Geological disasters are a great threat to people's lives and property. At present, it is difficult to evaluate quantitatively the cascading effects of regional geological disasters, and the development of new methods for such evaluation is much needed. In this study, the authors have developed a joint procedure that couples the Newmark model and the RockFall Analyst model based on a GIS platform in order to identify the impact of seismic landslides on roads. The new method effectively combines two processes-seismic landslide occurrence probability analysis and mass movement trajectory simulation. The permanent displacement derived from the Newmark model is used to identify potential source areas of landslides. Based on the RockFall Analyst model, the possible impact of mass movement on the roads can be simulated. To verify the reliability of the method, the landslides induced by the 2017 Jiuzhaigou Earthquake were taken as a case study. The results suggest that about 21.37% of the study area is at high risk of seismic landslides, and approximately 3.95 km of road sections are at extremely high risk of large landslides. The simulated area is consistent with the distribution of disasters revealed by post-earthquake remote sensing image interpretation and field investigation in existing studies. This indicates that the procedure, which joins the Newmark and RockFall models, has a high reliability for risk identification and can be applied to seismic landslide risk assessment and prediction in similar areas.
Driven by global climate change, sea-level rise would exacerbate the hazard of extreme water level as a disaster-inducing factor. Based on Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5, this study explored the inundation risk of extreme water levels under climate change and Rongcheng was a case study. Pearson Type III (P-III) distribution was used for refitting recurrence periods of extreme water level. Expected losses exposed to extreme water levels were assessed through inundated area and depth per-unit loss values and vulnerability curves of land-use types. Results indicated that sea-level rise significantly shortened recurrence period in 2050 and 2100, which suggested a higher frequency of extreme water level in future. A large increase in expected direct losses would reach an average of 60% with a 0.82-m sea-level rise (under RCP 8.5) in 2100. Moreover, affected population and gross domestic product would grow 4.95% to 13.87% and 3.66% to 10.95% in 2050, respectively, while the increment in 2100 would be twice. Residential land and farmland were demonstrated as at greater inundation risk because of higher exposure and losses. Consequently, the intensifying hazard and the increase in possible losses suggested that sea-level rise would exacerbate future inundation risk in coastal region.
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