Most flood inundation models do not come with an uncertainty analysis component chiefly because of the complexity associated with model calibration. Additionally, the fact that the models are both data- and compute-intensive, and since uncertainty results from multiple sources, adds another layer of complexity for model use. In the present study, flood inundation modeling was performed in the Godavari River Basin using the Hydrologic Engineering Center—River Analysis System 2D (HEC-RAS 2D) model. The model simulations were generated for six different scenarios that resulted from combinations of different geometric, hydraulic and hydrologic conditions. Thus, the resulted simulations account for multiple sources of uncertainty. The SRTM-30 m and MERIT-90 m Digital elevation Model (DEM), two sets of Manning’s roughness coefficient (Manning’s n) and observed and estimated boundary conditions, were used to reflect geometric, hydraulic and hydrologic uncertainties, respectively. The HEC-RAS 2D model ran in an unsteady state mode for the abovementioned six scenarios for the selected three flood events that were observed in three different years, i.e., 1986, 2005 and 2015. The water surface elevation (H) was compared in all scenarios as well as with the observed values at selected locations. In addition, ‘H’ values were analyzed for two different structures of the computational model. The average correlation coefficient (r) between the observed and simulated H values is greater than 0.85, and the highest r, i.e., 0.95, was observed for the combination of MERIT-90 m DEM and optimized (obtained via trial and error) Manning’s n. The analysis shows uncertainty in the river geometry information, and the results highlight the varying role of geometric, hydraulic and hydrologic conditions in the water surface elevation estimates. In addition to the role of the abovementioned, the study recommends a systematic model calibration and river junction modeling to understand the hydrodynamics upstream and downstream of the junction.

中文翻译：

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印度戈达瓦里河流域的二维洪水淹没模型-模型输出不确定性的见解

大多数洪水淹没模型都没有附带不确定性分析组件，主要是因为模型标定具有复杂性。此外，模型既需要大量数据，又需要大量计算，并且由于不确定性来自多个来源，因此增加了模型使用的复杂性。在本研究中，戈达瓦里河流域使用水文工程中心—河流分析系统2D（HEC-RAS 2D）模型对洪水进行了建模。针对不同几何，水力和水文条件的组合产生的六种不同情景生成了模型仿真。因此，结果模拟说明了不确定性的多种来源。SRTM-30 m和MERIT-90 m数字高程模型（DEM），两组曼宁粗糙度系数（Manning's n）以及观察和估计的边界条件分别用于反映几何，水力和水文不确定性。对于在三个不同年份（即1986、2005和2015年）观察到的所选三个洪水事件，上述六个场景的HEC-RAS 2D模型以非稳态模式运行。比较了所有水面高度（H）。情景以及选定位置的观测值。此外，针对计算模型的两个不同结构分析了“ H”值。观察到的H值与模拟H值之间的平均相关系数（r）大于0.85，对于MERIT-90 m DEM的组合并进行了优化（通过反复试验获得），Manning's n观察到最高r，即0.95。 。分析表明河流几何信息的不确定性，结果突出了几何，水力和水文条件在水面高程估算中的不同作用。除上述作用外，该研究还建议进行系统的模型标定和河流交汇处建模，以了解交汇处上游和下游的水动力。