Water Quality and Planktonic Composition of River Henwal (India) Using Comprehensive Pollution Index and Biotic-Indices

Matta, Gagan; Kumar, Avinash; Nayak, Anjali; Kumar, Pawan; Kumar, Amit; Tiwari, Ashwani Kumar

doi:10.1007/s41403-020-00094-x

Cited by 39 publications

(13 citation statements)

References 30 publications

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“…The WQIs uses different selection process, statistical transformation, weighing of parameters and interpretation of final numeric values (Lumb et al 2011;Alobaidy et al 2010). Many of the research work has been used various WQIs for the assessment and monitoring of different surface water quality (Shah and Joshi 2017;Matta et al 2018a;Son et al 2020;Matta et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Water quality assessment using NSFWQI, OIP and multivariate techniques of Ganga River system, Uttarakhand, India

et al. 2020

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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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Section: Introductionmentioning

confidence: 99%

Water quality assessment using NSFWQI, OIP and multivariate techniques of Ganga River system, Uttarakhand, India

et al. 2020

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“…e CPI method is one of the most common approaches used in China to qualitatively evaluate the water quality [18][19][20][21]. e following equation calculates the index P as…”

Section: Comprehensive Pollution Index (Cpi) Methodmentioning

confidence: 99%

A Comprehensive Method for Water Environment Assessment considering Trends of Water Quality

Wang²,

et al. 2021

Advances in Civil Engineering

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Water quality is a significant issue, and its assessment plays an important role in environmental management and pollution control. In this paper, we proposed a comprehensive water quality assessment method which takes into account both absolute and temporal trends in water quality. As the first step, we derived and applied a comprehensive pollution index (CPI) to characterize water pollution in 16 major tributaries to the Danjiangkou Reservoir, located in the upper reaches of the Hanjiang River in China. Next, we used Spearman’s rank correlation analysis to quantify temporal CPI trends in each tributary. As the final step, we conducted principal component analysis (PCA) using data on 8 water quality parameters and the temporal CPI trend from each of the 16 tributaries. The resultant comprehensive water quality assessment method identified tributaries, which stand to improve and threaten water quality in the Danjiangkou Reservoir from both immediate and future perspectives.

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“…The calculated values were compared and graded based on scores i.e. for Excellent (31)(32)(33)(34)(35), Good (25)(26)(27)(28)(29), Fair (19)(20)(21)(22)(23), poor (13)(14)(15)(16)(17), and for very poor (7)(8)(9)(10)(11).…”

Section: Water Pollution Index (Wpi)mentioning

confidence: 99%

“…PCA bi-plot is a well-known statistical tool for the analysis of speci c variable and their interdependency on the other environmental variables (Singh et al, 2019). The principal component analysis is a widely accepted multivariate statistical tool used for the analysis of the wide number of environmental factors affecting the diversity and density of the planktonic species (Pratiwi et al, 2019;Herawati et al, 2020 andMatta et al, 2020). In this nding as the 1st PC is having positive loading with conductivity, total hardness, salinity, total suspended solids, calcium, chlorophyll-B, and chlorophyll-C while the negative loading was found with dissolved oxygen and silicate.…”

Section: 3physico-chemical Propertiesmentioning

confidence: 99%

Variation of Aulacoseira granulata as an eco-pollution indicator in subtropical large river Ganga in India: a multivariate analytical approach

Mohanty

Tiwari

Kumari

et al. 2022

Environ Sci Pollut Res

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Aulacoseira granulata (Ehrenberg) Simonsen 1979 is one of the major ecological indicators of the water quality of lotic as well as lentic aquatic ecosystems. To assess major environmental factors contributor to A.granulata bloom in the riverine system, a study was carried out from 2018 to 2019 comprising four different seasons at 11 sampling sites of river Ganga in the middle and lower stretch of river Ganga comprising freshwater and estuarine zones. For the analysis, different univariate, as well as multivariate analytical tools such as Principal Component Analysis (PCA) and Water pollution Index (WPI), were used. In the nding, it was observed that the average abundance of Aulacoseira granulata was found maximum during the winter season. Among all the studied sites, the maximum average abundance was at Balagarh (71576 cell l -1 ) and minimum at Diamond Harbour (68 cell l -1 ). The environmental factors such as dissolved oxygen, depth, and altitude showed a positive and water temperature negatively in uencing the growth rate of A. granulate. WPI showed a signi cantly negative correlation with cell length. Finally, the study concludes that the blooming of Aulacoseira granulata is highly in uenced by varied environmental conditions along the river Ganga suggesting possible eutrophication. Therefore, a certain minimum ow and depth especially during the lean season have to be maintained for the sustenance of planktonic biota in the river Ganga. Material And Methods Study sitesRiver Ganga is the largest in India and the fth-largest in the world. The river emerges out to be cool in the uplands in the north and warmer during its course of ow until it's nally con uence to form the biggest delta in the world before draining into the Bay of Bengal in the east. The sites covered were almost 1208 Kilometers and a total of 11 sampling stations comprising the Indian States of Bihar and West Bengal. The entire stretch has been divided into two zones based on their hydrological characteristics. Freshwater zones are mainly comprised of Buxar, Patna, Bhagalpur, Farakka, Jangipur, and Berhampore. Likewise, the estuarine stretch covers the regions Balagarh, Tribeni, Godakhali, Diamond Harbour, and Fraserganj. All the sites have been selected based on their physical nature of water (tidal, etc.) and altitude gradient (Fig. 01). Climatic conditionThe entire Ganga basin speci cally the middle and lower stretches experiences a typical monsoon n climate extending from June to October. Although there are some differences in precipitation between the middle and lower Ganga, the annual amount of rainfall remains the same which is 1000 mm (Quincey, 2017). Warm and dry seasons extend from March to May however, winter starts from November and ends in February. Sample collection and identi cationPlankton samples were collected quarterly for one year(2018 to 2019) covering all four tropical seasons. Composite samples from the mid-channel of the river were collected manually against the water current using the typical country boat. To maintain un...

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Water Quality and Planktonic Composition of River Henwal (India) Using Comprehensive Pollution Index and Biotic-Indices

Cited by 39 publications

References 30 publications

Water quality assessment using NSFWQI, OIP and multivariate techniques of Ganga River system, Uttarakhand, India

Water quality assessment using NSFWQI, OIP and multivariate techniques of Ganga River system, Uttarakhand, India

A Comprehensive Method for Water Environment Assessment considering Trends of Water Quality

Variation of Aulacoseira granulata as an eco-pollution indicator in subtropical large river Ganga in India: a multivariate analytical approach

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