Risk assessment of debris flow in Yushu seismic area in China: a perspective for the reconstruction

In: Natural hazards and earth system sciences: NHESS, Band 13, Heft 11, S. 2957-2968

Abstract

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.