The Ganga River is a major river of North India and is known for its fertile alluvium deposits formed due to floods throughout the Indo-Gangetic plains. Flood frequency analysis has been carried out through various approaches for the Ganga River by many scientists. With changes in river bed brought out by anthropogenic changes the intensity of flood has also changed in the last decade, which calls for further study. The present study is in a part of the Upper Indo-Ganga plains subzone 1(e). Statistical distributions applied on the discharge data at two stations found that for Haridwar lognormal and for Garhmukteshwar Gumbel EV1 is applicable. The importance of this study lies in its ability to predict the discharge for a return period after a suitable distribution is found for an area. Keywords Discharge Á Flood frequency Á Generalized extreme value Á Goodness of fit tests Á Gumbel distribution Á Lognormal 3P Á Log Pearson type III

This paper focuses on the suitability of spring water for drinking and irrigation purposes in a part of eastern Himalaya, south Sikkim. There are many anthropogenic and geogenic factors contributing as a source of major cations and anions in the spring water. The spring water chemistry show a variation in EC, pH, TDS, Temperature, Na+, K+, Mg2+, Ca2+, Fe2+, Pb, Mn, Cu, HCO3−, Cl−, PO43−, NO3−, F− and SO42−. Mainly two types of water quality indexing has been used, one for suitability of spring water for drinking purposes and the other for irrigation purposes. For drinking purposes, Piper diagram used for determination of water type, water quality index (WQI) for quality monitoring and saturation index for mineral dissolution in water. % Na, RSC (Residual Sodium Carbon) and SAR (sodium absorption ratio) have been used for irrigation suitability. Piper diagram shows that CaHCO3 type of water was dominant in the study area. The WQI depicted excellent category and SAR, percent sodium and RSC (Residual Sodium Carbon) depict excellent, good and permissible category for irrigation purposes. Principle component analysis (PCA) was used to determine the major influencing factor responsible for the variability in the parameters analysed of spring water.

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