Risk Assessment of the Bureau Storm Disaster by the Application of Extension Theory in Sichuan

DOI

10.2991/rac-16.2016.53How to use a DOI?

Keywords

Rainstorm disaster; risk assessment; extension theory; Sichuan

Abstract

Based on 1966-2013 daily precipitation data of 141 sites in Sichuan, GIS elevation and social statistics in Sichuan, extension theory and analytic hierarchy process, return period, correlation function and other methods to build the risk evaluation model of the bureau storm of local heavy rain in Sichuan and application analysis. Extension can create process models in selected hazard factors, disaster environment hazard bearing body, disaster prevention and mitigation capability assessment as a factor, the total amount of heavy rain, the average amount of heavy rainfall, the maximum daily amount of rain, topography, slope, population density, places are GDP, the proportion of arable land, per capita GDP, highway mileage rating parameters studied risk assessment criteria as a secondary factor assessment, calculation of AHP rights assessment factor weight coefficient, comprehensive study of the correlation function rainstorm disaster risk rating, indicating the occurrence of heavy rain in Sichuan disaster is the result of various factors interaction. Application results show that the extension theory is an effective risk assessment methodology.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tiangui Xiao
AU  - Fengrong Jing
AU  - Yawen Zhu
AU  - Yujie Fang
AU  - Wan Li
PY  - 2016/11
DA  - 2016/11
TI  - Risk Assessment of the Bureau Storm Disaster by the Application of Extension Theory in Sichuan
BT  - Proceedings of the 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention
PB  - Atlantis Press
SP  - 329
EP  - 334
SN  - 1951-6851
UR  - https://doi.org/10.2991/rac-16.2016.53
DO  - 10.2991/rac-16.2016.53
ID  - Xiao2016/11
ER  -