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Spatial variability of ground water quality: a case study of Udupi district, Karnataka State, India

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Abstract

Groundwater is a reliable source of fresh water for domestic and agricultural water users. It supports subsurface ecosystem by balancing the geo-biological and bio-geochemical processes at micro- and macro-scales of the ecosystem. Overexploitation, anthropogenic activities and improper agricultural practices have contributed to the pollution of groundwater sources all around the globe. The water quality index (WQI) is the most extensively used indicator which transforms the water quality information derived from several parameters into a single value/rating to categorize and provide a general perception of water quality standard. Groundwater quality analysis and mapping via geographical information system (GIS) proves to be beneficial in identifying the locations where the groundwater quality is deteriorating. In the current study, the WQI of groundwater was determined for the samples collected from open and tube wells located within the Udupi district of Karnataka state, India. The groundwater quality parameters such as pH, hardness, calcium, chlorides, nitrates, iron, fluoride, sulfates, manganese, sodium, magnesium, potassium, turbidity, and phosphate were analyzed for water samples collected from 112 randomly chosen open/tube wells in order to determine the WQI. Interpolation approaches such as inverse distance weighting (IDW) and kriging were adopted in the GIS environment to quantify the spatial variability of groundwater quality over the entire geographical area. The groundwater quality maps were generated using the best fit models. The results portray that, the accuracy of interpolation using IDW and kriging methods was dependent on the measures of central tendency and variability of water quality data of different parameters. The kriging interpolation was much accurate for most of the groundwater quality parameters compared to IDW maps. The WQI maps, perhaps signposted the poor quality of groundwater quality in about 1.88% of the geographical area of Udupi district. Further, about 21.69% of the area was affected by poor quality of groundwater where suitable strategies for replenishment of groundwater resources should be taken up by the concerned authorities. The spatial distribution maps of groundwater quality aid to locate vulnerable places where immediate action is required.

Highlights

  • Water quality index mapping clearly depicts the critical areas that need policy measures for the groundwater sustainability.

  • Current study acts as a decision support system for taking up water quality management activities for groundwater remediation in the study area.

  • Geostatistical methods prove to be ideal for the evaluation of spatial groundwater quality assessment and distribution.

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References

  • Akter T, Jhohura F T, Akter F, Chowdhury T R, Mistry S K, Dey D, Barua M K, Islam M A and Rahman M 2016 Water quality index for measuring drinking water quality in rural Bangladesh: A cross-sectional study; J. Health Popul. Nutr. 35 4.

    Article  Google Scholar 

  • Ambiga K and Annadurai R 2015 Development of water quality index and regression model for assessment of groundwater quality; Int. J. Adv. Remote Sens. GIS. 4 931–943.

    Article  Google Scholar 

  • APHA 2005 Standard Methods for the Examination of Water and Wastewater; American Public Health Association/American Water Works Association/Water Environment Federation, Washington DC.

    Google Scholar 

  • Arslan H and Ayyildiz Turan N 2015 Estimation of spatial distribution of heavy metals in groundwater using interpolation methods and multivariate statistical techniques: Its suitability for drinking and irrigation purposes in the Middle Black Sea Region of Turkey; Environ. Monit. Assess. 187 516.

    Article  Google Scholar 

  • BIS:10500 2012 Drinking water – Specification; Tech. Report. Bureau of Indian Standards, New Delhi.

  • Brown R M, McClelland N I, Deininger R A and Tozer R G 1970 A water quality index – Do we dare; Water Sew. W. 117 339–343.

  • CGWB 2012 Ground Water Information Booklet, Udupi District, Karnataka; Central Ground Water Board, South Western Region, Bangalore.

    Google Scholar 

  • Dinius S H 1987 Design of an index of water quality; J. Am. Water Resour. Assoc. 23 833–843.

    Article  Google Scholar 

  • Ducci D 1999 GIS Techniques for mapping groundwater contamination risk; Nat. Hazards 20 279–294.

