1- Introduction

2- Geological setting

3- Methods and data

4- Field observations

5- Discussion

6- Conclusions

References

Abstract

A speleoseismological study has been conducted at over a dozen cave sites along the Longmen Shan fault zone of the eastern Qinghai-Tibet Plateau. The aim was to assess the damage inflicted on speleothems by the Mw 7.9 Wenchuan earthquake. Results show that the earthquake led to either partial or complete collapse of the caves. ‘Soda straws’ are shown to be particularly vulnerable to earthquake damage, but statistical analyses indicate that the spindle and slender shapes are also very likely to break. Cave depth is also shown to play an important role in the fracture development during the earthquake. The measured orientations of fallen stalactites are preferentially aligned to the coseismic surface offset peaks and therefore to the direction of earthquake wave propagation. Several such damaged speleothems resulting from sudden co-seismic movements were observed. The direction of ceiling (hanging wall) movement caused by the Wenchuan earthquake is NW-NNW, consistent with block motion on the footwall of the Yingxiu-Beichuan fault. We inferred that the faults in the caves were not co-seismic structures of the Wenchuan earthquake; but instead they are likely normal faults as the result of gravity creeping induced by the earthquake.

Introduction

Speleothems are cave deposits forming from dripping of mineral -rich water. They are quite common in karst landforms and include stalagmites, stalactites and flowstones , etc . Speleothems are usually regarded as good proxies for high -resolution palaeoclimatic reconstructions, in that carbon and oxygen isotopes preserved in speleothems document climatic oscillations throughout the Quaternary (Wang, 2001; Tan et al., 2006; Fairchild et al., 2006; Calaforra et al., 2008; Sorin et al., 2010) . In tectonically active regions , deposition of speleothems is sometimes interrupted by earthquake s , forming damaged speleothems that are usually called as speleoseismites. Therefore, speleothems have also been used for palaeoseismi c research (Forti, 2001; Lacave et al., 2004; Kagan et al., 2005) and a concise overview of this topic has been given by Forti and Postpichl (1984) and Becker et al., (2006) . Earthquake -related speleoseismites include deformed (broken or offset) (stalactites and stalagmites) (Lemeille et al., 1999; Delaby, 2001; Šebela, 2008) , irregular stalagmite growth (Postpischl et al., 1991; Forti, 2001; Shao et al., 2014; Rajendran et al., 2016) , cave sediment deformation, rock falls in cave s , fault displacement in cave walls and ceilings (Becker et al., 2006; Forti, 2007; Camelbeeck et al., 2012; Camelbeeck et al., 2018) , and the termination and re -initiation of stalagmite growth (Panno et al., 2009; Shao et al., 2014; Panno et al., 2016) .

A combination of Geological mapping and two-dimensional electrical resistivity (2D-ER) surveys was applied to study the Unilorin Dam and its environment. The purpose of the study was to investigate the dam for structural anomalies that may compromise the purpose and safety of the dam. Field equipment for the study comprised a SuperSting R8/IP Multi-Electrodes Resistivity Meter, 84 metallic electrodes and the accessories, compass clinometer, and portable GPS equipment. Geological data were processed and plotted to obtain a Geological Map and Rosette Diagram that were used for structural interpretations. The structures interpreted include an asymmetric fold and a strike-slip fault. The 2D resistivity data were processed and tomographically inverted to obtain the resistivity models of the subsurface around the dam. Interpretations of 2D resistivity models showed that the dam reservoir floor is underlain by competent basement rocks, however, the basement rock is weathered in some places. Patches of low resistivities structures interpreted as seepages, fractures and water-saturated cavity were delineated in different sections of the dam. The surface structural elements from geological study support the subsurface structures interpreted in the 2D resistivity models. Weathered structures, fractures, and seepage in the reservoir floor constitute areas of excessive water loss in the dam. The cavity delineated in the dam foundation is a potential threat to the dam’s safety. The dam section with cavity has been referred to structural engineers for detailed study.

Introduction

Safety assessment test on civil engineering constructions such as dams, tunnels, and bridges is a necessary endeavor to forestall sudden failure and collapse of engineering infrastructure. The mechanical properties of old dams that have outlived their life span, or new dams affected by natural hazards might have suffered degradation that can cause some structural damages that may not be obvious on the surface. If such damages are not detected by routine safety checks and addressed in good time, it may deteriorates and consequently lead to the failure of the dam. A dam is a barrier constructed to slow down, direct, or obstruct the free flow of water. The purpose of dam construction includes irrigation, supply of water for human and industry uses, hydro-electric power generation, control of flood, fish rearing, recreation, and navigation (Biswas and Charttergee, 1971; Plata and Iragüen, 1992). In addition to water scarcity, dam failure can lead to flooding and monumental loss of lives and properties. The old method of dam testing for structural damages include drilling and sample testing. Usually, 250–300 mm hole(s) is drilled in some parts of the dam and the samples collected are structurally examined and tested in the laboratory. Despite the cost and time required, drilling provide limited information on the possible structural anomalies/damages in dams (Kepler et al., 2000).

1- Introduction

2- Geology, gravity, seismic network and data

3- Methodology

4- Results and discussions

5- Conclusions

References

Abstract

We herein use the joint inversion of P-receiver functions and fundamental mode group velocity dispersion data (9–70 s) of Rayleigh and Love waves to estimate crustal and lithospheric thicknesses at twenty three-component mobile broadband stations in Kachchh, Gujarat. Modeled Moho depths range from 35 to 43 km, while lithospheric thicknesses vary from 64 to 106 km. The main result of our modelling is the delineation of a marked crustal (∼2–4 km) as well as lithospheric (∼10–20 km) thinning and a 2–6% drop in Vs across the lithosphere-asthenosphere-boundary (LAB), within the Samkhiali graben (associated with gravity high) underlying the central Kachchh rift zone (KRZ), where 95% of the continued aftershock activity took place since 2001. Such a large drop in Vs could be attributed to the presence of carbonatite melts in the upper mantle. Our modeling reveals a 4 km crustal thinning below the central KRZ and a 4 km crustal thickening below the surrounding riftless regions. This kind of crustal structure is inferred to induce large flexural deviatoric stresses (∼50–100 MPa) in the upper crust, thereby, these stresses in the presence of regional plate tectonic stresses can bring the Samkhiali graben below the central KRZ near to the critical stress level. While stress-transfer, meteoric water (in the upper crust), and metamorphic fluid as well volatile CO2 flows (in the lower crust) provide the required triggering effect to the critically stressed graben structure (down to 35 km depth) for generating continued aftershock activity in the Kachchh rift zone, since 2001. We also propose that the deeper circulation of volatile CO2 through the inferred conduit (related to the 65 Ma Deccan Plume activity) extending from lower crust down to asthenosphere plays a key role in the generation of uninterrupted occurrence of earthquakes in the Kachchh rift zone, Gujarat, India.

Introduction

The lithosphere underlying the Mesozoic Kachhchh rift zone (KRZ), northwest India, has been significantly affected by two-phase rifting episodes (viz. 184 Ma African and 88 Ma Madagascar) and the 65 Ma Deccan volcanism (Courtillot et al., 1986; Mahony et al., 2002; Sen et al., 2009). The influence of the above tectonic episodes on the crust-mantle structure has been seen through the mapped present-day thinning of crust and lithosphere below the Kachchh rift zone (Mandal, 2016 and 2017). Also, this effect has been reflected in the Bouguer gravity anomaly map of the region, showing alternate regional gravity highs (crustal thinning) and lows (crustal thickening) (Mishra et al., 2005; Khan et al., 2016).This thinning model gets further support from the results of local earthquake tomography, surface wave dispersion and receiver function modelling studies, which have imaged crustal mafic underplating, Moho upwarping and asthenospheric thinning underlying the 2001 Bhuj earthquake region (Mandal and Pujol, 2006; Mandal, 2012). In India, topography and crustal density heterogeneities associated with the Deccan volcanic province (India) have shown to induce intraplate stresses of the order of 100 MPa (Mandal et al., 1996). Thus, the crustal stresses associated with the density heterogeneities might play a key role in generating the intraplate earthquakes in the Kachchh rift zone also. It has been seen that the occurrences of earthquakes in the continental shelf as well as in the continental rift zones are found to be significantly influenced by flexural stresses (Stein et al., 1989; Assumpcao, 1998; Assumpco et al., 2011; Zoback and Richardson, 1996).

