Gravity anomalies and deep structure of the Ninetyeast Ridge north of the equator,eastern Indian Ocean — a hot spot trace model

The Ninetyeast Ridge north of the equator in the eastern Indian Ocean is actively deforming as evidenced by seismicity and its eastward subduction below the Andaman Trench. Basement of the ridge is elevated nearly 2 km with respect to the Bengal Fan; seismic surveys demonstrate continuity of the ridge beneath sediment for 700 km north of 10° N where the ridge plunges below the Fan sediment. The ridge is characterised by a free-air gravity high of 50 mgal amplitude and 350 km wavelength, and along-strike continuity of 1500 km in a north-south direction, closely fringing (locally, even abutting) the Andaman arc-trench bipolar gravity field. Regression analysis between gravity and bathymetry indicates that the ridge gravity field cannot be explained solely by its elevation. The ridge gravity field becomes gradually subdued northwards where overlying Bengal Fan sediments have a smaller density contrast with the ridge material. Our gravity interpretation, partly constrained by seismic data, infers that the ridge overlies significant crustal mass anomalies consistent with the hot spot model for the ridge. The anomalous mass is less dense by about 0.27 g cm^–3 than the surrounding oceanic upper mantle, and acts as a cushion for isostatic compensation of the ridge at the base of the crust. This cushion is up to 8 km thick and 400–600 km wide. Additional complexities are created by partial subduction of the ridge below the Andaman Trench that locally modifies the arc-trench gravity field.     

Derivation of coastal wind and wave parameters from offshore measurements of TOPEX satellite using ANN

The paper discusses an artificial neural network (ANN) approach to project information on wind speed and waves collected by the TOPEX satellite at deeper locations to a specified coastal site. The observations of significant wave heights, average wave period and wind speed at a number of locations over a satellite track parallel to a coastline are used to estimate corresponding values of these three parameters at the coastal site of interest. A combined network involving an input and output of all the three parameters, viz., wave height, period and wind speed instead of separate networks for each one of these variables was found to be necessary in order to train the network with sufficient flexibility. It was also found that network training based on statistical homogeneity of data sets is essential to obtain accurate results. The problem of modeling wind speeds that are always associated with very high variations in their magnitudes was tackled in this study by imparting training in an innovated manner.     

Prediction of breaking waves with neural networks

The height of a wave at the time of its breaking, as well as the depth of water in which it breaks, are the two basic parameters that are required as input in design exercises involving wave breaking. Currently the designers obtain these values with the help of graphical procedures and empirical equations. An alternative to this in the form of a neural network is presented in this paper. The networks were trained by combining the existing deterministic relations with a random component. The trained network was validated with the help of fresh laboratory observations. The validation results confirmed usefulness of the neural network approach for this application. The predicted breaking height and water depth were more accurate than those obtained traditionally through empirical schemes. Introduction of a random component in network training was found to yield better forecasts in some validation cases.     

Field testing of single instrumented steel driven batter piles under vertical vibrations

Acta Geotechnica - The forced vertical vibration tests were performed in the field on 3.3-m-long driven steel pipe on a single vertical pile, P1 (β?=?0°), and single batter...     

Mechanisms for the land/sea warming contrast exhibited by simulations of climate change

