Numerical Modeling of Suspended Sediment Transport in the Gulf of Kachchh Including Kandla Creek, West Coast of India

A depth-averaged numerical model has been developed to study tidal circulation and suspended sediment transport in the Gulf of Kachchh including Kandla creek, west coast of India. The resolution of the model is taken as 750 m × 750 m, which is found to be adequate for the gulf region. However, this resolution could not produce the realistic circulation pattern and suspended sediment concentration in the Kandla creek region. There is a major seaport at Kandla which serves as the sea gate to northwest India. Therefore, a 2-D fine resolution (75 m × 75 m) model for Kandla creek has been developed and coupled with the coarser gulf model to compute the flow features in the creek region. The model dynamics and basic formulation remain the same for both the gulf model and the creek model. The models are barotropic, based on shallow water equations, and neglect horizontal diffusion and wind stress terms in the momentum equations. The models are fully nonlinear and use a semiexplicit finite difference scheme to solve mass, momentum, and advection-diffusion equations in a horizontal plane. The tide in the gulf is represented in the model by the semidiurnal M₂ constituent mainly. In this study, no fresh water discharge conditions have been considered so the results are appropriate for the dry season. Numerical experiments are carried out to study the circulation and suspended sediment concentrations in the gulf and the creek regions. The computed results are validated with the available observations.     

A Breadth Averaged Numerical Model for Suspended Sediment Transport in Hooghly Estuary,East Coast of India

Sedimentation is of vital concern in the conservation, development and utilization ofour soil and water resources. The suspended sediment in estuarine waters is hazardousto navigation in estuaries, which have important ports and harbours. A breadth-averagednumerical model to study circulation and sediment transport is presented in this paper.The model is applied to Hooghly estuary, along the east coast of India. The model is fullynon-linear and uses a semi-explicit finite difference scheme to solve mass, momentum andadvection diffusion equation for suspended sediments in a vertical plane. The erosion anddeposition have been computed by empirically developed source and sink terms in thesuspended sediment equation.     

Seasonal variation of oxidative biomarkers in gills and digestive gland of green-lipped mussel Perna viridis from Arabian Sea

Investigations on seasonal variation in oxidative stress biomarkers were carried out on the natural population of green-lipped mussel Perna viridis collected from Bambolim beach area of Goa. Oxidative stress indices such as lipid peroxidation (LPX), hydrogen peroxide (H₂O₂), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), glutathione transferase (GST), glutathione reductase (GR), reduced glutathione (GSH) and ascorbic acid (ASA) were measured in gills and digestive gland of P. viridis during February, May, August and November. The present study reveals two important aspects regarding the antioxidant defence status of tissues of P. viridis. Firstly, antioxidant capacity of tissues of P. viridis exhibits seasonal variation. Secondly, various components of antioxidant capacity such as oxidative stress markers, levels of antioxidant enzymes and small antioxidant molecules vary differently in tissues with respect to different seasons. Although the oxidative stress status of gills and digestive gland of P. viridis expressed in terms of LPX and H₂O₂ was the lowest in February, its level was maximal in gills and digestive gland during May and November, respectively. While activities of SOD and GPX of tissues of P. viridis were found to be low in August, activities of CAT and GR were recorded to be low in February. GST activity in gills although remained high in February, in digestive gland elevated values were recorded in August and November. A seasonal variation in the levels of small antioxidant molecules was also noticed. Among non enzymatic antioxidants ASA content of tissues was maximal in May and August in comparison to February and November, but GSH remained high in November. It therefore appears that environmental factors may play a crucial role in regulating the oxidative stress capacity of tissues of P. viridis.     

