Optimization of Emergency Evacuation Paths for Personnel in Tailings Dam Failure Disasters

The tailings dam failure poses a significant threat to the life and property security of downstream residents, with emergency evacuation serving as a crucial measure to mitigate disaster losses. Herein, a multiobjective evacuation path model is developed to address the key issue of emergency evacuation path planning following a tailings dam failure. The model is based on multiobjective evacuation mathematical theory, with the goals of minimizing evacuation time and reducing personnel risk, while considering the downstream road network structure and the inundation area of the dam break as constraints. To further solve the multisource point problem within the model, a Dijkstra’s algorithm with high compatibility to GIS road networks is employed. Additionally, the algorithm is improved using a circular search range limitation method, significantly enhancing the solution efficiency of the evacuation path model. An evacuation route‐planning system for tailings‐dam breach emergencies was developed using the ArcGIS Engine and Visual Studio, with data stored and managed in a geodatabase. Benchmark results show that, compared with the standard Dijkstra’s algorithm, the improved algorithm reduced the number of nodes and arcs traversed by 168 and 106, respectively, and achieved a 49.6% speedup (runtime reduced from 876.47 to 441.23 ms). Then, the system is successfully applied to the emergency evacuation of downstream residents following the tailings dam failure at the Tongshankou tailings dam in Hubei Province. Dam break simulation for Tongshankou indicated four downstream villages were threatened, with peak depths of ~ 4.5–7.5 m and flow velocities > 6 m/s. Computed total evacuation times were 4.09 min (Chengongjin village), 7.92 min (Chentingjie village), 10.21 min (Chenxizhen village), and 9.76 min (Wangjia village), all shorter than the corresponding inundation arrival times of 6.35 min, 10.91 min, 12.24 min, and 17.44 min, respectively, yielding positive safety margins ( Δt = 2.03 to 7.68 min).