Force history inverted from long-period seismic records for a landslide has been widely used to extract its physical parameters. Most previous studies have adopted the point-source constant-mass landslide model during the inversion. In this study, we quantitatively investigate the effects of mass entrainment at different locations along the sliding path during the interpretation of inversion results. To demonstrate our analysis, we carried out the long-period seismic waveform inversion for the 2003 Qianjiangping landslide to obtain its force history and subsequently estimated its movement parameters. We propose a mass entrainment model based on the conservation of kinetic energy. The predictions of our mass entrainment model are verified using the inversion results of the Qianjiangping landslide and other events. Results from our mass entrainment model suggest that when half of the sliding mass is entrained at different locations along the sliding path, the estimated masses and maximum velocities vary between 50–100

2022年1月15 日汤加火山剧烈喷发产生了波及全球的大气重力波,距离火山8 736～12 758 km的中国大陆所有地应变观测站清晰记录到由此产生的短时地表应变变化.应用小波分析方法系统分析了中国近200个地应变观测站记录数据的时空响应与频率特征,主要表现为:由大气重力波激发的短时地表应变变化的持续时间约为1.5 h,其中能量最强的变化集中在前40 min,面应变平均变幅约为186×10-10,呈现出单脉冲起伏状变化,形态具有很强的一致性,具备兰姆波传播属性;短时地表应变变化的平均传播速度约为310 m/s,与大气重力波传播速度基本一致.部分观测站还记录到绕地球一圈后再次到达的大气重力波对地表的作用.这是首次通过大范围布设的高精度地应变观测仪记录到大气重力波作用于地表的痕迹,有助于认识地壳运动和大气圈层相互影响的机制.

四川省阿坝州理县蒲溪乡河坝村后山边坡属于老滑坡区,2014年6月以来,出现地表拉裂、鼓胀、下挫及挡墙剪切错断等现象,并不断加剧恶化,严重威胁当地民众安全.为预防滑坡灾害,当地政府在边坡前修建防护坝.为评估该防护工程效果,获取6个新建GNSS观测点实时变形观测数据,运用灰色关联法,明确降水变率是造成该区形变的主要因素,进而采用边坡变形量行业常用GM(1,1)模型,预测可能的边坡形变量,并与GNSS观测点实测值对比,结果表明,在防护坝建成1年7个月后,边坡变形速率逐渐减缓,防护工程治理效果显现.

Earth and Space Science Open Archive This preprint has been submitted to and is under consideration at Geophysical Research Letters. ESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]On rebuilding landslide parameters from long-period seismic waveform inversionAuthorsXiaoWangXinghuiHuangiDPoCheniDLeiXuHengWangWenzeDengDanYuZhengyuanLiQiangXuSee all authors Xiao WangChina Earthquake Networks Centerview email addressThe email was not providedcopy email addressXinghui HuangiDCorresponding Author• Submitting AuthorChina Earthquake Networks CenteriDhttps://orcid.org/0000-0002-0493-1350view email addressThe email was not providedcopy email addressPo CheniDUniversity of WyomingiDhttps://orcid.org/0000-0002-5148-9788view email addressThe email was not providedcopy email addressLei XuThe 7th Institute of Geology & Mineral Exploration of Shandong Provinceview email addressThe email was not providedcopy email addressHeng WangUniversity of Wyomingview email addressThe email was not providedcopy email addressWenze DengChina Earthquake Networks Centerview email addressThe email was not providedcopy email addressDan YuChina Earthquake Networks Centerview email addressThe email was not providedcopy email addressZhengyuan LiChina Earthquake Networks Centerview email addressThe email was not providedcopy email addressQiang XuState Key Laboratory of Geo-Hazard Prevention and Geo-Environment Protection, Chengduview email addressThe email was not providedcopy email address

