Inhomogeneous cosmological models in the presence of massless scalar fields

Non-static inhomogeneous cosmological models are obtained in general relativity for the case of a plane symmetric massless scalar field with cosmological constant A,when the source of the gravitational field is a viscous fluid.Some physical and geometrical behaviors of the solutions are also discussed.     

Understanding the Cyclicity of Chemical Weathering and Associated CO<Subscript>2</Subscript> Consumption in the Brahmaputra River Basin (India): The Role of Major Rivers in Climate Change Mitigation Perspective

Weathering of rocks that regulate the water chemistry of the river has been used to evaluate the CO₂ consumption rate which exerts a strong influence on the global climate. The foremost objective of the present research is to estimate the chemical weathering rate (CWR) of the continental water in the entire stretch of Brahmaputra River from upstream to downstream and their associated CO₂ consumption rate. To establish the link between the rapid chemical weathering and thereby enhance CO₂ drawdown from the atmosphere, the major ion composition of the Brahmaputra River that drains the Himalaya has been obtained. Major ion chemistry of the Brahmaputra River was resolved on samples collected from nine locations in pre-monsoon, monsoon and post-monsoon seasons for two cycles: cycle I (2011–2012) and cycle II (2013–2014). The physico-chemical parameters of water samples were analysed by employing standard methods. The Brahmaputra River was characterized by alkalinity, high concentration of Ca²⁺ and HCO₃ ^? along with significant temporal variation in major ion composition. In general, it was found that water chemistry of the river was mainly controlled by rock weathering with minor contributions from atmospheric and anthropogenic sources. The effective CO₂ pressure (log\({{\text{P}}_{{\text{C}}{{\text{O}}_{\text{2}}}}}\)) for pre-monsoon, monsoon and post-monsoon has been estimated. The question of rates of chemical weathering (carbonate and silicate) was addressed by using TDS and run-off (mm year^?1). It has been found that the extent of CWR is directly dependent on the CO₂ consumption rate which may be further evaluated from the perspective of climate change mitigation The average annual CO₂ consumption rate of the Brahmaputra River due to silicate and carbonate weathering was found to be 0.52 (×10⁶ mol Km^?2 year^?1) and 0.55 (×10⁶ mol Km^?2 year^?1) for cycle I and 0.49 (×10⁶ mol Km^?2 year^?1) and 0.52 (×10⁶ mol Km^?2 year^?1) for cycle II, respectively, which were significantly higher than that of other Himalayan rivers. Estimation of CWR of the Brahmaputra River indicates that carbonate weathering largely dominates the water chemistry of the Brahmaputra River.     

Homogeneous region determination using linear and nonlinear techniques

Similarity between catchments in a region can be determined depending on catchment properties. This helps to understand the response behavior of the similar catchments more appropriately. Catchment classification plays a major role in the process of hydrological prediction in the case of ungauged catchments. The following categorization was carried out for 32 catchments of India. Principal Component Analysis (PCA) along with K-means clustering, was applied as linear classification; and Self-Organizing Map (SOM) and Kernel Principal Component Analysis (KPCA) were implemented as nonlinear classification methods on catchment attributes and daily streamflow time series. The classification established on streamflow signatures was taken as the reference classification. Results obtained from PCA, SOM, and KPCA were compared with results of the reference classification. The absence of discordant catchments from the clusters of SOM, based on catchment attributes, suggests homogeneity among SOM-derived clusters. Similarity index scores are 0.48 and 0.47, 0.46 and 0.42 ?for first, second, third and fourth clusters of SOM respectively with that of the reference classification technique. Nonlinear techniques with high similarity index values outperformed standard techniques. This study demonstrated the ability of classification based on catchment attributes to classify ungauged catchments.     

Holocene relative shore-level changes and development of the Ģipka lagoon in the western Gulf of Riga

