility and associated uncertainty alongside guidelines for creating such maps using free and open-source software.