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Wang L.,University of Potsdam | Wang L.,China Earthquake Networks Center | Hainzl S.,German Research Center for Geosciences | Zoller G.,University of Potsdam | Holschneider M.,University of Potsdam
Journal of Geophysical Research: Solid Earth

[1] Both aftershocks and geodetically measured postseismic displacements are important markers of the stress relaxation process following large earthquakes. Postseismic displacements can be related to creep-like relaxation in the vicinity of the coseismic rupture by means of inversion methods. However, the results of slip inversions are typically non-unique and subject to large uncertainties. Therefore, we explore the possibility to improve inversions by mechanical constraints. In particular, we take into account the physical understanding that postseismic deformation is stress-driven, and occurs in the coseismically stressed zone. We do joint inversions for coseismic and postseismic slip in a Bayesian framework in the case of the 2004 M6.0 Parkfield earthquake. We perform a number of inversions with different constraints, and calculate their statistical significance. According to information criteria, the best result is preferably related to a physically reasonable model constrained by the stress-condition (namely postseismic creep is driven by coseismic stress) and the condition that coseismic slip and large aftershocks are disjunct. This model explains 97% of the coseismic displacements and 91% of the postseismic displacements during day 1-5 following the Parkfield event, respectively. It indicates that the major postseismic deformation can be generally explained by a stress relaxation process for the Parkfield case. This result also indicates that the data to constrain the coseismic slip model could be enriched postseismically. For the 2004 Parkfield event, we additionally observe asymmetric relaxation process at the two sides of the fault, which can be explained by material contrast ratio across the fault of ∼ 1.15 in seismic velocity. © 2012. American Geophysical Union. Source

This paper studied the water temperature changes caused by the Earth tide, based on 356 water temperature monitoring wells from the Groundwater Monitoring Network of China. First, 35 wells were selected since they had tidal responses from water temperature data. Then, harmonic analysis was performed to the water temperature data to derive Earth tide constituents (M2, S2, K2, O1, P1, S1, K1), using the Baytap-G software. The result showed that the amplitudes were 0.00017~0.01825°C, the phase lags were -149.98°~61.47°, the amplitude ratios were 0.01~10°C/10-6m · s-2, for the M2 Earth tide constituent which was low contaminated. The tidal variations of water temperature were result from tidal variations of water level, since all the water levels that showed tidal variations and the amplitudes of water temperature in different depths of one well had similar order. Besides, the tidal variations of water temperature were influenced by the sun-radiation heat, water flow from the aquifer and geothermal gradient. The tidal variations of water temperature near the aquifer had greater amplitudes. The amplitudes of tidal variations of water temperature were proportional to the geothermal gradients. The tidal variations of water temperature could be more easily recorded in artesian wells than non-artesian wells, as the sun-radiation heat was an interference of tidal variations of water temperature and it had less influence on the changes of water temperature in artesian wells than non-artesian wells. The tidal variations of water temperature could be more easily recorded in the eastern China than the west, since the influence depths of sun-radiation heat in the gorge and mountain areas were deeper than plains. Source

Zhang G.-W.,Chinese Institute of Crustal Dynamics | Lei J.-S.,Chinese Institute of Crustal Dynamics | Liang S.-S.,China Earthquake Networks Center | Sun C.-Q.,Chinese Institute of Crustal Dynamics
Chinese Journal of Geophysics (Acta Geophysica Sinica)

