Low-cost seismic network for earthquake disaster mitigation in Taiwan
Date Issued
2016
Date
2016
Author(s)
Hsieh, Chih-Yih
Abstract
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.
Subjects
shaking map
earthquake early warning
MEMS accelerometer
peak ground acceleration
peak ground velocity
SDGs
Type
thesis
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