This paper presents an improved Bayesian Model for evaluating the likelihood and consequences of dam failure. It is based on a comprehensive state-of-the-art review of risk assessment associated with dam breaks, with a particular emphasis on the application of Bayesian Models. The study delves into the most recent developments in the field, investigating the utilization of Bayesian Models, while focusing on two distinct dam types: tailing dams and water dams. Through an extensive survey of over 50 recent articles, the review systematically examines the parameters considered and the effectiveness of Bayesian Models in the context of dam break risk assessment. The paper seeks to provide insights into the advantages and limitations of Bayesian approaches, shedding light on their practical utility in enhancing our understanding of dam failure risks. Furthermore, the study proposes two new Bayesian Models – one applicable to tailing dams, and the other to water dams. The study also identifies gaps in the current body of knowledge and delineates potential avenues for future research. By critically assessing the efficiency of Bayesian Models, this work offers valuable guidance to researchers, engineers, and stakeholders involved in dam safety, disaster preparedness, and risk mitigation. The ultimate goal is to advance our ability to safeguard lives and critical infrastructure in the face of potential dam failures, contributing to a more resilient and secure future.