Holocene relative shore-level changes and development of the Ģipka palaeolagoon in the western Gulf of Riga are reconstructed using multiproxy analyses by combining litho-, biostratigraphical and chronological data with remote sensing and geophysical data. The results show the development of the Ģipka basin from the Ancylus Lake/Initial Litorina Sea coastal zone (before c. 9.1 cal. ka BP) to coastal fen (c. 9.1 to 8.4 cal. ka BP) and gradual development of the Litorina Sea lagoon (c. 8.4 to 4.8 cal. ka BP) and its transition to a freshwater coastal lake (c. 4.8 to 4.6 cal. ka BP), fen (c. 4.6 to 4.2 cal. ka BP), and river floodplain (since c. 4.2 cal. ka BP). The highest shorelines of the Ancylus Lake and Litorina Sea were mapped at an elevation of 12–11 and 9 m a.s.l., respectively. A new relative shore level (RSL) curve for the western Gulf of Riga was constructed based on RSL data from the Ģipka area and from nearby Ruhnu Island studied earlier. The reconstruction shows that the beginning of the last marine transgression in the western Gulf of Riga started at c. 8.4 cal. ka BP, and concurred with the 1.9 m RSL rise event recorded from the North Sea basin. Diatom analysis results indicate the existence of the Ģipka lagoon between c. 7.7 and 4.8 cal. ka BP, with the highest salinity c. 6.1 cal. ka BP. During the existence of the brackish lagoon, settlement sites of the Neolithic hunter–gatherer groups existed on the shores of the lagoon in the period c. 6.0 to 5.0 cal. ka BP.     

Differences in tree species diversity and soil nutrient status in a tropical sacred forest ecosystem on Niyamgiri hill range, Eastern Ghats, India

We have quantitatively analyzed the tree species diversity with respect to soil nutrient status in three sites of a sacred forest ecosystem of Niyamgiri hill range,Eastern Ghats,India.Extensive field surveys and sampling were conducted in 3 sites of the hill range:Site 1 Pterocarpus dominated forest(PTF)(19°40’02.2" N and 83°21’23.1" E),Site 2 Mangifera dominated forest(MAF)(19°40’02.8" N and 83°21’40.8" E) and Site 3 Mixed forest(MIF)(19°36’47.1" N and 83°21’02.7" E).A total of 28 families,42 genera,46 tree species,and 286 individual trees were recorded on an area of 0.6 ha.Tree density varied between 470 and 490 individuals ha-1 and average basal area between 3.16 and 10.04 m2 ha-1.Shannon Index(H’) ranged from 2.34 to 4.53,Simpson’s Index ranged from 0.07 to 0.09,and equitability Index ranged from 0.7 to 1.34.The number of individuals was highest in the girth at breast height(GBH) class of 50-70 cm.The soil nutrient status of the three forest types was related to tree species diversity.The soil pH value of the three sites reflected the slightly acidic nature of the area.Species diversity was positively correlated with organic carbon and phosphorus and negatively with nitrogen,EC and pH.The results of the current study may be helpful to further develop a conservation planfor tree species in tropical sacred forest ecosystems.     

Performance of Multi Model Canonical Correlation Analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output

The emerging advances in the field of dynamical prediction of monsoon using state-of-the-art General Circulation Models (GCMs) have led to the development of various multi model ensemble techniques (MMEs). In the present study, the concept of Canonical Correlation Analysis is used for making MME (referred as Multi Model Canonical Correlation Analysis or MMCCA) for the prediction of Indian summer monsoon rainfall (ISMR) during June-July-August-September (JJAS). This method has been employed on the rainfall outputs of six different GCMs for the period 1982 to 2008. The prediction skill of ISMR by MMCCA is compared with the simple composite method (SCM) (i.e. arithmetic mean of all GCMs), which is taken as a benchmark. After a rigorous analysis through different skill metrics such as correlation coefficient and index of agreement, the superiority of MMCCA over SCM is illustrated. Performance of both models is also evaluated during six typical monsoon years and the results indicate the potential of MMCCA over SCM in capturing the spatial pattern during extreme years.     

Markov chain model to study the occurrence of pre-monsoon thunderstorms over Bhubaneswar,India

The present work deals with pre-monsoon thunderstorms over Bhubaneswar belonging to the state of Orissa, India. A Markovian approach has been adopted to discern the probabilistic behavior of the time series of the occurrence and non-occurrence of this hazardous weather event by introducing a dichotomy within the time series. After a painstaking analysis through chi-square tests, we have identified serial independence in a few years and first-order two-state Markovian dependence in a few years (2000, 2001, 2004 and 2006). Finally, for the years of first-order two-state Markovian dependence, it has been observed that the probability of occurrence or non-occurrence of thunderstorm gets higher if the state of the previous day is similar to that of the current day. Furthermore, the probability of getting non-thunderstorm day followed by non-thunderstorm day is higher than the probability of getting thunderstorm day followed by thunderstorm day. It has been also observed that the unconditional climatological probability of the occurrence of severe pre-monsoon thunderstorm implied by the Markov chain is closely in agreement with the observed relative frequencies. However, it could be revealed that Markov chain cannot, in general, be suggested as a predictive tool for pre-monsoon thunderstorms under study without investigating the serial dependence inherent in the time series.