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The dynamic effect is a very important issue widely debated by scholars when studying the genetic and disaster-causing mechanisms of earthquake-triggered landslides. First, the dynamic effect mechanism and phenomena of earthquake-triggered landslides were summarized in this paper. Then, the primary types of dynamic effects were further used to interpret the Mogangling landslide in Moxi Town of Luding County, China. A field investigation, remote sensing, numerical calculation and theoretical analysis were carried out to illustrate the failure mechanism of slope rock masses affected by earthquakes. The interaction between seismic waves and slope rock masses and the induced dynamic effect of slope rock masses were primarily accounted for in the analysis. The slope topography, rock mass weathering and unloading characteristics, river erosion, regional seismogenic structure, and rock mass structure characteristics were also discussed. The results showed that the formation of the Mogangling landslide was mainly related to the high amplification effect of seismic acceleration and back slope effects, interface dynamic stress effects, and double-sided slope effects of seismic waves caused by the catastrophic Ms 7.75 Moxi Earthquake in 1786. The principles for the site and route selection of large-scale infrastructure in the planning stage and the scientific prevention of seismic geological disasters were proposed on the basis of the dynamic effect of earthquake-induced landslides. [ABSTRACT FROM AUTHOR]

Based on the results of the seismic hazard survey in Yunnan Province, four exceedance probabilities of peak ground acceleration were converted into earthquake magnitudes using the empirical relationship between epicentral intensity and magnitude. By using logistic regression, earthquake magnitude, source depth, cover layer thickness, and fault type were used as independent variables to calculate the probability of co-seismic displacement for different earthquake magnitudes. Using the magnitude-displacement empirical model in the southwestern region of China, horizontal and vertical displacements were obtained with a 95 % confidence level. The results show that all Holocene faults have the ability to produce surface displacement, but from the perspective of probabilistic hazard, the probability of surface rupture in the short term is low, while the probability of surface rupture for each fault significantly increases over a long time scale. Buildings with different service lives should adopt different avoidance strategies, and buildings with shorter service lives (<50a) can consider not avoiding active faults. [ABSTRACT FROM AUTHOR]

Runoff prediction has a pivotal role in the flood warning system. For mountainous small-sized watersheds, establishing a reliable and efficient model to forecast flood is multifarious and disorderly work. The ensemble framework for flash flood forecasting (EF5) provides a new opportunity to model simply and practically. However, the EF5 has not successfully verified its feasibility in mountainous small-sized basins and without satellite rainfall products. This paper used the framework to structure a flood forecast model without any satellite rainfall support for a small watershed in China where flash floods occur frequently. The evaluation indicated that the EF5 model performs well in flood prediction cases, with over 0.9 Pearson's linear correlation coefficient (PCC) values and over 0.85 Nash–Sutcliffe coefficient of efficiency (NSE) values during the validation. In addition, statistical results revealed that the EF5 model can maintain a PCC of more than 0.9, NSE of more than 0.7, and flood peak bias (FPB) of more than -0.2 when the forecast lead time exceeds 3 h. Numerous indicators and plots proved the excellent effect of the model forecasting. Considering the convenience and validity of this framework, the research and verification of the EF5 model in the mountainous small-sized basin are of significance to flood prediction. [ABSTRACT FROM AUTHOR]

Meteorological disasters frequently occur in China and around the world. These natural hazards can cause huge economic losses and threaten the personal safety of citizens. The public's willingness to engage with disaster relief efforts and the degree of participation is critical to reduce the impact of such disasters. This study conducted a survey with 62,903 respondents from China. The study utilized statistical analysis and correlation analysis in order to understand the differences and similarities of the public's willingness to take part in disaster relief across gender and age. The study found that: (1) the public's awareness of insurance and willingness to make donations during climate disasters is low, and that more than half of the public are only willing to insure for very less money; (2) although the public has very high enthusiasm to participate in disaster relief, they are less willing to learn the basic skills of reducing disasters and for participating in training for disaster reduction as volunteers. This was especially the case for elderly citizens and females; (3) the willingness of the public to prevent and reduce disasters is high, and this was the case across various gender and age groups. Finally, the study puts forward several measures to improve the uptake of disaster relief and disaster prevention among citizens. [ABSTRACT FROM AUTHOR]

Typhoons have inflicted significant damage and loss of life to China, a large number of typhoon–rainstorm–debris flow–tunnel accidents occur in the southeastern coastal areas each year. Considering the disaster prevention and mitigation decision-making of disaster accidents in coastal areas and the reduction of regional economic losses, this Express Letter presents some typical accident scenes and rescue measures in recent years and analyses the hazard mechanism from three aspects. On this basis, we propose some suggestions such as the monitoring and early-warning system, which can provide a few references for reducing disaster losses and improving disaster treatments. [ABSTRACT FROM AUTHOR]

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Recently, global climate change has led to a high incidence of extreme weather and natural disasters. How to reduce its impact has become an important topic. However, the studies that both consider the disaster's real-time geographic information and environmental factors in severe rainstorms are still not enough. Volunteered geographic information (VGI) data that was generated during disasters offered possibilities for improving the emergency management abilities of decision-makers and the disaster self-rescue abilities of citizens. Through the case study of the extreme rainstorm disaster in Zhengzhou, China, in July 2021, this paper used machine learning to study VGI issued by residents. The vulnerable people and their demands were identified based on the SOS messages. The importance of various indicators was analyzed by combining open data from socio-economic and built-up environment elements. Potential safe areas with shelter resources in five administrative districts in the disaster-prone central area of Zhengzhou were identified based on these data. This study found that VGI can be a reliable data source for future disaster research. The characteristics of rainstorm hazards were concluded from the perspective of affected people and environmental indicators. The policy recommendations for disaster prevention in the context of public participation were also proposed.

Rural areas are vulnerable to natural disasters and tend to suffer severe losses. An EF4 tornado occurred in Funing on 23 June 2016, killing 99 people, injuring at least 846 people, and destroying more than 2000 houses. Using a multinomial logistic regression model, this study explored the influencing factors between housing damage and variables of building conditions, tornado intensity, and village environmental factors. The results show that 2-story houses and masonry houses were more likely to be slightly damaged or be in a dangerous state. Furthermore, the building area was positively related to houses in two categories: slight damage (SD) and dangerous and requiring immediate repair (DR), indicating that the larger or taller the house, the more severe the damage. In terms of tornado intensity, houses classified as SD were more likely to be hit by EF4 tornados than by EF3 tornados, and houses were damaged more by EF1 or EF2 tornados. This finding demonstrates that the level of housing damage was not strongly correlated with the tornado intensity. Slightly damaged houses exhibited the highest correlation with environmental factors. The proportion of slightly damaged houses was positively correlated with the water area in the village, unlike the proportion of houses in the DR and unable to be repaired (UR) categories. Moreover, the larger the water area of a village, the less housing damage it suffered. These findings provide new insights into minimizing housing damage in wind disasters to improve disaster prevention planning in rural areas.