We examine the variability of storm surges along the English Channel coasts and their connection with the global atmospheric circulation at the interannual and interdecadal timescales using hybrid approaches combining wavelet techniques and probabilistic generalized extreme value models. Our hypothesis is that the physical mechanisms of the atmospheric circulation change according to the timescales and their connection with the local variability improve the prediction of the extreme surges.

We compare and analyse flood hazard maps from eight global flood models that represent the current state of the global flood modelling community. We apply our comparison to China as a case study, and for the first time, we include industry models, pluvial flooding, and flood protection standards. We find substantial variability between the flood hazard maps in the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods and in expected annual exposed GDP.

The prediction of multiple scenarios of flood hazard in mountain regions is typically based on expensive high-resolution models that simulate the flood propagation using significant computational resources. In this investigation we develop a surrogate model that provides a rapid evaluation of the flood hazard using a statistical approach and precomputed scenarios. This surrogate model is an advanced tool that can be used for early warning systems and to help decision makers and city planners.

Coastal regions are affected frequently by extreme waves resulting from storms, causing human fatalities and economic losses. Using a bispectral analysis based on the wavelet-based bicoherence tool, we present an experimental study of the propagation of large-amplitude focused wave groups in coastal regions. The results are consistent with the spectral broadening demonstrated in previous works using the classic Fourier analysis.

Open check dams are flood protection structures trapping sediment and large wood. Large wood obstructs openings of dams, thus increasing flow levels. If flow levels become higher than the dam crest, the trapped large wood may overtop the structure and be suddenly released downstream, which may also eventually obstruct downstream bridges. This paper is based on experiments on small-scale models. It shows how to compute the increase in flow level and conditions leading to sudden overtopping.

An alluvial Mediterranean river changed its riverine and deltaic landscape. The delta has been heavily retreating (up to 800 m) for more than a century. We focus on the river, channelized in the last 50 years, trying to link its sandy sediment yield to the delta evolution. Sediment availability in the last 30 km of the river channel is deemed responsible for the decrease in the sediment yield to the delta. Sediment supply reduction to the coast jeopardizes the future of the delta and beaches.

Scientists demystify stress changes before mainshocks and utilize the foreshocks as an indicator. We investigate changes in seismicity far from mainshocks by using tens of thousands of M ≥ 2 quakes for 10 years in Taiwan and Japan. The results show that wide areas exhibit increased seismicity occurring more than several times in areas of the fault rupture. The stressed crust triggers resonance at frequencies varying from ~ 5 × 10–4 to ~ 10–3 Hz that is supported by the resonant frequency model.

In this study, model tests were used to analyze the effects of rainfall intensity on the formation of the eroded zone and the occurrence of sinkholes due to groundwater infiltration through pipe defects. The model tests were conducted to simulate the actual site conditions considering the soil used around sewer pipe networks and the sewer pipe landfill standards. The groundwater level was applied to the model tests by setting three hydraulic heads based on heavy-rainfall characteristics.

This paper examines the roles of earth science information (data, knowledge, advice) in land-use decision-making in Christchurch, New Zealand, in response to the 2010–2011 Canterbury earthquake sequence. A detailed timeline of scientific activities and information provisions relative to key decision-making events is provided. We highlight the importance and challenges of the effective provision of science to decision makers in times of crisis.

This paper deals with the evaluation of the risk associated with coastal flooding by combining the tide with extreme storm surges (SSs). In this work, methods for tide and SS combination were compared. Le Havre in France was used as a case study. Overall, the example has shown that the return level estimates using different combinations are quite different. It has also been suggested that the questions of coincidence and dependency are essential for a combined tide and SS hazard analysis.

We investigate the contemporary ground deformation along the RLHR-HZ using Sentinel-1 data and find that the RLHR-HZ runs through two main subsidence areas. A total length of 35 km of the RLSR-HZ is affected by the two subsidence basins. Considering the previous investigation coupled with information on human activities, we conclude that the subsidence is mainly caused by extraction of groundwater and underground mining.

