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This paper addresses how residents can safely access shelters from their buildings. Firstly, we investigated Xiaying Village, a typical community with severe buildings damage at the epicentre of the Ms5.0 magnitude earthquake in Tonghai that occurred on August 13, 2018, and found that the injured residents when escaping resulted from the damage to masonry buildings. Secondly, a probabilistic approach combining response spectrum and allowable maximum acceleration is proposed to estimate the damage risk of masonry buildings with inadequate seismic performance in old communities. Thirdly, three models are proposed to assess the risk of the escape path, which include all scenarios of the escape of residents to shelters. Finally, an accessibility analysis of the paths that residents may choose to escape to the shelter is presented. The results of the community escape case study in the Tonghai earthquake show that the probabilistic approach to estimating the escape risk is feasible, and the number of damaged buildings in the escape path dictates the accessibility of residents to the shelter. The proposed method is important for guiding old community residents to escape when a strong earthquake strikes, and it is an effective way to improve community disaster resilience. [ABSTRACT FROM AUTHOR]

Multivariate storm frequency modeling would help to gain improved understanding of complex storm process, and provide useful information for regulating flooding risk. In this paper, the dependency between magnitudes and directional occurrence dates of storm events was investigated with copula models. Taking account of extreme storms under various return periods, the concurrence risks as well as temporal representations of the recurrence risk were evaluated by the exceedance probability levels. A case study was demonstrated through the selected storms out of a 53-year long daily rainfall time series in the Shenzhen bay area by using the annual maximum precipitation and peak-over-threshold sampling method. Based on multiple univariate probability functions, a mixed distribution was proposed to determine the most suitable marginal distribution of storm magnitudes and directional dates at three spatially separated stations. The goodness-of-fit tests and ordinary least squares criterion of root-mean-square error were then employed to determine the copula model from the Archimedean and Plackett copulas. According to the coincidence exceedance probabilities of 200, 100, 50 and 20 years return periods, results showed an increase in the conjunctive risk of extreme rainfall events for recent 30 years with regards to pair and triple station, implying the significance to further strengthen the regional flooding control measures. Besides, temporal variations of exceedance probabilities at each station revealed an increasingly concentrated risk during wet period and a shift of the risk peak to earlier dates during 1 year, which would indicate the flooding precautions should be prepared in advance. [ABSTRACT FROM AUTHOR]

A modified version of a seismic risk assessment method is presented that generalises original risk analytical processes, constructs interrelationships among hazard variables in pre-assign weight-based formats, and establishes priorities to address potentially vulnerable dams. The concerned parameter values contained in each component are labelled based on adjusted grading standards, respecting the regional difference in hydraulic structure attributes and safety acceptability ranges. The cascade dams in Dadu River, China, are selected to test the applicability of the proposed method. We systematically investigate potential seismic hazards to demonstrate the implications of earthquake on dam safety. The results indicate that the adapted parameter ranges correspond with the physical aspects of the dams and potential social-economic consequences in seismic-prone regions. Correspondingly, the hazard recognition levels accommodate their local near-source earthquake conditions. Moreover, the investigation guides local emergency services with warnings of potential dam damages and ensuing floods when encountering critical earthquake shaking. [ABSTRACT FROM AUTHOR]

Climate and extreme hydrometeorological studies are required to reduce risk and vulnerabilities. This study uses different cumulus and microphysics schemes in Weather Research and Forecasting (WRF) model to simulate heavy rainfall events and Cyclone Sidr in Bangladesh, where many extreme events occur. Results show that WRF can capture the cyclone track, intensity, and landfall position. In addition, regionalization and an ensemble method through Bayesian regression model (BRM) are used to improve WRF rainfall simulations. Although regionalization can improve results of the experiments with different schemes, BRM leads to the best performance. To consider uncertainties and evaluate hazards, a probabilistic framework and proper indices based on distributions are used. Spatiotemporal precipitation distributions are used to develop the flash flood index (FFI) to compare the intensity of heavy rainfall events. Results show a large FFI over the central and southeast divisions that indicates the areas prone to the flash flood hazards and high-level risk. We use standardized precipitation index (SPI) in 6- and 12-month time scales based on monthly precipitation of ACCESS-CM2 in 2015–2100 under two scenarios (SSP-126 and 585) to evaluate long-term precipitation changes and drought/flood tendency. In addition, the probability distributions of the precipitation and wind speed are used in reliability analysis of the infrastructure. Target reliability indices determine the proper design rainfall (105 mm d−1) and wind speed (60 m s−1) that leads to a safe design of infrastructure. This study provides an integrated analysis of extreme hydrometeorological events, which is crucial for sustainable adaptation and mitigation plans. [ABSTRACT FROM AUTHOR]

This study conducts a time-dependent probabilistic tsunami hazard analysis using stochastic rupture sources, which enables the consideration of numerous heterogeneous earthquake slip distributions. Earthquake occurrence modeling is based on temporal renewal and magnitude recurrence models. To account for various combinations of alternative models for temporal occurrence process, earthquake magnitude distribution, and spatial earthquake slip distribution, a logic-tree approach is implemented, facilitating more comprehensive characterization of epistemic uncertainties for the stochastic rupture source approach. To demonstrate the effects of different model components on tsunami hazard curves, a case study for coastal plain areas of Miyagi Prefecture in Japan is set up. The sensitivity analysis clearly indicates that the selection of renewal and magnitude models has paramount influence on the tsunami hazard results. The results also depend on the situations of interest in terms of current time and time-horizon with respect to the recurrence process of the earthquake rupture. In light of significant uncertainties of tsunami hazard and risk due to future mega-thrust subduction events, consideration of epistemic uncertainties is of critical importance. [ABSTRACT FROM AUTHOR]

We propose a stochastic methodology for risk assessment of a large earthquake when a long time has elapsed from the last large seismic event. We state an approximate probability distribution for the occurrence time of the next large earthquake, by knowing that the last large seismic event occurred a long time ago. We prove that, under reasonable conditions, such a distribution is exponential with a rate depending on the asymptotic slope of the cumulative intensity function corresponding to a nonhomogeneous Poisson process. As it is not possible to obtain an empirical cumulative distribution function of the waiting time for the next large earthquake, an estimator of its cumulative distribution function based on existing data is derived. We conduct a simulation study for detecting scenario in which the proposed methodology would perform well. Finally, a real-world data analysis is carried out to illustrate its potential applications, including a homogeneity test for the times between earthquakes. [ABSTRACT FROM AUTHOR]

We created a fault model with a Tohoku-type earthquake fault zone having a random slip distribution and performed stochastic tsunami hazard analysis using a logic tree. When the stochastic tsunami hazard analysis results and the Tohoku earthquake observation results were compared, the observation results of a GPS wave gauge off the southern Iwate coast indicated a return period equivalent to approximately 1,709 years (0.50 fractile), and the observation results of a GPS wave gauge off the shore of Fukushima Prefecture indicated a return period of 600 years (0.50 fractile). Analysis of the influence of the number of slip distribution patterns on the results of the stochastic tsunami hazard analysis showed that the number of slip distribution patterns considered greatly influenced the results of the hazard analysis for a relatively large wave height. When the 90 % confidence interval and coefficient of variation of tsunami wave height were defined as an index for projecting the uncertainty of tsunami wave height, the 90 % confidence interval was typically high in locations where the wave height of each fractile point was high. At a location offshore of the Boso Peninsula of Chiba Prefecture where the coefficient of variation reached the maximum, it was confirmed that variations in maximum wave height due to differences in slip distribution of the fault zone contributed to the coefficient of variation being large. [ABSTRACT FROM AUTHOR]