Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India
The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water qualit...
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MDPI AG
2023-11-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/23/4109 |
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| author | Pradip Debnath Stabak Roy Satarupa Bharadwaj Samrat Hore Harjeet Nath Saptarshi Mitra Ana-Maria Ciobotaru |
| author_facet | Pradip Debnath Stabak Roy Satarupa Bharadwaj Samrat Hore Harjeet Nath Saptarshi Mitra Ana-Maria Ciobotaru |
| author_sort | Pradip Debnath |
| collection | DOAJ |
| description | The water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of the study area, an esteemed Ramsar site in North Eastern India, using a combined application of multivariable statistical and geospatial techniques. In this study, 24 water samples were designed based on their use and collected along the periphery and the inner areas of the lake employing the Latin Square Matrix. This research also examines the spatial variations of water quality involving quartile-based water quality categorization of parameters, with Pearson’s Correlation analysis, Principal Component Analysis (PCA), and Hierarchy Cluster Analysis (HCA) applied for dimension reduction. The analysis involved quartile-based water quality categorization of parameters, with PCA and HCA applied for dimension reduction. Meanwhile, the Inverse distance weighted (IDW) approach was used to interpolate the spatial distribution of the quartile score using the ArcGIS platform. The Bureau of Indian Standards (BIS) was followed for water quality assessment. The results revealed significant spatial variation, providing valuable insights for future water management strategies. PCA indicates 57.26% of the variance in the dataset, whereas samples were classified into three subgroups and two groups in a dendrogram representing the result of the HCA. This study demonstrates the utility of PCA, HCA, and IDW interpolation in water quality assessment, highlighting the effect of human-induced activities in the lake’s vicinity. |
| first_indexed | 2024-03-09T01:40:43Z |
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| id | doaj.art-103bf65ff4db4e65babc0b2dda4c9d6e |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T01:40:43Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-103bf65ff4db4e65babc0b2dda4c9d6e2023-12-08T15:28:29ZengMDPI AGWater2073-44412023-11-011523410910.3390/w15234109Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of IndiaPradip Debnath0Stabak Roy1Satarupa Bharadwaj2Samrat Hore3Harjeet Nath4Saptarshi Mitra5Ana-Maria Ciobotaru6Department of Geography and Disaster Management, Tripura University, Suryamaninagar 799022, IndiaDepartment of Geography and Disaster Management, Tripura University, Suryamaninagar 799022, IndiaDepartment of Geography and Disaster Management, Tripura University, Suryamaninagar 799022, IndiaDepartment of Statistics, Tripura University, Suryamaninagar 799022, IndiaDepartment of Chemical and Polymer Engineering, Tripura University, Suryamaninagar 799022, IndiaDepartment of Geography and Disaster Management, Tripura University, Suryamaninagar 799022, IndiaGheorghe Balș’ Technical College, 107 Republicii Street, 625100 Adjud, RomaniaThe water quality of Rudrasagar Lake, the second-largest natural reservoir of Tripura is of great ecological and economic importance as it serves a diverse range of purposes, including fishing, irrigation, aquaculture, domestic use, and recreation activities. This study investigates the water quality of the study area, an esteemed Ramsar site in North Eastern India, using a combined application of multivariable statistical and geospatial techniques. In this study, 24 water samples were designed based on their use and collected along the periphery and the inner areas of the lake employing the Latin Square Matrix. This research also examines the spatial variations of water quality involving quartile-based water quality categorization of parameters, with Pearson’s Correlation analysis, Principal Component Analysis (PCA), and Hierarchy Cluster Analysis (HCA) applied for dimension reduction. The analysis involved quartile-based water quality categorization of parameters, with PCA and HCA applied for dimension reduction. Meanwhile, the Inverse distance weighted (IDW) approach was used to interpolate the spatial distribution of the quartile score using the ArcGIS platform. The Bureau of Indian Standards (BIS) was followed for water quality assessment. The results revealed significant spatial variation, providing valuable insights for future water management strategies. PCA indicates 57.26% of the variance in the dataset, whereas samples were classified into three subgroups and two groups in a dendrogram representing the result of the HCA. This study demonstrates the utility of PCA, HCA, and IDW interpolation in water quality assessment, highlighting the effect of human-induced activities in the lake’s vicinity.https://www.mdpi.com/2073-4441/15/23/4109IDWHCAPCAspatial variationwater quality |
| spellingShingle | Pradip Debnath Stabak Roy Satarupa Bharadwaj Samrat Hore Harjeet Nath Saptarshi Mitra Ana-Maria Ciobotaru Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India Water IDW HCA PCA spatial variation water quality |
| title | Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India |
| title_full | Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India |
| title_fullStr | Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India |
| title_full_unstemmed | Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India |
| title_short | Application of Multivariable Statistical and Geo-Spatial Techniques for Evaluation of Water Quality of Rudrasagar Wetland, the Ramsar Site of India |
| title_sort | application of multivariable statistical and geo spatial techniques for evaluation of water quality of rudrasagar wetland the ramsar site of india |
| topic | IDW HCA PCA spatial variation water quality |
| url | https://www.mdpi.com/2073-4441/15/23/4109 |
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