Earthq Sci (2020)33: 281–292 281 doi: 10.29382/eqs-2020-0281-01 Earthquake early warning system in Liaoning, China based on PRESTo* Wuchuan Xu1 Xiangyu An2 Enlai Li2 Chengwei Wang2 Li Zhao1,* 1 School of Earth and Space Sciences, Peking University, Beijing 100871, China 2 Liaoning Earthquake Agency, Shenyang, 110034, China Abstract Liaoning is located in northeast China with fault zone, the Tancheng-Lujiang fault zone, also known as a high level of seismic activity, and earthquake early warning Tanlu fault zone (TLFZ), crosses the middle of the is important for the mitigation of seismic hazard. In this work, province in a northeast direction. The TLFZ has a mainly we implement PRESTo, an open-source software platform for right-lateral strike-slip motion and is considered to be the earthquake early warning based on regional seismic records, eastern margin of the North China basin (Allen et al., to the Liaoning seismic network. For the early warning of earthquakes in Liaoning, a travel-time table is created for 1997; Yin, 2010). It is seismically active and faults in and event detection and location using an average crustal model, around the TLFZ are predominantly striking northeast. All and the empirical relation is established between the earth- major historical earthquakes in eastern China, and in quake magnitude and the initial P-wave amplitudes. Using Liaoning Province in particular, are related to the TLFZ. archived seismic records of past earthquakes, we determine Although not as seismically active as other earthquake- the optimal values for Liaoning using the core algorithms of prone regions such as the western Pacific or the PRESTo. Based on the optimal parameters, the uncertainty in Himalayas, there are frequent earthquakes in Liaoning and event location is generally less than 5 km, and the lead time of surrounding areas (Figure 1) with a dozen or so strong the early warning is ~15 s at 100-km epicentral distance. The historical earthquakes, such as the 1944 M 6.6 earthquake implemented system can be directly put into routine W in Dandong (39.887°N, 124.148°E) near the China-Korea earthquake early warning operation by linking it with the real- time data stream from the Liaoning seismic network. border; the famous 1975 Haicheng earthquake (MS7.5), which was arguably the first successfully “predicted” Keywords: PRESTo; earthquake early waring; Liaoning seismic major earthquake in human history (Wang et al., 2006); network and the disastrous 1976 Tangshan earthquake (MW7.6) which occurred in the neighboring Hebei Province and killed more than 200,000 people. There are also occasional moderate (M5~6) earthquakes with very shallow depths 1 Introduction that can cause extraordinary damages, such as the 2013 MS5.1 Dengta earthquake (Su et al., 2020). Therefore, Liaoning is located in northeast China and is Liaoning is a region with a high earthquake hazard considered as part of the Northeast Asia Active Block potential and, given the high population density and recent (Zhang, 2003). The region is under the influence from the economic development, earthquake early warning (EEW) east by the subduction of the Pacific Plate under the is very important for the mitigation of seismic disasters. Eurasian Plate and from the southwest by the collision of In the past few decades, with the development in the Indian Plate with the Eurasian Plate. As shown in seismic monitoring networks and telecommunications Figure 1, the topography of Liaoning Province varies in technologies, EEW systems have been developed and put ESE direction with uplifts on both the east and west border into routine operation in many parts of the world, regions and a depression in between. A major NE-trending including Japan (UrEDAS, Kamigaichi et al., 2009), Mexico (SASMEX, Espinosa-Aranda et al., 2009), * Received 3 August 2020; accepted in revised form 14 December California (ShakeAlert, Kohler et al., 2018), Italy 2020; published 26 December 2020. (PRESTo, Zollo et al., 2009; Satriano et al., 2011), Turkey * Corresponding author. e-mail: [email protected] © The Seismological Society of China and Institute of Geophysics, (SOSEWIN, Fleming et al., 2009) and Taiwan (Hsiao et China Earthquake Administration 2020 al., 2009). Since the turn of the century, especially after the 282 Earthq Sci (2020)33: 281–292 118°E 120° 122° 124° 126° 44°N Inner Mongolia Jilin HXQ XFN FKU TIL FXI XMN QYU BEP FSH 42° JIP Liaoning SNY MQI CHY LHT Shenyang BZH GSH TanluLYN Fault ZoneBXI HUR LYA NAP JZH ANS H58 JCA SHS Haicheng KDN SUZ YKO XYN GAX Hebei DDO North Korea GUS 40° WFD HSH DLD Bohai Sea DL2 2.5 ≤ ML ≤ 3.0 Yellow Sea 3.0 < ML ≤ 3.5 (12) 38° 3.5 < ML ≤ 6.0 (13) 6.0 ≤ M < 7.0 (9) M ≥ 7.0 (5) −500 0 500 1000 1500 2000 Elevation (m) Figure 1 Map of Liaoning Province and surrounding areas. Background color shows the topography. Black triangles indicate locations of the