Skip to main content

Advertisement

Log in

Statistical Approach in Determining the Spatial Changes of Surface Water Quality at the Upper Course of Kano River, Nigeria

  • Published:
Water Quality, Exposure and Health Aims and scope Submit manuscript

Abstract

In this study, statistical techniques were used to evaluate the spatial variation of surface water quality and pollution source apportionment in Kano River, Nigeria. Triplicate water samples were collected from 30 sampling sites along the upper course of Kano River and analyzed for 23 parameters which include dissolved oxygen (DO), 5-day biochemical oxygen demand \((\hbox {BOD}_{5})\), chemical oxygen demand, pH, temperature, salinity, conductivity, dissolved solids, suspended solids, total solids, turbidity, chloride (Cl), ammonia \((\hbox {NH}_{3})\), nitrate \((\hbox {NO}_{3})\), potassium (K), magnesium (Mg), sodium (Na), calcium (Ca), phosphate \((\hbox {PO}_{4})\), iron (Fe), zinc (Zn), Escherichia coliform (E. coli), and total coliform (T. coli). Hierarchical agglomerative cluster analysis grouped the 30 sampling sites into three statistically significant clusters based on similarities of surface water quality characteristics. Principal component and factor analyses (PCA and FA) were used to investigate the source of water quality parameters and to identify three major water pollution sites: high pollution sites, moderate pollution site, and low pollution site which explained more than 65 % of the total variance in water quality. Discriminant analysis provided a better result with great discriminatory ability, pattern recognition, and important data reduction using only seven parameters (DO, \(\hbox {BOD}_{5}\), pH, \(\hbox {NH}_{3}\), Cl, E. coli, and T. coli) for spatial variation and affording more than 90 % correct cases assignation. Further, one-way analysis of variance (one-way ANOVA) was applied to the three factors obtained from PCA and FA to compare the variation within and between the factors, the result showed significant differences \((p < 0.05)\) between the factors. The study provides a new insight into the environmental quality in Kano River for effective surface water quality management and protection.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Alberto WD, Valeria AM, Fabiana PS, Cecilia HA, Los Angeles BM (2001) Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study of Suquia River Basin (Córdoba-Argentina). Water Res 35(12):2881–2894

    Article  CAS  Google Scholar 

  • APHA A (2008) Standard methods for the examination of water and wastewater. American Public Health Association

  • Aris AZ, Praveena SM, Isa NM, Lim WY, Juahir H, Yusoff MK, Mustapha A (2013) Application of environmetric methods to surface water quality assessment of Langkawi Geopark (Malaysia). Environ Forensics 14(3):230–239

    Article  Google Scholar 

  • Armah FA, Obiri S, Yawson DO, Onumah EE, Yengoh GT, Afrifa EKA, Odoi JO (2010) Anthropogenic sources and environmentally relevant concentrations of heavy metals in surface water of a mining district in Ghana: a multivariate statistical approach. J Environ Sci Health A 45(13):1804–1813

    Google Scholar 

  • Arslan H (2012) Application of multivariate statistical techniques in the assessment of groundwater quality in seawater intrusion area in Bafra Plain, Turkey. Environ Monit Assess 185(3):2439–2452

    Article  Google Scholar 

  • Avtar R, Kumar P, Singh C, Mukherjee S (2011) A comparative study on hydrogeochemistry of Ken and Betwa Rivers of Bundelkhand using statistical approach. Water Qual Expo Health 2(3):169–179

    Article  CAS  Google Scholar 

  • Awadallah AG, Yousry M (2012) Identifying homogeneous water quality regions in the Nile River using multivariate statistical analysis. Water Resour Manag 26(1):2039–2055

    Google Scholar 

  • Brodnjak-Voncina D, Dobcnik D, Novic M, Zupan J (2002) Chemometrics characterisation of the quality of river water. Anal Chim Acta 462(1):87–100

