Earth-rock dams are critical components of hydraulic engineering, undertaking core functions such as flood control and disaster mitigation. However, the potential occurrence of dam breach poses a severe threat to regional socioeconomic stability and ecological security. To address the limitations of traditional Bayesian network (BN) in capturing the complex nonlinear coupling and dynamic mutual interactions among risk factors, they are integrated with machine learning techniques, based on a collected dataset of earth-rock dam breach case samples, the PC structure learning algorithm was employed to preliminarily uncover risk associations. The dataset was compiled from public databases, including the U.S. Army Corps of Engineers (USACE) and Dam Safety Management Center of the Ministry of Water Resources of China, as well as engineering reports from provincial water conservancy departments in China and Europe. Expert knowledge was integrated to optimize the network topology, thereby correcting causal relationships inconsistent with engineering mechanisms. The results indicate that the established hybrid model achieved AUC, accuracy, and F1-Score values of 0.887, 0.895, and 0.899, respectively, significantly outperforming the data-driven model G1. Forward inference identified the key drivers elevating breach risk. Conversely, backward inference revealed that overtopping was the direct failure mode with the highest probability of occurrence and the greatest contribution. The integration of data-driven approaches and domain knowledge provides theoretical and technical support for the probabilistic quantification of earth-rock dam breach and risk prevention and control decision-making.

As dams age, operating costs increase and associated risks intensify. Addressing the mechanisms influencing dam economic life is crucial for accurate assessment and operation management. Dam economic life is affected by social and ecological environmental factors, whose types, relationships, and influence degree vary over time. In this study, influencing factors were identified across five dimensions: safety, cost, benefit, social impact, and ecological and environmental impact. Using the Random Forest method, the interaction degrees among individual factors were analyzed. Using on Markov theory, the Decision-making Trial and Evaluation Laboratory (DEMATEL) method, and the Interpretative Structural Modeling Method (ISM), a time-varying analysis model was constructed to reveal the mechanisms of these influencing factors. The model was applied to the Luhun Reservoir in Luoyang City, Henan Province, China. Results showed that during the first 20 years of dam operation, factors such as total reservoir capacity and management level considerably affected dam economic life. Over the next 20 years, total reservoir capacity and population protection became the dominant factors. Dam economic life can be extended using management measures, including improving storage capacity utilization, enhancing silt control, and increasing flood control storage capacity.

In recent years, dam failures have occurred frequently because of extreme weather, posing a significant threat to downstream residents. The establishment of emergency shelters is crucial for reducing casualties. The selection of suitable shelters depends on key information such as the number and distribution of affected people, and the effective capacity and accessibility of the shelters. However, previous studies on siting shelters did not fully consider population distribution differences at a finer scale. This limitation hinders the accuracy of estimating the number of affected people. In addition, most studies ignored the impact of extreme rainfall on the effective capacity and accessibility of shelters, leading to a low applicability of the shelter selection results. Therefore, in this study, land-use and land-cover change (LUCC) and nighttime lighting data were used to simulate population distribution and determine the number and distribution of affected people. Qualified candidate shelters were obtained based on screening criteria, and their effective capacity and accessibility information under different weather conditions were quantified. Considering factors such as population transfer efficiency, construction cost and shelter capacity constraints, a multi-objective siting model was established and solved using the non-dominated sorting genetic algorithm II (NSGA- II) to obtain the final siting scheme. The method was applied to the Dafangying Reservoir, and the results showed the following: (1) The overall mean relative error (MRE) of the population in the 35 downstream streets was 11.16 %, with good fitting accuracy. The simulation results truly reflect the population distribution. (2) Normal weather screening generated 352 qualified candidate shelters, whereas extreme rainfall weather screening generated 266 candidate shelters. (3) Based on the population distribution and weather factors, four scenarios were set up, with 63, 106, 73, and 131 shelters selected. These two factors have a significant impact on the selection of shelters and the allocation of evacuees, and should be considered in the event of a dam-failure floods.

The scientific evaluation of a dam's economic life is necessary to determine its management strategy rationally. However, most studies have mainly focused on analyzing the current economic characteristics of reservoir dams without considering their long-term development trend. And they have failed to incorporate the potential loss caused by dam breaches as one of the operating costs for dams. Consequently, this results in the inability to scientifically calculate the economic life of reservoir dam operations. Therefore, this study analyzed the factors influencing the economic life of reservoir dams in term of safety, costs, benefits and society, and established an economic life evaluation indicator system for reservoir dams. Based on the analyses of costs and benefits of reservoir dams, an economic life evaluation model for reservoir dams was constructed by comprehensively considering the impact of potential dam breaches and the social impact of reservoir dams on the production and lives of local residents. Moreover, based on economic theory, the economics of various types of management measures for reservoir dams and their impact on the economic life of dams were analyzed. The proposed model was applied to the Luhun Reservoir in Henan Province, China, to quantify the comprehensive costs and benefits of its operation for each year after 1990 s, analyze the trend of its “cost-benefit” relationship, and calculate its expected economic life. The results showed that when considering its own risks and social impacts, the expected economic life of the Luhun Reservoir was 74 years. The Luhun Reservoir is expected to operate up to its non-economic life span till 2039. Finally, suggestions for expanding the economic life of dams were proposed. Potential dam breach losses can significantly reduce the economic life of reservoir dams. And risk management measures for reservoir dams should be particularly strengthened during daily operations and management.