##plugins.themes.bootstrap3.article.main##

Groundwater is the major source of municipal and private potable water supply for meeting the drinking, domestic, agricultural and industrial requirements on man around the world. The cost of analyzing water quality in the laboratory to ascertain its potability is usually high and sometimes not available. Groundwater samples were collected from fifty (50) spatially referenced bore well locations in Warri and its environs in the dry and wet seasons (November 2019 to January 2020) in the study area. The water samples were analyzed for twenty-six (26) physical, chemical and bacteriological parameters both in the field and laboratory in line with APHA standard procedures for testing water and waste water inorder to evaluate the status of potability of groundwater across Warri, Delta State Nigeria. The data analysis tool in Microsoft Excel was used to explore and study the interrelationship between some conservative parameters measured in the field (pH, EC, TDS, and DO) as independent variables and some cations, anions and heavy metals (Na, Mg, Ca, HCO3, SO4 Cl, Fe, Cd, Cr, Cu and Pb) analysed in the laboratory as dependent variables. The results obtained from the parameters analysed insitu in the field which are cheap to perform and easily affordable were used to check and evaluate and the inter-relationships with some cations, anions and heavy metals. Highly correlated water quality parameters were determined by correlation coefficient (R) values obtained from correlation matrix and related by Regression equations (models). The regression models can be adopted to predict the concentration of these cations, anions and heavy metals before the rigorous laboratory analysis, to serve as a quick check for concentration of most disease-causing pollutants and to save time, money and resources, especially the near absence of AAS for analysing heavy metals in a good number of laboratories. The regression models developed in the study can be used for monitoring the water quality parameters by knowing the concentration of independent parameters obtained in the field alone. There is a relationship between variables which show that one variable actually causes changes in another variable. It was observed that multiple regression models can predict most parameters at 5% level of significance. Significantly positive correlation at 1 and 5% was found between many parameters. This technique studied and calculated the correlation coefficients between various physico-chemical parameters of drinking water and provided an excellent device for the calculation of parameter values within realistic degree of accuracy. The results proved to be easiest, useful, and rapid means for monitoring of water quality with the help of systematic calculations of correlation coefficient. It is recommended to treat groundwater prior to domestic use.

Downloads

Download data is not yet available.

