臺北市強降雨即時淹水預報平台之精進研發－熱啟動技術連續運行之應用

近年來都市地區積淹水多為短延時強降雨暴雨所造成，此些強降雨於短時間內形成過量之逕流量造成排水系統無法負荷，因而產生積淹水現象。為了縮短淹水模擬所需時間以及減少重複計算，並可以結合地表、雨水下水道初始流況，同時利用每10分鐘更新的QPESUMS降雨預報進行淹水預報，因此，本研究因此更新臺大細胞自動機快速淹水模式（NTU-CAFIM）並研發熱啟動技術（Hot-start Module），利用每次模擬時所產製的熱啟動文件（Hot Start File）進行即時淹水模擬的資料暫存，其資料包含地表以及雨水下水道流況（水位、流速），同時結合QPESUMS降雨預報進行未來2小時的淹水預報，以此方式進行每10分鐘更新頻率的熱啟動文件（Hot Start File）暫存與淹水預報發布，讓原先每30分鐘更新的未來2小時淹水預報精進為每10分鐘更新。以臺北市2021年0604豪雨事件進行熱啟動模式測試之結果，熱啟動模式能提供與非熱啟動模式幾乎完全一樣的淹水預報結果，然而僅需後者的39%的計算時間。

關鍵字

即時淹水模擬；細胞自動機；雨水下水道；熱啟動；淹水預報

並列摘要

Recently, urban floodings in Taipei city are mainly attributed to short-duration high-intensity rainfalls that drop massive water volume in a considerably short duration and result in excess runoffs beyond the capacity of drainage systems. For this situation, the Taipei City Government and the research team of the National Taiwan University worked together to establish a real-time flood inundation forecasting platform based on the developed National Taiwan University Cellular Automata Flood Inundation Model (NTU-CAFIM) of the research team. The platform sequentially and automatically conducts 2-hour urban flood forecasting in a 30-min frequency, and each flood inundation simulation comprises 4-hour observed rainfall and 2-hour forecasted rainfall by QPESUMS. To further increase the efficiency without losing the required accuracy of the platform, for each simulation, the 4-hour observed rainfall is replaced with the settings of initial conditions for the NTU-CAFIM and the 10-min observed rainfall. Correspondingly, the overland flow model (OFM) and the sewer flow model (SFM) of the NTU-CAFIM are both modified to incorporate the hot-start module to accomplish this task. At the beginning of a simulation, OFM and SFM (i.e., the SWMM) both read the formatted hot-start files that come from the previous simulation to set their initial conditions (i.e., water depths and water velocities) As the simulation time reaches the end of the 10-min observed rainfall, OFM and SFM both save the water depths and velocities at this time into their formatted hot-start files for the subsequent simulation. In this way, the frequency of the flood inundation simulation is shortened from 30 minutes to 10 minutes, which greatly enlarges the efficiency of the developed platform and more detailed measured data can be input into the simulation. The accuracy and efficiency of the advanced platform are evaluated and compared with the original platform through the 4 June 2021 extremely heavy rainfall event in Taipei. From the results, the advanced platform only takes 39% computational time of the original platform to perform the flood inundation simulation with almost the same accuracy as the original platform, which is a remarkable improvement.

並列關鍵字

Real-time flood inundation modeling ； Cellular automata ； SWMM ； Hot Start ； Flood inundation forecasting platform

參考文獻

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