Situated as the eastern boundary of the Sichuan-Yunnan block, the Xianshuihe fault system exhibits a notably high left-lateral strike-slip rate, establishing itself as one of the most active regions for seismic activity in the Chinese mainland, profoundly influencing the occurrence of large earthquakes within the region. The fault zone and its surrounding area are relatively densely populated, intersecting with the famous Sichuan-Xizang National Highway No. 317 and No. 318 and serving as a significant focal point in the design of the Sichuan-Xizang railway. Given its substantial seismogenic capacity and associated earthquake risk, notable attention is warranted. Notably, on September 5, 2022, a left-lateral strike-slip MS6.8 earthquake struck Luding County, Ganzê Prefecture, Sichuan Province, rupturing the Moxi fault of the Xianshuihe fault zone within the southeastern margin of the Qinghai-Xizang Plateau. Our study used Sentinel-1 SAR images to obtain both the interseismic deformation (2014-2020) and coseismic deformation resulting from the 2022 Luding M6.8 earthquake. Furthermore, we estimated the fault slip rate and locking depth during interseismic periods and inverted the coseismic slip distribution model. Utilizing the co-seismic dislocation model, we quantified Coulomb stress changes on surrounding fault planes induced by the Luding event. Finally, we provide an in-depth discussion on the seismogenic structure of the Luding earthquake and offer insights into the future seismic hazard implications associated with the Moxi fault and its adjacent faults.
We collected Sentinel-1 SAR imagery data spanning from October 2014 to April 2020 for both the descending orbit T135 and ascending orbit T026, and calculated the Line-of-Sight(LOS)direction deformation during the interseismic period covering the Moxi Fault of the Xianshuihe fault zone. The InSAR-derived interseismic deformation presented in this study effectively captures the long-term slip behavior of the seismogenic fault associated with the 2022 Luding earthquake. Our analysis reveals an aestimated slip rate of(5.9±1.8)mm/yr along the Moxi Fault. Combined with the GNSS and InSAR deformation observations, we generated a fused three-dimensional deformation field characterized by high density and precision. Additionally, we calculated the strain rate field based on the three-dimensional deformation within the study area. Our findings indicate pronounced shear deformation near the Moxi Fault, with strain highly concentrated along the fault trace. Notably, the strain concentration in the southern section of the Moxi Fault surpasses that observed in the northern section before the earthquake event. Furthermore, our analysis suggests that the Moxi Fault was locked at shallow depths before the earthquake occurrence, indicating a predisposition for seismic activity. The Luding earthquake thus transpired within the context of a seismically active background associated with the Moxi Fault.
Following the 2022 Luding 6.8 earthquake, we acquired InSAR coseismic deformation data within the seismic region, revealing predominantly horizontal surface displacements induced by the event. Employing the Most Rapid Descent Method(SDM), we conducted inversion of the fault plane slip distribution resulting from the earthquake. Our analyses indicate maximal dislocation quantities located south of the central earthquake zone, indicative of predominantly pure strike-slip movement. Dislocations are primarily observed at depths ranging between 5km to 15km, with the maximum left-lateral strike-slip dislocation measuring 1.71m and occurring at a depth of approximately 10km. In the north of the epicenter, fault slip manifests as predominantly sinistral strike-slip motion with a partial thrust component, exhibiting a progressively deepening slip pattern towards the northern region.
Utilizing the coseismic slip distribution derived from the 2022 Luding MS6.8 earthquake, we conducted calculations to assess the Coulomb stress changes induced by the coseismic dislocation effects across the fault plane of the Moxi Fault and its surrounding major fault zones. These fault zones include the Xianshuihe fault zone(comprising the Moxi, Yalahe, Selaha, Zheduotang, and Kangding segments), the Anninghe fault zone(encompassing the Shimian-Mianning and Mianning-Xichang segments), the Zemuhe Fault zone, and the Daliangshan fault zone(comprising the Zhuma, Gongyihai, Yuexi, Puxiong, Butuo, and Jiaojihe segments).Our analysis reveals that the Luding earthquake caused a substantial decrease in Coulomb stress within its rupture section, resulting in the formation of a stress shadow area in the southern segment of the Moxi Fault. However, it significantly increased the Coulomb stress in the northern section of the Moxi Fault that was not ruptured in the earthquake. Concurrently, the Coulomb stress on the fault plane increases significantly in the southeast section of the Zheduotang fault, the northwest section of the Shimian-Mianning segment of the Anninghe fault zone, as well as the southeast section of the Zhuma segment, and the southeast section of the Gongihai segment of the Daliangshan fault zone.