Abstract

This article presents the collaboration of two inter-disciplinary research projects on earthquake risk management for Slovenia and its capital city Ljubljana. Seismic resistance, structural vulnerability and fundamental frequency assessments of individual buildings were made and, using data from the Real Estate and Central Population registers, scenarios for the impact of different earthquake intensities were constructed. In addition, four applications were developed: guidance on earthquake preparedness for the public; a web application for self-assessment of building vulnerability; a support system for earthquake damage inspection; and an early post-earthquake damage assessment tool for planning rescue operations.

Introduction

The article presents the scientific basis and the applications of numerous research projects which lately culminated in a Slovenian national research project “Earthquake Risk in Slovenia” (Lutman et al. 2013) and Ljubljana’s municipal research project “Earthquake Risk Assessment” (Banovec et al. 2012). After many years of planned research on earthquake hazard, structural vulnerability and earthquake risk, conducted separately by different scientific disciplines and professions, the time was ripe to start a joint research project with practical applications. Joining civil engineering, seismology, geology, mathematic, computer science and disaster management was not an easy task. But the effort paid off with numerous project outputs enhancing knowledge on possible earthquake effects in Slovenia and producing tools to tackle some of them. With knowledge on structural vulnerability, gained by analyses of numerous buildings, backed by knowledge of general seismicity, seismic microzonation, and the fundamental frequency of buildings it was possible to extrapolate, by applying mathematical modeling and computer science, to all building stock, using data from the newly established Slovenian National Real Estate Register. When data from other national and local registers, namely the Central Population Register and the rescue personnel register was used, hitherto unknown aspects of the social effects of an earthquake became apparent. This knowledge became the basis for development of a set of tools for disaster managers. Most obvious are earthquake risk assessment with different scenarios to be used for planning and preparedness and response instructions for the public. Others are an internet based application giving information on possible structural damage of an individual building after an earthquake, an internet based application for early post-earthquake damage assessment joined with on-line data gathering from public on the earthquake effects, and a support system for after earthquake building inspection.

Matching pursuit is an algorithm for sparse representation of signals. It adaptively decomposes a signal into a series of time-frequency atoms that match the time-frequency characteristics of the signal (Mallat and Zhang, 1993). The matching pursuit decomposition of seismic signals has been widely used in seismic data processing and interpretation, such as migration (Wang and Pann, 1996; Li et al, 1998), filtering (Nguyen and Castagna, 2000), interpolation (Øzbek, 2009), inversion (Yang et al, 2011; Zhou et al, 2013), and spectral analysis for hydrocarbon recognition (Castagna et al, 2003; Wang, 2007) and channel detection (Liu and Marfurt, 2007). The Gabor wavelet is used as the time-frequency atoms in a conventional matching pursuit algorithm. Considering the characteristics of seismic signals, Liu et al (2004) applies the Ricker wavelet as the time-frequency atoms to decompose seismic data. Liu and Marfurt (2005), and Wang (2007) implement matching pursuit decomposition of seismic signals based on the Morlet wavelet. A conventional matching pursuit algorithm costs a huge amount of computation, because it searches the optimal time-frequency atoms from an abundant dictionary (Mallat and Zhang, 1993). Liu and Marfurt (2005) introduce complex-trace analysis into the algorithm to avoid the blind search of time-frequency atoms, greatly improving its computation speed. Based on this, Wang (2007) summarizes “three-stage procedure” for matching pursuit decomposition of seismic signals where the decomposition is more precise by executing local search around the complex-trace attributes. In order to improve the spatial continuity of the decomposition, Wang (2010) further proposes multichannel matching pursuit. Although matching pursuit decomposition of seismic signals has been greatly improved, the local search of time-frequency atoms and iterative implementation of the algorithm still cost lots of time. To further enhance its execution speed, in addition to the algorithm itself, with the help of high-performance computers to accelerate the decomposition could also be considered. Liu and Marfurt (2007) perform matching pursuit to seismic data by searching a suite of optimal time-frequency atoms at one iteration rather than one at a time as in a conventional algorithm. Because the search of optimal time-frequency atoms has the same implementation and is independent of each other, Liu and Marfurt (2007) inspire us to execute matching pursuit decomposition in parallel by parallel computer systems. Hence, in this paper, we design a parallel decomposition algorithm of matching pursuit to effectively improve the computation speed of the matching pursuit decomposition of seismic signals. It gives full play to the advantages of parallel computing and has good expandability. We believe that the realization of matching pursuit parallel decomposition for seismic data will benefit the application of matching pursuit in the processing and interpretation of large-scale 3D seismic data.

