Dividing landscapes into hillslopes greatly improves predictions of landslide potential across landscapes, but their scaling is often arbitrarily set and can require significant computing power to delineate. Here, we present a new computer program that can efficiently divide landscapes into meaningful slope units scaled to best capture landslide processes. The results of this work will allow an improved understanding of landslide potential and can help reduce the impacts of landslides worldwide.

Landslide risk analysis is a powerful tool because it allows us to identify where physical and economic losses could occur due to a landslide event. The purpose of our work was to provide the first regional-scale analysis of landslide risk for central Asia, and it represents an advanced step in the field of risk analysis for very large areas. Our findings show, per square kilometer, a total risk of about USD 3.9 billion and a mean risk of USD 0.6 million.

We explore how Hurricane Sandy (2012) could flood New York City under different scenarios, including climate change and internal variability. We find that sea level rise can quadruple coastal flood volumes, while changes in Sandy's landfall location can double flood volumes. Our results show the need for diverse scenarios that include climate change and internal variability and for integrating climate information into a modelling framework, offering insights for high-impact event assessments.

Following the destructive Lahaina Fire in Hawaii, our team has modeled the wind and fire spread processes to understand the drivers of this devastating event. The simulation results show that extreme winds with high variability, a fire ignition close to the community, and construction characteristics led to continued fire spread in multiple directions. Our results suggest that available modeling capabilities can provide vital information to guide decision-making during wildfire events.

This paper presents a methodology to estimate the total emergency costs based on modelled damages for earthquakes and floods, together with the demographic and building characteristics of the study area. The methodology has been applied in five countries in central Asia, the first time that these estimates are made available for the study area and are intended to be useful for regional and local stakeholders and decision makers.

This article is aimed at developing a method to quantify the influence of inclement weather on the accessibility of emergency medical services (EMSs) in Beijing, China, and identifying the vulnerable areas that could not get timely EMSs under inclement weather. We found that inclement weather could reduce the accessibility of EMSs by up to 40%. Furthermore, towns with lower baseline EMSs accessibility are more vulnerable when inclement weather occurs.

This paper critically reviews disaster recovery literature from a multi-risk perspective. Identified key challenges encompass the lack of approaches integrating physical reconstruction and socio-economic recovery, the neglect of multi-risk interactions, the limited exploration of recovery from a pre-disaster planning perspective, and the low consideration of disaster recovery as a non-linear process in which communities need change over time.

Our study introduces new earthquake forecasting models for Albania, aiming to map out future seismic hazards. By analysing earthquakes from 1960 to 2006, we have developed models that predict where activity is most likely to occur, highlighting the western coast and southern regions as high-hazard zones. Our validation process confirms these models are effective tools for anticipating seismic events, offering valuable insights for earthquake preparedness and hazard assessment efforts.

Meteotsunami are the result of atmospheric disturbances and can impact coastlines causing injury, loss of life, and damage to assets. This paper introduces a novel intensity index to allow for the quantification of these events at the shoreline. This has the potential to assist in the field of natural hazard assessment. It was trialled in the UK but designed for global applicability and to become a widely accepted standard in coastal planning, meteotsunami forecasting, and early warning systems.

Severe weather such as hail, lightning, and heavy rainfall can be hazardous to humans and property. Dual-polarization weather radars provide crucial information to forecast these events by detecting precipitation types. This study analyses the importance of dual-polarization data for predicting severe weather for 60 min using an existing deep learning model. The results indicate that including these variables improves the accuracy of predicting heavy rainfall and lightning.

Contributions to social capital, risk awareness, and preparedness constitute the parameters to test applications in disaster risk management. We propose an evaluation of four of these: mobile positioning data, social media crowdsourcing, drones, and satellite imaging. The analysis grants the opportunity to investigate how different methods to evaluate surveys' results may influence final preferences. We find that the different assumptions on which these methods rely deliver diverging results.

The Upper Rhine Graben, located in France and Germany, is bordered by north–south-trending faults, posing a potential threat to dense population and infrastructures on the Alsace plain. We build upon previous seismic hazard studies of the graben by exploring uncertainties in greater detail, revisiting a number of assumptions. There is a 99 % probability that a maximum-magnitude earthquake would be below 7.3 if assuming a purely dip-slip mechanism or below 7.6 if assuming a strike-slip one.

Through the development of micro-individual social vulnerability indicators and cluster analysis, this study assessed the level of social vulnerability of 599 residents from 11 communities in the Hongshan District of Wuhan. The findings reveal three levels of social vulnerability: high, medium, and low. Quantitative assessments offer specific comparisons between distinct units, and the results indicate that different types of communities have significant differences in social vulnerability.

This work describes Flood-PROOFS East Africa, an impact-based flood forecasting system for the Greater Horn of Africa. It is based on hydrological simulations, inundation mapping, and estimation of population and assets exposed to upcoming river floods. The system supports duty officers in African institutions in the daily monitoring of hydro-meteorological disasters. A first evaluation shows the system performance for the catastrophic floods in the Nile River basin in summer 2020.

Mozambique is highly exposed to the impact of floods. To reduce flood damage, it is necessary to develop mitigation measures. Hydrological software is a very useful tool for that purpose, since it allows for a precise quantification of flood hazard in different scenarios. We present a methodology to quantify flood hazard in data-scarce regions, using freely available data and software, and we show its potential by analysing the flood event that took place in the Umbeluzi Basin in February 2023.

Climate warming is changing mountain snowpack patterns, leading in some cases to rain-on-snow (ROS) events. Here we analyzed near-present ROS and its sensitivity to climate warming across the Pyrenees. ROS increases during the coldest months of the year but decreases in the warmest months and areas under severe warming due to snow cover depletion. Faster snow ablation is anticipated in the coldest and northern slopes of the range. Relevant implications in mountain ecosystem are anticipated.

The influence of model resolution and settings on the reproduction of heat waves in Germany between 1980–2009 is analyzed. Outputs from a high-resolution model with settings tailored to the target region are compared to those from coarser-resolution models with more general settings. Neither the increased resolution nor the tailored model settings are found to add significant value to the heat wave simulation. The models exhibit a large spread, indicating that the choice of model can be crucial.

For the release of cross-country harmonised hazard and risk models, a communication strategy co-defined by the model developers and communication experts is needed. The strategy should consist of a communication concept, user testing, expert feedback mechanisms, and the establishment of a network with outreach specialists. Here we present our approach for the release of the European Seismic Hazard Model and European Seismic Risk Model and provide practical recommendations for similar efforts.

We improve an existing impact forecasting model for the Philippines by transforming the target variable (percentage of damaged houses) to a fine grid, using only features which are globally available. We show that our two-stage model conserves the performance of the original and even has the potential to introduce savings in anticipatory action resources. Such model generalizability is important in increasing the applicability of such tools around the world.

Ambient heat in European cities will substantially increase under global warming, as projected by three heat metrics calculated from high-resolution climate model simulations. While the heat metrics consistently project high levels of ambient heat for several cities, in other cities the projected heat levels vary considerably across the three heat metrics. Using complementary heat metrics for projections of ambient heat is thus important for assessments of future risks from heat stress.