Regolith mass balance inferred from combined mineralogical, geochemical and geophysical studies: Mule Hole gneissic watershed, South India

The aim of this study is to propose a method to assess the long-term chemical weathering mass balance for a regolith developed on a heterogeneous silicate substratum at the small experimental watershed scale by adopting a combined approach of geophysics, geochemistry and mineralogy. We initiated in 2003 a study of the steep climatic gradient and associated geomorphologic features of the edge of the rifted continental passive margin of the Karnataka Plateau, Peninsular India. In the transition sub-humid zone of this climatic gradient we have studied the pristine forested small watershed of Mule Hole (4.3 km(2)) mainly developed on gneissic substratum. Mineralogical, geochemical and geophysical investigations were carried out (i) in characteristic red soil profiles and (ii) in boreholes up to 60 m deep in order to take into account the effect of the weathering mantle roots. In addition, 12 Electrical Resistivity Tomography profiles (ERT), with an investigation depth of 30 m, were generated at the watershed scale to spatially characterize the information gathered in boreholes and soil profiles. The location of the ERT profiles is based on a previous electromagnetic survey, with an investigation depth of about 6 m. The soil cover thickness was inferred from the electromagnetic survey combined with a geological/pedological survey. Taking into account the parent rock heterogeneity, the degree of weathering of each of the regolith samples has been defined using both the mineralogical composition and the geochemical indices (Loss on Ignition, Weathering Index of Parker, Chemical Index of Alteration). Comparing these indices with electrical resistivity logs, it has been found that a value of 400 Ohm m delineates clearly the parent rocks and the weathered materials, Then the 12 inverted ERT profiles were constrained with this value after verifying the uncertainty due to the inversion procedure. Synthetic models based on the field data were used for this purpose. The estimated average regolith thickness at the watershed scale is 17.2 m, including 15.2 m of saprolite and 2 m of soil cover. Finally, using these estimations of the thicknesses, the long-term mass balance is calculated for the average gneiss-derived saprolite and red soil. In the saprolite, the open-system mass-transport function T indicates that all the major elements except Ca are depleted. The chlorite and biotite crystals, the chief sources for Mg (95%), Fe (84%), Mn (86%) and K (57%, biotite only), are the first to undergo weathering and the oligoclase crystals are relatively intact within the saprolite with a loss of only 18%. The Ca accumulation can be attributed to the precipitation of CaCO3 from the percolating solution due to the current and/or the paleoclimatic conditions. Overall, the most important losses occur for Si, Mg and Na with -286 x 10(6) mol/ha (62% of the total mass loss), -67 x 10(6) mol/ha (15% of the total mass loss) and -39 x 10(6) mol/ha (9% of the total mass loss), respectively. Al, Fe and K account for 7%, 4% and 3% of the total mass loss, respectively. In the red soil profiles, the open-system mass-transport functions point out that all major elements except Mn are depleted. Most of the oligoclase crystals have broken down with a loss of 90%. The most important losses occur for Si, Na and Mg with -55 x 10(6) mol/ha (47% of the total mass loss), -22 x 10(6) mol/ha (19% of the total mass loss) and -16 x 10(6) mol/ha (14% of the total mass loss), respectively. Ca, Al, K and Fe account for 8%, 6%, 4% and 2% of the total mass loss, respectively. Overall these findings confirm the immaturity of the saprolite at the watershed scale. The soil profiles are more evolved than saprolite but still contain primary minerals that can further undergo weathering and hence consume atmospheric CO2.

Spatial Variability of the Depth of Weathered and Engineering Bedrock using Multichannel Analysis of Surface Wave Method

In this paper an attempt has been made to evaluate the spatial variability of the depth of weathered and engineering bedrock in Bangalore, south India using Multichannel Analysis of Surface Wave (MASW) survey. One-dimensional MASW survey has been carried out at 58 locations and shear-wave velocities are measured. Using velocity profiles, the depth of weathered rock and engineering rock surface levels has been determined. Based on the literature, shear-wave velocity of 330 ± 30 m/s for weathered rock or soft rock and 760 ± 60 m/s for engineering rock or hard rock has been considered. Depths corresponding to these velocity ranges are evaluated with respect to ground contour levels and top surface levels have been mapped with an interpolation technique using natural neighborhood. The depth of weathered rock varies from 1 m to about 21 m. In 58 testing locations, only 42 locations reached the depths which have a shear-wave velocity of more than 760 ± 60 m/s. The depth of engineering rock is evaluated from these data and it varies from 1 m to about 50 m. Further, these rock depths have been compared with a subsurface profile obtained from a two-dimensional (2-D) MASW survey at 20 locations and a few selected available bore logs from the deep geotechnical boreholes.

