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New Sensitivity Indices of a 2D Flood Inundation Model Using Gauss Quadrature Sampling

机译：使用高斯正交采样的二维洪水淹没模型的新灵敏度指标

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摘要

A new method for sensitivity analysis of water depths is presented based on a two-dimensional hydraulic model as a convenient and cost-effective alternative to Monte Carlo simulations. The method involves perturbation of the probability distribution of input variables. A relative sensitivity index is calculated for each variable, using the Gauss quadrature sampling, thus limiting the number of runs of the hydraulic model. The variable-related highest variation of the expected water depths is considered to be the most influential. The proposed method proved particularly efficient, requiring less information to describe model inputs and fewer model executions to calculate the sensitivity index. It was tested over a 45 km long reach of the Richelieu River, Canada. A 2D hydraulic model was used to solve the shallow water equations (SWE). Three input variables were considered: Flow rate, Manning’s coefficient, and topography of a shoal within the considered reach. Four flow scenarios were simulated with discharge rates of 759, 824, 936, and 1113 m 3 / s . The results show that the predicted water depths were most sensitive to the topography of the shoal, whereas the sensitivity indices of Manning’s coefficient and the flow rate were comparatively lower. These results are important for making better hydraulic models, taking into account the sensitivity analysis.
机译：提出了一种基于二维水力模型的水深敏感性分析的新方法，作为蒙特卡洛模拟的一种方便且具有成本效益的替代方法。该方法涉及扰动输入变量的概率分布。使用高斯正交采样为每个变量计算相对灵敏度指数，从而限制了液压模型的运行次数。预期水深的变量相关最大变化被认为是最有影响力的。所提出的方法被证明是特别有效的，需要较少的信息来描述模型输入并且需要较少的模型执行来计算灵敏度指数。在加拿大黎塞留河（Richelieu River）45公里长的河段进行了测试。使用二维水力模型求解浅水方程（SWE）。考虑了三个输入变量：流量，曼宁系数和所考虑范围内的浅滩地形。模拟了四种流量情景，流量分别为759、824、936和1113 m 3 / s。结果表明，预测的水深对浅滩的地形最敏感，而曼宁系数和流量的敏感指数相对较低。考虑到灵敏度分析，这些结果对于建立更好的水力模型很重要。

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