英文摘要
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Whenever a typhoon strikes with torrential rainfall, it tends to bring exceeding amount and high intensity precipitation in a very short period of time. With such condensed rainfall in a short period of time, it may bring catastrophes and result in compounded disasters. For the disaster prevention countering personnel to perform early decision making judgment, instantaneous and effective flooding alert and precipitation forecast become a vital issue in Taiwan. However, the sources of water information are many and complex and that they often require complicated procedures and operation within the current pre-warning system in Taiwan to provide early warning information for the flood prevention countering personnel. In order to integrate the pre-warning procedures and elevate the efficiency in generating pre-warning graphic data, this study develops an Operational Information Platform for Inundation Forecasting to integrate and interconnect the precipitation forecast data and inundation forecasting. This operational platform can reduce the massive operation time and the cost of manual labor, which provides visualization interface for the flood prevention countering personnel to conduct the latest flood pre-warning simulation data inquiries and comparison. This platform also cut the time required in data connection and compiling to achieve the goal of real-time decision making. It runs periodically and automatically to generate the simulation graphic data to provide the flooding prevention countering personnel to conduct the comparison between archived pre-warning data and actual disaster situation to improve future disaster prevention strategies. This study also conducts the comparison between the original operation and the present system operation on the pre-warning procedures. The results indicate that the platform reduces the time that is normally required by the original semi-automatic early pre-warning procedures as well as the risk of simulation data error resulted from the human negligence. It is proven that this platform increases the efficiency of flood inundation forecasting in flood prevention contingency and decision making.
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