JOURNAL OF YANGTZE RIVER SCIENTIFIC RESEARCH INSTI ›› 2011, Vol. 28 ›› Issue (7): 32-36.

• HEALTHY CHANGJIANG RIVER • Previous Articles     Next Articles

Research on Risk Probability Model and Calculation Method for River Closure System

HE Chang-hai1 , LIU Yong-yue2   

  1. 1.Experimental Research Center on Hydraulic Model, State Key Laboratory of Water Resources and  Hydropower Engineering Science, Wuhan University, Wuhan 430072 China ; 2. Department of Power Generation,  Heilongjiang Provincial Research Institute of Electric Power Exploration and Design, Harbin 150010 China
  • Online:2011-07-01 Published:2012-11-08

Abstract:  To make scientific decision on river closure for water conservancy and hydropower projects, this paper firstly makes a brief review on the research history of river closure risk. Based on the actual engineering, the random factors of river closure system are identified, and the resulting factors of possible risk events are analyzed. Taking the hydrological, hydraulic and construction uncertainties into consideration, a new mathematical model is proposed and the calculation of risk probability for river closure system is improved. The model uses average velocity, water depth and average dumping intensity at the closure gap axis as risk variables to assess the integrated risk of the river closure system. Furthermore, by comparing the defects and merits of different calculation methods, the Monte-Carlo method of calculating the risk probability based on complete hydraulic calculation is put forward. At last, problems including the correlation of risk variables, dynamic and static risk differentiation, sampling frequency, and sampling error are discussed and a specific numerical example is presented. The calculation results show that the integrated risk of the river closure system varies greatly with the change of designed discharge and is closely correlated with dumping intensity which indicates the organizing ability of the construction.

Key words: river closure system ,    risk probability  ,   Monte-Carlo method ,    construction uncertainty  ,   sampling error

CLC Number: