Groundwater samples from alluvial aquifers of Bathinda district, southwest Punjab were measured for physicochemical parameters as well as major ion chemistry to evaluate the groundwater suitability for drinking and irrigation purposes and to present the current hydrochemical status of groundwater of this district. (39 %), SO 4 2-(22 %), TH (28 %), NO 3 -(22 %) and TDS (28 %) during post-monsoon above permissible limits for drinking, while rest of the parameters fall within the limits. Irrigation suitability was checked using sodium absorption ratio (SAR), residual sodium carbonate (RSC), percent sodium (Na%) and permeability index (PI). Most of the samples fall under good to suitable category during premonsoon period, but fall under doubtful to unsuitable category during post-monsoon period. Presence of high salt content in groundwater during post-monsoon season reflects leaching of salts present in the unsaturated zone by infiltrating precipitation. Hydrochemical data was interpreted using Piper's trilinear plot and Chadha's plot to understand the various geochemical processes affecting the groundwater quality. The results indicate that the order of cation dominance is Na ? [ Mg 2? [ Ca 2? , while anion dominance is in the order ClThe geochemistry of groundwater of this district is mainly controlled by the carbonate and silicate mineral dissolution and ion exchange during pre-monsoon and leaching from the salts deposited in vadose zone during post-monsoon. The main sources of contamination are soluble fertilizers and livestock wastes. This study is significant as the surface water resources are limited and the quality and quantity of groundwater are deteriorating with time due to anthropogenic inputs.

Filling gaps in climate data concerning mountainous areas with high spatial variability is significantly important since gaps tend to decrease the accuracy of trend estimation. In this study, the performance of seven classical methods in estimating missing values of maximum temperature, minimum temperature and precipitation at different time scales, i.e. daily (with different cases of missing data), weekly, biweekly and monthly, over Karakoram Himalaya was evaluated. Four performance indicators, i.e. mean absolute error, root mean squared error, co-efficient of efficiency and skill score, were used to evaluate the relative performance of the methods; the mean absolute error was preferred over the other three measures for selecting the best method. The results indicate that multiple linear regression using the least absolute deviation criterion is best suited for estimation of all variables at all temporal scales except monthly precipitation data. It was also found that, for any variable, the deviation from the observed values decreased with increasing time step, i.e. there was more deviation on a daily scale than monthly.

Evaluation of groundwater quality to ascertain its utility gain extra concern in the present day life. This study was carried out to reveal the various factors responsible for deterioration of water quality using environmetric techniques (principal component analysis and cluster analysis), water quality index (WQI) and conventional graphical representation such as Piper trillinear diagram in the industrial area of Baddi Barotiwala Nalagarh, Himachal Pradesh, India. The analysis of parameters like pH, EC, TDS, TH and major ions concentrations such as Ca 2? Mg 2? , Na ? , K ? , HCO 3 -, Cl -, SO 4 2and PO 4 2were carried out to assess the source of pollution in the study area. The parameters like Cl -, NO 3 and SO 4 2are within desirable limit as per Bureau of Indian Standards (BIS) for drinking and domestic purposes. pH, TH and Mg 2? exceeded the permissible limits at certain sites and about 50 % samples of EC, TDS, Ca 2? and Mg 2? were above the desirable limits which gives us caution. Piper trillinear diagram classified 93.75 and 90.63 % of groundwater samples for both seasons falls in the fields of Ca 2? -Mg 2? -HCO 3 water type indicating temporary hardness. Results of WQI indicate majority of samples falls in poor to unfit range in both seasons. PCA and CA identifies that the groundwater chemistry were influenced by natural as well as minor anthropogenic activities. Thus, the affirmative solution will be proper groundwater development and management practices through artificial recharge to maintain both quality and quantity.

