Abstract
This work aims to use geostatistical tools to understand the spread of groundwater quality variables across the state. Ordinary kriging, simple kriging, and universal kriging techniques were used in this study with root mean square error (RMSE), mean square error (MSE), root mean square standardized error (RMSSE), and averaged standard error (ASE) metrics. Groundwater quality variables such as bicarbonate, chloride, electrical conductivity, fluoride, potassium, magnesium, sodium, nitrate, pH, SAR, and sulfate were tested in this study over a GIS workspace. A correlation map was generated to show the strong correlation between the variables. Principal component analysis was performed to extract principal components from the dataset. Cluster analysis was performed, and 9 clusters were obtained. The size of the first cluster is 904, with an explained proportion of within-cluster heterogeneity of 0.979 and a silhouette score of 0.629. The total sum of squares for all the clusters is 13,740, and the sum of squares value is 3697.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Audet, R. H., & Abegg, G. L. (1996). Geographic information systems: Implications for problem solving. Journal of Research in Science Teaching, 33(1), 21–45. https://doi.org/10.1002/(SICI)1098-2736(199601)33:1<21::AID-TEA2>3.0.CO;2-R
APHA (1998) Standard Methods for the Examination of Water and Wastewater. 20th Edition, American Public Health Association, American Water Works Association and Water Environmental Federation, Washington, DC.
Banerji, P. K. (1990). On the geology of the Eastern Ghats of Orissa and Andhra Pradesh, India. In S. M. Naqvi (Ed.), Developments in Precambrian geology (Vol. 8, pp. 391–407). Elsevier. https://doi.org/10.1016/S0166-2635(08)70176-2
Cressie, N. (1990). The origins of kriging. Mathematical Geology, 22(3), 239–252. https://doi.org/10.1007/BF00889887
Etikala, B., Golla, V., Li, P., & Renati, S. (2019). Deciphering groundwater potential zones using MIF technique and GIS: A study from Tirupati area, Chittoor District, Andhra Pradesh, India. HydroResearch, 1, 1–7. https://doi.org/10.1016/j.hydres.2019.04.001
Golz, S., Schinke, R., & Naumann, T. (2015). Assessing the effects of flood resilience technologies on building scale. Urban Water Journal, 12(1), 30–43. https://doi.org/10.1080/1573062X.2014.939090
Goovaerts, P. (1998). Ordinary cokriging revisited. Mathematical Geology, 30(1), 21–42. https://doi.org/10.1023/A:1021757104135
Govil, P., Reddy, G., & Krishna, A. (2001). Contamination of soil due to heavy metals in the Patancheru industrial development area, Andhra Pradesh, India. Environmental Geology, 41(3), 461–469. https://doi.org/10.1007/s002540100415
Goyal, D., Haritash, A. K., & Singh, S. K. (2021). A comprehensive review of groundwater vulnerability assessment using index-based, modelling, and coupling methods. Journal of Environmental Management, 296, 113161. https://doi.org/10.1016/j.jenvman.2021.113161
Kamaraju, M. V. V., Bhattacharya, A., Reddy, G. S., Rao, G. C., Murthy, G. S., & Rao, T. C. M. (1996). Ground-water potential evaluation of West Godavari District, Andhra Pradesh State, India—A GIS approach. Groundwater, 34(2), 318–325. https://doi.org/10.1111/j.1745-6584.1996.tb01891.x
Karan, E. P., & Irizarry, J. (2015). Extending BIM interoperability to preconstruction operations using geospatial analyses and semantic web services. Automation in Construction, 53, 1–12. https://doi.org/10.1016/j.autcon.2015.02.012
Kleijnen, J. P. C. (2009). Kriging metamodelling in simulation: A review. European Journal of Operational Research, 192(3), 707–716. https://doi.org/10.1016/j.ejor.2007.10.013
Kune, R., Konugurthi, P. K., Agarwal, A., Chillarige, R. R., & Buyya, R. (2016). The anatomy of big data computing. Software: Practice and Experience, 46(1), 79–105. https://doi.org/10.1002/spe.2374
Langford, M., & Bell, W. (1997). Land cover map** in a tropical hillsides environment: A case study in the Cauca region of Colombia. International Journal of Remote Sensing, 18(6), 1289–1306. https://doi.org/10.1080/014311697218421
Matheron, G. (1976). A simple substitute for conditional expectation: The disjunctive kriging. In M. Guarascio, M. David, & C. Huijbregts (Eds.), Advanced geostatistics in the mining industry (pp. 221–236). Springer. https://doi.org/10.1007/978-94-010-1470-0_14
McCall, M. K., & Minang, P. A. (2005). Assessing participatory GIS for community-based natural resource management: Claiming community forests in Cameroon. The Geographical Journal, 171(4), 340–356. https://doi.org/10.1111/j.1475-4959.2005.00173.x
Murthy, K. S. R. (2000). Ground water potential in a semiarid region of Andhra Pradesh—A geographical information system approach. International Journal of Remote Sensing, 21(9), 1867–1884. https://doi.org/10.1080/014311600209788
Mutheneni, S. R., Mopuri, R., Naish, S., Gunti, D., & Upadhyayula, S. M. (2018). Spatial distribution and cluster analysis of dengue using self organizing maps in Andhra Pradesh, India, 2011–2013. Parasite Epidemiology and Control, 3(1), 52–61. https://doi.org/10.1016/j.parepi.2016.11.001