Gas hydrates are formed due to the high hydraulic pressure present under the cold seabed over long periods of time. Gas hydrates are stable under the temperature and pressure conditions typical of water depths greater than 500 m in oceanic sediments along the continental margins. In the South China Sea, gas hydrates were found by the Guangzhou Marine Geologic Survey (GMGS) in 2007 (Zhang et al., 2007). Gas hydrates can be summarized as pore-filling or fracturefilling based on their morphologies in sediments. In the process of exploiting hydrates, the gas hydrates existence in sediments must first be known. The exploitation methods would be different according to the hydrate morphology. In 2013, GMMS once again conducted a drilling program that targeted the gas hydrate deposits in the northern South China Sea. A total of 23 holes were drilled at 13 sites (Zhang et al., 2014b). The logging data and core analysis indicated the occurrence of gas hydrates from approximately 5 m to 220 m below mudline (BML). Gas hydrates occur as solid nodules, disseminated within pore spaces of sediments and fracture fillings in veins (Yang et al., 2014; Zhang et al., 2014a, b). Nowadays, many researchers have studied the presence and amounts of gas hydrate. Still, we cannot identify the morphology of gas hydrate in sediments before we drill the site. There’s no such research to give a way to solve the problem. In this paper, we will discuss how to identify the gas hydrate morphology in sediments based on the frequency dependent reflection coefficient.

2. Mesoscopic-loss mechanism

Previous studies found that the major cause of attenuation occurs at three scales: macroscopic, mesoscopic, and microscopic. At macroscopic scale, the Biot theory (Biot, 1962) gives the attenuation mechanisms. The drawback of this is that the macroscopic-flow mechanism underestimates the velocity dispersion and attenuation in rocks. At the microscopic scale, the so-called squirt flow is incapable of describing the measured levels of dissipation at seismic frequencies. Pride et al. (2004) studied the mesoscopic loss mechanism and found that the mesoscopic model provides the proper attenuation to explain the field data, and therefore, we use the mesoscopic theory to study the reflection coefficient varying with frequency at BSR.