Mapping of Average Shear Wave Velocity for Bangalore Region: A Case Study

Mapping the shear wave velocity profile is an important part in seismic hazard and microzonation studies. The shear wave velocity of soil in the city of Bangalore was mapped using the Multichannel Analysis of Surface Wave (MASW) technique. An empirical relationship was found between the Standard Penetration Test (SPT) corrected N value ((N1)60cs) and measured shear wave velocity (Vs). The survey points were selected in such a way that the results represent the entire Bangalore region, covering an area of 220 km2. Fifty-eight 1-D and 20 2-D MASW surveys were performed and their velocity profiles determined. The average shear wave velocity of Bangalore soils was evaluated for depths of 5 m, 10 m, 15 m, 20 m, 25 m and 30 m. The sub-soil classification was made for seismic local site effect evaluation based on average shear wave velocity of 30-m depth (Vs30) of sites using the National Earthquake Hazards Reduction Program (NEHRP) and International Building Code (IBC) classification. Mapping clearly indicates that the depth of soil obtained from MASW closely matches with the soil layers identified in SPT bore holes. Estimation of local site effects for an earthquake requires knowledge of the dynamic properties of soil, which is usually expressed in terms of shear wave velocity. Hence, to make use of abundant SPT data available on many geotechnical projects in Bangalore, an attempt was made to develop a relationship between Vs (m/s) and (N1)60cs. The measured shear wave velocity at 38 locations close to SPT boreholes was used to generate the correlation between the corrected N values and shear wave velocity. A power fit model correlation was developed with a regression coefficient (R2) of 0.84. This relationship between shear wave velocity and corrected SPT N values correlates well with the Japan Road Association equations.

Applicability of Statistical Learning Algorithms for Spatial Variability of Rock Depth

Two algorithms are outlined, each of which has interesting features for modeling of spatial variability of rock depth. In this paper, reduced level of rock at Bangalore, India, is arrived from the 652 boreholes data in the area covering 220 sqa <.km. Support vector machine (SVM) and relevance vector machine (RVM) have been utilized to predict the reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth. The support vector machine (SVM) that is firmly based on the theory of statistical learning theory uses regression technique by introducing epsilon-insensitive loss function has been adopted. RVM is a probabilistic model similar to the widespread SVM, but where the training takes place in a Bayesian framework. Prediction results show the ability of learning machine to build accurate models for spatial variability of rock depth with strong predictive capabilities. The paper also highlights the capability ofRVM over the SVM model.

Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

Probabilistic evaluation of seismic soil liquefaction potential based on SPT data

The performance-based liquefaction potential analysis was carried out in the present study to estimate the liquefaction return period for Bangalore, India, through a probabilistic approach. In this approach, the entire range of peak ground acceleration (PGA) and earthquake magnitudes was used in the evaluation of liquefaction return period. The seismic hazard analysis for the study area was done using probabilistic approach to evaluate the peak horizontal acceleration at bed rock level. Based on the results of the multichannel analysis of surface wave, it was found that the study area belonged to site class D. The PGA values for the study area were evaluated for site class D by considering the local site effects. The soil resistance for the study area was characterized using the standard penetration test (SPT) values obtained from 450 boreholes. These SPT data along with the PGA values obtained from the probabilistic seismic hazard analysis were used to evaluate the liquefaction return period for the study area. The contour plot showing the spatial variation of factor of safety against liquefaction and the corrected SPT values required for preventing liquefaction for a return period of 475 years at depths of 3 and 6 m are presented in this paper. The entire process of liquefaction potential evaluation, starting from collection of earthquake data, identifying the seismic sources, evaluation of seismic hazard and the assessment of liquefaction return period were carried out, and the entire analysis was done based on the probabilistic approach.

Relationship between Low Strain Shear Modulus and Standard Penetration Test N Values

A low strain shear modulus plays a fundamental role in the estimation of site response parameters In this study an attempt has been made to develop the relationships between standard penetration test (SPT) N values with the low strain shear modulus (G(max)) For this purpose, field experiments SPT and multichannel analysis of surface wave data from 38 locations in Bangalore, India, have been used, which were also used for seismic microzonation project The in situ density of soil layer was evaluated using undisturbed soil samples from the boreholes Shear wave velocity (V-s) profiles with depth were obtained for the same locations or close to the boreholes The values for low strain shear modulus have been calculated using measured V-s and soil density About 215 pairs of SPT N and G(max) values are used for regression analysis The differences between fitted regression relations using measured and corrected values were analyzed It is found that an uncorrected value of N and modulus gives the best fit with a high regression coefficient when compared to corrected N and corrected modulus values This study shows better correlation between measured values of N and G(max) when compared to overburden stress corrected values of N and G(max)

Seismic Hazard and Microzonation Studies using Geographic Information System - A Case Study of Bangalore city