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This study evaluated the performance of 07 gridded datasets viz. Asian Precipitation Highly-resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE), Climate Research Unit Time-Series (CRU-TS), University of Delaware (UDEL), Tropical rainfall Measurement Mission (TRMM)/ TMPA (TRMM Multi-Satellite Precipitation Analysis), Global Precipitation Climatology Centre (GPCC), Princeton Global Forcings Dataset (PGF), and European Reanalysis Interim (ERA-I) in capturing the amount, seasonality and trend of precipitation over different climatic zones of Northwestern Himalaya (NWH) i.e. Lower Himalaya (LH), Greater Himalaya (GH) and Karakoram Himalaya (KH). A similar comparison was also done for the temperature data but only with 05 datasets, viz. APHRODITE, CRU-TS, PGF, UDEL and ERA-I since TMPA and GPCC are precipitation datasets only. This study is a maiden attempt where in situ observation includes the data from elevations above 5000 m amsl (07 observatories) in NWH (Indian sub-region). Results reveal that for precipitation over NWH; ERA-I, GPCC, and TMPA/TRMM were found to be quite reliable datasets. For temperature, all datasets performed quite well but CRU-TS and ERA-I provided more reliable estimates. The mean absolute error ranged from 13.5 mm/month to 150.7 mm/month for precipitation and 0.75°C/month to 9.9°C/month for temperature. High values of the errors underpin the need for bias correction. On the basis of this analysis, monthly correction factors for wintertime temperature and precipitation have also been suggested for each dataset which when multiplied with corresponding datasets would result in closely approximated values for the area of interest. These results can serve as a guide for bias correction and selection of appropriate gridded datasets for use in studies pertaining to hydrological modeling over NWH.

Sirsa River flows through the central part of the Nalagarh valley, belongs to the rapid industrial belt of Baddi, Barotiwala and Nalagarh (BBN). The appraisal of surface water quality to ascertain its utility in such ecologically sensitive areas is need of the hour. The present study envisages the application of multivariate analysis, water utility class and conventional graphical representation to reveal the hidden factor responsible for deterioration of water quality and determine the hydrochemical facies and its evolution processes of water types in Nalagarh valley, India. The quality assessment is made by estimating pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness, major ions (Na ? and K ? ions for pre monsoon and EC during pre and post monsoon at few sites and approx 40% samples of BOD and TC for both seasons exceeds the permissible limits indicate organic contamination from human activities. Water quality classification for designated use indicates that maximum surface water samples are not suitable for drinking water source without conventional treatment. The result of piper trillinear and Chadha's diagram classified majority of surface water samples for both seasons fall in the fields of Ca 2? -Mg 2? -HCO 3 -water type indicating temporary hardness. PCA and CA reveal that the surface water chemistry is influenced by natural factors such as weathering of minerals, ion exchange processes and anthropogenic factors. Thus, the present paper illustrates the importance of multivariate techniques for reliable quality characterization of surface water quality to develop effective pollution reduction strategies and maintain a fine balance between the industrialization and ecological integrity.,

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The water quality in mountain regions of Himalaya is considered to be good and quantity adequate. However, recent reports suggest that urbanisation and population growth have been tremendous, which are impacting the land use/cover changes and also endangering the water resources both in quality and quantity. This paper elaborates the systematic investigation carried out on different attributes impacting the drinking water resources in Kullu valley. Two approaches were employed in this study: (1) ex-ante approach involving field survey and secondary data analysis from ancillary sources and (2) hydrochemical approach for the measurement of water quality parameters from springs. Results from ex-ante approach infer rise in population of about 15% during 2001-2011, which led to a significant change in land use pattern, microclimate and also increased water demand. Hydrochemistry of the water samples in the study area has indicated that the current status of spring waters is satisfactory for drinking purposes with a few incidences of high NO 3 − which is mostly attributed to contamination from sewage, while F − , Cl − and TDS contamination is mainly confined to hot springs. From both ex-ante approach and primary hydrochemical data it can be inferred that springs need to be restored in terms of both quantity and quality. Hydrochemical interpretation suggests two main groups of samples: (1) low TDS and Ca-Mg-Cl-HCO 3 type, which are mainly recharging waters with very less interaction with the aquifer material and (ii) moderate TDS and Mg-Ca-Cl, Ca-Na-HCO 3 , Na-CaCl-SO 4 and Ca-Mg-HCO 3 and have undergone water-rock interaction. Based on the inferences obtained from the Piper's, Chadha's and Durov's classification no evidence of hot springs contaminating or contributing to other cold springs and shallow groundwater (hand pump) is found. The study concludes that the water resources are vulnerable to anthropogenic interventions and needs treatment prior to drinking. Periodic monitoring of water quality and adopting proper treatment procedures are essential for supplying safe and sustainable water to the community in the Kullu valley, Himachal Pradesh.