Surface Water Quality Assessment of Wular Lake, A Ramsar Site in Kashmir Himalaya, Using Discriminant Analysis and WQI

Abstract

Multivariate techniques, discriminant analysis, and WQI were applied to analyze a water quality data set including 27 parameters at 5 sites of the Lake Wular in Kashmir Himalaya from 2011 to 2013 to investigate spatiotemporal variations and identify potential pollution sources. Spatial and temporal variations in water quality parameters were evaluated through stepwise discriminant analysis (DA). The first spatial discriminant function (DF) accounted for 76.5% of the total spatial variance, and the second DF accounted for 19.1%. The mean values of water temperature, EC, total-N, K, and silicate showed a strong contribution to discriminate the five sampling sites. The mean concentration of NO 2 -N, total-N, and sulphate showed a strong contribution to discriminate the four sampling seasons and accounted for most of the expected seasonal variations. The order of major cations and anions was Ca 2+ > Mg 2+ > Na + > K + and Cl − > SO4 2− > SiO 2 2− respectively. The results of water quality index, employing thirteen core parameters vital for drinking water purposes, showed values of 49.2, 46.5, 47.3, 40.6, and 37.1 for sites I, II, III, IV, and V, respectively. These index values reflect that the water of lake is in good condition for different purposes but increased values alarm us about future repercussions.

The Storage and Water Quality Characteristics of Rungiri Quarry Reservoir in Kiambu, Kenya, as a Potential Source of Urban Water

“…The ideal value for pH = 7, dissolved oxygen = 14.6 mg/L, with zero for the other parameters [28]. The computed WQI values were classified according to [49,50] as shown in Table 2.…”

Development of a water quality index (WQI) for the Loktak Lake in India

“…Later, numerous researchers have carried out studies on water quality assessment using WQIs around the world in various water bodies (Pesce and Wunderlin 2000;Bordalo et al 2001;Abdul et al 2010;Akbal et al 2011;Altansukh and Davaa 2011;Hector et al 2012;Abdulwahid 2013;Mohamed et al 2014;Chrysoula et al 2014;Mehmet and Huseyin 2014;Will et al 2015;Gerald et al 2015;Hefni and Romanto 2015;Lobato et al 2015;Mehrnoosh et al 2015). Similarly, a number of studies have been carried out in India (Dwivedi and Pathak 2007;Joshi et al 2009;Samantray et al 2009;Chauhan and Singh 2010;Alam and Pathak 2010;Parmar and Parma 2010;Chaturvedi and Bassin 2010;Kalavathy et al 2011;Kankal et al 2012;Srinivas et al 2013;Prerna et al 2014;Salim and Ashok 2014;Jindal et al 2014;Mrunmayee et al 2015;Krishna et al 2014Krishna et al , 2015Kosha and Geeta 2015). However, there was no literature which reveals scientific study carried out with respect to WQI in NorthEast India, a mega biodiversity region.…”

Spatio-temporal patterns and factors controlling the hydrogeochemistry of the river Jhelum basin, Kashmir Himalaya

“…Similarly, NO 3 − contributes 1.2-19.5 % to the ionic budget. The significant contribution of NO 3 − can be attributed to the disposal of wastes from the vicinity of the river and to the nitrogen fertilizers applied to farmlands (Bhat and Pandit 2014). SiO 2 contributes 5.4-9.9 % to the ionic budget and is derived exclusively from silicate rocks and biogenic silica of carbonate rocks (Jansen et al 2010) whereas the F − ion contributes in a narrow range between 0.69 and 0.47 %.…”

“…This observation further strengthens the hypothesis that higher concentration of Cl − and NO 3 − ions is caused due to anthropogenic activities like through the frequent and higher use of fertilizers during summer season (high flow period). The nitrogen fertilizers applied to farmland are the main source of NO 3 − pollution in surface waters and may be dominant during high flow period due to the production of large agricultural runoff (Yan et al 1999;Si et al 2000;Bhat and Pandit 2014). NO 3 − may also originate from livestock wastes (Kotti et al 2005).…”