Earthquake risk assessment in NE India using deep learning and geospatial analysis

Earthquake prediction is currently the most crucial task required for the probability, hazard, risk mapping, and mitigation purposes. Earthquake prediction attracts the researchers' attention from both academia and industries. Traditionally, the risk assessment approaches have used various traditional and machine learning models. However, deep learning techniques have been rarely tested for earthquake probability mapping. Therefore, this study develops a convolutional neural network (CNN) model for earthquake probability assessment in NE India. Then conducts vulnerability using analytical hierarchy process (AHP), Venn's intersection theory for hazard, and integrated model for risk mapping. A prediction of classification task was performed in which the model predicts magnitudes more than 4 Mw that considers nine indicators. Prediction classification results and intensity variation were then used for probability and hazard mapping, respectively. Finally, earthquake risk map was produced by multiplying hazard, vulnerability, and coping capacity. The vulnerability was prepared by using six vulnerable factors, and the coping capacity was estimated by using the number of hospitals and associated variables, including budget available for disaster management. The CNN model for a probability distribution is a robust technique that provides good accuracy. Results show that CNN is superior to the other algorithms, which completed the classification prediction task with an accuracy of 0.94, precision of 0.98, recall of 0.85, and F1 score of 0.91. These indicators were used for probability mapping, and the total area of hazard (21,412.94 km²), vulnerability (480.98 km²), and risk (34,586.10 km²) was estimated.     

Characterization of hydrocarbon-bearing fluid inclusion in sandstones of Jaisalmer basin, Rajasthan: A preliminary approach

The quartz grains from the sandstone of Jaisalmer, Pariwar and Goru Formations of the Jaisalmer basin, Rajasthan, India, exhibits a variety of primary and secondary fluid inclusions. Most of them are hydrocarbon bearing fluid inclusions. Laser Raman studies indicate that the primary fluid inclusions were mostly having aliphatic hydrocarbons with lower degree of maturity, while the secondary fluid inclusions were generally with aliphatic as well as aromatic hydrocarbons with higher degree of maturity. This inference was consistent with their fluorescence characteristics. The homogenization temperatures of primary monophase CH₄ rich fluid inclusions varied from ?80°C to ?100°C, whereas the primary biphase fluid inclusions (CH₄-CO₂) homogenized between +80°C and +150°C. The secondary petroleum rich monophase fluid inclusions were having homogenization temperature between ?80°C to ?90°C, whereas the secondary biphase fluid inclusions homogenized between +130°C and +180°C. Most of the secondary biphase fluid inclusions were having the mixtures of H₂O-CO₂-NaCl, and were identified on the basis clathrate formation and they got homogenized between +140°C and + 250 °C. The three past events of migration of petroleum inferred in the host rock which were marked by the presence of characteristic secondary fluid inclusions. They were identified on the basis of cross-cutting relationships of different trails of fluid inclusions in the quartz. The cement generation in the basin might have been occurred in two stages as per the fluid inclusion petrography.     

Microstructure-compositional variation in iron oxy-hydroxide minerals formed with manganese mineralization,Eastern Ghats Supergroup,Orissa

Large volume of iron oxy-hydroxide minerals occur in association with manganese oxide phase in manganese ores of the Eastern Ghats Supergroup, Koraput district, Orissa. On the basis of OH content, the iron mineral can be classified into hydrohematite, goethite, and hydrogoethite. These minerals exhibit eight types of microstructures such as ooloidal, caterpillar, disseminated, reniform, worm, mosaic, globular and spherulitic. Chemical composition of such micro-structures obtained through EPMA, distinguishes them into three domains, developed under different environment. Hydrohematite, having 8–10 % H₂O, characteristically contains higher pc of manganese (>5%) and phosphorous (>0.6%) but have low silica and alumina. These are formed syngenetically with Mn-oxide minerals in a manganese rich paragenesis. Goethite containing 11 to 12% water, has relatively low level of manganese and phosphorous, and formed in a later period, as secondary open space filling. Hydrogoethite shows very high water content (>16%), almost devoid of manganese, and impoverished in phosphorous but having higher percentage of alumina, silica and appreciable copper and nickel. This was latest to form in the zone of oxidation under supergene condition.