The base of the seismic hazard studies to mitigate future earthquake losses is to understand the earthquakes that hit a region in the past. Seismic catalogs incorporate information about past events by palaeoseismological, archaeological and historical studies. A multidisciplinary combination of historical, archaeological and palaeosismological data can provide insight into the seismogenic fault, recurrence, location and socioeconomic effects (e.g. Nur and Cline, 2000; Meghraoui et al., 2003; Michetti et al., 2005; Caputo and Helly, 2008; Karakhanian et al., 2008; Berberian et al., 2012; Udías, 2015). The study of the seismogenic fault by palaeoseismological studies of the surface rupture is one of the data sources (on-fault) that provide estimation of fault rupture, magnitude, location and recurrences for seismic catalogs. Unfortunately, catastrophic earthquakes of low to moderate magnitudes (M< 6.5) may not leave evidence of the surface ruptures (e.g., Pizzi and Scisciani, 2012; Martinez-Diaz, et al. 2012; Martin-Gonzalez et al, 2012; Mckey and Quigley, 2014). Therefore, for earthquakes for which seismogenic fault and surface ruptures have not been identified (because of the low to moderate magnitudes, blind faults, or just because it is not observed at the surface due to subsequent burial, erosion by surface processes or destruction by human activity), the evidence of the seismic events is found in the earthquake damage (ED) observed in historical or archaeological sites. Earthquake information can be obtained by the study off-fault of the ED recorded in historical and archaeological sites or in historical photographs and descriptions of the earthquakes (archaeoseismology, historical seismology) (e. g., Mallet, 1862; Musson, 1996; Korjenkov and Mazor, 1999; Nur and Cline, 2000; Marco et al., 2003; Ambraseys, 2006; Galadini et al., 2006; Al-Tarazi and Korjenkov, 2007; Marco, 2008; Guidoboni and Ebel, 2009; Reicherter et al., 2009; Sintubin et al., 2010; Talwani, 2014; Stiros and Blackman, 2014; Kyriakides et al., 2016). This information, along with how the population felt the earthquake in many cases has been used to make estimations of the earthquake dates, locations of epicenters, focal depths, magnitude or intensity, ground shaking and seismic moments of the seismic events (Guidoboni and Ebel, 2009). All this information is crucial to evaluate the seismic hazard and regulatory seismic codes (Musson, 1996; Korjenkov and Mazor 1999, 2013; ASCE, 2010; Galadini et al., 2006).

حوزه مطالعاتی فعلی، در منطقه متا رابی ناحیه شوآی غربی در ایالت منطقه ای ارومیای اتیوپی واقع شده است. هدف اصلی مطالعه ی فعلی، ارزیابی ناحیه بندی خطر زمین لغزه (LHZ) با استفاده از رویکردهای “جایگذاری شبکه” و “مدلسازی GIS ” بود. از این گذشته، سعی شد اثر بخشی دو روش، شناخته شود. متدولوژی دنبال شده مبتنی بر تحلیل زمین لغزه های گذشته در ناحیه بود. برای مطالعه کنونی شش عامل سببی بویژه مواد شیب، شیب، جهت شیب، زاویه فراز، کاربری زمین و پوشش زمین و آثار سطحی آب های زیر زمینی، مد نظر قرار گرفتند. بعدها، شاخص آمادگی زمین لغزه (LSI) بر مبنای تاثیر نسبی عوامل سببی بر زمین لغزه ها، محاسبه شد. برای روش “جایگذاری شبکه ای”، یک شبکه ی دارای سلولهای m10 در m 10 روی ناحیه ی مورد مطالعه جایگذاری شد و بعد برای ترسیم دسته های فرعی هر عامل سببی، مورد پردازش زمین شناسی قرار گرفت. ارزشهای LSI به هر عامل سببی فرعی در هر خانه شبکه اختصاص داده شد و یک “شاخص آمادگی خطر زمین لغزه ی کلی” برای تولید نقشه LHZ محاسبه شد. برای مدلسازی GIS، عوامل سببی یکسان و ارزشهای LSI مشابه بکار رفت. در مورد نقشه  LHZ تهیه شده توسط روش “جایگذاری شبکه ای” در مورد 82% از زمین لغزه های گذشته، بین نواحی “بسیار پر خطر” یا نواحی ” با خطر بالا” قرار میگیرند در حالیکه مورد “مدلسازی GIS” در مورد 95% زمین لغزع ها در نواحی “بسیار پر خطر” یا “با خطر بالا” واقع میشود. نهایتا، این ارزیابی نشان داد “مدلسازی GIS” نقشه ی LHZ بهتری را ایجاد نمود. از این گذشته، روش “جایگذاری شبکه” در مقایسه با مدلسازی GIS کسل کننده تر و زمان برتر است.