Comparative assessment of groundwater quality indices of Kannur District, Kerala, India using multivariate statistical approaches and GIS

被引:19
|
作者
Arumugam, Thangavelu [1 ]
Kinattinkara, Sapna [2 ]
Kannithottathil, Socia [1 ]
Velusamy, Sampathkumar [3 ]
Krishna, Manoj [1 ]
Shanmugamoorthy, Manoj [3 ]
Sivakumar, Vivek [4 ]
Boobalakrishnan, Kaveripalayam Vengatachalam [5 ]
机构
[1] Kannur Univ, Dept Environm Studies, Mangattuparamba 670567, Kerala, India
[2] PSG Coll Arts & Sci, Dept Environm Sci, Coimbatore 641014, Tamil Nadu, India
[3] Kongu Engn Coll, Dept Civil Engn, Erode 638052, India
[4] Hindusthan Coll Engn & Technol, Dept Civil Engn, Coimbatore 641008, Tamil Nadu, India
[5] Dr NGP Inst Technol, Dept Civil Engn, Coimbatore 641032, Tamil Nadu, India
关键词
Groundwater; GIS; IDW; Kannur; Physicochemical parameters; Multivariate statistics; WATER-QUALITY; TAMIL-NADU; DRINKING; IRRIGATION; REGION; AQUIFER; AREA; WQI; SUITABILITY; CHEMISTRY;
D O I
10.1007/s10661-022-10538-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The aim of the study was to determine the groundwater characteristics of rural and industrial zones in the Kannur region. In 2011, 25 groundwater data were collected from the centre for water resource development management (CWRDM), and in 2019, 25 groundwater samples from rural and near-industrial areas were collected and analysed for major anions (HCO3-, CO32-, Cl-, NO3- and SO42-), and cations (TH, Ca2+, Mg2+, Na+, K+ and Fe2+) using APHA standards. To better understand the link between water quality parameters, multivariate statistical analysis approaches such as principal component analysis (PCA), hierarchical cluster analysis (HCA), correlation matrix analysis (CMA), and Pearson correlation bivariate one-tailed analysis (PCBOTA) were used to analyse the inter-relationship of data. The Inverse Distance Weighed (IDW) method was used to generate the spatial distribution of the groundwater quality index (GWQI). In 2011, the water quality index (WQI) value of groundwater samples was excellent at 24.42% and good at 54.14%, which were used for drinking purposes and moderate at 17.22% and poor at 4.22% for irrigation purposes in this study area. In 2019, excellent 21.62%, good 51.56% were used for drinking purpose, and moderate at 18.14%, and poor at 8.68% for irrigation purposes. By comparing the data with BIS and WHO standards, it is clear that groundwater in Kannur district is of good quality. In groundwater samples, the PCA eigen values were reported in 2011 (84.7%) and 2019 (73.4%) for statistical approaches. This study uses HCA and PCBOTA to analyse the elements, resulting in a better understanding of groundwater quality development. GIS based WQI maps were obtained and utilised to gain a better knowledge of the study area's past and present water quality status. We observed that the quality of groundwater in the study region's north-western portion is insufficient for drinking water.
引用
收藏
页数:30
相关论文
共 50 条
  • [31] Spatiotemporal assessment of groundwater quality in the Central Ganga Plain, India, using multivariate statistical tools
    Sandhya Maurya
    Abhishek Saxena
    Environmental Monitoring and Assessment, 2022, 194
  • [32] Spatiotemporal assessment of groundwater quality in the Central Ganga Plain, India, using multivariate statistical tools
    Maurya, Sandhya
    Saxena, Abhishek
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2022, 194 (12)
  • [33] Assessment of fluoride hazard in groundwater of Palghat District, Kerala: a GIS approach
    Arumugam, Thangavelu
    Kunhikannan, Sapna
    Radhakrishnan, Prabitha
    INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION, 2019, 66 (1-3) : 187 - 211
  • [34] Groundwater quality assessment using geospatial and statistical tools in Salem District, Tamil Nadu, India
    Arulbalaji P.
    Gurugnanam B.
    Applied Water Science, 2017, 7 (6) : 2737 - 2751
  • [35] Assessment of groundwater quality with special reference to arsenic in Nawalparasi district, Nepal using multivariate statistical techniques
    Yadav, Ishwar Chandra
    Devi, Ningombam Linthoingambi
    Mohan, Devendra
    Qi Shihua
    Singh, Surendra
    ENVIRONMENTAL EARTH SCIENCES, 2014, 72 (01) : 259 - 273
  • [36] Assessment of groundwater quality with special reference to arsenic in Nawalparasi district, Nepal using multivariate statistical techniques
    Ishwar Chandra Yadav
    Ningombam Linthoingambi Devi
    Devendra Mohan
    Qi Shihua
    Surendra Singh
    Environmental Earth Sciences, 2014, 72 : 259 - 273
  • [37] Human health risk and hydro-geochemical appraisal of groundwater in the southwest part of Bangladesh using GIS, water quality indices, and multivariate statistical approaches
    Chakraborty, Tapos Kumar
    Islam, Md Shahnul
    Ghosh, Gopal Chandra
    Ghosh, Prianka
    Zaman, Samina
    Habib, Ahsan
    Hossain, Md Ripon
    Bosu, Himel
    Islam, Md Rashidul
    Al Imran, Mostafa
    Khan, Abu Shamim
    Josy, Md Shahariea Karim
    TOXIN REVIEWS, 2023, 42 (01) : 285 - 299
  • [38] Assessment of spatial and temporal variations in water quality using multivariate statistical analysis in the Munroe Island, Kerala, India
    Arya, M. S.
    Biju, A.
    Benchamin, Dani
    ACTA ECOLOGICA SINICA, 2023, 43 (05) : 751 - 763
  • [39] Assessment of groundwater quality status by using water quality index (WQI) and geographic information system (GIS) approaches: a case study of the Bokaro district, India
    Poornima Verma
    Prasoon Kumar Singh
    Ritu Ranjan Sinha
    Ashwani Kumar Tiwari
    Applied Water Science, 2020, 10
  • [40] Assessment of groundwater quality status by using water quality index (WQI) and geographic information system (GIS) approaches: a case study of the Bokaro district, India
    Verma, Poornima
    Singh, Prasoon Kumar
    Sinha, Ritu Ranjan
    Tiwari, Ashwani Kumar
    APPLIED WATER SCIENCE, 2019, 10 (01)