Jian He

The Hong Kong University of Science and Technology | UST · Department of Civil and Environmental Engineering

Real-time information on flooding extent, severity, and duration is necessary for effective metropolitan flood emergency management. Existing pluvial flood analysis methods are unable to simulate real-time regional flooding processes under spatiotemporally varying rainstorms. This paper presents a deep learning-enabled super-resolution hydrodynamic...

Landslides are one of the most destructive hazard processes that cause tremendous loss of lives and damage to the built environment. As a crucial part of disaster risk management, building vulnerability assessment aims to link building damage with landslide hazard intensity and building characteristics in a physically based manner. This thorough re...

An extreme rainstorm can cause thousands of landslides and kill hundreds of people. In the changing climate, fatal rainstorms become more frequent and intense. The current landslide emergency management evaluates hazard intensities but lacks key information on likely consequences. This study presents a novel prompt quantitative risk assessment meth...

Landslide debris will travel certain distances and threaten people and properties along its runout path, highlighting the importance of runout path prediction in landslide risk management. Conventional landslide runout models, either statistical or machine learning-based, only consider the geographic characteristics at the source without fitting th...

In October and November of 2018, the upper reach of the Yangtze River was blocked twice by landslide dams. A large landslide dam on a major river can impound a huge amount of water and trigger catastrophic flooding once it fails, imposing great risk to the downstream communities. Considering the chain of large dams and densely populated cities alon...

A large-scale landslide in a deep valley often travels a long distance. The moving landslide debris impacts into the valley and interacts with the river and the opposite side of the valley. In the landslide movement process, energy, mass and momentum transfers inevitably take place. An in-depth study of energy and mass transfer mechanisms in variou...

Probabilistic modelling of debris flow data provides useful information for quantitative risk assessment, such as exceedance probabilities (EPs) of debris flow quantities. This task can defy many classical statistical models because debris flow data are frequently collected over years or even decades, and the nonuniformity of the nature and the com...

To cope with frequent debris flow hazards, many cascade check dams and diversion channels have been adopted in Wenchuan, Sichuan, China, on the eastern margin of the Tibetan plateau. Yet severe damage to local infrastructure still occurred upon large-scale debris flows, and the most common cascading effect of debris flows, river blockage, is often...

Snow preserves fresh water and impacts regional climate and the environment. Enabled by modern satellite Earth observations, fast and accurate automated snow mapping is now possible. In this study, we developed the Automated Snow Mapper Powered by Machine Learning (AutoSMILE), which is the first machine learning-based open-source system for snow ma...

On 10 October and 3 November 2018, two large landslides occurred at Baige on the Qinghai-Tibet Plateau, and completely blocked the Jinsha River. Accordingly two landslide dams formed and breached sequentially, with the breaching of the 3 Nov. dam generating a flood larger than the 10,000-year return period flood over a river reach of approximately...

Study region Hong Kong, China. Study focus This paper aims to develop a flood analysis model to integrate the effects of multiple flooding triggers (i.e. rainfall, high sea levels and wave overtopping) during powerful tropical cyclones and investigate coastal flood hazards in an urban area at the street scale. The process of wave overtopping is pr...

Urban areas in Hong Kong are often developed on hillside due to the lack of land resources. The densely distributed buildings located on the hillslope are thus threatened by landslide hazards. The Po Shan Road landslide occurred on June 18, 1972 is one of the most notable landslides in Hong Kong. The slip area of the landslide was about 270 m × 60...

On February 7, 2021, a catastrophic landslide occurred in Chamoli, India on the southern hills of the Himalayas (30.37°N, 79.73°E). About 28 × 106 m3 of landslide mass detached from the mountain face, entrained deposits in the valley and riverbed, and generated a huge debris flood along the Dhauliganga River. In this study, the geomorphological and...

Landslide susceptibility assessment is essential for regional landslide risk assessment and mitigation. Most past studies involved cell-based analysis that takes landslide incidents as geo-spatial points. Nevertheless, given that a landslide is a two-dimensional polygon on maps and a three-dimensional object in the real world, an object-wise assess...

Many coastal cities face growing flood risks due to interactions of multiple triggers related to the changing climate such as intense rainstorms, rising sea level, severe storm surges, etc. The complex urban morphology and infrastructural systems have profound effects on flow routing and need to be properly considered in flood modelling. In particu...

Physical building vulnerability to debris flows is defined as the potential damage degree of buildings for a given debris flow intensity. In this paper, the physical characteristics of both debris flow intensity and building response are considered. Uncertainties in building capacity and debris flow intensity are explicitly quantified to evaluate t...

Landslide hazards often occur in succession with multiple hazardous processes. The elements at risk such as buildings are therefore exposed to a multi-hazard environment. Multi-vulnerability assessment is a critical component of multi-hazard risk analysis. In this paper, effect of hazard interactions on the physics of building damage is formulated...

Many cities face high flood risks due to intense rainstorms and dense urban environments. Quantifying the degree and duration of flood impact to urban systems under extreme rainstorms is essential for long-term flood risk management and short-term emergency response. This study aims to develop a novel stress testing framework for evaluating urban s...

The break of large landslide dam will trigger catastrophic flood hazard to the downstream area. To manage the flood risk, multiple mitigation measures are required, such as evacuation and removal of obstacles in the river channel. Design of these mitigation measures relies on the estimation of critical flood parameters, namely, peak discharges and...

Two landslide dams were formed on the upper reach of the Jinsha River on 10 October 2018 and 3 November 2018, respectively. Considering the great threats to the lives and properties in downstream areas, it is important to rapidly simulate the dam breaching and the flood routing for risk management. This paper focuses on the second landslide dam tha...

Ice-soil mixture landslide dams formed frequently in the Tibetan Plateau in response to global warming, which pose great threats to both upstream and downstream areas due to inundation and lake bursting. On 17 October 2018, a large landslide, induced by an ice-avalanche at the Sedongpu Basin of the Yarlung Tsangpo, blocked the main course of the ri...

The Yangtze River is one of the most important rivers in China due to its large basin size, the large population along the river, and the numerous large dams and reservoirs on the river. The Jinsha River, the upper reach of the Yangtze River, was dammed twice recently at Baige, Tibet, one on 10 October 2018 and the other on 3 November 2018 (UTC + 8...

Site characterization is usually carried out based on geotechnical data from site investigation. However, the existence of outliers in geotechnical data might lead to an incorrect characterization result, which necessitate the outlier detection. Site-specific geotechnical data is usually multivariate, sparse and might has a certain trend. This stud...