The seismogenic structure of the 2022 Luding earthquake is a part of the Moxi Fault of the Xianshuihe fault zone. However, the magnitude and rupture length of the earthquake are significantly smaller than that of the Moxi M7$\frac{3}{4}$ earthquake in 1786, resulting in a less pronounced stress unloading effect. Additionally, the Luding earthquake triggered a noteworthy increase in Coulomb stress along the northern segment of the Moxi Fault. Consequently, the Luding earthquake did not ultimately reduce the seismic hazard within the Xianshuihe fault zone. Thus, greater attention should be directed towards the unruptured section of the Moxi Fault and its adjoining rupture with the background of large earthquakes.
Coseismic surface rupture length is one of the critical parameters for estimating the moment magnitude based on the empirical relationships and later used in assessing the potential seismic risk of a region. On 22 May 2021, the MW7.4 Madoi earthquake occurred in the northeastern part of the Tibetan plateau(Madoi County in Qinghai Province, China)and ruptured the poorly known Jiangcuo Fault along the extension line of the southeastern branch of the Kunlun Fault. We began our data acquisition using aerial photogrammetry by UAV three days after the earthquake. Between 24 May and 15 June 2021, more than 40000 high-resolution low-altitude aerial photos were acquired covering a total length of 180km along the surface rupture. Based on detailed field investigations, combined with a fine interpretation of sUAV-derived orthophotos and high-resolution DEMs, we determined a total length of~158km of the coseismic surface rupture extending to the eastern end at 99.270°E, which is basically consistent with the position given by previous geophysical methods. Although the extending segment is located beyond the end of the continuous surface rupture trace near Xuema Township, it should be included in the calculation of the length of the surface rupture as part of the tectonic surface rupture. The surface rupture is segmented into four sections, named from west to east: the Eling Lake, Yematan, Yellow River, Jiangcuo branch sections. Additionally, to the east of Dongcaoa’long Lake, we mapped semi-circular arc-shaped continuous tension-shear fractures in the dune area with a short gap(~3km)connecting to the east of the Jiangcuo branch. The surface ruptures along the southeastern Youyunxiang segment also sporadically appear in several sites, locally relatively continuous, covered by the sand dune with vertical displacements of up to 30cm. After passing through the dunes, the surface rupture of the Youyunxiang segment began to spread widely, extending continuously with a strike of nearly east-west. However, it should be noted that the rupture lengths of the Youyunxiang segment and other branches are not counted in the total earthquake rupture length. By comparing the current research results, we believe that the critical factors causing the significant differences of the measured length of coseismic surface ruptures would depend on: 1)more extensive and detailed field investigations combined with a fine interpretation of high-resolution images; 2)avoidance of repeated calculation of superimposed sections on both sides of the complex geometrical area. In this study, combined with the fine interpretation of high-precision image data, many surface rupture traces in the dunes of the Youyunxiang segment were identified(verified and confirmed by field inspection)and more continuous surface rupture segments on the F1 fault, which is difficult to reach by human beings, were discovered, also highlights the important role of digital photogrammetry in the study of active tectonics. The studies of the strong historical earthquakes around the Bayan Har block show that the coseismic surface rupture length is larger than that estimated by the empirical relationships. Further research thus is highly necessary to uncover its mechanism and indicative significance.
Earthquake surface ruptures are the key to understand deformation pattern of continental crust and rupture behavior of tectonic earthquake, and the criteria to directly define the active fault avoidance zone. Traditionally, surface fissures away from the main rupture fault are usually regarded as the result triggered by strong ground motion. In recent years, the earth observation technology of remote sensing with centimeter accuracy provides rich necessary data for fine features of co-seismic surface fractures and fissures. More and more earthquake researches, such as the 2019 MW7.3 Ridgecrest earthquake, the 2016 MW7 Kumamoto earthquake, the 2020 MW6.5 Monte Cristo Range earthquake, suggest that we might miss off-fault fissures associated with tectonic interactions during the seismic rupture process, if they are simply attributed to effect of strong ground motion. Such distribution pattern of co-seismic surface displacement may not be isolated, it encourages us to examine the possible contribution of other similar events. The 22 May 2021 MW7.4 Madoi earthquake in Qinghai Province, China ruptured the Jiangcuo Fault which is the extension line of the southeastern branch of the Kunlun Fault, and caused the collapse of the Yematan bridge and the Cangmahe bridge in Madoi County. The surface rupture in the 2021Madoi earthquake includes dominantly ~158km of left-lateral rupture, which provides an important chance for understanding the complex rupture system. The high-resolution UAV images and field mapping provide valuable support to identify more detailed and tiny co-seismic surface deformation. New 3 to 7cm per pixel resolution images covering the major surface rupture zone were collected by two unmanned aerial vehicles (UAV) in the first months after the earthquake. We produced digital orthophoto maps (DOM), and digital elevation models (DEM) with the highest accuracy based on the Agisoft PhotoScanTM and ArcGIS software. Thus, the appearance of post-earthquake surface displacement was hardly damaged by rain or animals, and well preserved in our UAV images, such as fractures with small displacement or faint fissures. These DOM and DEM data with centimeter resolution fastidiously detailed rich details of surface ruptures, which have been often easily overlooked or difficult to detect in the past or on low-resolution images. In addition, two large-scale dense field investigation data were gathered respectively the first and fifth months after the earthquake. Based on a lot of firsthand materials, a comprehensive dataset