The catastrophic Sanyanyu and Luojiayu debris flows, which were induced by heavy rain, struck Zhouqu County in Gannan Prefecture, Gansu Province, at approximately midnight, 7 August 2010 (Beijing time, UTC + 8), causing 1765 fatalities and huge economic loss. The ZHQ seismic station is located approximately 170 m west of the outlet of the Sanyanyu gully, and its power system was destroyed by the Sanyanyu debris flow when its leading edge reached the vicinity of the seismic station. In this paper, seismic signals recorded approximately 10 min before its termination are collected and analyzed to study the Sanyanyu debris flow. A double-exponential model is first proposed to quantitatively characterize seismic energy distributions in the frequency domain, which reveals that the peak frequency of seismic signals is around 5 Hz. Influenced by the Doppler effect, the peak frequency of the N–S component is the highest, and the U–D component is the lowest. Time–frequency analysis is applied to the seismic signals. From the spectrogram, it is easily observed that the formation time of the Sanyanyu debris flow is around 23:33:10. The entire debris flow is divided into three phases with distinct frequency characteristics, using 23:36:20 and 23:37:35 as crucial times. The frequency energy distributions in the first two phases are relatively stable, and are constrained in 0–8.8 Hz and 0–17.8 Hz, respectively. For the third phase, the upper boundary of frequency energy increases in a nearly linear manner, reaching approximately 35 Hz at the end. We calculate synthetic seismograms of the Sanyanyu debris flow. Generally, synthetic seismograms have morphological features and characteristics in key stages similar to those of the actual seismic records, and their maximum values are of the same magnitude. Our results suggest that the seismic source of a debris flow can be represented by a single-force model, and reveal that real-time monitoring and rapid identification of potential debris flows using broadband seismic network records is possible, which can provide approximately 15 min of pre-event warning for local residents and hopefully save many lives.

从仪器原理、传递函数和观测数据等方面分析目前在网进行1 Hz采样的VP型垂直摆倾斜仪在2～60 s周期内的频率特性,认为该仪器可以观测到频带内的信号变化,但因处于过渡带,观测幅度较真实幅度削弱约20～40 dB.对VP型垂直摆倾斜仪观测频带进行拓展,使2～60 s周期内的观测信号由之前的过渡带进入到仪器的通频带,结果与相同采样率的其他定点形变仪器的观测效果相同,将地倾斜观测量转换为加速度表达后,其幅频特性符合全球地震背景噪声模型.改进后的VP型垂直摆倾斜仪对于远距离震级不大的同震体波震相记录效果略优于改进前,但受地脉动影响,在识别非地脉动信号时需要采用更精细的方法和手段来提高识别效果.

On August 7th, 2010, Sanyanyu and Luojiayu debris flows triggered by a heavy rain have lashed Zhouqu City around midnight, leading to catastrophic destruction which killed 1765 people and resulted in enormous economic loss. The ZHQ Seismic Station is located approximately 170 m west of the outlet of the Sanyanyu Gully. The seismometer deployed at the seismic station started recording seismic signals of ever-enlarging amplitude around 10 minutes before the debris flow rushed out of the Sanyanyu Gully, showing ever approaching seismic source, i.e. the debris flow. In this study, we analyze this seismic event and propose an inversion algorithm to estimate the velocity of the debris flow by searching the best-fitting pairs of envelopes in the synthetic seismograms and the corresponding field seismic records in a least-square sense. Inversion results reveal that, before rushing out of the outlet, the average velocity of the debris flow gradually increased from 6. 2 m/s to 7. 1 m/s and finally reached 15 m/s at approximately 0. 5 km above the outlet and kept this value since then. Obviously, the ever-increasing velocity of the debris flow is the key factor for the following disasters. Compared with other studies, our approach can provide the velocity distribution for the debris flow before its outbreak; Besides, it has the potential to provide technological support for a better understanding of the disaster process of a debris flow.

A catastrophic landslide struck the Xiaoba village in Fuquan, Guizhou, southwestern China at about 8:30 p.m. (Beijing Time, UTC + 8) on August 27, 2014. The landslide and induced impulse water waves destroyed two villages and killed 23 persons. By reprocessing seismic signals from a seismic network deployed in the surrounding area of the landslide, we recognized the event from low-frequency seismic signals and subsequently performed a long-period seismic waveform inversion to obtain its force–time history. The inversion results reveal that the maximum force for the landslide is 5 × 109 N, and the duration of the landslide is 38.4 s. The landslide reached its maximum velocity of 12.4 m/s at 13.2 s after its initiation, and the mass center plugged into the quarry at 24.2 s. Based on the inversion results, we estimated basal friction of the landslide. We found the friction coefficient rapidly reduces to a relatively steady-state value of ~ 0.4 at a steady-state distance of 35 m and subsequently reduces in a near-linear manner that satisfies the empirical formula $$ \mu = - 1.4d + 0.44 $$, where $$ d $$ is sliding distance in km. The reduction in friction revealed by the formula is compatible with the finding of previous studies for landslides of similar volume in landslide acceleration stage. However, our result does not make it possible for the friction coefficient to increase again in landslide deceleration stage that a velocity-dependent friction law would allow. The friction variation patterns can be used to constrain input parameters in numerical landslide simulation, which can predicate runout distance and deposit areas for massive landslides to carry out landslide hazard assessment.

