Preface The last couple of decades have witnessed a tremendous research initiative in developing new quantitative methods and models for earth science. The advent of powerful com puters equipped with sophisticated mathematical and statistical tools has inspired geo-scientists to attempt more objective interpretation of their data. The earth science data are typically either too numerous or too sparse and are rarely complete. It is thus often difficult to identify a definitive pattern in them or to arrive at a comprehensive abstraction. The recent availability of mathematical and statistical tools, customized for such data sets, provides the opportunity for more objective analyses. Active research is presently underway to devise newer methodologies for analyzing data that were traditionally considered unsuitable for quantitative treatment. The geometry of geological features, that often provide important clues to their formative process, is one such example. Recent advances in the field of Geographical Information Science are now providing a bounty of potential tools for objective analysis of geometry and spatial interrelationship. With the help of new technologies, it is now possible to study the earth processes that were beyond the scope of observation due problems with their rate, scale or accessibility. Where direct observation is yet not feasible, sophisticated numerical models for explaining geological phenomena are now made increasingly available. By embedding our knowledge of the geological processes in a logical framework, these models allow us to explore areas where our understanding of these processes are flawed or weak, towards which new research efforts are to be directed. On the other hand, a holistic approach to understand earth requires integrating observations from many different sources. The new technologies have helped this process by providing the facility of sharing earth science data over intranet and Internet. This in turn necessitated development of exclusive standards, protocols and strategies to manage collaborative exchange of data. It is difficult to encompass this whole wave of new developments in a single book. However, the seven original research papers presented here provide the reader with a glimpse of new quantitative methods and numerical models that are presently used to interpret the earth in a more meaningful way. In the first two chapters Mukul and his co-workers and Mallick and her co-workers demonstrate how the geographic positioning system, that can measure plate motions with unprecedented accuracy, may be used in understanding crustal deformations in eastern Himalayas. The detail of a numerical model to study the relationship between crustal shortening and the resulting rock fabrics, developed by Mitra and his co-authors, is given in the third chapter. In the fourth chapter Purkait shows how statistical analysis of modern river sand helps in understanding fluvial transport mechanisms. Dutta and his co-workers propose a new quantitative technique for comparative study of bone geometry of archaic species in chapter five. In the sixth chapter Porwal and his co-authors demonstrate how zones of mineralization can be identified from earth science data sets with the help of GIS techniques. In the seventh chapter, Saha and his co-authors address the methodologies and strategies adopted for enterprise level earth science data collaboration and management tasks. I would like to thank F. P. Agterberg (GSC, Canada), A. Aoudia (ASICTP, Trieste Italy), P. Banerjee (WIHG, Dehradun, India), P. Bourke (UWA, Crawley, Australia), S. Chatterjee (Minnesota), P. Dasgupta (Presidency College, Kolkata, India), B. L. Deekshatulu (Hyderabad), J. Ghosh (Purdue), R. W. King (MIT), B. Köbben (ITC, The Netherlands), G. Mitra (Rochester), D. K. Mukhopadhyay (IIT, Roorke, India), T. Munshi (CEPT University, Ahmedabad), S. Purkayastha (ISI, Kolkata, India), K. Rajendran (IISc., Bangalore), S. Sikdar (George Mason University, Washington D. C.), L. P. Singh (Hyderabad), J. S. Steyer (Paris) and others for reviewing the manuscripts and their constructive suggestions. I am grateful to the authors for their cooperation. I thank D. P. Sangupta and C. Chakraborty and my other colleagues for their help and encouragements.

Abstract High precision Geodetic Global Positioning System measurements have become important for studying present-day tectonics in active orogenic belts such as the Himalayas. Geodetic Global Positioning System measurements in the Darjiling-Sikkim Himalayas (DSH) during 2000-2004 indicate that the frontal part of the Darjiling Himalaya is locked to the Indian plate and statistically negligible shortening is accumulating there at present. While this observation is in conformity with observations made in Nepal to the west of the DSH, it differs in the fact that about ~ 12 mm/yr of convergence is accommodated in the DSH and the western Bhutan Himalayas as opposed to about ~ 20 mm/yr in Nepal Himalaya. About 16 mm of convergence is accommodated in the Arunachal Himalaya, to the east of DSH, of which about 6 mm is accommodated in the Lesser Arunachal Himalaya. These observations indicate that there is a fair amount of heterogeneity in the way convergence is accommodated along the length of the Himalayan arc and the Himalayan seismic hazard estimations need to account for this. Seismicity patterns in the DSH indicate that active deformation in the area is driven by strike-slip as well as thrust tectonics. Strain accumulation in the DSH during 2000-2004 appears to be dominated by strike-slip tectonics in the region and about ~ 4-5 mm/yr of sinistral strike-slip is observed along a NNE-SSW trending near-vertical fault identified in the area (named as the Gish transverse fault).

