Exact solution of the equation of radiative transfer for semi-infinite plane-parallel isotropic scattering atmosphere with scattering albedo ω0 ≤ 1 by a method based on Laplace transform and Wiener-Hopf technique

By performing the one-sided Laplace transform on the scalar integro-differential equation for a semi-infinite plane-parallel isotropic scattering atmosphere with a scattering albedo ₀ 1, an integral equation for the emergent intensity has been derived. Application of the Wiener-Hopf technique to this integral equation will give the emergent intensity. The intensity at any optical depth for a positive scattering angle is also derived by inversion. The intensity at any optical depth for a negative scattering angle is also derived in terms of Cauchy's principal value using Plemelj's formulae.     

Propagation of Rayleigh waves in soils

Summary Propagation of Rayleigh type waves in soils is considered in this paper. It is a well known fact that soils do not behave like an ordinary isotropic elastic medium where the ratio of Young's modulus to the modulus of rigidity is much less than that in sandy soils. Considering the velocity of Rayleigh type wave as less than that of distortional wave (which is an observed fact) a probable value of this ratio is determined, and also assuming the value of this ratio based on some experimental data, the velocity of wave propagation in the medium is deduced.     

Behaviour of dissipative accretion flows around black holes

We investigate the behaviour of dissipative accreting matter close to a black hole, as this provides important observational features of galactic and extragalactic black hole candidates. We find a complete set of global solutions in the presence of viscosity and synchrotron cooling. We show that advective accretion flow can have a standing shock wave and the dynamics of the shock is controlled by the dissipation parameters (both viscosity and cooling). We study the effective region of the parameter space for standing as well as oscillating shock. We find that the shock front always moves towards the black hole as the dissipation parameters are increased. However, viscosity and cooling have opposite effects in deciding the solution topologies. We obtain two critical cooling parameters that separate the nature of the accretion solution.     

Impact of vegetation on the simulation of seasonal monsoon rainfall over the Indian subcontinent using a regional model

The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation, surface radiation, etc., that in turn induces changes in the model simulated outputs. The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model. The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization) versus that of USGS (United States Geological Survey) vegetation dataset on the simulation of the Indian summer monsoon. The present study has been conducted for five monsoon seasons (1998–2002), giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal) and 2002 (deficient). The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon. Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast. The MM5-USGS has greater tendency of overestimation of rainfall. It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation. Among the five years of study, it is seen that the RMSE of July and JJAS (June–July–August–September) for All India Rainfall is mostly lower for MM5-ISRO. Also, the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO. The wind fields at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation. The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the verification analysis by ISRO vegetation. The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India, showing greater spatial variability over the region. However, the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation. Sensible heat flux over north-west India is also better simulated by MM5-USGS.     

Linearized and non-linearized isotherm models comparative study on adsorption of aqueous phenol solution in soil

Use of native soil in adsorption of phenol from industrial wastewater has been one of the attractive option for dephenolation, especially in view of low cost and ease in accessibility, as well as scope for regeneration (or, at least reuse). However, an effective usage of the adsorbent necessitates a deeper understanding of the adsorption characteristics. Most of the study of adsorption characteristics are confined to analysis of mono- and bi- parametric isotherm models (and rarely, linearized multi-parametric isotherm models), due to the difficulties in solving higher parametric models, as well as fairly satisfying results by lower-parametric models. In the present study, adsorption batch studies were carried out using a naturally and widely available common soil of south India (namely, Adhanur soil), for removal of phenol from the aqueous solution, with an explicit objective of comparison of linear and non-linear regression methods for finding variation in isotherm coefficients and fitness of the models. Six linearized isotherm models (including four linearized Langmuir models) and three non-linear isotherm model were discussed in this paper, and their coefficients were estimated. Although all the studied isotherm models showed fairly good fit to the experimental data, but Redlich—Peterson isotherm was found to be the best representative for phenol-sorption on the used soil adsorbent. Besides, it was observed that to determine the isotherm parameters non-linear isotherm models were found to be the best representative of adsorption characteristics, than their linearized counter-parts.     

