Articles | Volume 17, issue 3
https://doi.org/10.5194/nhess-17-367-2017
https://doi.org/10.5194/nhess-17-367-2017
Research article
 | 
09 Mar 2017
Research article |  | 09 Mar 2017

Assessment of the ripple effects and spatial heterogeneity of total losses in the capital of China after a great catastrophic shock

Zhengtao Zhang, Ning Li, Wei Xie, Yu Liu, Jieling Feng, Xi Chen, and Li Liu

Abstract. The total losses caused by natural disasters have spatial heterogeneity due to the different economic development levels inside the disaster-hit areas. This paper uses scenarios of direct economic loss to introduce the sectors' losses caused by the 2008 Wenchuan earthquake (2008 WCE) in Beijing, utilizing the Adaptive Regional Input–Output (ARIO) model and the Inter-regional ripple effect (IRRE) model. The purpose is to assess the ripple effects of indirect economic loss and spatial heterogeneity of both direct and indirect economic loss at the scale of the smallest administrative divisions of China (streets, villages, and towns). The results indicate that the district of Beijing with the most severe indirect economic loss is the Chaoyang District; the finance and insurance industry (15, see Table 1) of Chaowai Street suffers the most in the Chaoyang District, which is 1.46 times that of its direct economic loss. During 2008–2014, the average annual GDP (gross domestic product) growth rate of Beijing was decreased 3.63 % by the catastrophe. Compared with the 8 % of GDP growth rate target, the decreasing GDP growth rate is a significant and noticeable economic impact, and it can be efficiently mitigated by increasing rescue effort and by supporting the industries which are located in the seriously damaged regions.

Download
Short summary
This paper was the first to assess and analyze the ripple effects of indirect economic loss and spatial heterogeneity of both direct and indirect economic loss caused by a hypothetical earthquake, with the same magnitude as the 2008 Wenchuan earthquake, in the disaster-hit area of Beijing at the scale of the smallest administrative divisions in China (streets, villages, and towns). The results will help the government better allocate rescue funds to the regions that may suffer serious damage.
Altmetrics
Final-revised paper
Preprint