低價位地震網應用於臺灣地震減災之探討

Abstract

大地震後，近乎即時製出的震度圖可以呈現不同空間位置的強地動及震度分布情形，以供快速評估地震對各地的影響。由地震規模及位置等震源的不確定對震度精度影響的研究得知，臺灣地區的地震速報系統基於點震源的假設，會產生震度0.5及最大加速度7.2cm/s2的誤差。近年來，在臺灣設置的高密度地震觀測網，每一測站都裝設由臺灣大學研究團隊發展的微機電地震儀。該地震網擷取的大量中、大型地震紀錄，被用於探討即時震度圖製作及門檻值判別型的現地預警系統應用的可行性。結果顯示，該地震網製作出地震圖不但詳細，且可即時顯示震源破裂方向，有助於災害應變，減少災損；該地震網亦顯現其在現地型地震預警的功能，可在強大震波到達前提供足夠的應變時間。另外，在新竹工業園區內由數部微機電地震儀及一部寬頻地震儀組成的地震觀測網，以其在2015年收錄到的地震紀錄，即建立可供迅速評估該地地動特性的Pd與PGV的迴歸關係式，此一作法可應用至以往未有完整地震資料的地區。由上可知，對於地震減災而言，低價位的微機電地震觀測網實在具有多方面的應用價值。

Nearly real-time shaking maps can promptly provide spatial distributions of ground motion and seismic intensity soon after significant earthquakes hit, which are valuable to conduct rapid assessments on possible seismic adverse impacts. First, this research investigates the affecting factors of source uncertainties (e.g., magnitudes and locations) as to determine seismic intensity estimations. Conclusive results of case studies indicate that the current rapid earthquake reporting system based on a point source assumption could have uncertainties of 0.5 in intensity and 7.2 cm/s2 in peak ground acceleration (PGA). According to recent case studies, a dense seismic network adopting the micro-electro-mechanical system (MEMS) accelerometers has been developed by an earthquake early warning (EEW) research group at National Taiwan University. Through data collected by the network, this research retrieves massive information from lots of moderate-to-large earthquake records to explore the feasibility of producing real-time shaking map and the performance of threshold-based on-site EEW approach. According to the studies of shaking maps, the dense network can produce higher-resolution shaking maps and identify direction of source rupture through real-time calculation which effectively benefits emergency response operations and disaster risk reduction. This research also demonstrates this network is desirable for a functional threshold-based implementation of EEW and issues early warnings with sufficient leading time. In addition, from the analysis of data collected by an array of MEMS accelerometers and a broad-band seismometer within 2015, this research finds Pd correlates well with peak ground velocity (PGV). The MEMS seismic network shows its potential capabilities in disaster mitigation.