Ganga River water is very much stressed with the rapidly increasing population, climate change and water pollution that increase domestic, agricultural and industrial needs. This study assesses the surface water quality of the River Ganga in India, using NSFWQI, OIP and multivariate techniques. During the current study, water samples from Ganga River were collected for the assessment of 19 physico-chemical determinants from 20 sampling locations. Water quality indices (WQIs) is used to classify the overall impact of different variables of water. Multivariate techniques were utilized to assess the water conditions for productive management of fresh water quality. The WQI results showed that surface water quality varied at the selected sampling sites among medium and good categories. The PCA generates the 6 principle components which highly contributes (80.3%) in influencing the hydro-chemistry of river water. Agricultural waste runoff, untreated effluents and many other anthropogenic activities were identified as main contributor in decreasing the water quality of the River Ganga. To maintain and protect this fresh water resources against contamination, the usage of stringent policies and rules are expected to preserve fresh water resources for people in the future.

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National river of India, Ganga River, nurturing ecological, economic, and socio-cultural aspects defining the last long history of country. Forming the largest catchment, fulfil the needs of millions of people for fresh water used in domestic, agriculture, commercial and industrial sectors. Therefore, River Ganga is always the center of attraction to the administrative authorities, institutions, academicians and researchers for its quality issues. The periodically examination of the river water quality for its conservation, restoration or rejuvenation is essential and conducted by many researcher on different quality aspects. The aim of the present investigation is to estimates the spatio-temporal variability in the Ganga River System's hydrology in upstream regions in the Himalayan Region of Uttarakhand state, India. The result clearly explains considerable variation in water quality index (WQI: 29.39–71.60) screening seasonal variation, defining the deterioration of water quality (WQ) of Ganga River from good to moderate polluted level through the overall index of pollution (OIP). Moreover, principal component analysis (PCA) has implied to identify the pollution sources. The PCA generates seven components and contributes (85.1%) to influencing river water's hydrochemistry. These outcomes give detailed information to understand the water quality affecting factors in the Ganga River system. The management and remedial practices are an urgent task required to conserve WQ in the upstream region to check WQ's further deterioration in the future.

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Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic process. To analyse the spatial–temporal variation and pollution source identification and apportionment, the dataset was subjected to a globally acknowledged coherent technique using water quality indices and chemometric techniques (principal component analysis (PCA) and cluster analysis. The bulk of the samples tested were below the BIS’s permissible levels. Groundwater samples from the pre- and post-monsoon seasons mostly contained the anions HCO − 3 > Cl − > SO 2− 4 > NO − 3 , while the primary cations were Ca 2+ > Mg 2+ > Na + > K + . Groundwater was alkaline and hard at most of the sites. According to hydro-geochemical facies and relationships, Piper diagrams, and principal component analysis, weathering, dissolution, leaching, ion exchange, and evaporation were the key mechanisms influencing groundwater quality. The hydrochemical facies classified the groundwater samples into the Ca-Mg-HCO 3 type. For all the sampling locations, PIG was determined to be 0.43, 0.52, 0.47, 0.48, 1.00, and 0.70; respectively. The majority of the test locations fell into the low to medium contamination zone, as determined by the groundwater pollution index (PIG) and contamination index. Three principal components, which together account for 93.8% of the total variance, were identified via PCA. The study’s findings confirm the value of these statistical techniques in interpreting and understanding large datasets and offering reliable information to reduce the time and expense of programmes for monitoring and evaluating water quality.

The Pandemic COVID-19 outbreak has significantly affected all sections of life, including a substantial reduction in economic development and production, from industrial activities to tourism and automobile congestion. During this phase, the maximum human activities were restricted, but COVID-19 came out as a blessing for the environment. Globally reported that all the environmental variables have improved since the pandemic outbreak, including water and air quality and water quality while minimizing the restrictions for wildlife even in urban areas. India has always been a hotspot of pollution, with rising air quality index (AQI) readings in all large cities due to its vast population, traffic congestion, and polluting industries. However, after the lockdown announced during the pandemic, air quality started improving, and Other environmental factors, such as the water quality of rivers, started to improve. This paper reviewed the studies conducted to define the improvement in India's air and water quality during the lockdown period. Different tools such as remote sensing technologies and onsite real-time monitoring are used in many studies to monitor India's air and water quality during this period.