Nageswara Rao, P. V., Appa Rao, S., & Subba Rao, N. (2017). Geochemical evolution of groundwater in the Western Delta region of River Godavari, Andhra Pradesh, India. Applied Water Science, 7(2), 813–822. https://doi.org/10.1007/s13201-015-0294-y
Oliver, M. A., & Webster, R. (1990). Kriging: A method of interpolation for geographical information systems. International Journal of Geographical Information Systems, 4(3), 313–332. https://doi.org/10.1080/02693799008941549
Pilz, J., & Spöck, G. (2008). Why do we need and how should we implement Bayesian kriging methods. Stochastic Environmental Research and Risk Assessment, 22(5), 621–632. https://doi.org/10.1007/s00477-007-0165-7
Rajesh, R., Brindha, K., Murugan, R., & Elango, L. (2012). Influence of hydrogeochemical processes on temporal changes in groundwater quality in a part of Nalgonda district, Andhra Pradesh, India. Environmental Earth Sciences, 65(4), 1203–1213. https://doi.org/10.1007/s12665-011-1368-2
Raju, N. J. (2007). Hydrogeochemical parameters for assessment of groundwater quality in the upper Gunjanaeru River basin, Cuddapah District, Andhra Pradesh, South India. Environmental Geology, 52(6), 1067–1074. https://doi.org/10.1007/s00254-006-0546-0
Rao, Y. S., Reddy, T. V. K., & Nayudu, P. T. (1997). Groundwater quality in the Niva River basin, Chittoor district, Andhra Pradesh, India. Environmental Geology, 32(1), 56–63. https://doi.org/10.1007/s002540050193
Rao, K. R. P., Reddy, T. A. K., Rao, K. V. S., Rao, K. S. B., & Rao, N. V. (1998). Geology, petrology and geochemistry of Narayanpet Kimberlites in Andhra Pradesh and Karnataka. Geological Society of India, 52(6), 6. https://samvad.sibmpune.edu.in/index.php/jgsi/article/view/69102
Reyes, A., Giraldo, R., & Mateu, J. (2015). Residual kriging for functional spatial prediction of salinity curves. Communications in Statistics – Theory and Methods, 44(4), 798–809. https://doi.org/10.1080/03610926.2012.753087
Ro, Y., & Yoo, C. (2022). Numerical experiments applying simple kriging to intermittent and log-normal data. Water, 14(9), 9. https://doi.org/10.3390/w14091364
Solow, A. R. (1986). Map** by simple indicator kriging. Mathematical Geology, 18(3), 335–352. https://doi.org/10.1007/BF00898037
Subba Rao, N. (2002). Geochemistry of groundwater in parts of Guntur district, Andhra Pradesh, India. Environmental Geology, 41(5), 552–562. https://doi.org/10.1007/s002540100431
Sujatha, D., & Reddy, B. R. (2003). Quality characterization of groundwater in the south-eastern part of the Ranga Reddy district, Andhra Pradesh, India. Environmental Geology, 44(5), 579–586. https://doi.org/10.1007/s00254-003-0794-1
Sullivan, J. (1984). Conditional recovery estimation through probability kriging—Theory and practice. In G. Verly, M. David, A. G. Journel, & A. Marechal (Eds.), Geostatistics for natural resources characterization: Part 1 (pp. 365–384). Springer. https://doi.org/10.1007/978-94-009-3699-7_22
Suresh, G., Ananthanarayana, R., Hanumanthu, R. C., Ghosh, S., Anil Kumar, A., & Reddy, K. V. S. (2010). Geology of Pulikonda and Dancherla alkaline complexes, Andhra Pradesh. Journal of the Geological Society of India, 75(4), 576–595. https://doi.org/10.1007/s12594-010-0052-6
Vadjunec, J. M., Colston, N. M., Fagin, T. D., Boardman, A. L., & Birchler, B. (2022). Fostering resilience and adaptation to drought in the southern high plains: Using participatory methods for more robust citizen science. Sustainability, 14(3), 3. https://doi.org/10.3390/su14031813
Wackernagel, H. (2003). Ordinary Kriging. In H. Wackernagel (Ed.), Multivariate geostatistics: An introduction with applications (pp. 79–88). Springer. https://doi.org/10.1007/978-3-662-05294-5_11
Webster, R., & McBratney, A. B. (1987). Map** soil fertility at Broom’s Barn by simple kriging. Journal of the Science of Food and Agriculture, 38(2), 97–115. https://doi.org/10.1002/jsfa.2740380203
Zhong, C., Wang, T., Zeng, W., & Müller Arisona, S. (2012). Spatiotemporal visualization: A survey and outlook. In S. M. Arisona, G. Aschwanden, J. Halatsch, & P. Wonka (Eds.), Digital urban modelling and simulation (pp. 299–317). Springer. https://doi.org/10.1007/978-3-642-29758-8_16
Zimmerman, D., Pavlik, C., Ruggles, A., & Armstrong, M. P. (1999). An experimental comparison of ordinary and universal kriging and inverse distance weighting. Mathematical Geology, 31(4), 375–390. https://doi.org/10.1023/A:1007586507433
Acknowledgments
The authors thank the Central Pollution Control Board, Government of India, for making the data available for this research through the website.
Conflict of Interest
The authors declare no conflict of interest.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mogaraju, J.K. (2023). Geostatistics Interceded Groundwater Quality Study with Emphasis on Kriging Across the Andhra Pradesh State of India. In: Mushtaq, F., Farooq, M., Mukherjee, A.B., Ghosh Nee Lala, M. (eds) Geospatial Analytics for Environmental Pollution Modeling. Springer, Cham. https://doi.org/10.1007/978-3-031-45300-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-031-45300-7_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-45299-4
Online ISBN: 978-3-031-45300-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)