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Oxygen (\({\updelta }^{18}\hbox {O}\)) and hydrogen (\({\updelta }^{2}\hbox {H}\) and \(^{3}\hbox {H}\)) isotopes of water, along with their hydrochemistry, were used to identify the source of a newly emerged seepage water in the downstream of Lake Nainital, located in the Lesser Himalayan region of Uttarakhand, India. A total of 57 samples of water from 19 different sites, in and around the seepage site, were collected. Samples were analysed for chemical tracers like \(\hbox {Ca}^{++}\), \(\hbox {Mg}^{++}\), \(\hbox {Na}^{+}\), \(\hbox {K}^{+}\), \({\hbox {SO}_{4}}^{--}\) and \(\hbox {Cl}^{-}\) using an Ion Chromatograph (Dionex IC-5000). A Dual Inlet Isotope Ratio Mass Spectrometer (DIIRMS) and an Ultra-Low Level Liquid Scintillation Counter (ULLSC), were used in measurements of stable isotopes (\({\updelta }^{2}\hbox {H}\) and \({\updelta }^{18}\hbox {O}\)) and a radioisotope (\(^{3}\hbox {H}\)), respectively. Results obtained in this study repudiate the possibility of any likely connection between seepage water and the lake water, and indicate that the source of seepage water is mainly due to locally recharged groundwater. The study suggests that environmental isotopes (\({\updelta }^{2}\hbox {H}\), \({\updelta }^{18}\hbox {O}\) and \(^{3}\hbox {H}\)) can effectively be used as ‘tracers’ in the detection of the source of seepage water in conjunction with other hydrochemical tracers, and can help in water resource management and planning.  相似文献   
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Recently, study in past trends of climate variables gained significant consideration because of its contribution in adaptions and mitigation strategies for potential future changes in climate, primarily in the area of water resource management. Future interannual and inter-seasonal variations in maximum and minimum temperature may bring significant changes in hydrological systems and affect regional water resources. The present study has been performed to observe past(1970-2010) as well as future(2011-2100)spatial and temporal variability in temperature(maximum and minimum) over selected stations of Sutlej basin located in North-Western Himalayan region in India. The generation of future time series of temperature data at different stations is done using statistical downscaling technique. The nonparametric test methods, modified Mann-Kendall test and Cumulative Sum chart are used for detecting monotonic trend and sequential shift in time series of maximum and minimum temperature. Sen’s slope estimator test is used to detect the magnitude of change over a period of time on annual and seasonal basis. The cooling experienced in annual TMax and TMin at Kasol in past(1970-2010) would be replaced by warming in future as increasing trends are detected in TMax during 2020 s and 2050 s and in TMin during 2020 s, 2050 s and 2080 s under A1 B and A2 scenarios. Similar results of warming are also predicted at Sunnifor annual TMin in future under both scenarios which witnessed cooling during 1970-2010. The rise in TMin at Rampur is predicted to be continued in future as increasing trends are obtained under both the scenarios. Seasonal trend analysis reveals large variability in trends of TMax and TMin over these stations for the future periods.  相似文献   
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Journal of Earth System Science - The annual and seasonal trend analysis of different surface temperature parameters (average, maximum, minimum and diurnal temperature range) has been done for...  相似文献   
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