Muti-Layered Grid Refinement for Flood Inundation Computations

• Main Authors: Tzu-Yao Hsu, 徐子堯
• Other Authors: 許銘熙
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/61170195393764258226

碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 102 === Global climate change has been increasing rainfall intensity and variability. The heavy rainfall and the special physiography including steep slope and easy precipitation-driven causes severe damage in Taiwan. Therefore, an efficient and accurate inundation model is developed for generating the inundation information to provide policy decision and reduce flood damage. The digital terrain model (DTM) and geographic information system (GIS) are employed to deal with the data of model. However, the remote sensing technique has obviously improved the spatial resolution and accuracy of digital terrain models in recent years. Despite advances in both computing software and hardware, high resolution flood modelling remains computationally demanding applying to a large study area. The multi-layered grid refinement can effectively reduce the computation time. Based on the thesis of "Down-scale Inundation Simulation for Local Area of a Basin" by Chen (2008), this study revised adopted three layers grid refinement (600m, 200m and 40m) in flood modelling to provide a much higher resolution grid with less computational time. The three layers grid refinement was applied to two cases. The first was a synthetic one. It was a 10 km×10 km square-shaped enclosed area with a designed rainfall pattern. The second was a real case that the multi-layered model applied to Tseng-Wen river basin with typhoon Morakot event (2009), which triggered the worst flooding that ever happened on this island in half a century. The two cases were compared with accuracy and efficiency. The result of three layers grid refinement is close the level of fine-grid simulation in the global area. Multi-layered approach is not only considering the accuracy, but also raising the efficiency of simulation. The contribution of this study could provide more efficient and more accurate model for the enhance decision-making and reduce flood damage in flood emergency operation.