We analyse broadband seismic records generated by the massive Xinmo landslide that occurred in southwestern China at 5:39 on 24 June 2017 (Beijing Time, IJTC + 8). Characteristics of landslide seismic signals, including propagation velocity, duration and frequency contents, are presented and discussed by comparing them with seismic signals generated by a local earthquake of similar magnitude. We perform a long-period seismic waveform inversion in the frequency band of 0.01-0.1 Hz to acquire the landslide force history using 46 seismic traces from 21 seismic stations with distances from the epicentre extending to 360 km. Based on the inversion, we calculate the dynamic parameters of the landslide and recognize its stages and movement characteristics. Landslide basal friction coefficients are also acquired using both a constant dip and varying dips along the slope. A combined analysis of near-field short-period seismic records and dynamic inversion results indicates that the high-frequency energy of landslide signals is most likely generated by rock fragmentations during collision and scraping. (C) 2019 Elsevier B.V. All rights reserved.

为解决分析预报等相关专业软件访问前兆数据库时存在的性能与安全问题,本文设计了地震前兆数据库系统共享接口软件.该软件可以隔离数据库与应用程序,对应用程序的数据使用情况进行审计与控制,切断非法、低效的数据访问请求;同时,使用连接池、数据缓存和数据压缩等技术提高前兆数据的访问速度.软件无需安装Oracle客户端,易于使用,屏蔽了数据库表结构的复杂性.

A catastrophic landslide struck the Xinmo Village in Maoxian County, Sichuan Province, China, at approximately 5:39 a.m. on 24 June 2017 (Beijing Time, UTC+8). About 4.3 million m(3) of rock detached from the crest of the mountain, entrained a large amount of pre-existing deposits, and destroyed the whole village after sliding about 2.6 km along the slope, resulting in serious casualties and property losses. We performed a waveform inversion of the long-period seismic signals extracted from 10 broadband seismic stations around the event to obtain its force time history. The location of this event was also simultaneously acquired using a stepwise refined grid search approach, with a negligible error. We calculated kinetic parameters of the sliding material from the inverted force time history and the deduced runout trajectories were consistent with the morphology. Combined analysis of the seismic signals, force time history, and kinetic parameters revealed that major movement of the landslide lasted approximately 79 s. A large intact rock volume detached at 5:38:50.2 and started accelerating afterward, until it reached its peak velocity of 52.1 m.s(-1) at 5:39:37.2. No significant fragmentation of the rock could be observed during this time period. Subsequently, the sliding rock mobilized and entrained a large amount of debris of an old landslide deposit along the path and fragmented in the same time. The sliding material started decelerating and finally stopped at 5:40:9.2. Small scale scattering of debris lasted for around 10 more seconds after the stop of the major movement.

The catastrophic Sanyanyu and Luojiayu debris flows, which were induced by heavy rainfall, occurred at approximately midnight, August 7th, 2010 (Beijing time, UTC + 8) and claimed 1,765 lives. Most seismic stations located within 150 km did not detect the debris flows except for the closest seismic station, ZHQ, indicating that the seismic signals generated by the debris flows decayed rapidly. We analyzed broadband seismic signals from the ZHQ seismic station, beginning approximately 20 min before the outbreak of the Sanyanyu debris flow, to rebuild its evolution processes. Seismic signals can detect development of the Sanyanyu debris flow approximately 20 min after a heavy rain started falling in its initiation area; this time was characterized by a gradual increase in seismic amplitude accompanied by a series of spike signals that were probably generated by rock collapses within the catchment. The frequency contents and the characteristics of seismic signals before and after 23:33:15 (T-1) are distinctively different, which we interpret as being generated by a large quantity of flowing material entering the main channel, marking the formation of the Sanyanyu debris flow. We attribute seismic amplitude increases between 23:33:15 (T-1) and 23:34:26 (T-2) and between 23:35:40 (T-3) and 23:36:49 (T-4) to entrainment of the deposit material after initiation of the debris flow and to its flow through a colluvial deposit area, respectively. The main frequency band broadening of seismic signals after 23:37:30 (T-5) is believed to have been induced by impacts between the flowing material and check dams.