Abstract Ten GPS stations have been set up in campaign mode in North Bengal in the Himalayan foothills and frontal zone, of which 7 have been reoccupied. Data from these 7 GPS stations over the period December, 2005 – January, 2007 have been processed using GAMIT/GLOBK suite of software and the velocities of these stations have been estimated. Since the data obtained so far cover a span of one year only, the conclusions derived from them are to be considered as preliminary. The stations are found to be moving at the rate of ~ 40-55 mm/yr in ITRF05 reference frame towards NNE. The baseline between LHAS (Lhasa) and IISC (Bangalore) is estimated to be shortened by ~10.2 mm over the period of our measurement. The southernmost station in our study, NBUV, at Siliguri is more or less collinear with LHAS-IISC baseline. The shortening of NBUV-IISC line is estimated to be ~ 3.8 mm over this period and that of NBUV-LHAS line is ~ 6.4 mm for the same period. These GPS stations were set up across the parallel set of previously marked fault scarps named Matiali (MT), Chalsa (CL) and Baradighi (BD) faults in North Bengal between longitudes 880 E and 890 E. The results from the GPS measurements show that stations to the south of the BD fault are moving at a faster rate than those to the north of MT fault. The baseline between stations AMBK (Ambiok) and NBUV has shortened by ~3 mm over the period of our observation. These two are the northernmost and southernmost stations respectively with respect to the three E-W running parallel faults and thus the shortening of baseline AMBK-NBUV is due to movements on the set of three faults taken together. A N-S to NNE-SSW running line of discontinuity between 88.50 E and 890 E longitudes separates the velocity vectors of the set of stations SAMS, JITI, PMSM, BRDH to the east of the line and the set of stations NBUV, BGKT, AMBK to the west. The line of demarcation of the two blocks containing the two sets of stations appears to coincide with the Gish transverse zone (GTZ).

Abstract This paper presents a kinematic analysis for explaining the spatial and temporal variations of deformational structures in the Cuddapah Proterozoic orogenic belt, South India. This belt shows virtually undeformed, flat-lying sedimentary rocks in its western margin, whereas strongly deformed and folded rocks in the eastern boundary. The structural variations indicate increasing deformation in the east direction, implying a relative tectonic convergence from the east side. Based on the corner flow theory, we use a viscous model to determine the heterogeneous strain field in the asymmetric convergent zone, and explain varying deformations from the foreland to hinterland. According to this model, the strain field in the hinterland part varies in a pulsating manner with progressive crustal thickening, giving rise to multiple deformational structures in the course of a single continuous tectonic movement. We also studied the strain field in finite element models considering the gravity forces, and obtained similar results. The foreland vergence of deformational structures in the Cuddapah belt indicates a top-to-west horizontal shear during the overall horizontal contraction. Our numerical models show that this horizontal shear component in the foreland region is likely to be associated with a vertical shear component in the hinterland.

Abstract Grain size distribution patterns of five rivers – Hooghly, Bhagirathi, Damodar, Ajoy and the Usri, were critically analyzed and compared with three model distributions: log-normal, log-hyperbolic and log-skew-Laplace. The log-normal and log-skew-Laplace are the limiting distributions of log-hyperbolic family. The Hooghly-Bhagirathi river system from where the sand samples were collected is tidal in nature whereas the other three rivers are non-tidal. The tidal effect on grain size distribution patterns was also studied. Bed load samples were collected from the foreset of different bedform sizes. A total number of 126 sediment samples were collected from different sections of the rivers under study. It is observed that the grain size distribution pattern of the tidal stretch of the Hooghly-Bhagirathi river system has a tendency of attaining a log-skew-Laplace distribution model whereas the other three non-tidal river sediments show a clear log-normal distribution pattern as a best-fit statistical model. A possible reason has been attributed. During prolonged transport of bed material, the coarser and finer sediments are separated in the following manner: coarser sediments are buried below the advancing ripple fronts whereas the finer sediments are transported further downstream as suspension load. As a result, sediments of a narrow range of size classes are active in the distribution pattern giving rise to symmetric and unimodal distribution patterns which are the main criteria of log-normality. On the other hand, due to the upstream and downstream movement during sediment transportation in tidal reaches, the same sediments are constantly reworked and the segregation of different size fractions is hindered causing a log-skew-Laplace distribution pattern.