    Article  Google Scholar 

  • Elumalai V, Brindha K, Sithole B and Lakshmanan E 2017 Spatial interpolation methods and geostatistics for mapping groundwater contamination in a coastal area; Environ. Sci. Pollut. R. 24 11,601–11,617.

    Article  Google Scholar 

  • Fathi E, Zamani-Ahmadmahmoodi R and Zare-Bidaki R 2018 Water quality evaluation using water quality index and multivariate methods, Beheshtabad River, Iran; Appl. Water Sci. 8 210.

    Article  Google Scholar 

  • Goodchild M F and Haining R P 2004 GIS and spatial data analysis: Converging perspectives; Pap. Reg. Sci. 83(1) 363–385.

    Article  Google Scholar 

  • Goovaerts P 2000 Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall; J. Hydrol. 228 113–129.

    Article  Google Scholar 

  • Gringarten E and Deutsch C V 1999 Methodology of variogram interpretation and modeling for petroleum reservoir; Soc. Petro. Eng., https://doi.org/10.2118/56654-MS.

    Book  Google Scholar 

  • Gunaalan K, Ranagalage M, Gunarathna M H J P, Kumari M K N, Vithanage M, Srivaratharasan T, Saravanan S and Warnasuriya T W S 2018 Application of geospatial techniques for groundwater quality and availability assessment: A case study in Jaffna peninsula, Sri Lanka; ISPRS Int. J. Geo-Inf. 7(1) 20.

    Article  Google Scholar 

  • Gunarathna M H J P, Kumari M K N and Nirmanee K G S 2016 Evaluation of interpolation methods for mapping pH of groundwater; Int. J Latest Tech. Eng. Manage. Appl. Sci. 5(3) 1–5.

    Google Scholar 

  • Hameed M, Sharqi S S, Yaseen Z M, Afan H A, Hussain A and Elshafie A 2017 Application of artificial intelligence (AI) techniques in water quality index prediction: A case study in tropical region, Malaysia; Neural Comput. Appl. 28 893–905.

    Article  Google Scholar 

  • Horton R K 1965 An index number system for rating water quality; J. Water Pollut. Control Feder. 37 300–306.

    Google Scholar 

  • Kumar A, Maroju S and Bhat A 2007 Application of ArcGIS geostatistical analyst for interpolating environmental data from observations; Environ. Prog. 26 220–225.

    Article  Google Scholar 

  • Lerner D N 2007 Groundwater in the environment: An introduction; Ground Water 45 253–253.

    Article  Google Scholar 

  • Lin Y, Chang T and Teng T-P 2001 Characterization of soil lead by comparing sequential Gaussian simulation, simulated annealing simulation and kriging methods; Environ. Geol. 41 189–199.

    Article  Google Scholar 

  • Luo W, Gao X and Zhang X 2018 Geochemical processes controlling the groundwater chemistry and fluoride contamination in the Yuncheng Basin, China – An area with complex hydrogeochemical conditions; PLoS ONE 13 e0199082.

    Article  Google Scholar 

  • Mueller T G, Pusuluri N B, Mathias K K, Cornelius P L, Barnhisel R I and Shearer S A 2004 Map quality for ordinary kriging and inverse distance weighted interpolation; Soil Sci. Soc. Am. J. 68 2042–2047.

    Article  Google Scholar 

  • Naganna S R and Deka P C 2018 Variability of streambed hydraulic conductivity in an intermittent stream reach regulated by vented dams: A case study; J. Hydrol. 562 477–491.

    Article  Google Scholar 

  • Nas B 2009 Geostatistical approach to assessment of spatial distribution of groundwater quality; Pol. J. Environ. Stud. 18 1073–1082.

    Google Scholar 

  • Nas B and Berktay A 2010 Groundwater quality mapping in urban groundwater using GIS; Environ. Monit. Assess. 160 215–227.