In order to further improve the management level of the National Earthquake Precursory Observation Networks of China,and evaluate rapidly and scientifically the quality of digital observation data on the basis of the current subject evaluation methods,the data quality evaluation method of the Earthquake Precursory Observation Networks are studied.A set of data quality evaluation index associated with data integrity,noise level,solid tidal effect,consistency and other aspects is obtained,and then the data quality evaluation method of the Earthquake Precursory Observation Networks is established with the help of standardized treatment and weighted average methods.Application results show data quality indexes of the evaluation method is relatively comprehensive and reasonable.The evaluation results are basically consistent with the actual situation of the networks data quality.The evaluation method has been used in the national regional precursory network appraisal work.The study lays a foundation for the rapid assessment and quality classification of the Earthquake Precursory Observation Networks.

Firstly,in this paper we outline the overall design framework of GNSS data product platform.And then we introduce an important module,GNSS data collection software.Further,following the introduction of Secure File Transfer Protocol (SFTP),we design and realize the gather software based on SFTP.The work mentioned above ensures the data security and platform construction.

GNSS地震数据中心建成后将作为地震行业GNSS原始数据汇集和产品对外服务的重要平台,因此,对其建设方案的研究设计是一项基础核心工作.本文主要对该数据中心的系统架构、设计模式、数据采集、以及数据安全四个方面进行了方案研究与实践.此方案保证了平台架构的稳定性、技术的先进性和数据的安全性,为项目的顺利建设与运行提供了有效保障与指导.

This paper first presents a BDS/GPS damped LAMBDA algorithm,then introduces a realtime remote deformation monitoring system based on this algorithm.We take the slope deformation monitoring system of Lixian slope for example:BDS has more visible satellites and more stable PDOP values than GPS.Besides,the relative positioning precision of BDS are 0.40 cm,0.31 cm,1.00 cm in north,east and up respectively,which are also better than the results of GPS.Long-term related analysis indicates that BDS is superior to GPS in slope deformation monitoring in southern China.During 23 months,the average displacements of the three stations in Lixian slope reach 8.70 cm,43.63 cm,18.03 cm in north,east and up respectively.As rainfall is a main factor for landslide in soil slope,we build a linear regression model using cumulative rainfall data and cumulative displacement data of which correlation coefficient is above 0.98.Accordingly,one should regard the real-time displacement data and rainfall data as important evidence in landslide early-warning.

分析了四川理县一处山体滑坡2014-08～2015-08的监测数据.结果表明,滑坡处于缓慢发生中,滑移的主要方向指向山体旁的学校;1a中3个监测点在该方向上的累积位移量分别为180 mm、262 mm和448mm.分析降雨量资料发现,降雨对山体滑坡有延迟的影响.利用ANSYS软件对滑坡发生的过程进行数值模拟,并计算监测点的位移,结果与实际观测情况吻合较好,得到降雨量与弹性模量、密度、粘聚力、内摩擦角之间的关系.该数值模拟实验提供了一种预测滑坡的新方法.

随着地震前兆台网规模不断扩大,对台网各个系统和设备的运行监控需求迫切,因此,开展其运行监控系统的研究工作则十分必要.本文就系统的总体架构设计、业务功能开发、以及主要的关键技术进行了方案研究与实践.此方案为整个项目的建设提供了顶层设计,有序地保障和推进了该系统的设计实现及运行.

地震前兆台网观测数据跟踪分析工作是中国地震局为推进地震前兆台网日常工作重心从观测为主向观测、应用并重转变而开展的一项重要工作。工作开展主要是以地震前兆台站为基本工作单元，以“地震前兆台网观测数据跟踪分析软件”为基本工作平台，及时分析判定形变、电磁、地下流体观测数据变化，依托前兆台网技术系统同步汇集、存储分析产品，通过国家中心网站提供共享服务[1]。

In this paper, through the analysis of the present situation of the instruments operation and maintenance of the earthquake precursor network of China, a maintenance support system composed of provincial maintenance center, regional maintenance center and instrument manufacturers is proposed, and its construction content and construction scheme are discussed. At present, the pilot construction of the regional maintenance center based on this shame has been completed, and has achieved initial results.