Abstract
In this study, we assess the drinking water quality of Jhelum city. Two hundred and ninety-two drinking water samples were randomly collected in the study area. These samples were chemically analyzed for three key toxic (in excess) elements such as pH, total dissolved solids (TDS), and calcium. Geostatistical techniques such as variogram and kriging were used to investigate the spatial variations of these minerals across the city. The spatial structure for each element was found to be anisotropic, and thus, anisotropic variograms were used. The kriging predictions revealed significant concentrations of the above-stated elements at some locations in the study area. While comparing with the World Health Organization, United States Environmental Protection Agency, and Pakistan Environmental Protection Agency standards, the water samples were found to be unsatisfactory for drinking. We conclude that the drinking water in this region is of poor quality and needs proper treatment to make it palatable.
Similar content being viewed by others
References
Bivand, R.S., Pebesma, E., & Gomez-Rubio, V. (2013). Applied spatial data analysis with R, 2nd edn. New York: Springer.
Carr, J.R., & Glass, C. E. (1989). Use of geostatistics for accurate mapping of earthquake ground motion. Geophysical Journal International, 97(2), 31–40.
Cidu, R., Frau, F., & Tore, P. (2011). Drinking water quality: comparing inorganic components in bottled water and italian tap water. Journal of Food Composition and Analysis, 24(2), 184–193.
Dagdelen, K., & Turner, A. (1996). Importance of stationarity for geostatistical assessment of environmental contamination. West Conshohocken: American Society for Testing and Materials.
Deutsch, C.V., & Journel, A.G. (1998). GSLIB - geostatistical software library and user’s guide. New York - Oxford: Oxford University Press.
Field, A. (2005). Discovering statistics using SPSS. SAGE Publications.
Gravetter, F., & Wallnau, L. (2014). Essentials of statistics for the behavioral sciences, 8th edn. Wadsworth: Belmont.
Hampel, F.R., Ronchetti, E.M., Rousseeuw, P.J., & Stahel, W.A. (1986). Robust statistics: the approach based on influence functions. Wiley Series in Probability and Statistics, 1st edn.: Wiley.
Haydar, S., Arshad, M., & Aziz, J. (2009). Evaluation of drinking water quality in urban areas of Pakistan: a case study of Southern Lahore. Pakistan Journal Engineering and Applied Science, 5, 16–23.
Isaaks, E.H., & Srivastava, R.M. (1990). An introduction to applied geostatistics. USA: Oxford University Press.
JMP Report (2015). Progress on sanitation and drinking water – 2015 update and MDG assessment. UNICEF and World Health Organization.
Journel, A.G., & Huijbregts, C.J. (1978). Mining geostatistics. London: Academic Press.
Kausar, S., Asghar, K., Anwar, S.M.S.F., & Kausar, R (2011). Factors affecting drinking water quality and human health at household level in Punjab, Pakistan. Pakistan Journal of Life and Social Science, 9(1), 33–37.
Kerry, R., Ingram, B.R., Goovaerts, P., & Oliver, M. (2008). How many samples are required to estimate a reliable REML variogram? In Ortiz, J., & Emery, X. (Eds.), Geostats 2008. Proceedings of the eighth international geostatistics congress (pp. 1155–1160). Santiago: Gecamin Ltd.
Khan, M., Sarwar, S., & Khattak, R. (2004). Evaluation of River Jehlum water of heavy metals (Zn, Cu, Fe, Mn, Ni, Cd, Pb, and Cr) and its suitability for irrigation and drinking purposes at districts Muzaffarabad (a.k). Chemical Society of Pakistan, 26(4), 436–442.
Kovitz, J.L., & Christakos, G. (2004). Spatial statistics of clustered data. Stochastic Environmental Research and Risk Assessment, 18(3), 147–166.
McMurry, J., & Fay, R. (2004). Hydrogen, Oxygen and Water, 4th edn. New Jersey: Pearson Education.
Menezes, R., Garcia-Soidan, P., & Febrero-Bande, M. (2008). A kernel variogram estimator for clustered data. Scandinavian Journal of Statistics, 35(1), 18–37.
Montero, J.M., Aviles, G.F., & Mateu, J. (2015). Spatial and spatio-temporal geostatistical modeling and kriging. England: Willy.
