Obtaining high-quality measurements close to a large earthquake is not easy: one has to be in the right place at the right time with the right instruments. Such a convergence happened, for the first time, when the 28 September 2004 Parkfield, California, earthquake occurred on the San Andreas fault in the middle of a dense network of instruments designed to record it. The resulting data reveal aspects of the earthquake process never before seen. Here we show what these data, when combined with data from earlier Parkfield earthquakes, tell us about earthquake physics and earthquake prediction. The 2004 Parkfield earthquake, with its lack of obvious precursors, demonstrates that reliable short-term earthquake prediction still is not achievable. To reduce the societal impact of earthquakes now, we should focus on developing the next generation of models that can provide better predictions of the strength and location of damaging ground shaking.

Implications for prediction and hazard assessment from the 2004 Parkfield earthquake

The basic elements of probabilistic seismic-hazard analysis (psha) were established almost four decades ago and psha has now become the most widely used approach for estimating seismic-design loads. Although the use of psha is widespread, considerable confusion remains regarding the details of how the calculations should be performed. This situation is largely a result of the way the discipline of psha evolved through a series of articles, reports, and software packages. This article demonstrates that the feature of psha about which there is perhaps the greatest degree of misunderstanding is the treatment of the aleatory variability in ground- motion prediction equations, which exerts a very pronounced influence on the calculated hazard. Probabilistic hazard studies performed in recent years have frequently resulted in appreciably higher design ground motions than had been obtained in previous assessments carried out in the 1970s and 1980s, often sparking controversial debate. Although several factors may contribute to the higher estimates of seismic hazard in modern studies, the main reason for these increases is that in the earlier studies the ground-motion variability was either completely neglected or treated in a way that artificially reduced its influence on the hazard estimates.

Why Do Modern Probabilistic Seismic-Hazard Analyses Often Lead to Increased Hazard Estimates?

We present a new three-dimensional (3D) compressional wavespeed ( V p) model for the Parkfield region, taking advantage of the recent seismicity associated with the 2003 San Simeon and 2004 Parkfield earthquake sequences to provide increased model resolution compared to the work of Eberhart-Phillips and Michael (1993) (epm93). Taking the epm93 3D model as our starting model, we invert the arrival-time data from about 2100 earthquakes and 250 shots recorded on both permanent network and temporary stations in a region 130 km northeast–southwest by 120 km northwest–southeast. We include catalog picks and cross-correlation and catalog differential times in the inversion, using the double-difference tomography method of Zhang and Thurber (2003). The principal V p features reported by epm93 and Michelini and McEvilly (1991) are recovered, but with locally improved resolution along the San Andreas Fault (saf) and near the active-source profiles. We image the previously identified strong wavespeed contrast (faster on the southwest side) across most of the length of the saf, and we also improve the image of a high V p body on the northeast side of the fault reported by epm93. This narrow body is at about 5- to 12-km depth and extends approximately from the locked section of the saf to the town of Parkfield. The footwall of the thrust fault responsible for the 1983 Coalinga earthquake is imaged as a northeast-dipping high wavespeed body. In between, relatively low wavespeeds (<5 km/sec) extend to as much as 10-km depth. We use this model to derive absolute locations for about 16,000 earthquakes from 1966 to 2005 and high-precision double-difference locations for 9,000 earthquakes from 1984 to 2005, and also to determine focal mechanisms for 446 earthquakes. These earthquake locations and mechanisms show that the seismogenic fault is a simple planar structure. The aftershock sequence of the 2004 mainshock concentrates into the same structures defined by the pre-2004 seismicity, confirming earlier observations (Waldhauser et al. , 2004) that the seismicity pattern at Parkfield is long lived and persists through multiple cycles of mainshocks.

Online material : 3D V p model and earthquake relocations.

/pdf/three-dimensional-compressional-wavespeed-model-earthquake-4xsedka7lo.pdf

Three-Dimensional Compressional Wavespeed Model, Earthquake Relocations, and Focal Mechanisms for the Parkfield, California, Region

The National Strong Motion Observation Network System (NSMONS) of China is briefly introduced in this paper. The NSMONS consists of permanent free-field stations, special observation arrays, mobile observatories and a network management system. During the Wenchuan Earthquake, over 1,400 components of acceleration records were obtained from 460 permanent free-field stations and three arrays for topographical effect and structural response observation in the network system from the main shock, and over 20,000 components of acceleration records from strong aftershocks occurred before August 1, 2008 were also obtained by permanent free-field stations of the NSMONS and 59 mobile instruments quickly deployed after the main shock. The strong motion recordings from the main shock and strong aftershocks are summarized in this paper. In the ground motion recordings, there are over 560 components with peak ground acceleration (PGA) over 10 Gal, the largest being 957.7 Gal. The largest PGA recorded during the aftershock exceeds 300 Gal.

