Existing dam risk analysis methods are suitable largely for a single reservoir/dam and the influence of uncertainty on risk assessment result is not taken into consideration.To overcome these limitations,the Bayesian network theory which can effectively deal with the uncertainty problem was adopted to study the risk of dam failure in a cascade reservoir group.In combination of statistics data and experts' experiences,extreme flood,upstream dam-break flood and strong earthquake were identified as the key risk factors of dam overtopping. Bayesian risk analysis network models of dam overtopping for a single reservoir and successive dam breaking for two cascade reservoirs under single or compound effects of extreme flood,earthquake and upstream dam-break flood were established and used to analyze dam overtopping risk of Houziyan and Changheba,two successive cascade reservoirs in the Dadu river basin,southwestern China.Results show that the overtopping risk magnitudes of cascaded reservoirs under single and compound effects of risk sources are relatively low,and the magnitude of overtopping risk caused by upstream dam-break flood of Houziyan is the least,which is correlated with characteristics of the upstream Shuangjiangkou reservoir,a control cascade in the basin. Both Houziyan and Changheba reservoirs are identified as weak cascades,and their main leading risk factors are excessive flood and strong earthquake,which can serve as an important support for formulating systemic risk prevention and control measures. Validity and practicability of the proposed model were verified through the case study.The solving process was fast and effective,and the identification of the risk factors correlation and the weak cascade reservoir was intuitive and clear. Using model analyses,risk change of cascade reservoirs under single and compound effects of risk sources can be obtained in time and corresponding risk decisions can be made,which is beneficial to rapid development of follow-up risk management and provides a new research way for risk analysis research in hydraulic and hydropower engineering.
