中文摘要：

城市的淹没由于异常暴风雨是为世界范围的许多城市的一个严重问题。因此，精确地模仿城市的水文学过程并且高效地为排水图案和紧急情况行动的实现的改进预言城市的洪水的潜在的风险是重要的。然而，城市的地形的复杂性和水力的基础结构的差异为模拟和对城市的排水过程的风险评价提出特别挑战。这研究开发了方法论包括地由动态地联合 1D 和 2D 水动力学模型模仿淹没过程。由允许降雨和流量的进程的同时的解决方案，城市的排水，并且泛滥，这个方法能被用来估计任何设计排水系统的潜在的淹没风险。而且，一个地理信息系统(GIS ) 基于站台与模型引擎是充分综合的有效地说明这个问题的上下文。发达模型然后在在 5 年、 50 年的设计的条件下面的 2008 奥林匹克村庄袭击的北京被表明。下水道分泌物，隧道分泌物，和洪水繁殖(淹没开始，程度，深度，和持续时间) 数字地被验证并且分析。结果识别了潜在的淹没风险。从学习，联合 GIS 和 1D 和 2D 水动力学模型有潜力模仿城市的淹没过程，这被发现，并且高效地因此预言洪水风险并且支持划算的排水设计和管理。它也关于高质量的数字数据， GIS 技术，和开发联机城市的淹没预报的开发得好的监视基础结构的宽可获得性暗示有希望的前景。

英文摘要：

Urban inundation due to anomalous storms is a serious problem for many cities worldwide. Therefore, it is important to accurately simulate urban hydrological processes and efficiently predict the potential risks of urban floods for the improvement of drainage designs and implementation of emergency actions. However, the complexity of urban landforms and the diversity of hydraulic infrastructure pose particular challenges for the simulation and risk assessment of urban drainage processes. This study developed a methodology to comprehensively simulate inundation processes by dynamically coupling 1D and 2D hydrodynamic models. By allowing the simultaneous solution of the processes of rainfall and runoff, urban drainage, and flooding, this method can be used to estimate the potential inundation risks of any designed drainage system. Furthermore, a Geographical Information System （GIS） based platform was fully integrated with the model engine to effectively illustrate the context of the problem. The developed model was then demonstrated on the Beijing 2008 Olympic Village under the conditions of the 5-year and 50-year design storms. The sewer discharge, channel discharge, and flood propagation （inundation initiation, extent, depths, and duration） were numerically validated and analyzed. The results identified the potential inundation risks. From the study, it is found that the coupled GIS and 1D and 2D hydrodynamic models have the potential to simulate urban inundation processes, and hence efficiently predict flood risks and support cost-effective drainage design and management. It also implies promising prospects about the wide availability of high quality digital data, GIS techniques, and well-developed monitoring infrastructure to develop online urban inundation forecasts.