Spatial Variation of Physico-Chemical and hydrological Parameters with land-use in Venkatapura Catchment,Karnataka

Social, economic and political development of a region is dependent on the health and quantity of the natural resources. Integrated approaches in the management of natural resources would ensure sustainability, which demands inventorying, mapping and monitoring of resources considering all components of an ecosystem. The monitoring of hydrological and catchment landscape of river resources have a vital role in the conservation and management of aquatic resources. This paper presents a case study Venkatapura river basin in Uttara Kannada district of Karnataka State, India based on stream hydrology and landuse analyses. The results revealed variations in dissolved oxygen and free carbon dioxide according to the flow nature of the water, and increased amount of phosphates and coliform contamination in streams closer to anthropogenic activities.

A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios

Concern over changes in global climate has increased in recent years with improvement in understanding of atmospheric dynamics and growth in evidence of climate link to long‐term variability in hydrologic records. Climate impact studies rely on climate change information at fine spatial resolution. Towards this, the past decade has witnessed significant progress in development of downscaling models to cascade the climate information provided by General Circulation Models (GCMs) at coarse spatial resolution to the scale relevant for hydrologic studies. While a plethora of downscaling models have been applied successfully to mid‐latitude regions, a few studies are available on tropical regions where the atmosphere is known to have more complex behavior. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling to interpret climate change signals provided by GCMs over tropical regions of India. Climate variables affecting spatio‐temporal variation of precipitation at each meteorological sub‐division of India are identified. Following this, cluster analysis is applied on climate data to identify the wet and dry seasons in each year. The data pertaining to climate variables and precipitation of each meteorological sub‐division is then used to develop SVM based downscaling model for each season. Subsequently, the SVM based downscaling model is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to assess the impact of climate change on hydrological inputs to the meteorological sub‐divisions. The results obtained from the SVM downscaling model are then analyzed to assess the impact of climate change on precipitation over India.

Chemical potential of germanium in its solid solutions with Cu, Ag and Au

Thin foils of copper, silver and gold were equilibrated with tetragonal GeO2 under controlled View the MathML source gas streams at 1000 K. The equilibrium concentration of germanium in the foils was determined by the X-ray fluorescence technique. The standard free energy of formation of tetragonal GeO2 was measured by a solid oxide galvanic cell. The chemical potential of germanium calculated from the experimental data and the free energies of formation of carbon monoxide and carbon dioxide was found to decrease in the sequence Ag + Ge > Au + Ge > Cu + Ge. The more negative value for the chemical potential of germanium in solid copper, compared to that in solid gold, cannot be explained in terms of the strain energy factor, electro-negativity differences or the vaporization energies of the solvent, and suggests that the d band and its hybridization with s electrons are an important factor in determining the absolute values for the chemical potential in dilute solutions. However, the variation of the chemical potential with solute concentration can be correlated to the concentration of s and p electrons in the outer shell.

SOS films and interfaces: chemical aspects

The possible chemical reactions that take place during the growth of single crystal films of silicon on sapphire (SOS) are analyzed thermodynamically. The temperature for the growth of good quality epitaxial films is dependent on the extent of water vapor present in the carrier gas. The higher the water vapor content the higher the temperature needed to grow SOS films. Due to the interaction of silicon with sapphire at elevated temperatures, SOS films are doped with aluminum. The extent of doping is dependent on the conditions of film growth. The doping by aluminum from the substrate increases with increasing growth temperatures and decreasing growth rates. The equilibrium concentrations of aluminum at the silicon-sapphire interface are calculated as a function of deposition temperature, assuming that SiO2 or Al6Si2O13 are the products of reaction. It is most likely that the product could be a solid solutio n of Al2O3 in SiO2. The total amount of aluminum released due to the interaction between silicon and sapphire will account only for the formation of not more than one monolayer of reaction product unless the films are annealed long enough at elevated temperatures. This value is in good agreement with the recently reported observations employing high resolution transmission electron microscopy.

Physically consistent simulation of mesoscale chemical kinetics: The non-negative FIS-alpha method

Biochemical pathways involving chemical kinetics in medium concentrations (i.e., at mesoscale) of the reacting molecules can be approximated as chemical Langevin equations (CLE) systems. We address the physically consistent non-negative simulation of the CLE sample paths as well as the issue of non-Lipschitz diffusion coefficients when a species approaches depletion and any stiffness due to faster reactions. The non-negative Fully Implicit Stochastic alpha (FIS alpha) method in which stopped reaction channels due to depleted reactants are deleted until a reactant concentration rises again, for non-negativity preservation and in which a positive definite Jacobian is maintained to deal with possible stiffness, is proposed and analysed. The method is illustrated with the computation of active Protein Kinase C response in the Protein Kinase C pathway. (C) 2011 Elsevier Inc. All rights reserved.

Kinetics and chemical analysis of photoinduced interdiffusion in nanolayered Se/As2S3 films

We have studied the kinetics of photoinduced effects in nanolayered Se/As2S3 film by in situ optical absorption measurements, which reveal that photodarkening in these films is followed by photoinduced diffusion. An increase in disorder during photodarkening and its subsequent decrease during photoinduced diffusion were also observed. The observation of photodarkening of Se at room temperature when confined between As2S3 layers suggests that the glass transition temperature of Se shifts to higher energy. The analysis shows that the atoms which take part in photodarkening play a vital role in photoinduced diffusion. The x-ray photoelectron spectroscopy measurements show the atomic movements during photoinduced diffusion. It also shows that some of the As–S bonds are converted into As–Se bonds. Since it is energetically difficult to break an As–S bond to form an As–Se bond, we assume that the new bond formations are taking place by the bond rearrangement mechanism.