Risk Assessment of 2011 Debris Flow Hazard Area in Yongin City

2015 ◽  
Vol 15 (2) ◽  
pp. 165-178
Author(s):  
Gou-moon Choi ◽  
Seung Woo Lee ◽  
Chan-Young Yune
2015 ◽  
Vol 15 (2) ◽  
pp. 197-203 ◽  
Author(s):  
Kyoung-Nam Kim ◽  
Suk-Woo Kim ◽  
Su-Jin Jang ◽  
Kwang-Youn Lee ◽  
Gi-Beom Seo ◽  
...  

2013 ◽  
Vol 13 (11) ◽  
pp. 2957-2968 ◽  
Author(s):  
H. X. Lan ◽  
L. P. Li ◽  
Y. S. Zhang ◽  
X. Gao ◽  
H. J. Liu

Abstract. The 14 April 2010 Ms = 7.1 Yushu Earthquake (YE) had caused severe damage in the Jiegu township, the residential centre of Yushu Tibetan Autonomous Prefecture, Qinghai Province, China. In view of the fragile geological conditions after YE, risk assessment of secondary geohazards becomes an important concern for the reconstruction. A quantitative methodology was developed to assess the risk of debris flow by taking into account important intensity information. Debris flow scenarios were simulated with respect to rainfall events with 10, 50 and 100 yr returning period, respectively. The possible economic loss and fatalities caused by damage to buildings were assessed both in the settlement area and in the low hazard settlement area regarding the simulated debris flow events. Three modelled building types were adopted, i.e. hollow brick wood (HBW), hollow brick concrete (HBC) and reinforced concrete (RC) buildings. The results suggest that HBC structure achieves a good balance for the cost-benefit relationship compared with HBW and RC structures and thus could be an optimal choice for most of the new residential buildings in the Jiegu township. The low hazard boundary presents significant risk reduction efficiency in the 100 yr returning debris flow event. In addition, the societal risk for the settlement area is unacceptable when the 100 yr returning event occurs but reduces to ALARP (as low as reasonably practicable) level as the low hazard area is considered. Therefore, the low hazard area was highly recommended to be taken into account in the reconstruction. Yet, the societal risk might indeed approach an unacceptable level if one considers that YE has inevitably increased the occurrence frequency of debris flow. The quantitative results should be treated as a perspective for the reconstruction rather than precise numbers of future losses, owing to the complexity of the problem and the deficiency of data.


Author(s):  
Byron Quan Luna ◽  
Jan Blahut ◽  
Mélanie Kappes ◽  
Sami Oguzhan Akbas ◽  
Jean-Philippe Malet ◽  
...  

2015 ◽  
Vol 25 (4) ◽  
pp. 439-447
Author(s):  
Jong Hyun Lee ◽  
Jung Yub Lee ◽  
Sang Won Yoon ◽  
Young Suk Oak ◽  
Jae Jeong Kim ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xinyu Xu ◽  
Mingwu Wang ◽  
Yafeng Li ◽  
Libiao Zhang

Risk assessment of debris flow is a complex problem involving various uncertainty factors. Herein, a novel asymmetric cloud model coupled with connection number was described here to take into account the fuzziness and conversion situation of classification boundary and interval nature of evaluation indicators for risk assessment of debris flow hazard. In the model, according to the classification standard, the interval lengths of each indicator were first specified to determine the digital characteristic of connection cloud at different levels. Then the asymmetric connection clouds in finite intervals were simulated to analyze the certainty degree of measured indicator to each evaluation standard. Next, the integrated certainty degree to each grade was calculated with corresponding indicator weight, and the risk grade of debris flow was determined by the maximum integrated certainty degree. Finally, a case study and comparison with other methods were conducted to confirm the reliability and validity of the proposed model. The result shows that this model overcomes the defect of the conventional cloud model and also converts the infinite interval of indicators distribution into finite interval, which makes the evaluation result more reasonable.


2017 ◽  
Vol 17 (4) ◽  
pp. 131-141
Author(s):  
Ji-Hyeob Ryu ◽  
Sang-Hoon Seo ◽  
Sehee Han ◽  
Suck-Rae Sim

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