We evaluate the skill of a regional climate model, HARMONIE-Climate, to capture the present-day characteristics of heavy precipitation in the Nordic region and investigate the added value provided by a convection-permitting model version. The higher model resolution improves the representation of hourly heavy- and extreme-precipitation events and their diurnal cycle. The results indicate the benefits of convection-permitting models for constructing climate change projections over the region.

We investigate the importance of morphodynamics on flooding estimation during storms with sea level rise conditions on a microtidal beach. XBeach and SWAN were the numerical models used to test several case studies. The results indicate that numerical modeling of flooding should be approached by considering morphodynamics; ignoring them can underestimate flooding by ~ 15 %. Moreover, beach erosion and flooding are intensified by sea level rise and high tides in ~ 69 % and ~ 65 %, respectively.

This article reviews current scientific literature in order to define vulnerability in the context of coastal Bangladesh facing cyclonic flooding. A new metric, called the socio-spatial vulnerability index, is defined as a function of both the probability of the cyclonic flood hazard and the sensitivity of delta inhabitants. The main result shows that three very densely populated districts, located in the Ganges delta tidal floodplain, are highly vulnerable to cyclonic flooding.

Rapid detection of landslides is critical for emergency response and disaster mitigation. Here we develop a global landslide detection tool in Google Earth Engine that uses satellite radar data to measure changes in the ground surface properties. We find that we can detect areas with high landslide density within days of a triggering event. Our approach allows the broader hazard community to utilize these state-of-the-art data for improved situational awareness of landslide hazards.

Groundwater-induced flooding, a rare phenomenon that is increasing in low-elevation coastal cities due to higher water tables, is often neglected in flood risk mapping due to its sporadic frequency and considerably lower severity with respect to other flood hazards. A loosely coupled flood model is used to simulate the interplay between surface and subsurface flooding mechanisms simultaneously. This work opens new horizons on the development of compound flood models from a holistic perspective.

Bridges are critical infrastructure components of transport networks. A large number of these critical assets cross or are adjacent to waterways and are therefore exposed to the potentially devastating impact of floods. This paper discusses a series of issues and areas where improvements in research and practice are required in the context of risk assessment and management of bridges exposed to flood hazard, with the ultimate goal of guiding future efforts in improving bridge flood resilience.

We analysed the correlation of sea level and wind waves at a coastal location in the Gulf of Finland using tide gauge data, wave measurements, and wave simulations. The correlation was positive for southwesterly winds and negative for northeasterly winds. Probabilities of high total water levels (sea level + wave crest) are underestimated if sea level and waves are considered independent. Suitably chosen copula functions can account for the dependence.

We present the database of Historical Impacts of Floods in the Arve Valley (HIFAVa). It reports flood occurrences and impacts (1850–2015) in a French Alpine catchment. Our results show an increasing occurrence of impacts from 1920 onwards, which is more likely related to indirect source effects and/or increasing exposure rather than hydrological changes. The analysis reveals that small mountain streams caused more impacts (67 %) than the main river.

The air pressure created by a tsunami causes a depression in the electron density in the ionosphere. The depression is measured at sparsely distributed, moving GPS satellite locations. We provide an estimate of the volume of the depression. When applied to the 2011 Tohoku-Oki earthquake in Japan, our method can warn of a tsunami event within 15 min of the earthquake, even when using only 5 % of the data. Thus satellite-based warnings could be implemented across the world with our approach.

Snow droughts, or below-average snowpack, can result from either dry conditions and/or rainfall instead of snowfall. Monitoring snow drought through time and across space is important to evaluate when snow drought onset occurred, its duration, spatial extent, and severity as well as what conditions created it or led to its termination. We present visualization techniques, including a web-based snow-drought-tracking tool, to evaluate snow droughts and assess their impacts in the western US.

The majority of past research used hypothesized landslides to simulate tsunamis, but they were still unable to properly explain the observed data. In this study, submarine landslides were simulated by using a slope-failure-theory-based numerical model for the first time. The findings were verified with post-event field observational data. They indicated the potential presence of submarine landslide sources in the southern part of the bay and were consistent with the observational tsunamis.