of surface features associated with co-seismic displacement was built, which includes four levels: main and secondary tectonic ruptures, delphic fissures, and beaded liquefaction belts or swath subsidence due to strong ground motion. Using our novel dataset, a complex distributed pattern presents along the fault guiding the 158km co-seismic surface ruptures along its strike-direction. The cumulative length of all surface ruptures reaches 310km. Surface ruptures of the MW7.4 Madoi earthquake fully show the diversity of geometric discontinuities and geometric complexity of the Jiangcuo Fault. This is reflected in the four most conspicuous aspects: direction rotation, tail divarication, fault step, and sharp change of rupture widths. We noticed that the rupture zone width changed sharply along with its strike or geometric complexity. Near the east of Yematan, on-fault ruptures are arranged in ten to several hundred meters. Besides clearly defined surface ruptures on the main fault, many fractures near the Dongo section and two rupture endpoints are mainly along secondary faulting crossing the main fault or its subparallel branches. Lengths of fracture zones along two Y-shaped branches at two endpoints are about 20km. At the rupture endpoints, the fractures away from the main rupture zone are about 5km. Some authors suggested the segment between the Dongcao along lake and Zadegongma was a “rupture gap”. In our field investigation, some faint fractures and fissures were locally observed in this segment, and these co-seismic displacement traces were also faintly visible on the UAV images. It is also worth noting that near the epicenter, Dongo, and Huanghexiang, a certain amount of off-fault surface fissures appear locally with steady strike, good stretch, and en echelon pattern. Some fissures near meanders of the Yellow River, often appear with beaded liquefaction belts or swath subsidences. In cases like that, fissure strikes are, in the main, orthogonal to the river. Distribution pattern of these fissures is different from usual gravity fissures or collapses. But they can’t be identified as tectonic ruptures because clear displacement marks are always absent with off-fault fissures. Therefore, it is difficult to determine the mechanism of off-fault co-seismic surface fissures. Some research results suggested, that during the process of a strong earthquake, a sudden slip of the rupturing fault can trigger strain response of surrounding rocks or previous compliant faults, and result in triggering surface fractures or fissures. Because of regional tectonic backgrounds, deep-seated physical environments, and site conditions(such as lithology and overburden thickness), the pattern and physicalcause of co-seismic surface ruptures vary based on different events. Focal mechanisms of the mainshock and most aftershocks indicate a near east-west striking fault with a slight dip-slip, but focal mechanisms of two MS≥4.0 aftershocks show a thrust slip occurring near the east of the rupture zone. On the 1︰250000 regional geological map, the Jiangcuo Fault is oblique with the Madoi-Gande Fault and the Xizangdagou-Cangmahe Fault at wide angles, and with several branches near the epicenter and the west endpoint at small angles. Put together the surface fissure distribution pattern, source parameters of aftershocks and the regional geological map, we would like to suggest that besides triggered slip of several subparallel or oblique branches with the Jiangcuo Fault, inheritance faulting of pre-existing faults may promote the development of off-fault surface fissures of the 2021Madoi earthquake. Why there are many off-fault distributed surface fissures with patterns different from the gravity fissures still needs further investigation. The fine expression of the distributed surface fractures can contribute to fully understanding the mechanism of the seismic rupture process, and effectively address seismic resistance requirements of major construction projects in similar tectonic contexts in the world.
After an earthquake, earthquake emergency response and rescue is one of the effective ways to reduce casualties from the earthquake. Earthquake emergency disaster information is one of crucial factors to effectively guide the rescue work. However, there is a "black box effect" on the emergency disaster information acquisition after an earthquake, which means real-time earthquake disaster information is insufficient. Hazard estimates are usually used as a substitute for the real-time disaster information in the "black box" period. However, it is subject to the accuracy and speed of the estimation. The development of the km grid technology provides good prospect to solve this problem. The paper suggests to develop earthquake disaster information pre-estimation data with the support of the km grid technology. The definition and source of the pre-estimation data are introduced and its possibility in improving the estimation speed and accuracy are analyzed theoretically. Then, we elaborate the calculation model of the pre-estimation data. The framework of the model includes disaster-bearing body data, disaster-causing factors used in calculation and calculation formula. The disaster-bearing body data in km grid format are introduced, including population data in km grid format and building data in km grid format. Then the four elements of the earthquake(earthquake occurrence time, earthquake location, earthquake magnitude and focal depth)are selected as disaster-causing factors for calculation. Map algebra method is used to realize the calculation model in which calculation parameters are associated with base map in the km grid format. So the pre-estimation data are developed by python and ArcGIS, which includes building damage dataset(100 layers), death toll dataset(10 layers)and direct economic loss dataset(5 layers). Finally, the pre-estimation data based method for earthquake emergency disaster information estimation is presented. With the support of this method, two real earthquake cases are used to validate the effect of the pre-estimation data. The validation results show the pre-estimation data can not only significantly improve the speed of the estimation but also greatly improve the accuracy of the estimation. Another good result is found in the validation process that with the support of the pre-estimation data, the estimated result can display the spatial distribution of the disaster information, which will effectively aid earthquake emergency response and rescues.
