Integrated risk assessment of multi-hazards in China

Abstract

Maps of population exposure, vulnerability and risk to natural hazards are useful tools for designing and implementing disaster risk mitigation programs in China. The ranking of provinces by relative risk to natural hazards would provide a metric for prioritizing risk management strategies. Using provinces as our study unit, from the perspectives of hazard exposure, susceptibility, coping capacity and adaptive capacity, this study first constructed China's disaster risk index for five types of major natural hazards: earthquakes, floods, droughts, low temperatures/snow and gale/hail. Then, the relative risk level at the provincial scale in China was assessed. Finally, the hotspots with the highest hazard exposure, vulnerability and risk were identified. The results showed that high exposure was a significant risk driver in China, whereas high vulnerability, especially social vulnerability, amplified the risk levels. Similar to the population exposure to disasters, the relative risk levels in the southwestern, central and northeastern regions of China were significantly higher than those in the eastern, northern and western regions. The highrisk regions or hotspots of multi-hazards were concentrated in southern China (less-developed regions), while the low-risk regions were mainly distributed in the eastern coastal areas (well-developed regions). Furthermore, a nonlinear relationship existed between the disaster risk level and poverty incidence as well as per capita GDP, demonstrating that 123Nat Hazards (2015) 78:257-280 DOI 10.1007/s11069-015-1713 disaster losses in middle-income areas are likely to increase if economic policies are not modified to account for the rising disaster risk. These findings further indicated that research on disaster risk should focus not only on hazards and exposure but also on the vulnerability to natural disasters. Thus, reducing vulnerability and population exposure to natural hazards would be an effective measure in mitigating the disaster risk at hotspots in China.

Major Natural Disasters in China, 1985–2014: Occurrence and Damages

“…China is one of the countries that suffer from frequent disasters because of the vast territory, various climatic zones, complex geographical environment, and fragile ecological conditions [7]. During the past three decades, China has experienced great changes in its population size, development patterns, economic conditions, and socio-economic status.…”

GIS-Based Risk Assessment of Hail Disasters Affecting Cotton and Its Spatiotemporal Evolution in China

“…The exposure as attributed to hazard-affected bodies has long been recognized as an important element of risk that influences the risk assessment result directly [62,63]. For example, Zhou et al [74] found that high exposure was a significant risk driver. The exposure analysis is mainly to determine the number of hazard-affected bodies and their spatiotemporal variation [76].…”

“…Most previous studies assessed the risk of hail disasters using three indices, which are sensitivity of the hazard-forming environment (sensitivity, usually regarded as a aspect of vulnerability [74]), hail hazard index (Hazard) and vulnerability of the hail-affected body (vulnerability) [69][70][71][72][73], and then assigned respective weights to sensitivity, hazard and vulnerability respectively as 0. [66].…”

“…For revealing the regional differentiation of hazard risk, relative risk is widely used because the data, which is limited by availability and quality, is inadequate for understanding the absolute level of risk [74]. However, even limited data is adequate for identifying the areas that are at relatively higher single-or multiple-hazard risk [63].…”

Construction of an integrated social vulnerability index in urban areas prone to flash flooding

“…It is therefore essential to carry out a social vulnerability analysis from a holistic point of view. It is important not only to identify which socio-economic and demographic characteristics increase population sensitivity to flash flood damage but also to know which features increase a population's capacity to resist, cope with and recover from its impact (Cutter et al, 2010;Frazier et al, 2014;Zhou et al, 2015), as demonstrated here. This would enable local competent authorities to plan and implement specific strategies to reduce vulnerability and strengthen resilience, in addition to developing specific mitigation measures to reduce flood risks (Frazier et al, 2014;Nelson et al, 2015;Hummell et al, 2016).…”