    Article  CAS  Google Scholar 

  • Chapman DV (1996) Water quality assessments: a guide to the use of biota, sediments, and water in environmental monitoring. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Chen K, Jiao JJ, Huang J, Huang R (2007) Multivariate statistical evaluation of trace elements in groundwater in a coastal area in Shenzhen, China. Environ Pollut 147(3):771–780

    Article  CAS  Google Scholar 

  • Das M, Kumar A, Mohapatra M, Muduli S (2010) Evaluation of drinking quality of groundwater through multivariate techniques in urban area. Environ Monit Assess 166(1):149–157

    Article  CAS  Google Scholar 

  • Delpla I, Jung AV, Baures E, Clement M, Thomas O (2009) Impacts of climate change on surface water quality in relation to drinking water production. Environ Int 35(8):1225–1233

    Article  CAS  Google Scholar 

  • Gibrilla A, Bam EKP, Adomako D, Ganyaglo S, Osae S, Akiti TT, Kebede S, Achoribo E, Ahialey E, Ayanu G (2011) Application of Water Quality Index (WQI) and multivariate analysis for groundwater quality assessment of the Birimian and Cape Coast Granitoid Complex: Densu River Basin of Ghana. Water Qual Expo Health 3(2):63–78

    Article  CAS  Google Scholar 

  • Gupta I, Dhage S, Kumar R (2009) Study of variations in water quality of Mumbai coast through multivariate analysis techniques. Indian J Mar Sci 38(2):170–177

    CAS  Google Scholar 

  • Hamzaoui F, Ketata M, Bouhlila R, Gueddari M, Riberio L (2011) Hydrogeochemical characteristics and assessment of drinking water quality in Zeuss-Koutine aquifer, Southeastern Tunisia. Environ Monit Assess 174(1):283–298

    Article  Google Scholar 

  • Hellar-Kihampa H, Wael K, Lugwisha E, Grieken R (2013) Water quality assessment in the Pangani River basin, Tanzania: natural and anthropogenic influences on the concentrations of nutrients and inorganic ions. Int J River Basin Manag 11(1):55–75

    Article  Google Scholar 

  • Hinkle DE, Wiersma W, Jurs SG (2003) Applied statistics for the behavioral sciences. Houghton Mifflin, Boston, MA

    Google Scholar 

  • Huang F, Wang X, Lou L, Zhou Z, Wu J (2010) Spatial variation and source apportionment of water pollution in Qiantang River (China) using statistical techniques. Water Res 44(5):1562–1572

    Article  CAS  Google Scholar 

  • Ige OO, Olasehinde PI (2011) Preliminary assessment of water quality in Ayede-Ekiti, Southwestern Nigeria. J Geol Min Res 3(6):147–152

    Google Scholar 

  • Juahir H, Zain SM, Yusoff MK, Hanidza TIT, Armi ASM, Toriman ME, Mokhtar M (2011) Spatial water quality assessment of Langat River Basin (Malaysia) using environmetric techniques. Environ Monit Assess 173(1):625–641

    Article  Google Scholar 

  • Kitsiou D, Karydis M (2011) Coastal marine eutrophication assessment: a review on data analysis. Environ Int 37(1):778–801

    Article  Google Scholar 

  • Kura NU, Ramli MF, Sulaiman WNA, Ibrahim S, Aris AZ, Mustapha A (2013) Evaluation of factors influencing the groundwater chemistry in a small tropical island of Malaysia. Int J Environ Public Health 10:1861–1881

    CAS  Google Scholar 

  • Landau S, Everitt B (2004) A handbook of statistical analyses using SPSS. CRC Press, Boca Raton, FL

    Google Scholar 

  • Leach NL, Barrett KC, Morgan GA (2005) SPSS for intermediate statistics: use and interpretation. Lawrence Erlbaum, Mahwah, NJ

