title: Water quality assessment and analysis of spatial patterns and temporal trends.
abstract: This study investigated relationships of a water quality index (WQI) with multiple water quality variables (WQVs), explored variability in water quality over time and space, and established linear and non-linear models predictive of WQI from raw WQVs. Data were processed using Spearman's rank correlation analysis, multiple linear regression, and artificial neural network modeling. Correlation analysis indicated that from a temporal perspective, the WQI, temperature, and zinc, arsenic, chemical oxygen demand, sodium, and dissolved oxygen concentrations increased, whereas turbidity and suspended solids, total solids, nitrate nitrogen (NO3-N), and biochemical oxygen demand concentrations decreased with year. From a spatial perspective, an increase with distance of the sampling station from the headwater was exhibited by 10 WQVs: magnesium, calcium, dissolved solids, electrical conductivity, temperature, NO3-N, arsenic, chloride, potassium, and sodium. At the same time, the WQI; Escherichia coli bacteria counts; and suspended solids, total solids, and dissolved oxygen concentrations decreased with distance from the headwater. Lastly, regression and artificial neural network models with high prediction powers (81.2% and 91.4%, respectively) were developed and are discussed.
authors.affiliation: Department of Environmental Sciences, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 Serdang, Selangur Darul Ehsan, Malaysia. NabeelMGazzaz@yahoo.com
authors.forename: Nabeel M
authors.initials: NM
authors.lastname: Gazzaz
authors.forename: Mohd Kamil
authors.initials: MK
authors.lastname: Yusoff
authors.forename: Hafizan
authors.initials: H
authors.lastname: Juahir
authors.forename: Mohammad Firuz
authors.initials: MF
authors.lastname: Ramli
authors.forename: Ahmad Zaharin
authors.initials: AZ
authors.lastname: Aris
mesh_terms: D005843:Geography; D016014:Linear Models; D008296:Malaysia; D016571:Neural Networks, Computer; D045483:Rivers / Q000737:chemistry*; D013997:Time Factors; D060753:Water Quality