Effective medium theory and multiple linear regression-based velocity estimation in syn-rift clastic sequence of the Krishna–Godavari basin,India

An inclusion model, based on the Kuster–Toksöz effective medium theory along with Gassmann theory, is tested to forward model velocities for fluid-saturated rocks. A simulated annealing algorithm, along with the inclusion model, effectively inverts measured compressional velocity (V_P) to achieve an effective pore aspect ratio at each depth in a depth variant manner, continuously along with depth. Early Cretaceous syn-rift clastic sediments at two different depth intervals from two wells [well A (2160–2274 m) and well B (5222–5303 m)], in the Krishna–Godavari basin, India, are used for this study. Shear velocity (V_S) estimated using modelled pore aspect ratio offers a high correlation coefficient (>0.95 for both the wells) with measured data. The modelled pore aspect ratio distribution suggests the decrease in pore aspect ratio for the deeper interval, mainly due to increased effective vertical stress. The pore aspect ratio analysis in relation to total porosity and volume of clay reveals that the clay volume has insignificant influence in shaping the pore geometry in the studied intervals. An approach based on multiple linear regression method effectively predicts velocity as a linear function of total porosity, the volume of clay and the modelled pore-space aspect ratio of the rock. We achieved a significant match between measured and predicted velocities. The correlation coefficients between measured and modelled velocities are considerably high (approximately 0.85 and 0.8, for V_P and V_S, respectively). This process indicates the possible influence of pore geometry along with total porosity and volume of clay on velocity.     

Changes in daily maximum temperature extremes across India over 1951–2014 and their relation with cereal crop productivity

This study used gridded daily maximum temperature data (1°?×?1°) for 1951–2014 period to analyze the trend in monthly extreme warm days (ExWD) and changes in its probability distribution in each grid. It also analyzed the trend in spatial spread of annual ExWD over the study period at four exceedance levels and further related the number of ExWDs with cereal crop productivity of India. Extreme warm days have increased throughout India but were statistically significant in 42% grids. The increase was consistent over all the months in north-eastern region, southern plateau and both the coastal plains. It also increased significantly over north-western and central India during April to June summer period. The probability distribution of ExWD also changed significantly in many grids, especially in southern plateau and both the coastal plains. The changes indicated increased frequency in the existing levels of extremes and new occurrences of higher frequency of extremes. The analysis of land area affected by different levels of extremes indicated significant increase, with the rate being highest for higher extremes. In terms of extreme warm day temperatures, the study identified southern plateau, east and west coast plains, and north-eastern India as highly vulnerable. Using copula probability model, study showed that increase in ExWD from 20 to 60% may increase the probability of 5% or more yield loss from 17 to 53% for Kharif cereals, 11 to 43% for Rabi cereals and 19 to 63% for wheat crop. The results may be used for devising zone specific adaptation strategies.     

Estimation of spatial variability of aquifer parameters from geophysical methods: a case study of Sindhudurg district,Maharashtra, India

Accurate estimation of aquifer parameters, especially from crystalline hard rock area, assumes a special significance for management of groundwater resources. The aquifer parameters are usually estimated through pumping tests carried out on water wells. While it may be costly and time consuming for carrying out pumping tests at a number of sites, the application of geophysical methods in combination with hydro-geochemical information proves to be potential and cost effective to estimate aquifer parameters. Here a method to estimate aquifer parameters such as hydraulic conductivity, formation factor, porosity and transmissivity is presented by utilizing electrical conductivity values analysed via hydro-geochemical analysis of existing wells and the respective vertical electrical sounding (VES) points of Sindhudurg district, western Maharashtra, India. Further, prior to interpolating the distribution of aquifer parameters of the study area, variogram modelling was carried out using data driven techniques of kriging, automatic relevance determination based Bayesian neural networks (ARD-BNN) and adaptive neuro-fuzzy neural networks (ANFIS). In total, four variogram model fitting techniques such as spherical, exponential, ARD-BNN and ANFIS were compared. According to the obtained results, the spherical variogram model in interpolating transmissivity, ARD-BNN variogram model in interpolating porosity, exponential variogram model in interpolating aquifer thickness and ANFIS variogram model in interpolating hydraulic conductivity outperformed rest of the variogram models. Accordingly, the accurate aquifer parameters maps of the study area were produced by using the best variogram model. The present results suggest that there are relatively high value of hydraulic conductivity, porosity and transmissivity at Parule, Mogarne, Kudal, and Zarap, which would be useful to characterize the aquifer system over western Maharashtra.     