    Google Scholar 

  • Li S, Liu W, Gu S, Cheng X, Xu Z, Zhang Q (2009) Spatio-temporal dynamics of nutrients in the upper Han River basin, China. J Hazard Mater 162:1340–1346

    Article  CAS  Google Scholar 

  • Li S, Zhang Q (2010) Spatial characterization of dissolved traced elements and heavy metals in the upper Han River (China) using multivariate statistical techniques. J Hazard Mater 176:579–588

    Article  CAS  Google Scholar 

  • Liang Z, He Z, Zhou X, Powell CA, Yang Y (2013) Impact of mixed land-use practices on the microbial water quality in a subtropical coastal watershed. Sci Total Environ 449(1):426–433

    Article  CAS  Google Scholar 

  • Liu CW, Lin KH, Kuo YM (2003) Application of factor analysis in the assessment of groundwater quality in a Blackfoot disease area in Taiwan. Sci Total Environ 313(1):77–89

    Article  CAS  Google Scholar 

  • Mahapatra SS, Sahu M, Patel RK, Panda BN (2012) Prediction of water quality using principal component analysis. Water Qual Expo Health 4(2):93–104

    Article  CAS  Google Scholar 

  • McGarigal K, Cushman S, Stafford SG (2000) Multivariate statistics for wildlife and ecology research. Springer, Berlin

    Book  Google Scholar 

  • Mustapha A, Nabegu AB (2011) Surface water pollution source identification using principal component analysis and factor analysis in Getsi River, Kano, Nigeria. Aust J Basic Appl Sci 5(12):1507–1512

    CAS  Google Scholar 

  • Mustapha A, Aris AZ (2012) Multivariate statistical analysis and environmental modeling of heavy metals pollution by industries. Polish J Environ Stud 21(5):1359–1367

    CAS  Google Scholar 

  • Mustapha A, Aris AZ, Ramli MF, Juahir H (2012a) Spatial-temporal variation of surface water quality in the downstream region of the Jakara River, north-western Nigeria: a statistical approach. J Environ Sci Health A 47(11):1551–1560

    Article  CAS  Google Scholar 

  • Mustapha A, Aris AZ, Ramli MF, Juahir H (2012b) Temporal aspects of surface water quality variation using robust statistical tools. Sci World J. doi:10.1100/2012/294540

  • Mustapha A, Aris AZ, Ramli MF, Juahir H, Kura NU (2013) River water quality assessment using environmentric techniques: case study of Jakara River Basin. Environ Sci Pollut Res 20(8):5630–5644

    Article  CAS  Google Scholar 

  • Nouri J, Karbassi AR, Mirkia S (2008) Environmental management of coastal regions in the Caspian Sea. Int J Environ Sci Technol 5(1):43–52

    Google Scholar 

  • Onojake MC, Ukerun SO, Iwuoha G (2011) A statistical approach for evaluation of the effects of industrial and municipal wastes on Warri Rivers, Niger Delta, Nigeria. Water Qual Expo Health 3(2):91–99

    Article  CAS  Google Scholar 

  • Omo-Irabor OO, Olobaniyi SB, Oduyemi K, Akunna J (2008) Surface and groundwater water quality assessment using multivariate analytical methods: a case study of the Western Niger Delta, Nigeria. Phys Chem Earth A/B/C 33(8–13):666–673

    Article  Google Scholar 

  • Papazova P, Simeonova P (2013) Environmetric data interpretation to assess the water quality of Maritsa River catchment. J Environ Sci Health A 48(8):963–972

    Article  CAS  Google Scholar 

  • Papaioannou A, Mavridou A, Hadjichristodoulou C, Papastergiou P, Pappa O, Dovriki E, Rigas I (2010) Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health. Environ Monit Assess 170(1):87–97

    Article  CAS  Google Scholar 

  • Rogerson PA (2010) Statistical methods for geography: a student’s guide. Sage Publications, London

