Hailstorms can cause severe damage to homes, crops, and infrastructure. Using high-resolution climate simulations, we tracked thousands of hailstorms across Europe to study future changes. Large hail will become more frequent, hail-covered areas will expand, and instances of extreme hail combined with heavy rain will double. These shifts could increase risks for communities and businesses, highlighting the need for better preparedness and adaptation.

Earthquakes are among the most disastrous natural calamities due to the release of accumulated strain energy from continuous tectonic movements. They have the potential to cause havoc in terms of both economic losses and loss of life. This paper presents a methodology to predict earthquakes in terms of seismic energy release globally using an ensemble machine learning technique, and then the approach is tested for one of the most seismically active regions of the world: the Western Himalayas.

This research investigates how seagrass meadows attenuate coastal waves. Our methodology integrates site measurements with numerical simulations, revealing that plant flexibility and seasonal growth cycles are crucial factors that enhance model fidelity for predicting wave damping. These insights aid ecosystem-based coastal protection and conservation of these vital habitats. Future work should address current–sediment–vegetation interactions for a more complete hydrodynamic understanding.

This study comprehends and predicts the socioeconomic effects of floods in the High Mountain Asia (HMA) region. We proposed a machine learning strategy for mapping socioeconomic flood damage. We predicted the life year index (LYI), which quantifies the financial cost and loss of life caused by floods, using variables including climate, geomorphology, and population. The study's overall goal is to offer useful information on flood susceptibility and subsequent risk mapping in the HMA region.

Glacial lake outburst floods (GLOFs) continue to threaten high-mountain communities in Nepal. We simulate potential GLOF events from five glacial lakes in the Everest region during the 21st century using a 3D flood model and several breach and SSP scenarios. Large GLOFs could extend over 100 km and inundate 80 to 100 km of roads/trails, 735 to 1989 houses and 0.85 to 3.52 km² of agricultural land. The results help to assess the changing GLOF impacts and support more accurate risk assessments.

This study examines how forms of resilience capital and disaster risk management shape health outcomes after floods. Using data from 66 communities across seven Global South countries, we find that preparedness consistently reduces both injuries and deaths. Social and human capital also help lower injury rates. By combining measures of resilience and disaster risk management, the study offers new insights into how community-level capacities influence post-flood health outcomes.

Developing seismo-volcanic monitoring tools is crucial for volcanic observatories. Our study reviews current methods using transfer learning techniques and finds that while these systems identify nearly 90 % of seismic events, they miss other important volcanic data due to the catalog-learning bias. We propose a weakly supervised technique to reduce bias and uncover new volcanic information. This method can improve existing databases and efficiently create new ones using machine learning.

South and south-eastern Spain has the highest seismicity in the country, but inconsistent fault data limit its use in seismic hazard assessment. This study applies the nearest-neighbour (NN) algorithm and graph theory to analyse clustering patterns. Two regions (western and eastern) with higher and lower (respectively) clustering complexities are identified. The results suggest alternative seismic zonation models, which could improve seismic hazard assessment.

Drought and heatwave risks in Europe will worsen due to climate change, especially when they occur together or successively. Our study shows that both events will become more frequent and severe across Europe, with even greater increases under high-emission scenarios. In Germany, drought-related economic losses may double, and heatwave deaths could rise ninefold by 2100. These findings stress the urgent need for climate action to reduce future impacts.

Advanced 3D numerical models can simulate alpine mass movements at the slope scale, but their use in natural hazard mapping remains challenging. We present a tool that converts 3D simulation results into 2D maps, making them more accessible and useful for hazard assessment and mitigation. Applied to an ice avalanche simulated with the Material Point Method, it reveals key features such as slope-normal velocities and flow detachment from terrain, which are often overlooked in simpler models.

When retrieving hydrometeors from reflectivity, there are two methods to allocate hydrometeor types: temperature-based and background hydrometer-dependent schemes. The temperature-based method divides hydrometeor proportions based on the background temperature, while the other scheme calculates average weights of each hydrometeor in various reflectivity intervals from background fields. The blending scheme adaptively combines these methods and is found to improve precipitation forecast accuracy.

This study analyses flood exposure in Rotterdam's unembanked areas from 1970 to 2150, exploring the interplay between rising sea levels, urban development, and flood protection measures. Without measures, flood exposure will increase, especially after 2100. The Maeslant storm surge barrier had the most impact on flood exposure, followed by sea level rise and urban development. Varied exposure levels across neighbourhoods suggest the need for localized adaptation strategies.

There is limited evidence on the potential of disaster risk management (DRM) games. This study explores the potential of serious games for improving DRM. We employed a qualitative approach combining content analysis of serious games with an online survey of experts featuring open-ended questions. For the first time, this paper provides a list of recommended features for a DRM game. The results can be of great help for teachers and game designers to improve DRM.

Debris flow susceptibility was assessed using erosion intensity, connectivity, and erodibility. A Bayesian model integrated precipitation and surface conditions to evaluate debris flow risks. Quantitative metrics elucidated debris flow likelihood across diverse spatiotemporal scales. The model accurately predicted a recent debris flow event, validating its disaster assessment.

Flood preparedness – how societies anticipate and act before floods – remains incomplete and reactive. This review examines preparedness in the context of compound flooding, floods induced by multiple interacting factors. The paper argues that effective preparation goes beyond risk analyses, flood maps, and infrastructures; it requires integrated planning, insights into human behaviour, and governance to enable swift and coordinated actions.

River water can be used to refill depleted underground reserves impacted by climate change and human use. In this study, we assessed water quality in Bavaria's Günz River by analyzing watershed risks, using continuous monitoring, and conducting laboratory tests for pollutants. High flows showed strong dilution of almost all parameters. The results indicated that the river is a suitable source for groundwater recharge.

A unified earthquake catalog for South Korea and its surroundings was developed, containing 63 298 events. Four declustering methods, including Gardner–Knopoff, Reasenberg, Uhrhammer, and Marsan, were compared to identify the mainshocks. The catalog offers a reliable database for seismic hazard assessments and seismotectonic studies. It fills gaps in previous studies, providing an up-to-date catalog for accurate seismic risk assessment and future earthquake forecasting in the region.

As climate change escalates, the Berlin-Brandenburg region faces new challenges. Climate change-induced extreme events are expected to cause new conflicts to emerge and aggravate existing ones. To guide future research, we co-develop a list of key questions on climate and water challenges in the region. Our findings highlight the need for new research approaches. We expect this list to provide a roadmap for actionable knowledge production to address climate and water challenges in the region.

The success of agricultural enterprises is affected by climate variability and other important factors like soil conditions and market prices. We have developed an agricultural drought forecasting system to help drought analysts and policymakers more accurately identify communities that are enduring financial stress. By coupling climate forecasts and agricultural models, we can skillfully predict crop yields and farm profits for the coming seasons, which will support proactive responses.

This study investigated the potential association between risk perception and flood preparedness in Nanjing by designing a questionnaire survey. Participants exhibited moderate perceptions of flood risk but demonstrated higher levels of flood preparedness. Participants relied more on threat appraisal to perceive risk, but this failed to trigger sufficient coping appraisal. Threat appraisal can transform into flood preparedness under the influence of response intention and socio-economic features.

This study presents a dashboard to help decision-makers manage risks in a changing climate. Using interactive visualizations, it simplifies complex choices, even with uncertain information. Tested with 54 users of varying expertise, it enabled accurate responses to 71–80 % of questions. Users valued its scenario exploration and detailed data features. While effective, the guidance and set of visualizations could be extended and the prototype could be adapted for broader applications.