Characterization of the sedimentary cover at the Himalayan foothills using active and passive seismic techniques

Mahajan, Ambrish Kumar; Galiana-Merino, Juan José; Lindholm, Conrad; Arora, B. R.; Mundepi, A. K.; Rai, Nitesh; Chauhan, Neetu

doi:10.1016/j.jappgeo.2011.01.002

Cited by 26 publications

(14 citation statements)

References 51 publications

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“…The method has also been applied to characterize the sedimentary cover and determine the depth to underlying bedrock (Mahajan et al, 2011). If a reasonable value of the V s of nearsurface materials is known or can be estimated, the thickness and variation in thickness of those loose or weathered materials over bedrock can be determined (Arai and Tokimatsu, 2004;Haefner et al, 2010;Grippa et al, 2011;Chandler and Lively, 2014;Owers et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Application of HVSR to estimating thickness of laterite weathering profiles in basalt

Nelson

McBride

2019

Earth Surf Processes Landf

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Lateritic weathering profiles (LWPs) are widespread in the tropics and comprise an important component of the Critical Zone (CZ). The Hawaiian Islands make an excellent natural laboratory for examining the tropical CZ, where the bedrock composition (basalt) is nearly uniform and rainfall varies greatly. This natural laboratory is employed to assess the utility of the HVSR (horizontal/vertical spectral ratio) method to characterize the shear‐wave velocity (Vs) structure of LWPs, particularly the depth to the contact between saprolite and basalt bedrock. LWP thicknesses determined from HVSR provide good agreement with multi‐channel analysis of surface waves (MASW) profiles, well logs and outcrop. LWP thicknesses may be estimated from the fundamental mode equation or through forward models. Prior knowledge about the subsurface from well, outcrop, and MASW profiles may greatly aid modeling in some cases. For the 3.2 to 1.8 Ma Koolau Volcano on Oahu, the downward rate of advance of the weathering front varies from 0.004 to 0.041 m/ka. For the 0.44 to 0.10 Ma Kohala Volcano (Big Island of Hawaii) rates vary from 0.013 to 0.047 m/ka. Simple H/V spectra develop in areas where the combined effects of time and elevated rainfall produce thick LWPs with a flat base and a general absence of core stones with an ideal layered geometry. Abundant buried core stones violate the assumption of simple layered geometries and scatter acoustic energy, leading to uninterpretable results. This is common where low rainfall and a young basaltic substrate leave abundant core stones as well as an undulating contact between saprolite and bedrock. Velocity inversions (high Vs intervals within low Vs saprolite) may also be present and originate from relatively intact bedrock horizons or mineralogical changes within saprolite. At Kohala, a gibbsite‐rich horizon produces such a velocity inversion due to enhanced weathering and subsequent collapse of saprolite in a discrete horizon. © 2019 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Application of HVSR to estimating thickness of laterite weathering profiles in basalt

Nelson

McBride

2019

Earth Surf Processes Landf

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“…Sitharam (2006) carried out an MASW survey and concluded that MASW can be effectively used for the soil layer profiling and identification of rock depth and measurement of dynamic properties. Mahajan et al (2011) have conducted studies on characterization of sediments in the Himalayan foothills using both active and passive MASW techniques. More recently, Pandey et al (2016) carried out extensive MASW studies for quantifying the influence of local site conditions on strong ground motions.…”

Section: Multichannel Analysis Of Surface Waves (Masw)mentioning

confidence: 99%

Estimation of bedrock depth for a part of Garhwal Himalayas using two different geophysical techniques

