Off-Network Earthquake Location by Earthquake Early Warning Systems: Methodology and Validation

ABSTRACT Regional source-based earthquake early warning systems perform three consecutive tasks: (1) detection and epicenter location, (2) magnitude determination, and (3) ground-motion prediction. The correctness of the magnitude determination is contingent on that of the epicenter location, and the credibility of the ground-motion prediction depends on those of the epicenter location and the magnitude determination. Thus, robust epicenter location scheme is key for regional earthquake early warning systems. Available source-based systems yield acceptably accurate locations when the earthquakes occur inside the real-time seismic network, but they return erroneous results otherwise. In this study, a real-time algorithm that is intended as a supplement to an existing regional earthquake early warning systems is introduced with the sole objective of ameliorating its off-network location capacity. The new algorithm combines measurements from three or more network stations that are analyzed jointly using an array methodology to give the P-wave slowness vector and S-phase arrival time. Prior to the S-phase picking, the nonarrival of the S phase is used for determining a minimum epicentral distance. This estimate is updated repeatedly with elapsed time until the S phase is picked. Thus, the system timeliness is not compromised by waiting for the S-phase arrival. After the S wave is picked, an epicentral location can be determined using a single array by intersecting the back-azimuth beam with the S-minus-P annulus. When several arrays are assembled, the back azimuth and P and S picks from all arrays are combined to constrain the epicenter. The performance of the array processing for back azimuth and S-wave picking is assessed using a large number of accelerograms, recorded by nine strong motion sensors of the KiK-net seismic network in Japan. The nine stations are treated as three distinct seismic arrays, comprising three stations each. Good agreement is found between array-based and catalog-reported parameters. Finally, the advantage of the new array methodology with respect to alternative schemes for back azimuth and distance is demonstrated.

Magnitude Estimation and Onsite Earthquake Early Warning using Cumulative Absolute Velocity in Taiwan

<p>Real-time magnitude determination is one of the critical issues for earthquake early warning (EEW). Magnitude determination may have saturation situation using initial seismic signals after an earthquake occurrence. Previous studies utilized eventual cumulative absolute velocity (eCAV) to determine magnitude up to 9.0 without any saturation. However, to determine eCAV will be too late for EEW application. In order to shorten time to obtain eCAV, 4,754 strong motion records from 64 events with M<sub>L </sub>large than 5.5 in Taiwan are used to establish the relationship between eCAV and initial shaking parameters (initial CAV, initial cumulative absolute displacement, initial cumulative absolute integral displacement,  P<sub>d</sub> and  τ<sub>c</sub>) from 1 s to 20 s after P arrival. Our preliminary results show that eCAV can be estimated using initial shaking parameters. Logarithm linear correlation coefficients vary from 0.78 to 0.97 with standard deviations from 0.27 to 0.10 for time windows from 1 s to 20 s after P arrival. Eventually, we can timely estimate eCAV for magnitude determination as well as or on-site EEW purpose.</p>

Updated determination of earthquake magnitudes at the Swiss Seismological Service

<p>The Swiss Seismological Service (SED; http://www.seismo.ethz.ch) at ETH Zürich is the federal agency in charge of monitoring earthquakes in Switzerland and neighboring areas, and for the assessment of seismic hazard and risk for the region. The SED seismic network largely relies on software and databases integrated in the SeisComP3 monitoring suite for waveform acquisition, automatic and manual event processing, event alerting, web infrastructure, data archiving and dissemination. Data from all digital seismic stations acquired by the SED over the last 30 years - broadband (presently ~230), strong-motion (~185), short-period (~65), permanent and temporary - are homogeneously integrated in the seismic network processing tools and products. Waveform data from the Swiss National Seismic Networks are openly available through the SED website and ORFEUS EIDA / Strong-Motion (http://orfeus-eu.org/data/) data gateways. The SED earthquake catalogue is publicly available through FDSN Event web services at  the SED (http://arclink.ethz.ch/fdsnws/event/1/). The Swiss seismic hazard maps are integrated in the EFEHR portal (http://www.efehr.org). The SED is updating its strategy for magnitude determination to make it fully consistent with the state-of-the-art in engineering seismology and seismic hazard studies in Switzerland, and to optimise the use of its dense seismic monitoring infrastructure. Among the planned changes are the: (a) adoption of a new ML relationship applicable in the near-source region at epicentral distances smaller than 15-20 km; (b) inclusion of ML station corrections based on empirically observed (de)amplification with respect to the Swiss reference rock velocity model and associated predictions; (c)  seamless computation of Mw based on spectral fitting of recorded FAS using a Swiss specific model. In this contribution we present and discuss the updated magnitude computations for a playback dataset of thousands of recorded earthquakes, and compare them with the current official estimates. We discuss the expected impacts of the new magnitude determination strategy on the SED event processing chain in SeisComP3, the SED catalogues and other seismological products. We welcome community feedback on our planned transition strategy.</p>

An IoT-Based Earthquake Warning System for Smart Cities

Earthquakes are the most common natural disasters that occur in India. An earthquake warning system minimizes damage and saves countless lives. A seismic wave analysis helps develop an early warning system. The bigger the earthquake, the stronger the shaking. Hence, magnitude determination is critical to developing an earthquake early warning system. The chapter deals with detecting earthquake magnitude by identifying the individual magnitude of earthquakes. An early warning system can be effectively implemented by the proposed method, along with high-end processors and the IoT (internet of things), which has the ability to collect and transfer data over networks with no manual intrusion. The proposed early earthquake warning (EEW) system can be used to support the development of smart cities so earthquake-prone zones are made less susceptible to disaster.