    Article  Google Scholar 

  • Nazari-Zade F, Arshadiyan F and Zand-Vakily K 2006 Study of spatial variability of groundwater quality of Balarood Plain in Khuzestan province; In: Proceedings of the first congress of optimized exploitation from water source of Karoon and Zayanderood Plain; Shahrekord University, Shahrekord. pp. P1236–P1240.

  • Neerja K, Kumar R, Yadav S S and Singh R T 2012 Water quality index assessment of ground water in Koilwar block of Bhojpur (Bihar); J. Chem. Pharm. Res. 4 1782–1786.

    Google Scholar 

  • Poon K F, Wong R W H, Lam M H W, Yeung H Y and Chiu T K T 2000 Geostatistical modelling of the spatial distribution of sewage pollution in coastal sediments; Water Res. 34 99–108.

    Article  Google Scholar 

  • Ramakrishnaiah C R, Sadashivaiah C and Ranganna G 2009 Assessment of water quality index for the groundwater in Tumkur Taluk, Karnataka State, India; E-J. Chem. 6 523–530.

    Article  Google Scholar 

  • Robinson T P and Metternicht G 2006 Testing the performance of spatial interpolation techniques for mapping soil properties; Comput. Electron. Agr. 50 97–108.

    Article  Google Scholar 

  • SAS 2008 SAS/STAT® 9.2 User’s Guide: The Variogram Procedure (Book Excerpt); SAS Institute Inc, NC.

  • Shepard D 1968 A two-dimensional interpolation function for irregularly-spaced data; In: Proceedings of the 23rd ACM National Conference, pp. 517–524.

  • Taghizadeh-Mehrjardi R 2014 Mapping the spatial variability of groundwater quality in Urmia, Iran; J. Mater. Environ. Sci. 5 530–539.

    Google Scholar 

  • Tiwari T N and Mishra M A 1985 A preliminary assignment of water quality index of major Indian rivers; Indian J. Environ. Prot. 5 276–279.

    Google Scholar 

  • Uddin M G, Moniruzzaman M, Quader M A and Hasan M A 2018 Spatial variability in the distribution of trace metals in groundwater around the Rooppur nuclear power plant in Ishwardi, Bangladesh; Groundw. Sustain. Dev. 7 220–231.

    Article  Google Scholar 

  • Uyan M and Cay T 2013 Spatial analyses of groundwater level differences using geostatistical modeling; Environ. Ecol. Stat. 20 633–646.

    Article  Google Scholar 

  • Webster R and Oliver M A 2008 Geostatistics for environmental scientists; 2nd edn, Wiley, Brisbane.

    Google Scholar 

  • Yaseen Z M, Ramal M M, Diop L, Jaafar O, Demir V and Kisi O 2018 Hybrid adaptive neuro-fuzzy models for water quality index estimation; Water Resour. Manag. 32 2227–2245.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Civil Engineering, Shri Madhwa Vadiraja Institute of Technology and Management, Bantakal, Udupi, 574 115, India

    B V Deepika

  2. Department of Civil Engineering, BMS College of Engineering, Bangalore, 560 019, India

    B V Deepika & C R Ramakrishnaiah

  3. Department of Civil Engineering, Siddaganga Institute of Technology, Tumkur, 572 103, Karnataka, India

    Sujay Raghavendra Naganna

Authors
  1. B V Deepika
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  2. C R Ramakrishnaiah
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  3. Sujay Raghavendra Naganna
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Contributions

Deepika B V: Conceptualization, investigation, data curation, methodology, writing – original draft, visualization, validation. C R Ramakrishnaiah: Supervision, conceptualization. Sujay Raghavendra Naganna: Writing – reviewing and editing.

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Correspondence to B V Deepika.

Additional information

Communicated by Abhijit Mukherjee

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Deepika, B.V., Ramakrishnaiah, C.R. & Naganna, S.R. Spatial variability of ground water quality: a case study of Udupi district, Karnataka State, India. J Earth Syst Sci 129, 221 (2020). https://doi.org/10.1007/s12040-020-01471-4

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  • DOI: https://doi.org/10.1007/s12040-020-01471-4

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