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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<p>A critical part of planning and managing road infrastructures in mountainous regions is the<br />pragmatic assessment of the prevailing and credible landslides hazard. Such assessments assume<br />greater significance for the Himalayan region, where seismically induced landslides present a<br />greater threat than commonly recognized, and require a robust comprehension of two hazards:<br />earthquake and the landslides induced by the former. However, the traditional practice of<br />landslide hazard assessment often neglects seismic factor due to paucity of pertinent data, which<br />may further be ascribed to the rarity of an extreme event. In this context, an endeavor has been<br />made in this study to evaluate the seismically induced landslide hazard for a scenario earthquake<br />of 10% exceedance probability in 50 years for an important road corridor in the lower Indian<br />Himalayas using Fuzzy algorithms. Probabilistic Seismic Hazard Assessment (PSHA) has been<br />carried out for the study area to calculate the Peak Ground Acceleration (PGA) of the scenario<br />earthquake, which is then used as a landslide triggering factor. PGA is integrated with eight<br />different landslide controlling factors viz. lithology, slope angle, aspect, elevation profile,<br />distance form fault, distance from drainage, distance from road, and land-use-land-cover patterns<br />in a Geographical Information System (GIS). 232 numbers of landslides are mapped for the<br />study area using high resolution Google earth imagery platform. The Fuzzy Cosine Amplitude<br />method is used to define the degree of similarity (strength of correlation) between the observed<br />landslides (dependent variable) and the landslide causative factors (independent variable(s)).<br />Expectedly, the probability of landslide occurrence correlates (degree of similarity) to the PGA<br />in a linear pattern (goodness of fit = 0.9954). The result of the study is discussed in terms of a<br />seismically induced Landslide Hazard Zonation (LHZ) map for the study, which is generated<br />using three Fuzzy operators (AND, OR and GAMMA). The prepared LHZ map demarcates more<br />than 40% of the study area as the zones of high to very high landslide hazard under the scenario<br />earthquake, with a prediction accuracy of 80%. The study shows that probabilistically generated<br />PGA can be included as seismic parameter for a more comprehensive assessment of the landslide<br />hazard in seismically active regions.</p> <p>Keywords: Fuzzy Cosine Amplitude, Probabilistic Seismic Hazard Assessment (PSHA), Peak<br />Ground Acceleration (PGA), Landslide Hazard Zonation (LHZ), the Himalayas</p>

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