Reasonable planning of emergency evacuation paths is a significant measure to reduce potential casualties caused by floods. However, due to the complexity of evacuation environments, large-scale personnel evacuation may lead to increased road traffic load and congestion, which dynamically change the overall evacuation time under varying traffic conditions and thus affects evacuation efficiency. Therefore, by comprehensively considering the dynamic impacts of various factors on evacuation time-such as road length, class, width, bending condition, traffic load condition, crowd disturbance, an emergency evacuation path planning model with the goal of shortest evacuation time was constructed by coupling the Dijkstra Algorithm with an Impedance Function. This model was applied to the emergency evacuation path planning of Changkai dike breach in Fuzhou City, Jiangxi Province, China. The results showed that: (1) The evacuation path planning scheme improved the overall evacuation efficiency and significantly reduced the evacuation time; (2) As the evacuation distance increases, the dynamics impact of the various factors on evacuation time cost becomes increasingly significant. In this case, the time cost of the shortest distance path will be much greater than the time cost of the shortest time path.

Lands and populations are the most direct and core disaster-bearing bodies in floods. Accurate and comprehensive identification their attributes is critical for differentiated flood prevention and mitigation strategies. However, two key challenges persist in current practices. First, the accuracy of urban land function (ULF) identification based on machine learning is constrained by data and grid scale, yet research on their impacts remains insufficient. Second, location-based service (LBS) data has sampling bias and nighttime distortion in characterizing dynamic population distribution, and its spatial resolution is insufficient for high-precision flood simulations. For ULF identification, abundant comparison schemes are generated through data traversal and multi-scale fusion, and an ensemble learning model is constructed to select the optimal ULF identification scheme. This avoids the accuracy uncertainty caused by subjective selection, and the results provide reliable data support for economic loss assessment and subsequent population spatial interpolation. For dynamic population distribution, a human-land relationship matching method based on spatiotemporal behavioral laws is proposed to reduce the impact of data bias. Meanwhile, spatial downscaling is achieved through regional division, land type and area weight calculation, generating dynamic population distribution maps with high spatiotemporal resolution. The results support the analysis of population mobility’s impact on flood risk. Hydraulic simulation is coupled with GIS (geographic information system) analysis to construct a grid-based diagnostic framework for multi-attributes of disaster-bearing bodies, including land function, population size, water depth, and spatial location. Case studies show that this framework provides reliable support for the accurate and comprehensive identification of flood disaster-bearing bodies.

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.

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.

Dam breaches often have catastrophic consequences in downstream areas. Hydrodynamic factors and the evacuation potential of the population at risk (PAR) have significant impacts on the loss of life (LOL) caused by dam breaches. However, the existing comprehensive evaluation models have not conducted in-depth research on the evacuation potential of populations. Thus, limited guidance is available for relevant departments to formulate emergency plans to reduce the potential LOL. Therefore, a new comprehensive evaluation model was proposed in this study. According to the relevant references and disaster theory, the main influencing factors and the process through which the LOL is caused by dam breaches were determined. The specific occurrence process was divided into six stages: a dam breach causes flood, the flood puts the PAR, the PAR complete the preparation work, the PAR evacuate, the un-evacuated population shelter themselves inside buildings, and flood causes the death of the exposed population. To calculate the LOL, the parameters relevant at each stage were defined. Furthermore, the Hydrologic Engineering Center's River Analysis System, Geographic Information System, and related materials were used to simulate the flood routing and evacuation potential of the PAR, quantifying the parameters in the model. The model was applied to 14 towns in the downstream areas of the Luhun Reservoir in Henan Province, China, and its accuracy was verified by comparing the results obtained from the two existing models. In addition, the specific suggestions for reducing the potential LOL were proposed based on the results of the simulation.

Dam breach has catastrophic consequences for human lives and economy. In previous studies, empirical models are often, to a limited extent, due to the inadequacy of historical dam breach events. Physical models, which focus on simulating human behavior during floods, are not suitable for fast analysis of a large number of dams due to the complexities of many key parameters. Therefore, this paper proposes a method for fast evaluation of potential consequences of dam breach. Eight main indices, i.e., capacity of reservoir (C_R), dam height (H_D), population at risk (P_R), economy at risk (E_R), understanding of dam breach (U_B), industry type (T_I), warning time (T_W), and building vulnerability (V_B), are selected to establish an evaluation index system. A catastrophe evaluation method is introduced to establish an evaluation model for potential consequences of dam breach based on the indices which are divided into five grades according to the relevant standards and guidelines. Validation of the method by twelve historical dam breach events shows a good accuracy. The method is applied to evaluate potential consequences of dam breach of Jiangang Reservoir in Henan Province, China. It is estimated that loss of life in the worst scenario is between that of Hengjiang Reservoir and that of Shimantan Reservoir dam breach, of which fatalities are 941 and 2717, respectively, showing that risk management measures should be taken to reduce the risk of potential loss of life.