Depositional history,processes and mechanism of early Miocene sediments of Upper Assam Basin

A detailed analysis of depositional history of Miocene sediments and various effects which are governed for creation of accommodation space as well as the processes of sedimentation inherent to the depositional system at that period is described in this work. The early Miocene clastic sediments are deposited in prograding environment where sediment supply exceeds the accommodation space available. The accommodation space created due to basin subsidence and source area upliftment due to local and regional tectonic activity in the basin. In the early Miocene time, the Assam shelf major transgression occurred and several minor transgression followed. There was wide spread deposition of the fluvial Tipam sandstones. In Miocene time due to thrust loading and flexure subsidence, accommodation space was created for deposition of the sediments. The Tipam Sandstone is deposited by cyclic deposition of fining upward sequence in a fluvial to brackish water environment of braided river processes. The mechanism of braided rivers is also discussed in which it laterally expanded, leaving sheet like or wedge — shaped deposits of channel and bar complexes preserving only minor amounts of flood plain material.     

Radon as seismic precursor: new data with well water of Jalpaiguri,India

This paper reports the measurement of radon concentration in well water at the site of Jalpaiguri (26°32′N, 88°46′E) near the active fault zone of West Bengal, India. Radon concentration has been measured in well water with the help of solid-state nuclear track detectors (SSNTD). The study indicates a positive correlation between radon anomaly and earthquake. The data of radon content in well water have been compared with that in soil gas at the same site.     

Impact of water demand on hydrological regime under climate and LULC change scenarios

The present study focuses on an assessment of the impact of future water demand on the hydrological regime under land use/land cover (LULC) and climate change scenarios. The impact has been quantified in terms of streamflow and groundwater recharge in the Gandherswari River basin, West Bengal, India. dynamic conversion of land use and its effects (Dyna-CLUE) and statistical downscaling model (SDSM) are used for quantifying the future LULC and climate change scenarios, respectively. Physical-based semi-distributed model Soil and Water Assessment Tool (SWAT) is used for estimating future streamflow and spatiotemporally distributed groundwater recharge. Model calibration and validation have been performed using discharge data (1990–2016). The impacts of LULC and climate change on hydrological variables are evaluated with three scenarios (for the years 2030, 2050 and 2080). Temperature Vegetation Dyrness Index (TVDI) and evapotranspiration (ET) are considered for estimation of water-deficit conditions in the river basin. Exceedance probability and recurrence interval representation are considered for uncertainty analysis. The results show increased discharge in case of monsoon season and decreased discharge in case of the non-monsoon season for the years 2030 and 2050. However, a reverse trend is obtained for the year 2080. The overall increase in groundwater recharge is visible for all the years. This analysis provides valuable information for the irrigation water management framework.     

Mapping the distribution of iron ore minerals and spatial correlation with environmental variables in hilltop mining areas

The prime contribution of this assignment was to examine the hyperspectral remote sensing, based on iron ore minerals identification using spectral angle mapper (SAM) technique. Correlation analyses between field iron contents and environmental variables (soil, water, and vegetation) have been performed. Spectral feature fitting (SFF) and multi-range spectral feature fitting (MRSFF) methods were used for accuracy assessment in extracting iron ore minerals from Hyperion EO-1 data. Spectral inspections as a reference were used in SAM technique for image classification for iron ore minerals: Hematite (24.26%), Goethite (32.98%) and Desert (42.76). Iron ore minerals classification is justified by the United States Geological Survey (USGS) spectral library and field sample points. The regression analysis of USGS and Hyperion reflectance spectra has shown the moderate positive correlation. The regression analyses between iron ore contents and environmental parameters (soil, water, and vegetation) have shown the moderate negative correlation. The examination was significantly effectual in extracting iron ore minerals: Hematite (SFF RMSE?≤?0.51 MRSFF RMSE?≤?0.48), Goethite (SFF RMSE?≤?0.047 MRSFF RMSE?≤?0.438) and Desert (SFF RMSE?≤?0.63 and MRSFF RMSE?≤?0.50); and the MRSFF RMSE histograms indicate the above result likened to a conventional SFF RMSE. MRSFF RMS error result is best because multiple absorption features typically characterize spectral signatures. This analysis demonstrates the potential applicability of the methodology for iron minerals identification framework and iron minerals impact on environmental parameters.     