  • Satheeshkumar P, Khan AB (2011) Identification of mangrove water quality by multivariate statistical analysis methods in Pondicherry coast, India. Environ Monit Assess 184(6):3761–3774

    Article  Google Scholar 

  • Salve PR, Gobre T, Lohkare H, Krupadam RJ, Bansiwal A, Ramteke DS, Wate SR (2012) Source identification and variation in the chemical composition of rainwater at coastal and industrial areas of India. J Atmos Chem 68(3):183–198

    Article  Google Scholar 

  • Sheykhi V, Moore F (2012) Geochemical characterization of Kor River water quality, Fars Province, southwest Iran. Water Qual Expo Health 4(1):25–38

    Article  CAS  Google Scholar 

  • Shrestha S, Kazama F (2007) Assessment of surface water quality using multivariate statistical techniques: a case study of the Fuji River Basin, Japan. Environ Model Softw 22(4):464–475

    Article  Google Scholar 

  • Silva RI, Cardoso O, Tonani KA, Julião FC, Trevilato TMB, Segura-Muñoz SI (2012) Water quality of the Ribeirão Preto Stream, a watercourse under anthropogenic influence in the southeast of Brazil. Environ Monit Assess 185(2):1151–1161

    Google Scholar 

  • Singh KP, 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 Res 38(18):3980–3992

    Article  CAS  Google Scholar 

  • Singh KP, Malik A, Mohan D, Sinha S, Singh VK (2005) Chemometric data analysis of pollutants in wastewater: a case study. Anal Chim Acta 532(1):15–25

    Article  CAS  Google Scholar 

  • Tabachnick BG, Fidell LS, Osterlind SJ (2001) Using multivariate statistics. Allyn and Bacon, Boston, MA

    Google Scholar 

  • Tlili-Zrelli B, hamzaoui Azaza F, Gueddari M, Bouhlila R (2012) Geochemistry and quality assessment of groundwater using graphical and multivariate statistical methods. A case study: Grombalia phreatic aquifer (Northeastern Tunisia). Arab J Geosci 6(9):3345–3561

    Google Scholar 

  • Varol M (2013) Dissolved heavy metal concentrations of the Kralkizi, Dicle and Batman dam reservoirs in the Tigris River Basin, Turkey. Chemosphere. doi:10.1016/j.chemosphere.2013.05.061

  • Vittori AL, Trivisano C, Gessa C, Gherardi M, Simoni A, Vianello G, Zamboni N (2010) Quality of municipal wastewater compared to surface waters of the river and crtificial canal network in different areas of the eastern Po Valley (Italy). Water Qual Expo Health 2(1): 1–13

    Google Scholar 

  • Wang X, Cai Q, Ye L, Qu X (2012) Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: a case study of the Xiangxi River Basin, China. Quatern Int. doi:10.1016/j.quaint.2012.15.015

  • Wu B, Zhao D, Zhang Y, Zhang X, Cheng S (2009) Multivariate statistical studies of organic pollutants in Nanjing reach of Yangtze River. J Hazard Mater 169(1):1093–1098

    Article  CAS  Google Scholar 

  • Xu H, Yang LZ, Zhao GM, Jiao JG, Yin SX, Liu ZP (2009) Anthropogenic impact on surface water quality in Taihu Lake region, China. Pedosphere 19(6):765–778

    Article  CAS  Google Scholar 

  • Zhang Z, Tao F, Du J, Shi P, Yu D, Meng Y, Sun Y (2010) Surface water quality and its control in a river with intensive human impacts: a case study of the Xiangjiang River, China. J Environ Manag 91(12): 2483–2490

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adamu Mustapha.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mustapha, A., Aris, A.Z., Yusoff, F.M. et al. Statistical Approach in Determining the Spatial Changes of Surface Water Quality at the Upper Course of Kano River, Nigeria. Water Qual Expo Health 6, 127–142 (2014). https://doi.org/10.1007/s12403-014-0117-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12403-014-0117-7

Keywords

Navigation