Flood Risk Analysis for Cascade Dam Systems: A Case Study in the Dadu River Basin in China

Cai Cai,Fan Fan,Zhu Zhu,Peng Peng,Wang Wang

doi:10.3390/w11071365

Abstract

To quantify the flood risks in cascade dam systems, it is critical to analyze the risk factors and potential breaking failure paths. In this study, Bayesian networks (BNs) were applied to create a flood risk analysis model for a cascade dam system. Expert experiment, historical data, and computational formulas were employed to estimate the prior probability and original conditional probability tables (CPTs) in the BN model; sensitivity analysis was used to ensure the original continuous breaking failure path in the system. To avoid the possible misperceptions of the probability of a certain event, Dam Breach Analysis Model (DB-IWHR) 2014 software and the flood regulation method were used to simulate the dam breaking progress. The posteriori continuous breaking failure paths were obtained, and then the original CPTs were refined based on the new evidence. The proposed method was applied to the Bala-Busigou-Shuangjiangkou (BL-BSG-SJK), which is located upstream of the Dadu River basin in China. The results show that three continuous breaking failure paths could be identified in the researched cascade dam system. A new BN model was created to determine the failure probability of the cascade dam system under the three continuous breaking failure paths. This analytical method may also be useful for other similar cases.

Highlights

In China, there are almost 98,000 dams with a combined storage capacity of 9.32 × 109 m3 [1]
As long asModel new evidence is offered in the directed acyclic graph, the information transmitted in the model
We found that the conditional probability tables (CPTs) are updated as flowing, through analyzing

Summary

Introduction

In China, there are almost 98,000 dams with a combined storage capacity of 9.32 × 109 m3 [1]. To achieve goals like flood control, hydroelectric power, irrigation, and navigation, several large-scale cascade dam systems have been constructed in the Yangtze River, Jinsha, Yellow River, Yalong River, Lancang River, Wujiang, Red River, and Dadu River Basin [2]. Among the diverse natural hazards, flooding is the most important risk factor affecting dam breaking. Flooding is the most disastrous natural hazard for the basin, and floods are transferred to the cascade dam system, like the domino effect [6]. Flood risk analysis for cascade dam systems is important. Chen et al developed a risk-based model for real-time flood control operation of dams under emergency and uncertain conditions [7]. Due to the properties of the engineering system, Bayesian networks (BNs) are employed to quantify the complex relational dependencies using Bayes’

Methods

Results

Discussion

Conclusion