In order to quantitatively emphasize the importance of economic ripple effect, this paper further integrates the multi-regional module to develop a new assessment model based on the established dynamic indirect economic loss assessment model, and then quantitatively evaluates the economic ripple effect of Hubei province and China caused by a disaster—“2016.07.06 Wuhan Flood”. The results show that: (1) the economic ripple effect suffered by outside disaster area (2430 million CNY) is 28% of direct economic loss (8740 million CNY), which is 4.4 times of indirect economic loss (550 million CNY) suffered by disaster area Wuhan city. The economic ripple loss of Hubei province (except Wuhan city) and China (except Hubei province) is 1557 million CNY and 873 million CNY, respectively; (2) the manufacturing industry in the outside disaster area suffers the most economic ripple effect, including 652 million CNY in Hubei province (except Wuhan city) and 294 million CNY in China (except Hubei province), accounting for 42% and 34% of the total economic ripple losses, respectively. Other sectors with serious damages successively are agriculture, other services and construction, etc. It is recommended that the government policy makers keep focus on the economic ripple loss coming from other regions, formulate targeted loss reduction measures by recognizing the mechanism of loss generation, and carry out more scientific and comprehensive risk prevention and post-disaster recovery and reconstruction.

Climate changes have contributed to increasing heatwaves all over the world. Wet bulb globe temperature, is a combined measure of temperature and humidity effects on the thermal condition. Thus it is a better indicator of the impact of heatwaves on humans than temperatures alone, and used to define heatwaves in this study. Utilizing simulated daily mean surface temperature and relative humidity from climate models participating in the Coupled Model Inter-comparison Project Phase 5 (CMIP5) and spatially explicit population projection from the Shared Socioeconomic Pathway (SSP), we estimate change in future population exposure to heat waves taking account of both climate and population factors. Results show that during the historical period (1986-2005), geographic variations in exposure are generally a function of population and tend to be the highest in the Indian subcontinent, east and southeast of China. During the 2081-2100 period, exposure remains high in these regions, however substantial portions of the globe are expected to have large increases, particularly across the tropical regions. Significant differences exist in exposure change among different regions. South Asia is projected to have the largest annual mean exposure increase of approaching 300 million person-days, but in North Australia, North Asia and Canada, the increase is less than 1 million person-days. For the vast majority of tropical regions, the combined effect contributes to total change in exposure most prominently. But the climate effect is the most important factor for the middle and high latitudes. At the global level, the combined effect is the most prominent contributor to overall change in exposure.

Based on the 0.5°×0.5° grid daily precipitation datasets and six climate model simulation results of CMIP5, taking the 2010 Zhouqu flash flood and debris flow disaster as the study case, the precipitation return period of this disaster was estimated, and the future precipitation at the same return period was inferred. Then, using the HEC-HMS and FLO-2D models, the mudflow deposition areas and total sediment amount under the future precipitation were simulated, and then the variation of the debris flow hazards was presented. The results show that the precipitation return period in the 2010 Zhouqu debris flow disaster is 1500 years, and the estimated future precipitation for the same return period is 113.7 mm. Under the same fortification, this precipitation will cause the debris flow deposition area in Zhouqu county town to reach 173% of that in 2010 Zhouqu debris flow, and the total amount of sediment will increase by 148%. In addition, the increased area of the debris flow is mainly located in the densely-populated area of Zhouqu county town in 2010. It can be said that the policy of relocating more than half of the residents in Zhouqu county town during the 2010 post-disaster reconstruction, is conducive to preventing the adverse effects of increased hazard of debris flow in the context of climate change.

Studying interplays among different geo-hazard triggers is crucial for mitigating integrated hazard risks and sustaining sustainability in mountain communities. Extreme precipitation and strong seismicity in mountain environment are major triggers for initiation of geo-hazards, such as landslides. Traditional studies on geo-hazards have been extensively carried out by treating them with single triggers, yet compound effects of earthquakes and extreme weathers on geo-hazards initiations have largely been ignored. Regional-scale geo-hazard cases that were jointly caused by earthquake and extreme weather have been reviewed to analyze the interplay between both triggers in initiating geo-hazards. Three major points can be drawn from existing literatures: 1) strong mountain earthquakes can alter mountain environments, which could significantly increase the likelihood of geo-hazards' initiations and magnify its magnitude; 2) this magnifying effect decays with time and may be controlled by climate; 3) extreme weathers have been increasing under climate change and its coalition with strong earthquakes in tectonic mountains will lead to more complicated problems. Due to a lack of observations, joint triggering mechanism of extreme weathers and earthquakes on geo-hazard initiation remains elusive.

In order to clearly understand the extreme climate background at the time of glacial lake outburst flood (GLOF) occurrence in high altitude mountain, we took 27 GLOF events recorded in Tibet since 1960 as samples. Based on the daily temperature data and the daily precipitation data recorded by these meteorological stations in the vicinity of the places where GLOF events occurred, 16 temperature extremes indices and 6 precipitation extremes indices were calculated in these places. By the method of Principal Component Analysis (PCA), a comprehensive extreme temperature index and a comprehensive extreme precipitation index were extracted, and the fluctuation of extreme climate in this period when the disaster occurred were obtained by compared the value of the comprehensive extreme climate index of the previous nine years on annual scale and monthly scale, respectively. The results showed that: (1) More frequent extreme temperature events and precipitation events appeared in the year when GLOF occurred by compared with the previous nine years on annual scale, which was validated in about 67% of GLOF events. (2) Among the 25 GLOF events with monthly outbreak time record, the monthly extreme temperature index and the monthly extreme precipitation index when disaster occurrence were more than 75% of that in the same period of previous nine years, which was validated in about 11 GLOF events. (3) The extreme climate events in several years when GLOF occurred were not very frequent, while both of the extreme temperature index and the extreme precipitation index on monthly scale were obviously higher than the same period of previous nine years, such as Zharicuo GLOF (June 1981), Longjiucuo GLOF (August 2000), Degacuo GLOF (September 2002), Ranzeria GLOF (July 2013) and the nameless lake (July 2015). (4) The monthly extreme temperature index of all GLOF events was higher than that of the same period of the previous nine years, which shows that the short-term extreme temperature events have an important impact on the formation of GLOF in high altitude mountain.