References

  1. Amadi A. N., Olasehinde P. I. and Yisa J. Characterization of Groundwater Chemistry in the Coastal plain-sand Aquifer of Owerri using Factor Analysis. International Journal of Physical Science, 5(8): 1306-1314, 2010.
     Google Scholar
  2. Idoko O. M. and Oklo A. Seasonal Variation in Physico- Chemical Characteristics of Rural Groundwater in Benue State, Nigeria. Journal of Asian Scientific Research, 2(10), 574-586, 2007.
     Google Scholar
  3. Wadie A.S.T. and Abduljalil G.A.D.S. Assessment of Hydro chemical Quality of Groundwater under some Urban areas within Sana’a Secretariat. Ecletica Quimica. www.SCIELO.BR/EQ. 35(1), 77-84, 2010.
     Google Scholar
  4. Agori J. E. Geostatistical Modelling of Groundwater Water Quality Parameters in Warri and its Environs; Unpublished Doctoral Dissertation, Federal Technology of Owerri, Imo State, Nigeria, 2020.
     Google Scholar
  5. Idoko O. M. Seasonal Variation in iron in rural groundwater of Benue State, middle belt Nigeria. Pakistan Journal of Nutrition, 9(9), 892-895, 2010.
     Google Scholar
  6. Makwe E. and Chup C. D. Seasonal variation in physico-chemical properties of groundwater around Karu abattoir. Ethiopian Journal of Environmental Studies and Management, 6 (5), 489- 497, 2013.
     Google Scholar
  7. Sajal K. A., Majur A-Elahi M., and Iqbal Hossain A. M. Assessment of shallow groundwater quality from six wards of Khulna City Corporation, Bangladesh. International Journal of Applied Sciences and Engineering Research, 1(3), 488-498, 2012.
     Google Scholar
  8. Aly U. I., Abbas M. S., Taha H. S. and Gaber E. S. I. Characterization of 6-Gingerol for In Vivo and In Vitro Ginger (Zingiber officinale) Using High Performance Liquid Chromatography, Global Journal of Botanical Science, 1(1), 9-17, 2013.
     Google Scholar
  9. Milovanovic M. Water quality assessment and determination of pollution sources along the Axios/Vardar River, South-eastern Europe. Desalination, 213(1-3), 159–173, 2007.
     Google Scholar
  10. Google Maps. Maplandia.com. Google Maps World Gazetteer. 2019. Retrieved from:
     Google Scholar
  11. http://www.maplandia.com/nigeria/delta/warrisouth/warri/.
     Google Scholar
  12. Izeze O. and Adipere K. Statistical and spatial analysis of groundwater quality in Warri and its environs, Delta State, Nigeria. International Journal of Science Inventions Today, 7(3), 401-421, 2018.
     Google Scholar
  13. Akpoborie I. A., Nfor B., Etobro A. A. I. and Odagwe S. Aspects of the Geology and Groundwater Condition of Asaba Nigeria. Archives of Applied Science Research, 3(2), 537-550, 2011.
     Google Scholar
  14. Fetter C. W. Contaminant Hydrogeology. Englewood, New York. Prentice Hall, 1999.
     Google Scholar
  15. Nwajide C. S. A guide for Geological Field Trips to Anambra and Related Sedimentary Basins in South Eastern Nigeria. PTDF Fund, University of Nigeria, Nsukka Nigeria. p. 68, 2006.
     Google Scholar
  16. Causapé J., Auqué L., Gimeno M. J., Mandado J., Quílez D., and Aragüés R. Irrigation effects on the salinity of the Arba and Riguel Rivers (Spain): present diagnosis and expected evolution using geochemical models. Environmental Geology. 45(5), 703–715, 2004.
     Google Scholar
  17. Nwankwo C. and Ogagarue D. Effects of gas flaring on surface and ground waters in Delta State Nigeria. Journal of Geology and Mining Research, 3(5), 2011.
     Google Scholar
  18. Oliveira J. P. W., Dos Santos R. N., and Boeira J. M. Genotoxicity and physical chemistry analysis of waters from Sinos River (RS) using Allium cepa and Eichhornia crassipes as bioindicators. Journal of Plant Biochemistry and Biotechnology, 1, 15–22, 2012.
     Google Scholar
  19. Thirumalaivasan D., Karmegam M. and Venugopal K. AHP-DRASTIC: Software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environmental Model Software 18: 645–656, 2003.
     Google Scholar
  20. Tyagi S., Sharma B., Singh P., and Dobhal R. Water Quality Assessment in Terms of Water Quality Index. American Journal of Water Resources. 1(3), 34-38, 2013.
     Google Scholar
  21. Amangabara G. T. and Ejenma E. Groundwater Quality Assessment of Yenagoa and Environs Bayelsa State, Nigeria between 2010 and 2011. Researches and Environment, 2(2), 20-29, 2012.
     Google Scholar
  22. Adejuwon O. A. Rainfall Seasonality in the Niger Delta Belt, Nigeria. Journal of Geography and Regional Planning, 5(2), 51-60, 2012.
     Google Scholar
  23. APHA (American Public Health Association). Standard methods for examination of water and wastewater, 23rd Ed. Washington, D.C., American Public Health Association, 2017.
     Google Scholar
  24. APHA, (American Public Health Association). Standard methods of examination of water and wastewater, 22nd Ed. Washington, D.C., American Public Health Association, 2012.
     Google Scholar
  25. WHO (World Health Organization). Guidelines for drinking water quality, Electronic Resource; Incorporation 1st and 2nd Addenda v. 1 Recommendations; 3rd Edition, Geneva, 515, 2008.
     Google Scholar
  26. WHO (World Health Organization) Manual of Basic Technique for a Health Laboratory. World Health Organization, 2nd Edition, Geneva, 2003.
     Google Scholar
  27. WHO (World Health Organization). Guidelines for drinking water quality, World Health Organization, Geneva, Switzerland, 2006.
     Google Scholar
  28. WHO. Guidelines for drinking-water quality; 4th Edn., Geneva, World Health Organization, 2011.
     Google Scholar
  29. Daraigan S. G., Wahdain A. S., BaMosa A. S. and Obid M. H. “Linear correlation analysis study of drinking water quality data for Al-MukallaCity, Hadhramout, Yemen” International Journal of Environmental Sciences, Science and Technology (HUST), Mukalla, Hadhramout, Yemen, 2011.
     Google Scholar
  30. Bohling G. Introduction to Geostatistics and Variogram Analysis. Kansas Geological Survey, Lawrence, 1-20, 2005.
     Google Scholar
  31. Adhikari K. R., Tan Y. C., Lai J. S. and Pant D. Irrigation Intervention: A Strategy for conserving Biodiversity and improving Food Security in Royal Chitwan National Park Buffer Zone, Nepal. Irrigation and Drainage; 58: 522-537, 2009.
     Google Scholar


Most read articles by the same author(s)