Failure risk assessment of discharge system of the Hanjiang-to-Weihe River Water Transfer Project

• Published in: Natural hazards (Dordrecht) 2021-09, Vol.108 (3), p.3159-3180
• Main Authors: Lei, Guan-jun, Wang, Wen-chuan, Liang, Yun, Yin, Jun-xian, Wang, Hao
• Format: Article
• Language: English
• Subjects: Bayesian analysis; Civil Engineering; Component reliability; Control systems; Earth and Environmental Science; Earth Sciences; Environmental Management; Failure analysis; Failure rates; Fault tree analysis; Floating; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Hydrogeology; Leakage; Mathematical analysis; Monte Carlo simulation; Natural Hazards; Network reliability; Original Paper; Probability theory; Reservoir storage; Reservoirs; Risk analysis; Risk assessment; Risk factors; Risk management; River water; Rivers; Security; Statistical methods; Theories; Water conveyance; Water discharge; Water storage; Water supply; Water transfer
• ISSN: 0921-030X; 1573-0840
• DOI: 10.1007/s11069-021-04818-2

The Hanjiang-to-Weihe River Water Transfer Project is a systematic water supply project which involves the water supply system, the water storage system and the water conveyance system. The water storage system of the reservoir involves the water retaining system and the discharge system. The function of the discharge system is an important guarantee for the safety of the project. Regarding the Hanjiang-to-Weihe River Water Transfer Project’s discharge system risk control as the goal, on the basis of risk events, the fault tree analysis of the risk causes and Bayesian network theory, a system of Bayesian networks is established. A reliable risk rate calculation method is chosen based on the feature of the risk. The Hanjiang-to-Weihe River Water Transfer Project discharge system failure risk calculation theory system is built based on the Bayesian network inference ability. The engineering of the Sanhekou reservoir drain system is taken as the research object. Based on the Monte Carlo simulation and the method of the reliability derivation, the component failure risk is calculated and the Bayesian network is constructed to compute the risk of system failure rate. The scenario analysis is used to judge the main risk factors that affect the drain system security. If the risk rate of floating debris and leakage increases by 50%, the rate of failure risk of the discharge system would increase by 1.35 × 10 –5 . If the risk rate of the discharge system is reduced to 0, the risk rate of floating objects and leakage should have to be reduced by 1.35 × 10 –5 . If the discharge system fails, the failure risk rate of floating objects and leaks is 1.82 × 10 –1 . It shows that the theory of Bayesian network system can dynamically identify, evaluate, reduce and control the risk of discharge system, which is of guiding significance for risk management of inter-basin water transfer projects.