Shock‐thermal history of the Agoudal (IIAB) iron meteorite from microstructural studies

The Agoudal IIAB iron meteorite exhibits only kamacite grains (~6 mm across) without any taenite. The kamacite is homogeneously enriched with numerous rhabdite inclusions of different size, shape, and composition. In some kamacite domains, this appears frosty due to micron‐scale rhabdite inclusions (~5 to 100 μm) of moderate to high Ni content (~26 to 40 wt%). In addition, all the kamacite grains in matrix are marked with a prominent linear crack formed during an atmospheric break‐up event and subsequently oxidized. This feature, also defined by trails of lowest Ni‐bearing (mean Ni: 23 wt%) mm‐scale rhabdite plates (fractured and oxidized) could be a trace of a pre‐existing γ–α interface. Agoudal experienced a very slow rate of primary cooling ~4 °C Ma^?1 estimated from the binary plots of true rhabdite width against corresponding Ni wt% and the computed cooling rate curves after Randich and Goldstein (1978). Chemically, Agoudal iron (Ga: 54 ppm; Ge: 140 ppm; Ir: 0.03 ppm) resembles the Ainsworth iron, the coarsest octahedrite of the IIAB group. Agoudal contains multiple sets of Neumann bands that are formed in space and time at different scales and densities due to multiple impacts with shock magnitude up to 130 kb. Signatures of recrystallization due to postshock low temperature mild reheating at about 400 °C are also locally present.     

A hybrid deterministic and stochastic approach for tsunami hazard assessment in Iquique,Chile

Natural Hazards - This paper presents an investigation of the collapse of a 325-year-old multi-tiered heritage temple during the 2015 Gorkha earthquake in Kathmandu, Nepal. The research comprises a...     

Seismic response analysis of a hydraulic fill dam

Acta Geotechnica - The seismic response of a highly heterogeneous hydraulic fill dam was evaluated by studying the natural frequencies of the first and second modes of vibration and analyzing the...     

Simulation of rain-bearing summer monsoon systems along the west coast of India by use of ARMEX re-analysis

Re-analysis, using surface, upper-air, and satellite observations specially collected during the Arabian Sea Monsoon Experiment-I (ARMEX-I), has been performed with a global data assimilation system at T-80/L18 resolution. Re-analysis was performed for the entire ARMEX-I period (15th June–16th August 2002). In this paper we discuss the results based on re-analysis and subsequent forecasts for two successive intensive observation periods associated with heavy rainfall along the west coast of India during 2–12 August, 2002. Results indicate that the re-analysed fields can bring out better synoptic features, for example troughs along the west coast and mid tropospheric circulation over the Arabian Sea. Simulated rainfall distribution using re-analysis as initial condition also matches observed rainfall better than data from the initial analysis.     

Damage‐based design with no repairs for multiple events and its sensitivity to seismicity model

Conventional design methodology for the earthquake‐resistant structures is based on the concept of ensuring ‘no collapse’ during the most severe earthquake event. This methodology does not envisage the possibility of continuous damage accumulation during several not‐so‐severe earthquake events, as may be the case in the areas of moderate to high seismicity, particularly when it is economically infeasible to carry out repairs after damaging events. As a result, the structure may collapse or may necessitate large scale repairs much before the design life of the structure is over. This study considers the use of design force ratio (DFR) spectrum for taking an informed decision on the extent to which yield strength levels should be raised to avoid such a scenario. DFR spectrum gives the ratios by which the yield strength levels of single‐degree‐of‐freedom oscillators of different initial periods should be increased in order to limit the total damage caused by all earthquake events during the lifetime to a specified level. The DFR spectra are compared for three different seismicity models in case of elasto‐plastic oscillators: one corresponding to the exponential distribution for return periods of large events and the other two corresponding to the lognormal and Weibull distributions. It is shown through numerical study for a hypothetical seismic region that the use of simple exponential model may be acceptable only for small values of the seismic gap length. For moderately large to large seismic gap lengths, it may be conservative to use the lognormal model, while the Weibull model may be assumed for very large seismic gap lengths. Copyright © 2006 John Wiley & Sons, Ltd.     

Remote sensing and GIS for artificial recharge study, runoff estimation and planning in Ayyar basin, Tamil Nadu, India

This paper focuses on artificial groundwater recharge study in Ayyar basin, Tamil Nadu, India. The basin is covered by hard crystalline rock and overall has poor groundwater conditions. Hence, an artificial recharge study was carried out in this region through a project sponsored by Tamil Nadu State Council for Science and Technology. The Indian Remote Sensing satellite 1A Linear Imaging Self Scanning Sensor II (IRS 1A LISS II) satellite imagery, aerial photographs and geophysical resistivity data were used to prioritize suitable sites for artificial recharge and to estimate the volume of aquifer dimension available to recharge. The runoff water available for artificial recharge in the basin is estimated through Soil Conservation Service curve number method. The land use/land cover, hydrological soil group and storm rainfall data in different watershed areas were used to calculate the runoff in the watersheds. The weighted curve number for each watershed is obtained through spatial intersection of land use/land cover and hydrological soil group through GeoMedia 3.0 Professional GIS software. Artificial recharge planning was derived on the basis of availability of runoff, aquifer dimension, priority areas and water table conditions in different watersheds in the basin.