Abstract:The observed retreat of several Himalayan glaciers and snow packs is a cause of concern for the huge population in southern Asia that is dependent on the glacial-fed rivers emanating from Himalayas. There is considerable uncertainty about how cryospheric recession in the Himalayan region will respond to climate change, and how the water resource availability will be affected. As a first step towards quantifying the contribution of glacier-melt water, hydrograph separation of River Ganga at Rishikesh into its constituent components, namely (i) surface runoff, (ii) glacial ice-melt and (iii) groundwater discharge has been done in this paper. A three-component mixing model has been employed using the values of υ 18 O and electrical conductivity (EC) of the river water, and its constituents, to estimate the time-varying relative fraction of each component. The relative fraction of the surface runoff peaks (70-90%) during winter, due to the near-zero contribution of glacial ice-melt, essentially represents the melting of surface snow from the catchment. The contribution of glacial ice-melt to the stream discharge peaks during summer and monsoon reaches a maximum value of ¾40% with an average of 32%. The fraction of groundwater discharge varies within a narrow range (15 š 5%) throughout the year. On the basis of the variation in the d-excess values of river water, it is also suggested that the snow-melt and ice-melt component has a significant fraction derived from winter precipitation with moisture source from mid-latitude westerlies (also known as western disturbances).
This article evaluates the use of bagasse flour — a waste generated by sugarcane refinery—as a filler in the PVC matrix. The aim of the study is to develop a value-added product from the sugar mills. For this purpose, bagasse powder was obtained after grinding the dried waste from sugar mills having particle sizes of 100—150 µm and <50 µm. In order to evaluate the effect of filler content and alkali treatment of bagasse, several PVC formulations were obtained by dry-mixing PVC compound with filler of varying particle size. The compounds were obtained by blending on a hot roll mill followed by compression molding. The test specimens were punched out from the sheets and the effect of filler content, particle size, and alkali treatment of bagasse powder on the properties of PVC were evaluated. Tensile strength, percent elongation at break, and impact strength of composites decreased whereas stiffness, modulus, and hardness of the composites increased with increasing amount of filler. The particle size had a large effect on the properties of composites, and the filler having particle size <50 µm gave better properties as compared to filler with particle size of 100—150 µm. Some improvement in properties was observed when treated bagasse powder was used as filler. An increase of ∼48% in tensile modulus, ∼10% in thermal stability, and 14% in impact strength was observed as compared to neat PVC at a filler loading of 30 phr. Morphological characterization was done using a scanning electron microscopy. A uniform dispersion of filler was observed.
This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.
River water is a major resource of drinking water on earth. Management of river water is highly needed for surviving. Yamuna is the main river of India, and monthly variation of water quality of river Yamuna, using statistical methods have been compared at different sites for each water parameters. Regression, correlation coefficient, autoregressive integrated moving average (ARIMA), box-Jenkins, residual autocorrelation function (ACF), residual partial autocorrelation function (PACF), lag, fractal, Hurst exponent, and predictability index have been estimated to analyze trend and prediction of water quality. Predictive model is useful at 95% confidence limits and all water parameters reveal platykurtic curve. Brownian motion (true random walk) behavior exists at different sites for BOD, AMM, and total Kjeldahl nitrogen (TKN). Quality of Yamuna River water at Hathnikund is good, declines at Nizamuddin, Mazawali, Agra D/S, and regains good quality again at Juhikha. For all sites, almost all parameters except potential of hydrogen (pH), water temperature (WT) crosses the prescribed limits of World Health Organization (WHO)/United States Environmental Protection Agency (EPA).
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