Identification of Suitable Hydrological Models for Streamflow Assessment in the Kangsabati River Basin,India, by Using Different Model Selection Scores

The increasing demand for water in developing countries, like India, requires efficient water management and resource allocation. This is crucial to accurately assess and predict hydrological processes such as streamflow, drought, and flood. However, simulations of these hydrologic processes from various hydrological models differ in their accuracy. By analyzing different characteristics of hydrological models, selection scores can be used to select the best model for the intended purpose based on their inherit strengths (i.e., some models are better for streamflow prediction). In this study, 13 different criteria were used for the model selection scores including temporal and spatial resolutions, and processes involved. Thereafter, based on different scores, we selected two different hydrological models for streamflow prediction in the Kangsabati River Basin (KRB) in eastern India, namely (1) Génie Rural à 4 paramètres Journalier (GR4J), a conceptual model, and (2) Variable Infiltration Capacity (VIC), a semi-distributed model. The models were calibrated against the daily observed streamflow at upper KRB (Reservoir) and lower KRB (Mohanpur) from 2000 to 2006 and validated during the period from 2008 to 2010. Despite the differences in model structure and data used, both models simulated streamflow at a daily time scale with Nash–Sutcliffe coefficient of 0.71–0.82 for the VIC model and 0.63–0.71 for the GR4J. Due to the simpler structure, parsimonious nature, fewer parameters, and reasonable accuracy, the results suggest that a conceptual rainfall—runoff model like GR4J can be used in data-deficient conditions.

     

Analytical expressions for determining the stability of cohesionless soil slope under generalized seismic conditions

In recent major earthquakes, the researchers have found the need for consideration of vertical seismic acceleration for the stability analysis of the man-made and natural slopes. However, in most past studies, the performance of slopes has been assessed by accounting only the horizontal seismic component of the ground motion, without giving due weightage to the effect of vertical component. In the present study, analytical expressions are derived to determine the factor of safety, yield seismic coefficient and consequently the seismic displacement of cohesionless soil slope under combined horizontal and vertical components of the ground motion. The derivation uses the Newmark’s sliding block approach, in which the soil slope with a planar failure surface within the framework of conventional pseudo-static analysis is assumed to follow the Mohr-Coulomb failure criterion. The effects of vertical seismic coefficient on the stability of cohesionless slope have been studied through a set of graphical presentations for a specific range of soil parameters. It is observed that overlooking the effect of the vertical component of the ground motion on factor of safety and the displacement while designing the slope may be detrimental, resulting in the slope failure. The general expressions presented in this paper may be highly useful in the field of earthquake geotechnical engineering practice for designing the cohesionless soil slopes under combined horizontal and vertical seismic loads.     

Mesonic stiff fluid distribution in five dimensional Bianchi type space time

In this paper, we have constructed mesonic stiff fluid cosmological models in five dimensional LRS Bianchi type-I and Bianchi type-VI₀ space times in general theory of relativity. Some physical and geometrical properties of the models are discussed.     

On Bianchi Type-I Mesonic Cosmological Model in Bimetric Theory

Anisotropic spatially homogeneous Bianchi type-I cosmological model in bimetric theory of gravitation (Rosen, 1973) is considered. It is shown that the Bianchi type-I cosmological model does not exist in case of both meson field and mesonic perfect fluid (with or without mass parameter). Hence only vacuum models can be obtained (Reddy and Venkateswarlu, 1989). This revised version was published online in July 2006 with corrections to the Cover Date.     

Evaluation of Recharge and Groundwater Dynamics of a Shallow Alluvial Aquifer in Central Ganga Basin,Kanpur (India)

Evaluation of recharge and groundwater dynamics of an aquifer is an important step for finding a proper groundwater management scenario. This has been performed on the basis of statistical Kendall Tau test to find a relationship between groundwater levels and hydro-meteorological parameters (e.g., precipitation, temperature, evaporation). Recharge to the aquifer was estimated for identification of critical areas/locations based on the analytical Soil and Water Assessment Tool. Moreover, spatiotemporal variability of groundwater levels has been quantified using space–time variogram. The overall characterization method has been applied to the shallow alluvial aquifer of Kanpur city in India. The analysis was performed using groundwater level data from 56 monitoring piezometer locations in Kanpur from March 2006 to June 2011. Groundwater level shows relatively higher correlation with temperature. Performance of the geostatistical model was evaluated by comparing with the observed values of groundwater level from January 2011 to June 2011 for two scenarios: “with limited spatiotemporal data” and “without spatiotemporal data.” It is evident that spatiotemporal prediction of groundwater level can be performed even for the unmonitored/missing data. This analysis demonstrates the potential applicability of the method for a general aquifer system.