This study aims to understand the concept of low-flow drought characteristics and the predictive significance of river storage draft rates in managing sustainable water catchment. This study consists of four types of analyses: streamflow trend analysis, low-flow frequency analysis, determination of the minimum storage draft rates and hydrological-drought characteristics. The results are useful for developing measures to maintain flow variability and can be used to develop water policies.

A tailings dam is an earth embankment used to store the waste from mines, known as tailings. In 2019, the Brumadinho tailings dam in Brazil failed, releasing a mudflow which killed ~ 300 people. This paper details the use of an agent-based model to estimate the risk to people downstream of this dam. The agent-based model represents each individual person. The modelling indicated that if a warning had been issued as the dam failed, the number of fatalities could have been reduced.

Droughts are mainly caused by a reduction of precipitation, and they affect both surface and groundwater resources. Drought propagates through the hydrological cycle and may impact vulnerable ecosystems. We investigated drought propagation in the hydrological cycle, focusing on assessing its impact on a groundwater-fed wetland ecosystem in the Doode Bemde wetland in central Belgium. We used a method combining meteorological drought indices, water balance models and groundwater models.

This study investigated one case of a tropical-like cyclone over the Mediterranean Sea under present and future climate conditions with a regional climate model. A pseudo global warming (PGW) technique is employed to simulate the cyclone under future climate, and our simulation showed that the cyclone is moderately strengthened by warmer climate. Other PGW simulations where only ocean and atmosphere are warmed reveal the interesting results that both have counteracting effects on the cyclone.

This paper aims to provide a quantitative evaluation of three remotely sensed fire datasets which have recently emerged as an important resource to improve our understanding of fire regimes. Our findings suggest that remotely sensed fire datasets can be used to proxy variations in fire activity on monthly and annual timescales; however, caution is advised when drawing information from smaller fires (< 100 ha) across the Mediterranean region.

Debris-flow research requires experimental data that are difficult to collect because of the intrinsic characteristics of these hazardous processes. This paper presents debris-flow data recorded in the Moscardo Torrent (Italian Alps) between 1990 and 2019. In this time interval, 30 debris flows were observed. The paper presents data on triggering rainfall, flow velocity, peak discharge, and volume for the monitored hydrographs.

Large volcanic eruptions are rare events; however, they may cause significant economic losses. This work explores a specific type of insurance (parametric insurance) applied to such events. Unlike traditional insurance where payouts occur after often lengthy loss assessments, this type of insurance makes automatic and prompt payments on the basis of the eruption attaining threshold values for objective and easily measurable characteristics (height and direction of the eruption column).

This study aimed to identify how well beach users could spot rip currents in real time at the beach. It was performed in response to the fact that rip currents are the leading cause of drownings on recreational beaches worldwide. We found that only one in five people were able to spot the rip current, meaning the vast majority would be unable to make good decisions about where it is safe to swim at the beach.

The present innovative modeling aims to combine the most realistic simulated strongest gusts driven by tornado-scale vortices within the eyewall and the most realistic complex terrain effects. The present modeling method could be easily extended to other small mountainous islands to improve the understanding of observed past damage and to develop safer urban management and appropriate building standards.

The present study evaluates the impacts of land use and climate change, based on scenarios, on landslide hazards in a Pyrenean valley from the present to 2100. The results demonstrate the influence of land cover on slope stability through the presence and type of forest. Climate change may have a significant impact because of the increase of the soil water content. The results indicate that the occurrence of landslide hazards in the future is expected to increase.

The storyline method is used to quantify the effect of climate change on a particular extreme weather event using a global atmospheric model by simulating the event with and without climate change. We present the method and its successful application for the climate change signals of the European 2003 and the Russian 2010 heatwaves.

This paper draws on the experiences of seven early career scientists, in different sectors and contexts, to explore the improved integration of natural hazard science into broader efforts to reduce the likelihood and impacts of disasters. We include recommendations for natural hazard scientists, to improve education, training, and research design and to strengthen institutional, financial, and policy actions. We hope to provoke discussion and catalyse changes that will help reduce disaster risk.

