Typhoon Hato was one of the most damaging natural disaster events in the western Pacific region in 2017. It caused the the worst flooding in Macau since its instrumental records began in 1925. We present a high-resolution survey map recording inundation depths and distances at 278 sites in Macau. We provide a series of inundation maps under different tidal and sea levels. The maps that highlight adaptive strategies are essential in order to keep up with the pace of rising sea level.

Multi-satellite/sensor observations and ground-based measurements combined with the HYSPLIT model were used to analyse the dynamical processes of the origin and transport of a strong dust storm. The optical and microphysical properties of the dust particles were analysed using AERONET measurements. The combined observations revealed comprehensive information about the dynamic transport of dust and the dust-affected regions, and the effect of dust storms on the aerosol properties.

Road development in Nepal promises to improve access to markets, education and healthcare, but not without hazardous consequences. Using GIS maps of monsoon-triggered landslides, we show that rural roads are responsible for doubling the number of landslides in one mountainous district. Engineers are seeking sustainable and affordable eco-solutions to help stabilize these roads in order to prevent further loss of life and property as Nepal approaches this next phase in its development.

This work analyzes the response of a beach under a series of storms using a numerical model, in situ measurements and video imaging. Time recovery after storms is a key issue for local beach managers, who are pressed by tourism stakeholders to nourish the beach after energetic processes in order to reach the quality standards required by beach users.

This study shows that a small deviation of the tropical cyclone (TC) track in the west–east direction (less than 250 km smaller than the average radius of the TC) has a more dominant effect on the extent and distribution of TC damage than TC intensity or size. This suggests that track information should be considered more carefully in assessments of future TC risk.

Coping with avalanche hazard has a long tradition in alpine countries. Hazard mapping has proven to be one of the most effective methods. In this paper we develop a new approach to automatically delineate avalanche release areas and connect them to state-of-the-art numerical avalanche simulations. This enables computer-based hazard indication mapping over large areas such as entire countries. This is of particular interest where hazard maps do not yet exist, such as in developing countries.

This paper focused on the indirect economic losses caused by the Wenchuan earthquake in 2008 and evaluated the progress of restoration and reconstruction based on nighttime light images. Results show that the GDP has a quadratic function relationship with the total nighttime lights under normal conditions, and the economy of the disaster area after the earthquake showed unstable and turbulent development. This research provides a basis for macro-control of earthquake recovery and reconstruction.

At Merapi volcano, lava dome failure may generate pyroclastic flow and threaten populations who live on its flanks. Here, we assessed the potential hazard of the Merapi lava dome by using drone photogrammetry and numerical modeling. Results show a weak structural depression that is associated with high thermal imaging in the southern Merapi lava dome sector. The southern lava dome sector may be further destabilized by typical rainfall at the Merapi summit and produce pyroclastic flow up to 4 km.

We adopted the projected rainfall coupled with the shallow landslide prediction, debris flow simulation, and loss assessment to investigate the impact in Xindian watershed, Taiwan. Upon comparing the worst events in the late 20th and 21st centuries, the economic losses are projected to increase by 27.8 % due to the increasing disasters on slope land caused by climate change. The influence downstream will be mainly in the form of indirect impacts such as a water supply shortage.

Forecasting droughts in Europe 1 month in advance would provide valuable information for decision makers. However, these extreme events are still difficult to predict. In this study, we develop forecasts based on predictors using the geopotential anomalies, generally more predictable than precipitation, derived from the ECMWF model. Results show that this approach outperforms the prediction using precipitation, especially in winter and in northern Europe, where 65 % of droughts are predicted.

The simultaneous occurrence of heavy precipitation and high coastal surge levels increases coastal flood risk. This study analyses the driving mechanisms behind these so-called compound events along the Dutch coast. It provides a first classification of events using the presence of atmospheric rivers (long filaments of high water vapour) and identifies differences in the meteorological conditions leading to events that can be used to setup an early warning system for coastal regions.

This paper proposes an innovative method for optimizing the transmissions of high throughput satellites based on weather forecasts. Such transmissions are particularly sensitive to the presence of hydrometeors, which attenuate the signal. A model to forecast the attenuation based on forecasted rainfall amounts is presented. The valuable contribution of weather forecasts in the system optimization is demonstrated as well as the benefit of using ensemble forecasts over deterministic forecasts.

Flow-like landslides, such as flow slides and debris avalanches, have caused serious infrastructure damage and casualties for centuries. Effective numerical simulation incorporating accurate soil mechanical parameters is essential for predicting post-failure landslide mobility. In this study, smoothed particle hydrodynamics (SPH) incorporating soil ring shear test results were used to forecast the long-runout mobility for a landslide on an unstable slope in China.

It is necessary to analyze the weight of multiple factors in the risk consequence of dam break. When the number of influencing factors exceeds 10, the analysis of its weight will become very difficult. In this paper, the cloud model, an artificial intelligence calculation method, is used to transform the subjective factors into a large number of data for the improved entropy weight method. The result is objective and reasonable, providing a new way of analyzing multi-factor weights.

Megacities are often located along coasts and are greatly exposed to multiple climatic hazards. We take New York City as an example of a coastal megacity highly affected by heat waves, inland flooding and coastal flooding. These hazards overlap spatially or temporally in the city. We develop a multi-hazard risk map to identify hotspots of risk and prioritize adaptation strategies. We find that New York City should prioritize adaptation of coastal areas while considering synergies and trade-offs.

As coastal zones are densely populated, marine flooding represents a hazard threatening populations and facilities (e.g., nuclear plants) along the shore. Using historical data can significantly improve the analysis of extremes. To address this issue, 500 years of historical storms were recovered from archives and used in frequency estimations of marine flooding extremes. The new dataset provides a valuable source of information on storm surges for future characterization of coastal hazards.