Beachgoers at unpatrolled Australian beaches were surveyed to gain an understanding of their demographics, beach safety knowledge, and behaviour. Most visited unpatrolled beaches out of convenience and because they wanted to visit a quiet location. Despite being infrequent beachgoers, with poor swimming and hazard identification skills, most intended to enter the water. Authorities should go beyond the swim between the flags safety message, as people will always swim at unpatrolled beaches.

Due to its geography and climate, densely populated Switzerland is often affected by water-related hazards such as surface runoff, floods, debris flows, landslides, rockfalls and avalanches. Almost every part of Switzerland is exposed to natural hazards, and anyone can be affected.

Mesoscale simulation provides a general approach that could be implemented to fulfill the purpose of planning and has relatively low requirements for computation time and data while still providing reasonable accuracy. The method is generally applicable to all coastal cities around the world for examining the effect of future climate change on typhoon-generated storm surge even where historical observed data are inadequate or not available.

This work addresses the problem of the ground motion estimation over large areas as an important tool for seismic-risk reduction policies. In detail, the near-real-time estimation of ground motion is a key issue for emergency system management. Starting from this consideration, the present work proposes the application of a machine learning approach to produce ground motion maps, using nine input proxies. Such proxies consider seismological, geophysical, and morphological parameters.

We studied the cumulative impact of future development and climate change scenarios on discharge and floods in the Cambodian Mekong floodplain. We found that hydropower impacts dominate, acting in opposition to climate change impacts to drastically increase dry season flows and reduce wet season flows even when considering the higher RCP8.5 level. The consequent reduction in flood extent and duration may reduce regional flood risk but may also have negative impacts on floodplain productivity.

To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.

To develop drought assessment and early warning systems, it is necessary to explore the characteristics of drought and its propagation process. In this article, a generalized and efficient drought research framework is studied and verified. It includes the evaluation of the spatiotemporal evolution, the construction of the return period calculation model, and the quantitative analysis of the meteorological trigger conditions of drought based on an improved Bayesian network model.

This study investigates how forests affect the behaviour of snow avalanches through the evaluation of the amount of snow stopped by the trees and the analysis of energy dissipation mechanisms. Different avalanche features and tree configurations have been examined, leading to the proposal of a unified law for the detrained snow mass. Outcomes from this study can be directly implemented in operational models for avalanche risk assessment and contribute to improved forest management strategy.

The monitoring of ash dispersion in the atmosphere is an important task for satellite remote sensing since ash represents a threat to air traffic. We present an AI-based method that retrieves the spatial extension and properties of volcanic ash clouds with high temporal resolution during day and night by means of geostationary satellite measurements. This algorithm, trained on realistic observations simulated with a radiative transfer model, runs operationally at the German Weather Service.

A neural network model based on publicly available data was developed to forecast the number of housing units for each of 1000 counties in the southeastern United States in each of the next 20 years. The estimated number of housing units is almost always (97 % of the time) less than 1 percentage point different than the observed number, which are predictive errors acceptable for most practical purposes. The housing unit projections can help quantify changes in future expected hurricane impacts.

Tsunami waveforms contain the features of its source, propagation path, and local topography. On 4 March 2021, two tsunamis were generated by earthquakes in the Kermadec Islands, New Zealand, within 2 h. This rare case gives us a valuable opportunity to study the characteristics of two tsunamis. We analyzed the records of two tsunamis at tide gauges with spectral analysis tools. It is found that two tsunamis superpose during the few hours after the arrival of the second tsunami.

Evacuation planning and management represent a key aspect of volcanic crises because they can increase people's protection as well as minimize the potential impacts on the economy, properties and infrastructure of the affected area. We present a simulation tool that assesses the effectiveness of different evacuation scenarios as well as a model to assess the economic impact of evacuation as a function of evacuation duration and starting period using the island of Vulcano (Italy) as a case study.

We comparatively evaluate the predictive performance of traditional and new approaches to estimate the probability distributions of extreme coastal water levels. The metastatistical approach maximizes the use of observational information and provides reliable estimates of high quantiles with respect to traditional methods. Leveraging the increased estimation accuracy afforded by this approach, we investigate future changes in the frequency of extreme total water levels.

Understanding where landslides occur in mountainous areas is critical to support hazard analysis as well as understand landscape evolution. In this study, we present a large compilation of inventories of landslides triggered by rainfall, including several that are described here for the first time. We analyze the topographic characteristics of the landslides, finding consistent relationships for landslide source and deposition areas, despite differences in the inventories' locations.