Seismic hazard and microzonation of cities enable to characterize the potential seismic areas that need to be taken into account when designing new structures or retrofitting the existing ones. Study of seismic hazard and preparation of geotechnical microzonation maps has been attempted using Geographical Information System (GIS). GIS will provide an effective solution for integrating different layers of information thus providing a useful input for city planning and in particular input to earthquake resistant design of structures in an area. Seismic hazard is the study of expected earthquake ground motions at any point on the earth. Microzonation is the process of sub division of region in to number of zones based on the earthquake effects in the local scale. Seismic microzonation is the process of estimating response of soil layers under earthquake excitation and thus the variation of ground motion characteristic on the ground surface. For the seismic microzonation, geotechnical site characterization need to be assessed at local scale (micro level), which is further used to assess of the site response and liquefaction susceptibility of the sites. Seismotectonic atlas of the area having a radius of 350km around Bangalore has been prepared with all the seismogenic sources and historic earthquake events (a catalogue of about 1400 events since 1906). We have attempted to carryout the site characterization of Bangalore by collating conventional geotechnical boreholes data (about 900 borehole data with depth) and integrated in GIS. 3-D subsurface model of Bangalore prepared using GIS is shown in Figure 1.Further, Shear wave velocity survey based on geophysical method at about 60 locations in the city has been carried out in 220 square Kms area. Site response and local site effects have been evaluated using 1-dimensional ground response analysis. Spatial variability of soil overburden depths, ground surface Peak Ground Acceleration’s(PGA), spectral acceleration for different frequencies, liquefaction susceptibility have been mapped in the 220 sq km area using GIS.ArcInfo software has been used for this purpose. These maps can be used for the city planning and risk & vulnerability studies. Figure 2 shows a map of peak ground acceleration at rock level for Bangalore city. Microtremor experiments were jointly carried out with NGRI scientists at about 55 locations in the city and the predominant frequency of the overburden soil columns were evaluated.

A comparative study of ordinary kriging and support vector machine models for the spatial variability of rock depth in Bangalore

In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 sq.km. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, ordinary kriging and Support Vector Machine (SVM) models have been developed. In ordinary kriging, the knowledge of the semivariogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of Bangalore, where field measurements are not available. A cross validation (Q1 and Q2) analysis is also done for the developed ordinary kriging model. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing e-insensitive loss function has been used to predict the reduced level of rock from a large set of data. A comparison between ordinary kriging and SVM model demonstrates that the SVM is superior to ordinary kriging in predicting rock depth.

Seismic site classification and correlation between standard penetration test N value and shear wave velocity for Lucknow city in Indo-Gangetic basin

Subsurface lithology and seismic site classification of Lucknow urban center located in the central part of the Indo-Gangetic Basin (IGB) are presented based on detailed shallow subsurface investigations and borehole analysis. These are done by carrying out 47 seismic surface wave tests using multichannel analysis of surface waves (MASW) and 23 boreholes drilled up to 30 m with standard penetration test (SPT) N values. Subsurface lithology profiles drawn from the drilled boreholes show low- to medium-compressibility clay and silty to poorly graded sand available till depth of 30 m. In addition, deeper boreholes (depth >150 m) were collected from the Lucknow Jal Nigam (Water Corporation), Government of Uttar Pradesh to understand deeper subsoil stratification. Deeper boreholes in this paper refer to those with depth over 150 m. These reports show the presence of clay mix with sand and Kankar at some locations till a depth of 150 m, followed by layers of sand, clay, and Kankar up to 400 m. Based on the available details, shallow and deeper cross-sections through Lucknow are presented. Shear wave velocity (SWV) and N-SPT values were measured for the study area using MASW and SPT testing. Measured SWV and N-SPT values for the same locations were found to be comparable. These values were used to estimate 30 m average values of N-SPT (N-30) and SWV (V-s(30)) for seismic site classification of the study area as per the National Earthquake Hazards Reduction Program (NEHRP) soil classification system. Based on the NEHRP classification, the entire study area is classified into site class C and D based on V-s(30) and site class D and E based on N-30. The issue of larger amplification during future seismic events is highlighted for a major part of the study area which comes under site class D and E. Also, the mismatch of site classes based on N-30 and V-s(30) raises the question of the suitability of the NEHRP classification system for the study region. Further, 17 sets of SPT and SWV data are used to develop a correlation between N-SPT and SWV. This represents a first attempt of seismic site classification and correlation between N-SPT and SWV in the Indo-Gangetic Basin.

Effects of site stiffness and source to receiver distance on surface wave tests' results

By using six 4.5 Hz geophones, surface wave tests were performed on four different sites by dropping freely a 65 kg mass from a height of 5 m. The receivers were kept far away from the source to eliminate the arrival of body waves. Three different sources to nearest receiver distances (S), namely, 46 m, 56 m and 66 m, were chosen. Dispersion curves were drawn for all the sites. The maximum wavelength (lambda(max)), the maximum depth (d(max)) up to which exploration can be made and the frequency content of the signals depends on the site stiffness and the value of S. A stiffer site yields greater values of lambda(max) and d(max). For stiffer sites, an increase in S leads to an increase in lambda(max). The predominant time durations of the signals increase from stiffer to softer sites. An inverse analysis was also performed based on the stiffness matrix approach in conjunction with the maximum vertical flexibility coefficient of ground surface to establish the governing mode of excitation. For the Site 2, the results from the surface wave tests were found to compare reasonably well with that determined on the basis of cross boreholes seismic tests. (C) 2015 Elsevier Ltd. All rights reserved.