Evaluation and Presentation of Dam Failure and Flood Risks

Abstract

Safety studies for existing dams have found that some do not satisfy current estimates of the probable maximum flood (PMF). An event or influence diagram can describe the random factors that contribute to major inflow floods and that determine reservoir operation and possible downstream damages during a flood event. This allows calculation of the probability of dam failure and the distributions of damages and loss of life using combinations of various analytical and Monte Carlo methods. This paper discusses the efficiency of different evaluation methods: event trees, simple Monte Carlo sampling, Latin hypercube sampling, importance sampling, and an analytical/stratified Monte Carlo (A/SMC) method. The analysis suggests that the A/SMC method and importance sampling have great potential for the efficient estimation of dam failure risks. Numerical examples employ the distributions of damages and loss of life to show the character of trade-offs presented by many dam safety decisions and illustrate problems with the partitioned multiobjective risk method (PMRM). The use of partial expected damage and loss of life functions is recommended to show the importance of low-probability/high-consequence events.