The choice of residential location is one of the drivers shaping risks in cities. We model likely outcomes of this decision-making process for distinct socioeconomic groups in the city of Leipzig, Germany, using random forests and geostatistical methods. In so doing, we uncover hot spots and cold spots that may indicate spatial patterns and trends in exposure and vulnerabilities of urban population, to shed light on how residential location choice affects these risk components as a process.

Coastal structures subjected to the actions of waves must be redesigned due to rising sea levels. Their design requires an estimate of the long return period of wave height, wave period, storm surge and more specifically their joint exceedance probabilities. We confirm that the best results are obtained by first aggregating the most correlated variables: wave height and wave period. Nevertheless, the choice of method of aggregation is much less important than the choice of the copula.

Forecasts of natural hazards save lives. But the accuracy of forecasts must be evaluated before use. Here we evaluate heavy rainfall advisories over Kenya. We assess their ability to anticipate heavy rainfall and show how well they warned of recent floods which had significant impacts. We find that although they effectively warn of heavy rainfall and flooding, issues such as a lack of spatial detail limit their utility for systematic approaches to preparedness.

How representative are local building insurers' claims to assess winter windstorm risk? In our case study of Zurich, we use a risk model for windstorm building damages and compare three different inputs: insurance claims and historical and probabilistic windstorm datasets. We find that long-term risk is more robustly assessed based on windstorm datasets than on claims data only. Our open-access method allows European building insurers to complement their risk assessment with modelling results.

Comprehensive and sustainable landslide management, including identification of landslide-susceptible areas, requires a lot of organisations and people to collaborate efficiently. In this study, we propose a concept for a system that provides users with a platform to share the location of landslide events for further collaboration in Nepal. The system can be beneficial for specifying potentially risky regions and consequently, the development of risk mitigation strategies at the local level.

Mass movements constitute a risk to property and human life. In this study we use machine learning to automatically detect and classify slope failure events using ground vibrations. We explore the influence of non-ideal though commonly encountered conditions: poor network coverage, small number of events, and low signal-to-noise ratios. Our approach enables us to detect the occurrence of rare events of high interest in a large data set of more than a million windowed seismic signals.

This paper describes the relationship between weather conditions, sea level changes and the rate of the receding seashore and the state of the orchid beech plant community (Baltic Sea coast, Wolin island, Poland). The orchid beech habitat (Cephalanthero rubrae–Fagetum type) on the Wolin island is the only such well known site in the world. It was found that for the functioning of the orchid beech habitat in the 21st century, climate changes are a relatively greater threat than seashore erosion.

Trends of extreme temperature episodes in cities are increasing due to regional climate change in interaction with urban effects. Urban morphologies and thermal properties of the materials used to build them are factors that influence climate variability and are one of the main reasons for the climatic singularity of cities. This paper presents a methodology to evaluate the urban and peri-urban effect on extreme-temperature exposure using land cover and land use maps.

Asset damage caused by tropical cyclones is often computed based on impact functions mapping wind speed to damage. However, a lack of regional impact functions can lead to a substantial bias in tropical cyclone risk estimates. Here, we present regionally calibrated impact functions, as well as global risk estimates. Our results are relevant for researchers, model developers, and practitioners in the context of global risk assessments, climate change adaptation, and physical risk disclosure.

This study proposes a new approach to accessing the economic impact of explosive eruptions on the tourism sector on São Miguel Island, which uses the loss present value method to estimate the benefits generated by accommodation units over 30 years for different scenarios. The results reveal that in a near-total-destruction scenario, the economic loss is ~ EUR 145 million. This method can be adapted to other volcanic regions and also to other geological hazards and economic sectors.

The study provides a comprehensive assessment and zonation of hazard, vulnerability, and risk of storm surge caused by the designed typhoon scenarios in the coastal area of Huizhou. The risk maps can help decision-makers to develop evacuation strategies to minimize civilian casualties. The risk analysis can be utilized to identify risk regions to reduce economic losses. The proposed methodology and procedure can be applied to any coastal city in China for making risk assessments.

The assimilation impact of four observation data sets on forecasts is studied in a mesoscale weather model. The ground-based Global Navigation Satellite System (GNSS) zenithal total delay data set with information on humidity has the largest impact on analyses and forecasts, representing an evenly spread and frequent data set for each analysis time over the model domain. Moreover, the reprocessing of these data also improves the forecast quality, but this impact is not statistically significant.