seismic stations of Liaoning seismic Network (LNNet). The black lines represent major faults (fault data are from https://gmt-china.org/data/) in the region, and the thick red lines depict the Tanlu fault zone. Black dots are epicenters of earthquakes of 2.5 ≤ ML < 3.0. Red squares and stars mark the epicenters of 25 earthquakes of magnitudes 3.0 < ML ≤ 3.5 and 3.5 < ML ≤ 6.0, respectively, during 2009–2019 whose records are used in this study to implement PRESTo for LNNet. Orange and red circles are strong historical earthquakes of magnitudes 6.0 ≤ M < 7.0 and M ≥ 7.0 since 1900, respectively. White circles show major cities in Liaoning Province disastrous MW7.9 Wenchuan earthquake in 2008, EEW Federico II in Naples, Italy. All the PRESTo-related files systems have been established quickly in earthquake prone including software as well as documentations such as in- provinces in Chinese mainland, such as in Sichuan and stallation instruction and user manual can be freely down- Yunnan region (Peng et al., 2013; 2015, 2017; 2019; 2020; loaded from its official website (http://www.prestoews. Peng and Yang, 2019), and in Fujian (Zhang et al., 2016). org). The software integrates recent algorithms for real- This study is the first effort in using the recently deployed time, rapid earthquake detection, location, magnitude estim- seismic network in Liaoning Province in northeast China ation and damage assessment into an easily configurable to build an effective EEW system. and portable package (Satriano et al., 2011). PRESTo has In establishing the EEW system for the Liaoning regi- been under active experimentation in southern Italy on the on, we employ the open source software PRobabilistic and Irpinia Seismic Network (ISNet). It is a readily adaptable Evolutionary early warning SysTem (PRESTo). PRESTo and user-friendly platform and has been adopted in the was developed by the RISSC (RIcerca in Sesmologia EEW operations in many seismic networks worldwide Sperimentale Conputazionale) laboratory of the University (e.g. Picozzi et al., 2015; Pitilakis et al., 2016). Earthq Sci (2020)33: 281–292 283 2 Method and seismic data The 25 events are listed in Table 1 and their locations are shown in Figure 1. Once PRESTo can run successfully for archived data, the EEW system can be put into practical We first make a brief introduction about the main operation by plugging in real-time data streams from the concept of PRESTo for the benefit of discussion in Section Liaoning seismic network. 3 on our implementation to the Liaoning region. Theo- retical and technical details on PRESTo can be found on the official website of the package (http://www.prestoews. 3 Implementation of PRESTo to LNNet org) as well as references listed therein. PRESTo is composed of four core algorithms for event In general, PRESTo is a user-friendly software detection, location, magnitude determination and ground platform that can easily be implemented in different motion prediction (Satriano et al., 2008). The first one is regions using local network such as the LNNet data. FilterPicker (FP) for automatic, real-time phase picking However, a number of parameters used by the core (Lomax et al., 2012; Vassallo et al., 2012). FP is designed algorithms in PRESTo must be tuned based on data from on the basis of the classical short-term average/long-term specific regions. Therefore, our aim in this study is to average (STA/LTA) algorithms (Allen, 1982; Baer and determine the optimal set of parameters for the LNNet and Kradolfer, 1987) and can realize real-time phase picking discuss the performance of the EEW system. For the from continuous data streams with high efficiency and implementation and offline testing purposes, PRESTo accuracy. FP adopts two picking thresholds S1 and S2, and can be run in simulation mode in which it reads the SAC the picking is carried out when the value of a characteristic files from the archived records and converts them into data streams to simulate the actual early warning operation function exceeds S1 and meanwhile the integral of the using real-time data. The implementation of PRESTo characteristic function exceeds S2. The second core algo- rithm in PRESTo is real-time evolutionary earthquake involves four major tasks: configuration of region-specific location algorithm (RTloc) (Satriano et al., 2008) for real- files according to the network information; building the time evolutionary earthquake location. It starts locating the travel-time table for all seismic stations involved; event as soon as the first station is triggered (i.e. when the supplying the equation for magnitude estimation and P-wave is detected and picked by FP), and stations that are ground motion prediction; and setting the optimal values not triggered can also be included to reduce the uncertainty of miscellaneous parameters for the algorithms in of the location result.