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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 13, issue 2
Nat. Hazards Earth Syst. Sci., 13, 439–454, 2013
https://doi.org/10.5194/nhess-13-439-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Nat. Hazards Earth Syst. Sci., 13, 439–454, 2013
https://doi.org/10.5194/nhess-13-439-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 18 Feb 2013

Research article | 18 Feb 2013

Dynamic decision making for dam-break emergency management – Part 2: Application to Tangjiashan landslide dam failure

M. Peng1,2 and L. M. Zhang1 M. Peng and L. M. Zhang
  • 1Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Hong Kong
  • 2Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Department of Geotechnical Engineering, Tongji University, Shanghai, China

Abstract. Tangjiashan landslide dam, which was triggered by the Ms = 8.0 Wenchuan earthquake in 2008 in China, threatened 1.2 million people downstream of the dam. All people in Beichuan Town 3.5 km downstream of the dam and 197 thousand people in Mianyang City 85 km downstream of the dam were evacuated 10 days before the breaching of the dam. Making such an important decision under uncertainty was difficult. This paper applied a dynamic decision-making framework for dam-break emergency management (DYDEM) to help rational decision in the emergency management of the Tangjiashan landslide dam. Three stages are identified with different levels of hydrological, geological and social-economic information along the timeline of the landslide dam failure event. The probability of dam failure is taken as a time series. The dam breaching parameters are predicted with a set of empirical models in stage 1 when no soil property information is known, and a physical model in stages 2 and 3 when knowledge of soil properties has been obtained. The flood routing downstream of the dam in these three stages is analyzed to evaluate the population at risk (PAR). The flood consequences, including evacuation costs, flood damage and monetized loss of life, are evaluated as functions of warning time using a human risk analysis model based on Bayesian networks. Finally, dynamic decision analysis is conducted to find the optimal time to evacuate the population at risk with minimum total loss in each of these three stages.

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