Abstract The study of size, shape and pattern of various bones in the skull of vertebrate fossils constitutes the foundation of their taxonomy and plays a role in understanding their evolution as well. Size and shape change during lifetime, and the growth of an individual bone involves both isotropic enlargement of its boundary due to uniform growth and differential enlargement that changes its shape. This paper attempts to develop a methodology for quantitative assessment of the pattern of ontogenic shape changes for all the individual skull roof bones of a taxon (Benthosuchus) of an extinct amphibian (temnospondyl) from the Lower Triassic of Russia. Published diagrams depicting skulls of different ontogenic stages have been used. A measure for the degree of shape changes is also proposed. In this study, the skull roof bones in dorsal view were represented as polygons. The boundary of each polygon of a juvenile skull was compared with that of an adult. For comparative purpose, the polygons of the younger skull were placed optimally inside that of the older skull, under the assumption of maximised uniform (isotropic) growth. The variance of the distances between the two boundaries measured at a number of points along the boundaries was considered as a measure for the degree of shape change. The results obtained are in partial concurrence with the published observations traditionally obtained from anatomical studies for the above mentioned growth series.

Abstract A key problem in spatial-mathematical-model-based mineral potential mapping is the selection of appropriate functions that can effectively approximate the complex relationship between target mineral deposits and recognition criteria. This paper evaluates a series of spatial mathematical models based on different linear and non-linear functions by applying them to base-metal potential mapping of the Aravalli province, western India. Linear models applied are an extended weights-of-evidence model and a hybrid fuzzy weights-of-evidence model, while non-linear models are knowledge and data-driven fuzzy models, a neural network model, a hybrid neuro-fuzzy model and an augmented naive Bayesian classifier model. The parameters of the knowledge-driven fuzzy model are estimated from the expert knowledge, while those of the neural network and Bayesian classifier model are estimated from the data. The two hybrid models use both expert knowledge and data for parameter estimation. As compared to the linear models, the non-linear models generally perform better in predicting the known base-metal deposits in the study area. Although the linear models do not fit the data as efficiently as the non-linear models, they are easier to implement using basic GIS functionalities and their parameters are more amenable to geoscientific interpretation. In addition, the linear models are less susceptible to the curse of dimensionality as compared to non-linear models, which makes them more suitable for applications to mineral potential mapping of the areas where there is a paucity of training mineral deposits. The hybrid models that conjunctively use both knowledge and data for parameter estimation generally perform better than purely knowledge-driven or purely data-driven models.

Abstract As part of the Enterprise Information Portal (EIP) project, an Enterprise-wide Geographic Information System has been implemented through which Intranet / Internet users enjoying different access levels can quickly search for, locate and visualize geoscientific information generated by Geological Survey of India (GSI). The proposed system will provide real-time response to information needs and will use secure Internet technology to deliver information to bonafide users. It consists of an application that will enable data owners to load new data sets, update/replace existing data sets in a highly secure environment, load and maintain metadata about their data sets in a Data Catalog and a subsystem that will query, search, locate and display geoinformation stored in the centralized Geodatabase. Enterprise GIS has been deployed primarily using a relational database, a spatial database engine tool, an Internet Map server tool, and integrating the existing ArcGIS desktop GIS clients. The approach is to import data from distributed data sources into the centralized repository using a customized extraction-transformation-loading (ETL) tool, thereby making appropriate structural changes to ensure homogeneity at various levels, and load into the main Geodatabase. While delineating the functionalities of enterprise GIS solution an earnest attempt was made to accommodate the diverse needs of the organization, including its processes, activities, products and the whole gamut of users at different levels from the field geologist to the decision makers. An effort was also made to standardize various data automation processes and to iron out the heterogeneities existing in legacy data. Ultimately, GSI aspires to create a seamless geospatial database for the entire geographic extent of the country, which can be easily shared by the geoscientific community.

Index A Ajoy river 71, 77 Aravalli 99, 101, 102, 118, 119 B Baseline 5, 16, 17, 19, 27, 28, 34, 35, 36, 38, 124, 125 Bayesian 99, 106, 107, 109, 111, 112, 113, 115, 119 Bayesian classifier 99, 106, 107, 109, 112 Bayesian model 113 Bhagirathi 69, 70, 71, 76, 77, 78 Bone boundary 83, 85, 86, 88, 94