Monitoring and evaluating the spatiotemporal variations of the water quality of a stretch of the Bhagirathi-Hugli River, West Bengal, India, using geospatial technology and integrated statistical methods

Das, Sanat Kr.; Sarkar, Rajib

doi:10.1007/s11356-020-11655-6

Cited by 15 publications

(2 citation statements)

References 61 publications

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“…The Principal Component Analysis (PCA) is used to reveal the "hidden" factors controlling surface water quality [28][29][30][31][32]. Numerous groups of studies use both CA and PCA as additions to the WQI to introduce the specific outputs of both techniques to water quality assessment [11,[33][34][35][36][37][38][39]. To investigate the temporal behavior of water quality indicators at regions with pronounced seasonality, Discriminant Analysis (DA) is used [13,[40][41][42][43][44].…”

Section: Introductionmentioning

confidence: 99%

Principal Component Analysis and the Water Quality Index—A Powerful Tool for Surface Water Quality Assessment: A Case Study on Struma River Catchment, Bulgaria

Benkov¹,

Varbanov

Venelinov

et al. 2023

Water

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The water quality assessment of the surface water bodies (SWBs) is one of the major tasks of environmental authorities dealing with water management. The present study proposes a water quality assessment scheme for the investigation of the surface waters’ physicochemical status changes and the identification of significant anthropogenic pressures. It is designed to extract valuable knowledge from the Water Frame Directive (WFD) mandatory monitoring datasets. The water quality assessment scheme is based on the Canadian Council of Ministers of the Environment water quality index (CCME-WQI), trend analysis of estimated WQI values, and Principal Component Analysis (PCA) using calculated excursions during the determination of WQI values. The combination of the abovementioned techniques preserves their benefits and additionally provides important information for water management by revealing the latent factors controlling water quality, taking into account the type of the SWB. The results enable the identification of the anthropogenic impact on SWBs and the type of the corresponding anthropogenic pressure, prioritization and monitoring restoration measures, and optimization of conducted monitoring programs to reflect significant anthropogenic pressures. The proposed simple and reliable assessment scheme is flexible to introducing additional water quality indicators (hydrological, biological, specific pollutants, etc.), which could lead to a more comprehensive surface water quality assessment.

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Section: Introductionmentioning

confidence: 99%

Principal Component Analysis and the Water Quality Index—A Powerful Tool for Surface Water Quality Assessment: A Case Study on Struma River Catchment, Bulgaria

Benkov¹,

Varbanov

Venelinov

et al. 2023

Water

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“…They found that demographic changes and the growth of economic activities contribute more than any other causative factors of LULC changes in the river basins. They have also investigated and discussed the sustainability issues of the river basin environment and its management (De, 2015;Das, 2020;Kumbhar et al, 2014;Islam et al, 2023;Jose et al, 2014;Iyer & Roy, 2005). Few studies on river basins of Assam have also been carried out to understand the cause-effect relationship of LULC change, river bank erosion, wetland conservation, soil loss estimation, lowering of groundwater table etc., at the individual level.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of causes and effects of environmental shifts in the Lower Digaru River Basin, Assam, India

Deka

Kumar

2023

Ecocycles

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Environmental issues like deforestation, biodiversity loss, soil erosion, siltation, wetland shrinkage, river bank erosion, etc. in drainage basin perspectives today are in a rapid flux triggered by population growth and developmental activities. Focusing on the Lower Digaru River basin of North-East India,the present study investigates the changes in theLand Use / Land Cover (LULC)trend using geospatial techniques and the cause-effect relationship by identifying the various environmental issues operating within the study area. The study area has been classified into nine LULC classes: dense forest, openforest, scrub forest, fallow land, barren land, cropland, dense scrub, mixed built-up land, and water body. The results revealed that the area under dense forest has drastically declined from 60.25 % to 16.63 % during 1999-2020. In contrast, the other important categories like Mix built-up land (8.11 % to 14.05 %), scrub forest (2.1 % to 25.11 %), barren land (0.2 % to 6.63 %) and open forest (11.9 % to 18.34 %) show an increasing trend of change during the said period. Post-classification comparison of the classified images based on the transition matrix indicated that approximately 40 % of the total area under forest had been converted to scrub forest, followed by 25.09 % to open forest and, most significantly, 5.22 % to mix built-up land during 1999 -2020. Increasing population pressure and growth of economic activities like the establishment of brick industries, coke industries, and sand mining were the major driving forces for such LULC changes. Environmental implications like wetland shrinkage, river bank erosion, alteration of human occupation and economy, etc., were the study area’s prime concern. The findings suggest that integrated watershed management and land use planning should be implemented in the Lower Digaru River Basin.

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Evaluation of River Health Status Based on Water Quality Index and Multiple Linear Regression Analysis

Gupta

2023

Lecture Notes in Civil Engineering

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Monitoring and evaluating the spatiotemporal variations of the water quality of a stretch of the Bhagirathi-Hugli River, West Bengal, India, using geospatial technology and integrated statistical methods

Cited by 15 publications

References 61 publications

Principal Component Analysis and the Water Quality Index—A Powerful Tool for Surface Water Quality Assessment: A Case Study on Struma River Catchment, Bulgaria

Principal Component Analysis and the Water Quality Index—A Powerful Tool for Surface Water Quality Assessment: A Case Study on Struma River Catchment, Bulgaria

Evaluation of causes and effects of environmental shifts in the Lower Digaru River Basin, Assam, India

Evaluation of River Health Status Based on Water Quality Index and Multiple Linear Regression Analysis

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