Understanding spatial patterns in earthquake-induced ground motions is key for assessing the seismic risk of distributed infrastructure systems. To study such patterns, we propose a novel model that accounts for spatial proximity, as well as site and path effects, and estimate its parameters from past earthquake data by explicitly quantifying the inherent uncertainties.

We studied annual maximum sea levels in the Finnish coastal region. Our aim was to better quantify the uncertainty in them compared to previous studies. Using four statistical models, we found out that hierarchical models, which shared information on sea-level extremes across Finnish tide gauges, had lower uncertainty in their results in comparison with tide-gauge-specific fits. These models also suggested that the shape of the distribution for extreme sea levels is similar on the Finnish coast.

Droughts in Thailand are becoming more severe due to climate change. Understanding the link between drought impacts on the ground and drought indicators used in drought monitoring systems can help increase a country's preparedness and resilience to drought. With a focus on agricultural droughts, we derive crop- and region-specific indicator-to-impact links that can form the basis of targeted mitigation actions and an improved drought monitoring and early warning system in Thailand.

Tornadoes represent disruptive and dangerous weather events. The prediction of these small-scale phenomena depends on the resolution of present weather forecast and climatic projections. This work discusses the occurrence of tornadoes in terms of atmospheric variables and provides analytical expressions for their conditional probability. These formulas represent a tool for tornado alert systems and for estimating the future evolution of tornado frequency and intensity in climate projections.

This study performed analysis on typhoon-induced coastal morphodynamics for the Mokpo coast. Wetland vegetation was severely impacted by Typhoon Soulik, with 87.35 % of shoreline transects experiencing seaward migration. This result highlights the fact that sediment resuspension controls the land alteration process over the typhoon period. The land accretion process dominated during the pre- to post-typhoon periods.

We used a novel database of simulated tropical cyclone tracks to explore whether typhoon-induced storm surges present a future flood risk to low-lying coastal communities around the South China Sea. We found that future climate change is likely to change tropical cyclone behaviour to an extent that this increases the severity and frequency of storm surges to Vietnam, southern China, and Thailand. Consequently, coastal flood defences need to be reviewed for resilience against this future hazard.

Hazard maps are fundamental to earthquake risk reduction, but research is missing on how to design them. We review the visualization literature to identify evidence-based criteria for color and classification schemes for hazard maps. We implement these for the German seismic hazard map, focusing on communicating four properties of seismic hazard. Our evaluation finds that the redesigned map successfully communicates seismic hazard in Germany, improving on the baseline map for two key properties.

Snow avalanches are a natural hazard that can cause danger to human lives. This threat can be reduced by accurate prediction of the danger levels. The development of mathematical models based on past data and present conditions can help to improve the accuracy of prediction. This research aims to develop a neural-network-based model for correlating complex relationships between the meteorological variables and the profile variables.

Meteotsunami are globally occurring water waves initiated by atmospheric disturbances. Previous research has suggested that in the UK, meteotsunami are a rare phenomenon and tend to occur in the summer months. This article presents a revised and updated catalogue of 98 meteotsunami that occurred between 1750 and 2022. Results also demonstrate a larger percentage of winter events and a geographical pattern highlighting the hotspot regions that experience these events.

A rapid sequence of cascading events involving thermokarst lake outburst, rock glacier front failure, debris flow development, and river blockage hit an alpine valley in Austria during summer 2019. We analyze the environmental conditions initiating the process chain and identify the rapid evolution of a thermokarst channel network as the main driver. Our results highlight the need to account for permafrost degradation in debris flow hazard assessment studies.

All accessible snow and ice avalanches together with previous scientific research, local knowledge, and existing or previously active adaptation and mitigation solutions were investigated in the high mountain Asia (HMA) region to have a detailed overview of the state of knowledge and identify gaps. A comprehensive avalanche database from 1972–2022 is generated, including 681 individual events. The database provides a basis for the forecasting of avalanche hazards in different parts of HMA.

We analyzed recent trends in heat and cold wave (HW and CW) risk in a European alpine region, defined by a time and spatially explicit framework to quantify hazard, vulnerability, exposure, and risk. We find a statistically significant increase in HW hazard and exposure. A decrease in vulnerability is observed except in the larger cities. HW risk increased in 40 % of the region, especially in highly populated areas. Stagnant CW hazard and declining vulnerability result in reduced CW risk.

We developed a model of fire spread that assumes that fire spreads in all directions at a constant speed and is extinguished at a constant rate. The model was fitted to 1003 fires in Peru between 2001 and 2020 using satellite burned area data from the GlobFire project. We fitted statistical models that predicted the spread and extinguish rates based on weather and land cover variables and found that these variables were good predictors of the spread and extinguish rates.

We developed a cost-effective and user-friendly approach to map shallow landslides using free satellite data. Our methodology involves analysing the pre- and post-event NDVI variation to semi-automatically detect areas potentially affected by shallow landslides (PLs). Additionally, we have created Google Earth Engine scripts to rapidly compute NDVI differences and time series of affected areas. Datasets and codes are stored in an open data repository for improvement by the scientific community.

Debris flows are common hazards in Taiwan, and debris-flow early warning is important for disaster responses. The rainfall thresholds of debris flows are analyzed and determined in terms of rainfall intensity, accumulated rainfall, and rainfall duration, based on case histories in Taiwan. These thresholds are useful for disaster management, and the cases in Taiwan are useful for global debris-flow databases.

We used an integrated model to evaluate the impacts of nature-based solutions (NBSs) on flood mitigation across the Little Pee Dee and Lumber River watershed, the Carolinas, US. This area is strongly affected by climatic disasters, which are expected to increase due to climate change and urbanization, so exploring an NBS approach is crucial for adapting to future alterations. Our research found that NBSs can have visible effects on the reduction in hurricane-driven flooding.

Testing of earthquake forecasts is important for model verification. Forecasts are usually spatially discretized with many equal-sized grid cells, but often few earthquakes are available for evaluation, leading to meaningless tests. Here, we propose solutions to improve the testability of earthquake forecasts and give a minimum ratio between the number of earthquakes and spatial cells for significant tests. We show applications of the proposed technique for synthetic and real case studies.