Spatio-temporal evaluation of physico-chemical parameters of snow-fed River Poonch in Northwest Himalayan region of India

Abstract

The rapid deterioration of freshwater ecosystems, particularly rivers, has threatened many living organisms, including human beings. In order to comprehend and maintain the well-being of a river ecosystem, it is important to assess the spatial and temporal variations in its physico-chemical parameters. The aim of the present study was to examine spatial and temporal physico-chemical parameters of snow-fed River Poonch in the Northwest Himalayas from July 2021 to June 2023. In order to generate precise and reliable data, one-way ANOVA, Duncan's multiple range test, Pearson correlation, linear regression, principal component analysis (PCA) and cluster analysis (CA) were used to analyse a total of fifteen physico-chemical parameters of the river. Significant (p < 0.05) differences spatio-temporally in physico-chemical parameters were found through one-way ANOVA followed by Duncan's multiple range test. Pearson correlation revealed that majority of the examined physico-chemical parameters exhibited a robust positive association (r > 0.70) in most cases, apart from DO (r ≥ − 0.80). Linear regression indicated significant (p < 0.05) associations among various physico-chemical parameters, which were substantial both in nature and size, with a coefficient of determination (r2 > 0.70) in most of the cases. PCA showed that physico-chemical parameters such as AT, WT, EC, TDS, FCO2, TA, TH, NO2-N, NO3-N, TP, SO42− and F− were significant for the determination of qualitative characteristics of River Poonch. In CA, two distinct clusters, viz. Cluster-I consisting of Site-III, downstream site prone to pollution and Cluster-II consisting of Site-II and Site-I, mid and upstream sites, respectively, less prone to pollution were obtained. The results of the study revealed that the water quality parameters were found well within the recommended ranges, suggesting that they are conducive for the existence of inhabitant fish species, which influence the local economy of the region.