The earthquake disaster rapid assessment(EDRA)is the core technical support for the post-earthquake emergency response. At present, with the popularization of high-precision population, social and economic data, most of the subordinate units of China Earthquake Administration(CEA)have heightened the precision of hazard bearing body data used in EDRA from the original county-level precision to the 30″×30″ precision. However, while the precision of fundamental data has been heightened, no efforts have been made to improve the main algorithms and the technical process of EDRA. It turns out that the assessment has become more accurate, but the problems of the time-consuming process(10-20 minutes, probably 20 minutes or more in great earthquakes)and the low-precision losses distributions that exposed in EDRA supported by county-level precision data remain unresolved.This paper introduces the high-precision(30″×30″)hazard bearing body data, and describes the principle of EDRA and its implementation under the support of county-level precision data at first. Then the paper elaborates the principle of improving EDRA's data foundation using high-precision hazard bearing body data, the principle of improving the computation efficiency and persisting the data precision in the assessment process by means of the cell-to-cell grid algebraic operation, and the method for improving the assessment speed through the segmentation and reorganization of the technical process of EDRA.It is validated that through the improvements, the EDRA has become more accurate and much less time-consuming(less than 1 minute), and is able to output high-precision(30″×30″)distributions of seismic losses. The high-precision hazard bearing body data of wide range are the simulated data but not the survey data. Though the data have been simulated based on the census data, there is still a gap between their accuracy and the real situation. Further research and optimization on the data are needed.
China is a country prone to serious earthquake disaster. After an earthquake, earthquake emergency and rescue are very important for the disaster relief, which is also one of three earthquake disaster mitigation jobs led by China Earthquake Administration. In earthquake emergency fields, earthquake preplans and GIS-based earthquake emergency command systems are the main researches and work. How to increase the intelligence and pertinence of the systems and preplans is an important and difficult issue in this area. Earthquake emergency decision-making knowledge provides a possible solution method. The modeling of earthquake emergency decision-making knowledge is the foundation for its use. We analyze the semantic need of earthquake emergency decision-making knowledge modeling. From the perspective of geospatial knowledge modeling, the earthquake emergency knowledge modeling primitives are put forward, which are adapted from geospatial knowledge modeling primitives. Using geo-ontology as the foundation, the earthquake emergency knowledge modeling primitives include: abstract geospatial modeling primitives, geographic modeling primitives and earthquake emergency field modeling primitives. A framework model for the earthquake emergency knowledge is proposed and according to the knowledge granularity the framework is divided into the earthquake emergency basic knowledge level, earthquake emergency rule knowledge level and earthquake emergency procedural knowledge level. Then the modeling of the earthquake emergency rule knowledge is discussed, which is composed of rule conditions and rule actions. Meanwhile, the modeling of the earthquake emergency procedural knowledge is introduced based on workflow method and consists of work nodes, control nodes and data nodes. Finally, Suzhou intelligent earthquake emergency decision-making assisting system is developed, in which several earthquake emergency decision-making knowledge are used. The protégé and ArcEngine software packages are used to realize the earthquake emergency knowledge modeling and application. Through the application system, the usage of framework model is demonstrated.
The hazard grade assessment,which simply and clearly reveals how big the damage is,is an important part of emergency response and rescue work after disaster. Upon collection and sorting out of the data on Asian natural disasters occurring between 1900 and 2011,this paper studies the method of classifying those disasters. After discussing the definition of catastrophe and that of earthquake-affected population and exploring the basis on which catastrophe could be classified,this paper comes up with a formula,in which the logarithms of three factors,death toll,direct economic loss and quake-affected population,are summed up. Then,Asian catastrophes are classified by the formula. The calculation based on the formula shows that the results of 54 of all the disasters are above 10.0,102 above 9.0 and 178 above 8.0.After repeated comparison with data from several other disaster databases,it is concluded that the result achieved by the formula of the disaster which is generally considered as a catastrophe,is above 8.0.Therefore,a disaster with a result above 8.0 is defined as a catastrophe. The formula mentioned above in this paper is simple and convenient,and is suitable for making a comparison of the damage caused by the disasters of different types in different regions in Asia.