The mapping of convective storms in the area of the transboundary Prut River basin was developed using a 15-year radar dataset (2003–2017). The analysis is based on data sampled in successive 6 min scans of the atmosphere, to detect and track the convective storms. The results highlighted a yearly, monthly, and daily variation of convective activity but also spatial distribution patterns. The study of atmospheric convection is important in assessing the risks associated with extreme weather.

Considering flood risk composed of hazard, exposure, and vulnerability from global to local scales, this paper reviews and presents increasing observed flood losses and projections of flood hazard and losses. We acknowledge existence of multiple driving factors and of considerable uncertainty, in particular with regards to projections for the future. Finally, this paper analyses options for flood risk reduction from a global framework to regional and local scales.

The aim of this work is to advance knowledge on the mechanisms of flood precautionary behavior in an area not adequately addressed. Risk managers may identify gaps in risk communication, advance their understanding of citizens' precautionary behaviors, and adjust their strategies to improve flood resilience. The survey was launched by meteo.gr. This work is part of the study of weather-related hazards and societal impact conducted by IERSD/NOA.

In this work, we present new methods for calculating the mean, standard deviation, median, and modal locations of the boundaries of volcanic hazards. These calculations are based on a new, mathematically rigorous definition of probabilistic hazard maps – a way to map the probabilities of inundation by a given hazard. We apply this analysis to several models of volcanic flows: simple models of viscous flows, complex models of a tabletop granular flow, and a complex model of a volcanic mud flow.

This paper introduces the INSPIRE index, which quantifies the relative seismic risk of reinforced concrete buildings. A rapid visual survey form is proposed, which allows us to (1) calculate the INSPIRE index, (2) calculate a tsunami risk index, and (3) define archetype buildings to be analysed in more detail. The effectiveness of such tools is demonstrated with an application to 85 school buildings in Indonesia, also providing detailed numerical simulations for an archetype building.

It is necessary to do some prevention study of landslide hazard like the early warning and deformation prediction. This research proposes a new strategy to predict displacement of the landslide. Results confirm the accuracy and effectiveness of this method in displacement prediction, which can provide assistance in early risk assessment and landslide forecasting.

We developed a new strategy for real-time early warning of gravity-driven slope failures (such as landslides, rockfalls, glacier break-off, etc.). This method enables us to investigate natural slope stability based on continuous monitoring and interpretation of seismic waves generated by the potential instability. Thanks to a pilot experiment, we detected typical patterns of precursory events prior to slide events, demonstrating the potential of this method for real-word applications.

In coastal environments, extreme water levels driving flooding are often generated by many individual processes like storm surge, streamflow, and tides. To estimate flood drivers along a coastal river, we merge statistical simulations of ocean and river forcing with a hydraulic model to produce water levels. We find both ocean and river forcing are necessary for producing extreme flood levels like the 100-yr event, highlighting the need for considering compound events in flood risk assessments.

This study aims to identify clusters of landslide events within a global database that are triggered by the same rainfall event. Results show that 14 % of all recorded landslide events are actually part of a landslide cluster consisting of at least 10 events. However, in a more regional analysis this number ranges from 30 % for the west coast of North America to 3 % in the Himalayan region. These findings provide an improved understanding for managing landslide mitigations on a larger scale.

This study investigates the use of measured water levels to reduce uncertainty bounds of two-dimensional hydrodynamic model output. Uncertainty assessment is generally not reported in practice due to the lack of best practices and too wide uncertainty bounds. Hence, a novel method to reduce the bounds by constraining the model parameter, mainly roughness, is presented. The operational practitioners as well as researchers benefit from the study in the field of flood risk management.

Portugal is recurrently affected by large wildfire events. We present a statistical model to estimate the probability that the summer burned area exceeds a given threshold. The model allows making outlooks of wildfire potential with up to 1 month in advance of the fire season. When applied to the 39-year period 1980-2018, only 1 severe (one weak) year is not anticipated as potentially severe (weak). The model will assist the fire community when planning prevention and combating fire events.

This paper presents an update of the tsunami catalogue of New Caledonia within the framework of the tsunami hazard assessment project TSUCAL. It provides 25 events for the last decade, leading to 37 tsunamis triggered by earthquakes reported in New Caledonia since 1875. It is a topic of great concern for modelers looking for real case data to set up potential scenarios and for decision makers to constrain hazard management including evacuation processes in the case of a tsunami.

Today, when extreme weather affects an urban area, huge numbers of digital data are spontaneously produced by the population on the Web. These digital trails can provide insight into the relation between climate-related risks and the social perception of these risks. The experiments presented in this paper show that big data exploration techniques can amplify debated issues and actors and explore how social media users behave.

Using Landsat data, the inversion model of soil salt content (SSC) for different seasons was determined in the Kenli District in the Yellow River Delta region of China. The SSC exhibited a gradual increasing trend from the southwest to northeast. The SSC accumulated in spring, decreased in summer, increased in autumn and reached its peak at the the end of winter. The results can provide data for the control of soil salt hazards and utilization of saline–alkali soil.

In this study, we show that both the model horizontal resolution and air–sea flux parameterization can exert a large influence on tropical cyclone intensity simulation but with different impacts on wind structures. We highlight the intensification and contraction of the TC eyewall in response to the reduction of grid spacing. We also suggest that a well-developed eyewall is more conducive to the positive effect of flux formulas on TC development.

Large positive and negative sea level anomalies on the coast of the Mediterranean Sea are produced by cyclones moving along the Mediterranean storm track, which are mostly generated in the western Mediterranean. The wind around the cyclone center is the main cause of sea level anomalies when a shallow water fetch is present. The inverse barometer effect produces a positive anomaly near the cyclone pressure minimum and a negative anomaly at the opposite side of the Mediterranean Sea.

The accuracy of tsunami hazard assessments is highly dependent on the reliability of earthquake source models. In this study, we combine the most updated geological and geophysical data of the Manila subduction zone to propose a series of possible rupture scenarios. These rupture models facilitate an improved understanding of the potential tsunami hazard in the South China Sea. The results highlight the grave consequences faced by the SCS, one of the world's most densely populated coastlines.