Landslides cause thousands of fatalities and cost billions of dollars of damage worldwide every year, but different inventories of landslide events can have widely diverging completeness. This can lead to spatial biases in our understanding of the impacts. Here we use a globally homogeneous model of landslide hazard and exposure to provide consistent estimates of where landslides are most likely to cause damage to people, roads and other critical infrastructure at 1 km resolution.

Tailings flows result from the breach of tailings dams. These flows contain waste products of the mineral processing operations and can travel substantial distances, causing significant loss of life, environmental damage, and economic costs. This paper establishes a new tailings-flow runout classification system, describes a new database of events that have been mapped in detail using the new system, and examines the applicability of a semi-physical area–volume relationship using the new data.

We describe critically low relative humidity and high wind speeds above which only documented wildfires were seen to occur and where no agricultural fires were documented in southern Canada. We then applied these thresholds to the much larger satellite record from 2002–2018 to quantify regional differences in both the rate of observed burning and the number of days with critical weather conditions to sustain a wildfire in this grassland and agricultural region.

We show how INSPIRE, the European initiative to standardize data across borders, can be used to produce explainable AI-based applications. We do so by producing landslide susceptibility maps for the Veneto region in Italy. EU countries are mandated by law to implement the INSPIRE data framework by 2021, but they are aligning and serving INSPIRE data at a slow pace. Our paper can provide a boost to INSPIRE implementation as it shows the value of standardized data.

Flood risk is an increasing threat to urban communities and their strategical assets worldwide. Non-structural practices, such as emergency management plans, can be effective in order to decrease the flood risk in strongly urbanized areas. Mobile phone data provide reliable estimates of the spatiotemporal variability in people exposed to flooding, thus enhancing the preparedness of stakeholders involved in flood risk management. Further, practical advantages emerge with respect to crowdsourcing.

We show the potential to observe the unconfined internal-motion behaviour of single clasts in landslides using a wireless sensor measuring acceleration and rotation. The probe's dimensions are 10 mm × 55 mm. It measures up to 16 g and 2000° s⁻¹ with a 100 Hz sampling rate. From the data, we derive transport mode, velocity, displacement and 3D trajectories of several probes. Results are verified by high-speed image analysis and laser distance measurements.

This work proposes methods for reducing the computational requirements of hydrological simulations for the estimation of very rare floods that occur on average less than once in 1000 years. These methods enable the analysis of long streamflow time series (here for example 10 000 years) at low computational costs and with modelling uncertainty. They are to be used within continuous simulation frameworks with long input time series and are readily transferable to similar simulation tasks.

We investigate patterns in how avalanche forecasters characterize snow avalanche hazard with avalanche problem types. Decision tree analysis was used to investigate both physical influences based on weather and on snowpack variables and operational practices. The results highlight challenges with developing decision aids based on previous hazard assessments.

We used 100 years of seismicity in Italy to predict the hypothetical tectonic style of future earthquakes, with the purpose of using this information in a new seismic hazard model. To squeeze all possible information out of the available data, we created a chain of criteria to be applied in the input and output selection processes. The result is a list of cases from very clear ones, e.g., extensional tectonics in the central Apennines, to completely random tectonics for future seismic events.

Wave observations have a fundamental uncertainty due to the randomness of the sea state. Such scatter is absent in model data, and we tried two methods to best account for this difference when combining measured and modelled wave heights. The results were used to estimate how rare a 2019 storm in the Bothnian Sea was. Both methods were found to have strengths and weaknesses, but our best estimate was that, in the current climate, such a storm might on average repeat about once a century.

Earthquakes cluster in space highlighting fault structures in the crust. We introduce a method to identify such patterns. The method follows a bottom-up approach that starts from many small clusters and, by repeated mergings, produces a larger, less complex structure. We test the resulting fault network model by investigating its ability to forecast the location of earthquakes that were not used in the study. We envision that our method can contribute to future studies relying on fault patterns.

Often, an abrupt increase in shallow seismicity at volcanoes is seen as an indicator for magmatic intrusions into the upper crust. If no eruption occurs and the seismic activity stops, this is called a failed eruption. Here, we report a failed eruption of Brava, Cabo Verde, in August 2016. We remotely monitored the seismicity of Brava with a seismic array, operating from October 2015 to December 2016. Other episodes with increased seismicity around the island were also observed during the study.