AI 中文总结
针对尾矿坝溃坝分析受多种不确定性影响的问题，提出集成不确定性量化和全局敏感性分析的概率方法，通过降维和元建模解决相关难题，经实验量化不确定性、表征分布并确定变量影响，其框架可支持更标准化和风险评估。
AI 中文摘要
尾矿坝溃坝分析对洪水灾害评估、应急规划和风险估计至关重要，但其结果受溃坝发展、泄放量和尾矿流变学等不确定性的强烈影响。本研究提出一种有效的概率方法，将不确定性量化和全局敏感性分析集成于尾矿坝溃坝研究。通过降维和元建模解决高维输出（空间图）及确定性模拟的计算成本问题。在复杂地形的基准案例上，使用HEC-RAS v6.6并考虑溃坝参数和流变特性的不确定性进行了方法演示。结果量化了最大水流深度和到达时间的不确定性，表征其统计分布，并通过敏感性图确定主要输入变量的空间影响。敏感性指标揭示了坝附近溃坝参数和下游更远位置屈服应力的主导性。该模块化和非侵入性框架可与其他确定性模型耦合，并应用于不同溃坝场景，支持更标准化和基于风险的评估。
英文摘要
Tailings dam-breach analyses are essential for flood-hazard assessment, emergency planning and risk estimation, but their results are strongly affected by uncertainties in breach development, released volume and tailings rheology. This study proposes an efficient probabilistic methodology that integrates uncertainty quantification and global sensitivity analysis for tailings dam-breach studies. High-dimensional outputs (spatial maps) and the computational cost of deterministic simulations are addressed through dimensionality reduction and metamodeling. The methodology is demonstrated on a benchmark case with complex terrain using HEC-RAS v6.6 and considering uncertainties in breach parameters and rheological properties. The results quantify uncertainty in maximum flow depth and arrival time, characterize their statistical distributions and identify the spatial influence of the main input variables through sensitivity maps. Sensitivity indices reveal the dominance of breach parameters near the dam and yield stress farther downstream. The modular and non-intrusive framework can be coupled with other deterministic models and applied to different dam-breach scenarios, supporting more standardized and risk-informed assessments.
