土石坝溃坝洪水模拟与损失评估

Study on flood simulation and loss assessment for embankment dam events

  • 摘要: 土石坝溃坝洪水风险评估对溃坝应急预案编制和抢险救灾具有至关重要的意义。目前土石坝溃坝洪水流量过程计算时对复杂结构坝体溃决机理考虑较少,溃坝洪水损失评估方法考虑的影响因素不够全面。提出了一个机理-数据双驱动的土石坝溃坝洪水模拟与损失评估方法,可考虑土石坝的溃坝过程、溃坝洪水演进过程,并采用贝叶斯模型定量评估溃坝洪水导致的生命与经济损失。评估方法主要包括3个模块:溃坝过程模拟方法、溃坝演进洪水致灾因子计算方法、生命与经济损失评估方法。并采用该方法对2018年中国射月沟溃坝案例进行反演分析,计算结果与实测值相比,溃口洪水峰值流量、溃口最终尺寸和溃口峰值流量出现时间的相对误差小于15%,淹没区典型断面最高水位的最大误差为-0.21 m,淹没区生命损失结果相近,验证了该风险评估方法计算结果的合理性。研究结果可为溃坝洪水应急防控和防灾减灾提供科技支撑。

     

    Abstract: The assessment of flood risk resulting from embankment dam breaching is essential for developing effective emergency response strategies and improving disaster relief efforts. Embankment dams, widely adopted for their cost-efficiency, construction simplicity, and adaptability to diverse terrains, are particularly susceptible to breaching under extreme hydrological conditions, structural deficiencies, or inadequate maintenance. When a breach occurs, the sudden release of stored water can trigger a catastrophic flood wave, causing severe consequences such as substantial loss of life, infrastructure damage, environmental degradation, and prolonged socio-economic disruption in downstream areas. Despite the urgency of accurate risk evaluation, existing methodologies for flood discharge simulation and loss assessment often exhibit critical limitations. Traditional models tend to oversimplify the complex breaching processes and inadequately capture the nonlinear dynamics of flood propagation. Additionally, many approaches lack robust techniques for estimating both direct and indirect losses and offer limited tools for quantifying predictive uncertainty. To address these challenges, this study introduces a novel mechanism-data dual-driven framework for flood simulation and loss assessment tailored to embankment dam breach scenarios. This method integrates detailed physical modeling of the dam breach process with data-driven statistical analysis of flood propagation and its consequences. By combining these complementary perspectives, the approach enables more realistic and accurate flood simulations, offering a stronger foundation for risk assessment. A central innovation of the methodology is the incorporation of a Bayesian statistical model, which facilitates probabilistic analysis and enables rigorous quantification of uncertainties in estimating both life loss and economic damage. The assessment framework consists of three interrelated modules. The first module simulates the breach process using a combination of physical models, empirical equations, and field data to reconstruct the timing, size, and evolution of the breach. The second module calculates key disaster-inducing factors during flood propagation—such as flow velocity, flood depth, inundation extent, and arrival time in affected areas—which are critical for evaluating the intensity and spatial reach of the event. The third module estimates human and economic losses by integrating the hydrodynamic outputs from the second module with demographic, land use, and infrastructure data to assess exposure and vulnerability. The Bayesian model is then employed to quantify uncertainty and generate probabilistic loss estimates. To validate the effectiveness and reliability of the proposed method, it was applied to the 2018 Sheyuegou dam breach case in China. This real-world event provided a comprehensive dataset for model calibration and verification. Inversion analysis results showed that the relative errors for key parameters—such as peak flood discharge, final breach dimensions, and timing of peak flow—were all within ±15% of observed values. Moreover, the maximum deviation in the highest water level at representative cross-sections within the inundation zone was only −0.21 meters. Regarding casualty estimation, the predicted number of fatalities closely matched the reported figures, underscoring the method’s accuracy and credibility. In conclusion, these findings confirm that the proposed mechanism-data dual-driven approach is an effective and practical tool for simulating dam breach scenarios and assessing associated flood risks. Its capacity to accurately replicate real-world outcomes while incorporating uncertainty in loss estimates provides valuable support for emergency preparedness, response planning, and disaster risk reduction. This research advances flood risk assessment methodologies by offering a more comprehensive, precise, and scientifically robust framework for managing the impacts of embankment dam failures.

     

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