Comparison of intact rock failure criteria using various statistical methods

This paper compares four different rock failure criteria based on triaxial test data of ten different rock strength data using various statistical methods. Least square, least median square and re-weighted least square techniques are used to determine the best fit parameters utilizing the experimental data that describes the failure state for each criterion. The least median square method could identify the scattered data and these scattered data points are observed at higher confining stress. It was observed that the fitting of failure criteria to different rock strength data depends upon the statistical methods used. The prediction of unconfined compressive strength and failure strength for different rocks estimated using various statistical methods are discussed in terms of different statistical performances of the prediction.     

Reconnaissance report on geotechnical effects and structural damage caused by the 3 January 2017 Tripura earthquake,India

Natural Hazards - An earthquake of moment magnitude Mw 5.7 shook the northeastern region of India on 3 January 2017 at 14 h:39 min:0.5 s local time. The duration of the...     

Biomarker evidence of macrophyte and plankton community changes in Zeekoevlei,a shallow lake in South Africa

Zeekoevlei is the largest freshwater lake in South Africa and has a century-long history of anthropogenic impact that caused hyper-eutrophic conditions. We used biomarkers (alkanes and pigments), stable isotopes (δ¹³C and δ¹⁵N), rates of primary palaeoproduction and total inorganic carbon (TIC) accumulation rates in the lake sediments to investigate changes in plankton and macrophyte communities in response to anthropogenic activities in this shallow lake. Specific alkanes (ΣC_15,17,19, pristane, phytane and n-C₂₉/n-C₁₇ ratio) and pigment (chlorophyll a, β,β-carotene, echinenone, fucoxanthin and zeaxanthin) concentrations in lake waters indicated the present-day hyper-eutrophic condition and seasonal fluctuations of cyanobacteria, zooplankton and diatom populations. Eutrophic conditions were initiated in the lake with the start of recreational activities and construction of a sewage treatment plant in the early 1920s. The lake transformed from a eutrophic to a hyper-eutrophic waterbody following damming, pondweed eradication and accelerated catchment-derived nutrient input. The change in lake trophic state was recorded by a sharp decline in the terrestrial to aquatic ratio (TAR) of specific n-alkanes, low carbon preference index (CPI) and increased δ¹³C values in the sediment core. In addition, the aquatic macrophyte n-alkane proxy (P_aq) values (~1) indicated a slow takeover by floating macrophytes after the eradication of submerged pondweeds in 1951. Elevated n-alkane (ΣC_15,17,19), total alkane and pigment (chlorophyll a, β,β-carotene, zeaxanthin and zeaxanthin to β,β-carotene ratio) concentrations, low δ¹⁵N values and low TIC accumulation rates in the upper middle section of the core indicated the beginning of intense cyanobacterial blooms after the dredging in 1983. Although the cyanobacterial population has decreased in recent years, hyper-eutrophic conditions are reflected by low CPI <0.04 and TAR <1 values at the top of the sediment core.     

A neurocomputing approach to predict monsoon rainfall in monthly scale using SST anomaly as a predictor

A relationship between summer monsoon rainfall and sea surface temperature anomalies was investigated with the aim of predicting the monthly scale rainfall during the summer monsoon period over a section (80°–90°E, 14°–24°N) of eastern India that depends heavily upon the rainfall during the summer monsoon months for its agricultural practices. The association between area-averaged rainfall of June over the study zone and global sea surface temperature (SST) anomalies for the period 1982–2008 was examined and the variability of rainfall in monthly scale was calculated. With a view to significant variability in the rainfall in the monthly scale, it was decided to implement the artificial neural network (ANN) for forecasting the monthly scale rainfall using the SST anomalies as a predictor. Finally, the potential of ANN in this prediction has been assessed.