Levee breaches can trigger severe flooding and substantial socioeconomic losses in flood-prone regions, making reliable risk assessment essential for targeted flood control and disaster mitigation. This study develops a comprehensive risk assessment framework that couples a 1D–2D hydrodynamic model with a multi-indicator evaluation system. First, the Integrated Flood Modeling System (IFMS) is employed to simulate flood inundation dynamics following levee failure under 50-, 100-, and 200-year return period scenarios at five representative breach locations along the middle and lower reaches of China’s Daling River. Then a multi-dimensional indicator system is built by overlaying the simulated inundation results with exposure data to quantify direct economic losses. The indicator system includes levee attributes, flood risk, typical exposed elements, and a new dimension termed the amplification effect, which characterizes the nonlinear escalation of disaster consequences and the exceedance sensitivity of the flood disaster system under extreme levee breach scenarios. The results reveal clear spatial heterogeneity in both inundation patterns and risk profiles among the five breach sites. As the return period increases from 50 to 200 years, the growth in direct economic losses consistently outpaces the expansion of inundation area. Moreover, the amplification intensity under the 200-year return period substantially exceeds that under the 100-year event at all five sites, indicating stronger nonlinear disaster escalation and lower system resilience under extreme exceedance flood conditions. Based on a weighted multi-indicator integration, Lituocun shows the highest composite risk, followed by Shenglitun, Youxicun, Yangguicun, and Xiangyangzha, with distinct risk drivers at each site underscoring the need for targeted mitigation measures. The proposed method can effectively identify weak levee sections and reveal their risk drivers, providing a scientific basis for local governments to formulate levee reinforcement plans and flood control management decisions.
Zhang et al. (Mon,) studied this question.