et al. 2018

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It has now been well established that the depth of bedrock is a key parameter in assessing the impact of local site conditions on seismic hazard analysis. Where conventional geotechnical testing like standard penetration test (SPT) or cone penetration test (CPT) requires a far greater cost and manpower to be used for such purposes, geophysical testing like ground-penetrating radar (GPR) and multichannel analysis of surface waves (MASW) may provide the researchers with more viable options to achieve conclusive evidence on bedrock depth. Application of geophysical techniques has become more and more extensive and advanced in many geo-morphological studies since the early 2000s. Geophysical techniques require less time and effort, and the easy processing of the obtained data is the primary reason for their popularity. However, due to variability in subsoil mechanical properties, wave attenuation and dispersion and diverse geological boundary conditions, the results obtained through geophysical techniques are often ambiguous and non-unique. The interpretation of the obtained data also requires skill and experience, as the range may vary widely and more often than not consensus is difficult to achieve. In this paper, an endeavor has been made to coalesce the results of two widely used geophysical techniques, namely GPR and MASW to derive more conclusive evidence for the detection of bedrock depth in a part of Garhwal Himalayas. The study area comprises of two different cities of Uttarakhand, India. Both the sites possess different geo-morphological attributes and thus prove to be a perfect platform to conduct the experimentations. Both GPR and MASW testing have been performed and results are shown in graphical format. A comparison of the GPR survey with a conventional geotechnical testing (SPT) is also presented here. This study shows that GPR and MASW can provide complementary results in estimating bedrock depth.

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“…Further, by using Heaversine's formula, distance between the event and the city has been determined and the time taken by the destructive S-wave to reach the particular city has been calculated. The calculated P-arrival and S-arrival time along with 4 sec of EEW algorithm decision time, 1 sec of transmission delay, and 1 sec of processing delay provide the lead time for the cities by using (1). The lead time for each city has been calculated and shown in Figure 5.…”

Section: Lead Time Calculation For Cities In Northern Indiamentioning

confidence: 99%

“…Such a case exists in Northern India where a lot of development has taken place in the vicinity of Himalayas which is one of the world's seismically very active zone. Himalaya has been repeatedly hit by damaging earthquakes including some of the great earthquakes, namely, 1897 Shilong (M 8.7), 1905 Kangra (M 8.6), 1934 Bihar (M 8.4), and 1950 Assam (M 8.7), along with other moderate earthquakes which occurred recently, for example, 1991 Uttarkashi (M 6.8), 1999 Chamoli (M 6.4), 2005 Muzaffarabad (M 7.6), and 2011 Sikkim earthquake (M 6.9) in which huge loss of life and property took place [1][2][3]. The recent 2015 Nepal earthquake may be considered as a whistle blower for revisiting our preparedness towards heavy losses which the local populace has to face in future due to such natural calamity.…”

Section: Introductionmentioning

confidence: 99%

Lead Time for Cities of Northern India by Using Multiparameter EEW Algorithm

Bhardwaj

Sharma

2018

International Journal of Geophysics

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Earthquake early warning (EEW) is considered one of the important real-time earthquake damage mitigation measures. The presence of seismogenic sources generating high seismicity in Himalayas and the cities of concern lying at appropriate distances makes Northern India a perfect case to be monitored using EEW systems. In the present study, an attempt has been made to estimate the lead times for Northern Indian cities for issuing early warning by using the EEW system deployed by IIT Roorkee in Central Himalayas. The instrumentation deployed at 100 locations between Uttarkashi and Chamoli has been used to estimate the lead time at six cities. The estimated lead time includes the time to reach S-wave after subtraction of the sum of P-wave arrival time at the station, time taken by EEW algorithm, transmission and processing delay. The study reveals that for Dehradun, Hardwar, Roorkee, Muzaffarnagar, Meerut, and Delhi the minimum calculated lead time is 5, 11, 20, 35, and 68 sec while the maximum lead time is 37, 36, 47, 59, and 90 sec, respectively. Such larger estimated lead times to these densely populated cities show that EEW can successfully work as one of the important real-time earthquake disaster reduction measures in Northern India.

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Characterization of the sedimentary cover at the Himalayan foothills using active and passive seismic techniques

Cited by 26 publications

References 51 publications

Application of HVSR to estimating thickness of laterite weathering profiles in basalt

Application of HVSR to estimating thickness of laterite weathering profiles in basalt

Estimation of bedrock depth for a part of Garhwal Himalayas using two different geophysical techniques

Lead Time for Cities of Northern India by Using Multiparameter EEW Algorithm

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