Nash, J., & Sutcliffe, J. (1970). River flow forecasting through conceptual models. Part i—a discussion of principles. Journal of Hydrology, 10(3), 282–290.
Nickson, R., McArthur, J., Shrestha, B., Kyaw-Myint, T., & Lowry, D. (2005). Arsenic and other drinking water quality issues, Muzaffargarh District, Pakistan. Applied Geochemistry, 20(1), 55–68.
Nychka, D., Furrer, R., Paige, J., & Sain, S. (2015). Fields: tools for spatial data. R package version 8.4-1.
Ouyang, Y., Nkedi-Kizza, P., Wu, Q., Shinde, D., & Huang, C. (2006). Assessment of seasonal variations in surface water quality. Water Research, 40(20), 3800–3810.
Pebesma, E.J. (2004). Multivariable geostatistics in S: the gstat package. Computers & Geosciences, 30, 683–691.
Pebesma, E.J., & Bivand, R.S. (2005). Classes and methods for spatial data in R. R News, 5(2), 9–13.
Phiri, O., Mumba, P., Moyo, B.H.Z., & Kadewa, W. (2005). Assessment of the impact of industrial effluents on water quality of receiving rivers in urban areas of Malawi. International Journal of Environmental Science & Technology, 2(3), 237–244.
Qadir, A., Malik, R.N., & Husain, S.Z. (2008). Spatio-temporal variations in water quality of Nullah Aik-Tributary of the River Chenab, Pakistan. Environmental Monitoring and Assessment, 140(1), 43–59.
R Core Team (2016). R: a language and environment for statistical computing. Vienna.
Reilly, C., & Gelman, A. (2007). Weighted classical variogram estimation for data with clustering. Technometrics, 49(2), 184–194.
Sarwar, S., Ahmad, F., & Khan, J. (2007). Assessment of the quality of Jhelum River water for irrigation and drinking. Sarhad Journal of Agriculture, 23(4), 1041–1046.
Shekhar, S., & Xiong, H. (2007). Encyclopedia of GIS, 1st edn. Springer Publishing Company, Incorporated.
Shrestha, S., & Kazama, F. (2007). Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji River Basin, Japan. Environmental Modelling &Software, 22(4), 464–475. Special section: Environmental Risk and Emergency Management.
Simeonov, V., Stratis, J., Samara, C., Zachariadis, G., Voutsa, D., Anthemidis, A., Sofoniou, M., & Kouimtzis, T. (2003). Assessment of the surface water quality in Northern Greece. Water Research, 37(17), 4119–4124.
Singh, K.P., Malik, A., Mohan, D., & Sinha, S. (2004). Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study. Water Research, 38(18), 3980–3992.
Sulehria, A.Q.K., S., M.Y., Kanwal, B., & Nazish, A (2013). Assessment of drinking water quality in Islampura, Distt.Lahore (local report). Science International, 25(2), 359–361.
Trochim, W.M., & Donnelly, J.P. (2006). The research methods knowledge base, 3rd edn. Cincinnati: Atomic Dog Publishing.
Wanda, E.M.M., Gulula, L.C., & Phiri, G. (2012). Determination of characteristics and drinking water quality index in Mzuzu City, Northern Malawi. Physics and Chemistry of the Earth, Parts A/B/C, 50–52, 92–97.
Warrick, A.W., & Myers, D.E. (1987). Optimization of sampling locations for variogram calculations. Water Resources Research, 23(3), 496–500.
Webster, R., & Oliver, M.A. (1989). Optimal interpolation and isarithmic mapping of soil properties. vi. Disjunctive kriging and mapping the conditional probability. Journal of Soil Science, 40(3), 497–512.
Webster, R., & Oliver, M.A. (2008). Geostatistics for environmental scientists, 2nd edn. England: Willy.
Acknowledgments
We acknowledge the Soil and Water Testing Laboratory Jhelum for providing data about the chemical properties of Jhelum ground waters.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Javed, S., Ali, A. & Ullah, S. Spatial assessment of water quality parameters in Jhelum city (Pakistan). Environ Monit Assess 189, 119 (2017). https://doi.org/10.1007/s10661-017-5822-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10661-017-5822-9