Using the double-difference algorithm, we relocated the Ludian MS6.5 mainshock and its 647 aftershocks during 3 to 7 August 2014 and finally obtained 471 relocated earthquakes. Our results show that the focal depth of main shock is 13.3 km, which is close to the initial rupture depth of the main shock. The aftershock sequence presents an asymmetric conjugate shape with lengths of 17 km in the EW direction and of 22 km in the NW direction. Small earthquakes are predominately located above 10 km depth, and extend toward the shallow parts above 10 km depth along the southeast and eastwest directions of conjugate faults from the main shock. In addition, distribution of small earthquakes also shows that the seismogenic fault has a high dip and is the NW Baogunao-Xiaohe fault that is one branch of the Zhaotong-Ludian fault. Because the mainshock centroid depth can provide important evidence for understanding the serious disaster caused by the mainshock, we determined 5 focal mechanism solutions (MS≥4.0) including the main shock using the gCAP(generalized Cut And Paste) method. Our results show that the centroid depth of the main shock is only 5 km, which is consistent with the 2~8 km depth of larger slip in the obtained rupturing process. The conjugate rupture and shallower centroid depth of main shock could be the important causes for the serious disaster of this earthquake. Source

Zhang L.-K.,China Earthquake Networks Center | Niu A.-F.,China Earthquake Networks Center
Chinese Journal of Geophysics (Acta Geophysica Sinica)

Based on the double bushing borehole strain observation mechanical model, we deduced the calculation formulae of two coupling coefficients(A, B)of each strain component under plane stress. This provides a basis for further determining the value and direction of maximum and minimum principal strain of the crustal strain field, and has a positive meaning for carrying out borehole strain observation of earthquakes, volcanoes and plate boundaries. Using a two-ring model and the complex variable function method to calculate the c (area strain response coefficient) and d (shear strain response factor), A and c, B and d have a relationship as c=2A, d=2B. And the variation curves are identical. Their physical meanings are respectively the crust rock area strain and shear strain observation borehole coupling coefficient. Source

Xu C.,China Earthquake Administration | Xu X.,China Earthquake Administration | Yao Q.,China Earthquake Networks Center | Wang Y.,Northeast Normal University
Quarterly Journal of Engineering Geology and Hydrogeology

The main purpose of this research is to evaluate the modelling capability and predictive power of a bivariate statistical method for earthquake-triggered landslide susceptibility mapping. A weight index (Wi) model was developed for the 2008 Wenchuan earthquake region in Sichuan Province, China, using a wide range of optical remote sensing data, and carried out on the basis of a geographic information system (GIS) platform. The 2008 Wenchuan earthquake triggered 196007 landslides, with a total area of 1150.43 km2, in an approximately oblong area around the Yingxiu-Beichuan coseismic surface fault-rupture (the Yingxiu-Beichuan fault). The landslides of the study area were mapped using visual interpretation of high-resolution satellite images and aerial photographs, both pre- and post-earth-quake, and checked in the field at various locations. As a consequence, a nearly complete inventory of landslides triggered by the Wenchuan earthquake was constructed. Topographic and geological data and earthquake-related information were collected, processed and constructed into a spatial database using GIS and image processing technologies. A total of 10 controlling parameters associated with the earthquake-triggered landslides were selected, including elevation, slope angle, slope aspect, slope curvature, slope position, lithology, seismic intensity, peak ground acceleration (PGA), distance from the Yingxiu-Beichuan fault, and distance along this fault. To assist with the development of the model, the complete dataset of 196007 landslides was randomly partitioned into two subsets; a training data-set, which contains 70% of the data (137204 landslides, with a total area of 809.96 km2), and a testing dataset accounting for 30% of the data (58803 landslides, with a total area of 340.47 km2). A landslide susceptibility index map was generated using the training dataset, the 10 impact factors, and the Wi model. In addition, for a conditionally dependent factor analysis, seven other factor-combination cases were also used to construct landslide susceptibility index maps. Finally, these eight landslide suscep-tibility maps were compared with the training data and testing data to obtain model capability (success rate) and predictive power (predictive rate) information. The validation results show that the success and predictive rates of the Wi modelling exceeded 90% for the approaches that include the use of seismic factors. The final landslide susceptibility map can be used to identify and delineate unstable suscepti-bility-prone areas, and help planners to choose favourable locations for development schemes, such as infrastructure, construction and environmental protection schemes. The generic component of this research would allow application in other regions affected by high-intensity earthquakes and unstable terrain covering very large areas. © 2013 The Geological Society of London. Source

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