# A Modeling of Human Reliability Analysis on Dam Failure Caused by Extreme Weather
## 5 Conclusions  
This study introduces human reliability analysis into dam risk assessment, focusing on accidents associated with dam failure pathways under extreme weather conditions. The models obtained from the discussion are generic and are not set to a specific reservoir. The database analysis is based on typical domestic and international historical dam failure accidents and is somewhat generalized. Therefore, this work can shed light on the human factors that need to be taken care of in extreme weather and provide assistance in decision making for risk analysis and management. The main findings are as follows:  
1. The paper firstly proposes a HRA analysis framework for dams incorporating Bayesian networks in the premise of existing methods from other domains, including four parts: familiarization, qualitative analysis, quantitative analysis and incorporation. The research methodology and process were systematically defined. Qualitative and quantitative analyses of human factors were conducted for the dam failure accidents.
2. By studying the path of human errors in the operation process of the dam failure accident, a cognitive model of the operator is proposed, which divides human actions into four processes, namely, \"monitoring and awareness-state diagnosis-plan formulation-operation execution\". The human behavior model at each stage was analyzed and combined with the node failure model to obtain the performance shaping factors, or PSFs, in the dam failure incidents. PSFs are an important characterization of human influences, and their successful combination contributes greatly to the improvement of human reliability.
3. Using Bayesian networks to characterize the resulting PSFs and the interdependencies between each other and using entropy reduction information for sensitivity analysis. The results show that the operator directly affects human reliability and is the subject of the accident. In contrast, its deep root cause is the ineffectiveness of the management organization, and the system.  
The model proposed in this study mainly accomplishes the conditional probabilities table, or CPT, using expert judgment methods. Due to the lack of data records for many human error accidents and the subjective nature of the expert judgment, the required precision in Bayesian probability calculations cannot be accomplished with a certain degree of uncertainty. Therefore, expert opinion can be combined with historical data by introducing fuzzy reasoning to improve the model. Furthermore, in Bayesian networks, due to the lack of relevant data, when the interpolation principle is used to calculate node dependencies, it is assumed that all parent nodes have the same weight value, which should be improved by introducing the relevant records in the dam failure database and using the assignment method to judge the weights of each node. Organizational factors are an essential part of human reliability analysis as well as a difficult issue that requires deeper consideration in future research.  
[PERSON] proposed methodology, ran the software and wrote the original draft preparation. [PERSON] conceived, reviewed and edited this paper, and administrated the project. [PERSON] and P.J. validated. [PERSON] conceived and supervised. [PERSON] investigated and acquired funding. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D Program of China (2022 YFC3005402), Central Public-Interest Scientific Institution Basal Research Fund (Y722004, Y723001).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
The authors declare no conflict of interest.