Department of Civil and Environmental Engineering, Imperial College, London, United Kingdom.
Water Sci Technol. 2010;61(10):2595-601. doi: 10.2166/wst.2010.178.
Reliable flood forecasting requires hydraulic models capable to estimate pluvial flooding fast enough in order to enable successful operational responses. Increased computational speed can be achieved by using a 1D/1D model, since 2D models are too computationally demanding. Further changes can be made by simplifying 1D network models, removing and by changing some secondary elements. The Urban Water Research Group (UWRG) of Imperial College London developed a tool that automatically analyses, quantifies and generates 1D overland flow network. The overland flow network features (ponds and flow pathways) generated by this methodology are dependent on the number of sewer network manholes and sewer inlets, as some of the overland flow pathways start at manholes (or sewer inlets) locations. Thus, if a simplified version of the sewer network has less manholes (or sewer inlets) than the original one, the overland flow network will be consequently different. This paper compares different overland flow networks generated with different levels of sewer network skeletonisation. Sensitivity analysis is carried out in one catchment area in Coimbra, Portugal, in order to evaluate overland flow network characteristics.
可靠的洪水预测需要能够足够快速地估算暴雨洪水的水力模型,以便能够成功地做出应对。通过使用一维/一维模型可以提高计算速度,因为二维模型的计算要求太高。通过简化一维管网模型、去除和更改一些次要元素,可以进一步进行更改。伦敦帝国理工学院的城市水研究小组(UWRG)开发了一种工具,可自动分析、量化和生成一维地表径流网络。该方法生成的地表径流网络特征(池塘和水流路径)取决于污水管网检查井和污水入口的数量,因为一些地表径流路径从检查井(或污水入口)位置开始。因此,如果简化的污水管网的检查井(或污水入口)数量少于原始管网,则地表径流网络也会相应不同。本文比较了不同管网简化程度生成的不同地表径流网络。在葡萄牙科英布拉的一个集水区进行了敏感性分析,以评估地表径流网络特征。