River water quality assessment using environmentric techniques: case study of Jakara River Basin View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-08

AUTHORS

Adamu Mustapha, Ahmad Zaharin Aris, Hafizan Juahir, Mohammad Firuz Ramli, Nura Umar Kura

ABSTRACT

Jakara River Basin has been extensively studied to assess the overall water quality and to identify the major variables responsible for water quality variations in the basin. A total of 27 sampling points were selected in the riverine network of the Upper Jakara River Basin. Water samples were collected in triplicate and analyzed for physicochemical variables. Pearson product-moment correlation analysis was conducted to evaluate the relationship of water quality parameters and revealed a significant relationship between salinity, conductivity with dissolved solids (DS) and 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), and nitrogen in form of ammonia (NH4). Partial correlation analysis (r p) results showed that there is a strong relationship between salinity and turbidity (r p=0.930, p=0.001) and BOD5 and COD (r p=0.839, p=0.001) controlling for the linear effects of conductivity and NH4, respectively. Principal component analysis and or factor analysis was used to investigate the origin of each water quality parameter in the Jakara Basin and identified three major factors explaining 68.11 % of the total variance in water quality. The major variations are related to anthropogenic activities (irrigation agricultural, construction activities, clearing of land, and domestic waste disposal) and natural processes (erosion of river bank and runoff). Discriminant analysis (DA) was applied on the dataset to maximize the similarities between group relative to within-group variance of the parameters. DA provided better results with great discriminatory ability using eight variables (DO, BOD5, COD, SS, NH4, conductivity, salinity, and DS) as the most statistically significantly responsible for surface water quality variation in the area. The present study, however, makes several noteworthy contributions to the existing knowledge on the spatial variations of surface water quality and is believed to serve as a baseline data for further studies. Future research should therefore concentrate on the investigation of temporal variations of water quality in the basin. More... »

PAGES

5630-5644

References to SciGraph publications

  • 2010-08. Assessment of surface water quality of the Ceyhan River basin, Turkey in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2012-12. Hydrogeochemical processes and quality assessment of groundwater in Dumka and Jamtara districts, Jharkhand, India in ENVIRONMENTAL EARTH SCIENCES
  • 2011-03. Assessment of temporal variation in water quality of some important rivers in middle Gangetic plains, India in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2012-09. Hydrogeochemical assessment of groundwater in Isfahan province, Iran in ENVIRONMENTAL EARTH SCIENCES
  • 2010-05. Quality of Municipal Wastewater Compared to Surface Waters of the River and Artificial Canal Network in Different Areas of the Eastern Po Valley (Italy) in EXPOSURE AND HEALTH
  • 2009-03. The water quality management in the Nakdong River watershed using multivariate statistical techniques in KSCE JOURNAL OF CIVIL ENGINEERING
  • 2013-06. Assessment of the effluent quality from a gold mining industry in Ghana in ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • 2012-06. Evaluation of the Influence of Natural and Antrhopogenic Processes on Water Quality in Karstic Region in WATER, AIR, & SOIL POLLUTION
  • 2011-10. A Statistical Approach for Evaluation of the Effects of Industrial and Municipal Wastes on Warri Rivers, Niger Delta, Nigeria in EXPOSURE AND HEALTH
  • 2000. Multivariate Statistics for Wildlife and Ecology Research in NONE
  • 2010-01. Analytical and chemometric characterization of the Cruces River in South Chile in ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • 2012-08. Spatiotemporal distributions of nutrients in the downstream from Gezhouba Dam in Yangtze River, China in ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • 2007-04. Anthropogenic impact on water quality of Chilika lagoon RAMSAR site: a statistical approach in WETLANDS ECOLOGY AND MANAGEMENT
  • 2010-03. Water Quality Assessment Using Multivariate Statistical Methods—A Case Study: Melen River System (Turkey) in WATER RESOURCES MANAGEMENT
  • 2010-11. Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2007-09. Application of Multivariate Statistical Methods to Water Quality Assessment of the Watercourses in Northwestern New Territories, Hong Kong in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2013-12. Surface water quality contamination source apportionment and physicochemical characterization at the upper section of the Jakara Basin, Nigeria in ARABIAN JOURNAL OF GEOSCIENCES
  • 2010-11. Seasonal and spatial variation of Yamuna River water quality in Delhi, India in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2013-09. Geochemistry and quality assessment of groundwater using graphical and multivariate statistical methods. A case study: Grombalia phreatic aquifer (Northeastern Tunisia) in ARABIAN JOURNAL OF GEOSCIENCES
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s11356-013-1542-z

    DOI

    http://dx.doi.org/10.1007/s11356-013-1542-z

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1026624019

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/23443942


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