The present study envisages the importance of monitoring and management of freshwater springs of Kashmir Himalaya due to role they play in meeting ever-increasing drinking water demands and maintaining various ecosystem services. Therefore, some of the most pressing issues fundamental to the existence of springs is their monitoring and management because of their geological, ecological, scientific, cultural, religious and societal importance. Despite the key role that they play, springs are today continuously facing various types of threats. Springs have attained recently an extraordinary importance as they play role in providing drinking water, irrigation, sustaining habitats for fisheries, aquatic biodiversity, endemism, spiritual enrichment, recreation, aesthetics etc. especially in scenario of climate change threat predicted for Himalayas. In this backdrop a study directed to assess water quality status and potential of springs to offer the solution to ever-increasing water shortages was carried out. Identification of main threats to spring ecosystems and their subsequent monitoring and management in Kashmir Himalaya has been pleaded in this article. Major research highlights of the work revealed very well to excellent water quality class and Piper trilinear diagram of spring water depicted Ca–Mg–HCO3 water type. ANOVA (Analysis of Variance) revealed significant variations whilst Principal Component Analysis (PCA) generated four principal components (PC1, PC2, PC3 and PC4) with higher Eigen values of 1.0 or more (1.4-9.5) accounting for 34.34, 30.03, 18.50 and 12.4% of the total variance respectively. Consequently, majority of the physico-chemical parameters (95.28%) loaded under PC1 and PC2 were having strong positive loading (>0.60) and are mainly responsible for regulating the hydrochemistry of spring waters. Cluster analysis revealed that springs like Kokernag, Achabal, Sherebagh, and Cheshmashahi and Dobinag fall in same cluster having 47-78% similarity while Verinag, Indraznag and Dobinag fall almost in same cluster showing similarity range of 61-80%.

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