http://zgkjcx.com/Article/UploadFiles/201303/李小军论文专著－英文6.pdf

Strong motion observations and recordings from the great Wenchuan Earthquake

The Mw 6.0 Parkfield earthquake struck central California at 17:15:14 UTC on 28 September 2004. The epicenter was located 11 km southeast of the rural town of Parkfield, adjacent to Gold Hill and on the San Andreas Fault (Figure 1). The California Integrated Seismic Network (CISN) reported that the hypocenter was located at 35.819°N, 120.364°W at a depth of 8.8 km. From the distribution of aftershocks and from models of seismograms, strain changes, and geodetic displacements from the earthquake, it appears that the rupture propagated to the northwest along the San Andreas Fault from its hypocenter beneath Gold Hill to Middle Mountain. Because of the earthquake's moderate size and the low population density, only minimal damage was reported, but strong ground motions of approximately 1 g were recorded at a few isolated points (Shakal et al. , 2005, this issue).

The 2004 Parkfield earthquake is the sixth of a series of historical events located on this reach of the San Andreas Fault; similar-sized earthquakes occurred in 1881, 1901, 1922, 1934, and 1966 (Bakun and McEvilly, 1984). Because of the frequency of moderate-sized earthquakes in the same locality, the Parkfield Prediction Experiment (Bakun and Lindh, 1985) was initiated in the mid-1980's, with cooperation between the U.S. Geological Survey (USGS), the California Geological Survey (CGS), and various universities to instrument the area densely to capture a future earthquake. In addition to enlarging the seismic network with more short-period, broadband, and strong-motion instruments, other instruments were installed that are unique to this experiment. These instruments include borehole strainmeters, Global Positioning System (GPS) receivers, a borehole seismic network, creepmeters, a telluric array, magnetometers, and fluid-pressure sensors (Roeloffs and Langbein, 1994). The goal of the experiment was to capture the complete earthquake cycle: the interseismic period, the actual earthquake, and the postseismic response. The …

Preliminary Report on the 28 September 2004, M 6.0 Parkfield, California Earthquake

The 2004 Mw 60 Parkfield earthquake of 28 September 2004 occurred on the San Andreas Fault near the small town of Parkfield in central California As a result of a widely accepted likelihood of an earthquake in the area, a large number of strong-motion stations and other types of seismic stations had been deployed in the area

The Parkfield earthquake occurred along the same segment of the San Andreas Fault that ruptured during the 1966 Parkfield earthquake, resulting in a unique set of strong-motion measurements by arrays designed specifically for the purpose of recording an event along this fault segment The most extensive and dense set of near-fault strong-motion recordings yet obtained for any earthquake in California was obtained in this event This paper provides a detailed description of the arrays and the resultant strong-motion measurements of the mainshock, as well as preliminary observations We also invite interested parties to participate in the Turkey Flat blind prediction experiment, described later in the paper More general preliminary seismological results for this earthquake can be found in Langbein et al (2005, this issue)

During the Parkfield earthquake, a total of 56 three-component strong-motion recordings of acceleration were obtained within 20 km of the fault, with 48 of these being within 10 km of the fault The strong-motion measurements by the Parkfield strong-motion array in the near-fault region are highly varied, with significant variations over relatively short distances A map of near-fault peak acceleration (Figure 1) shows striking variations over only a few kilometers The map also shows a concentration of strong shaking at both ends of the fault

Measurements in the near-fault region range from 013 g to more than 25 g (which may be the highest acceleration recorded to date) The largest peak accelerations occurred near the northwest end …

Preliminary Analysis of Strong-motion Recordings from the 28 September 2004 Parkfield, California Earthquake

Over decades, the Eldorado National Forest landscapes have experienced multiple disturbances including numerous events of wildfires, flooding, atmospheric river drenching, and rapid snowmelt which have promoted landslide activity over a palimpsest of forest management activities and post-fire recovery. LiDAR provides a very effective way to identify unstable landforms and capture the occurrence of mass wasting over broad regions rapidly. Lidar facilitates an accurate and detailed identification and mapping of mass wasting features. Multitemporal lidar was used to identify mass wasting features and judge their activity in relation to various managed forest conditions due to a series of stressing storms that triggered widespread landslides in 2017, resulting in a federal disaster declaration. Three pre-storm lidar datasets that covered previously burned areas were compared to a post-2017 storm survey to reveal triggered slope movements in separate disturbed slopes that burned in 1992, 2004, and 2014 where two generations of aerial lidar data exist. We used lidar differencing techniques to reveal differences in slope response based on the length of the recovery time since disturbance at intervals of 3, 13, 25, and 34 years. Results will reveal the effects of vegetation change and management actions on slope stability. 

Storm induced mass wasting on disturbed slopes across a thirty-four year timeline

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Preliminary Analysis of Strong-motion Recordings from the 28 September 2004 Parkfield, California Earthquake

Storm induced mass wasting on disturbed slopes across a thirty-four year timeline