The land/sea warming contrast is a phenomenon of both equilibrium and transient simulations of climate change: large areas of the land surface at most latitudes undergo temperature changes whose amplitude is more than those of the surrounding oceans. Using idealised GCM experiments with perturbed SSTs, we show that the land/sea contrast in equilibrium simulations is associated with local feedbacks and the hydrological cycle over land, rather than with externally imposed radiative forcing. This mechanism also explains a large component of the land/sea contrast in transient simulations as well. We propose a conceptual model with three elements: (1) there is a spatially variable level in the lower troposphere at which temperature change is the same over land and sea; (2) the dependence of lapse rate on moisture and temperature causes different changes in lapse rate upon warming over land and sea, and hence a surface land/sea temperature contrast; (3) moisture convergence over land predominantly takes place at levels significantly colder than the surface; wherever moisture supply over land is limited, the increase of evaporation over land upon warming is limited, reducing the relative humidity in the boundary layer over land, and hence also enhancing the land/sea contrast. The non-linearity of the Clausius–Clapeyron relationship of saturation specific humidity to temperature is critical in (2) and (3). We examine the sensitivity of the land/sea contrast to model representations of different physical processes using a large ensemble of climate model integrations with perturbed parameters, and find that it is most sensitive to representation of large-scale cloud and stomatal closure. We discuss our results in the context of high-resolution and Earth-system modelling of climate change.     

Impact of seismic factors on landslide susceptibility zonation: a case study in part of Indian Himalayas

Landslides are one of the most widespread natural hazards in high mountain terrains such as the Himalayas, which are one of the youngest tectonically and seismically active mountain ranges in the world. The crustal movements along the longitudinal thrusts and transverse faults give rise to earthquakes and in turn initiate landslides in the region. In fact, in addition to various static factors causing landslides, earthquakes are one of the major causes of landslides. It is thus imperative to incorporate seismic factor also while carrying out landslide susceptibility zonation map preparation in a seismically active areas like Garhwal Himalayas. In this paper, a study on the effect of earthquakes on landslide susceptibility zonation has been demonstrated by taking Chamoli earthquake as an example.     

An approach for GIS-based statistical landslide susceptibility zonation—with a case study in the Himalayas

Landslide susceptibility zonation (LSZ) is necessary for disaster management and planning development activities in mountainous regions. A number of methods, viz. landslide distribution, qualitative, statistical and distribution-free analyses have been used for the LSZ studies and they are again briefly reviewed here. In this work, two methods, the Information Value (InfoVal) and the Landslide Nominal Susceptibility Factor (LNSF) methods that are based on bivariate statistical analysis have been applied for LSZ mapping in a part of the Himalayas. Relevant thematic maps representing various factors (e.g., slope, aspect, relative relief, lithology, buffer zones along thrusts, faults and lineaments, drainage density and landcover) that are related to landslide activity, have been generated using remote sensing and GIS techniques. The LSZ derived from the LNSF method, has been compared with that produced from the InfoVal method and the result shows a more realistic LSZ map from the LNSF method which appears to conform to the heterogeneity of the terrain.     

Spectral models for estimation of chlorophyll content, growth and yield of wheat crop

Field experiments were conducted during 1998–99 and 1999–2000 at research farm of the Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar. Five wheat cultivars: WH 542, PBW 343, UP 2338, Raj 3765 and Sonak were sown on 25^th November, 10^th and 25^th December with four nitrogen levels viz., no nitrogen. 50, 100 and 150% of recommended dose. Leaf area index, dry matter at anthesis, final dry biomass and grain yield were recorded in all the treatments. Chlorophyll and wax contents of wheat leaves were estimated at different growth stages. Multiband spectral reflectance was measured using hand-held radiometer. Spectral indices such as simple ratio, normalized difference, transformed vegetation index, perpendicular vegetation index and greenness index were computed using the multiband spectral data. Values of all the spectral indices were maximum in 25 November sown crop with maximum dose of nitrogen (180 kg N ha^-1). PBW 343 showed higher values of all the spectral indices in comparison with other cultivars. The spectral indices recorded during maximum leaf area index stage were correlated with crop parameters. Using stepwise regression, empirical models for chlorophyll, leaf area index, dry biomass and yield prediction were developed. The ’R²’ values of these models ranged between 0.87 and 0.95.     

Evaluation and Assessment of Blast-Induced Ground Vibrations in an Underground Gold Mine: A Case Study

Natural Resources Research - Ground vibrations induced during rock fragmentation by blasting remain a potential source of hazard for the stability of nearby structures. In this paper, to forecast...