Spatial and temporal variation of trace metals in water and source identification using environmetric techniques in the Kuantan river, Pahang - Fikriah Faudzi
Rapid development along the Kuantan River was long perceived as the river serves many communities in terms of domestic, commercial, recreation, fisheries and agricultural purposes. Trace metals are well-documented with the toxicity and bioaccumulative characteristics which are detrimental to human health. Thus, spatial and temporal variations of selected trace metals were studied in order to determine the contributions of sources as well as to assess and forecast the pollution level affecting the Kuantan River, using environmetric techniques. Water samples from 12 sampling stations were collected from downstream of the estuary towards the upstream of the Kuantan River from January until December 2017. Trace metals were analyzed using ICP-MS after pre-concentrated with Chelex-100 and digested using Teflon Bomb procedures for dissolved and particulate fractions, respectively. Total metals obtained from laboratory analysis were specified as current data and a collective set of 12 years data (2005-2016) provided by the Department of Environment were quantified as historical data. A precise environmetric technique of principal component analysis (PCA), hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA) and artificial neural network (ANN) were equipped as advanced tools for trace metals modeling and forecasting. Based on the similarity of variable characteristics, the output demonstrates by HACA has grouped 12 sampling stations into two clusters, i.e. urban, commercial and industrial areas (UCI) and settlement, industrial and agriculture areas (SIA). UCI was subjected to the downstream areas, while SIA was situated in the upstream areas. Data reduction that was provided via DA has presented more than 80% correct assignations in spatial and temporal analysis. In the current data, PCA reveals 83.99% and 75.66% of the total variance, representing six and five principal components in the UCI and SIA, respectively. Meanwhile, six principal components were found responsible for the historical data structure provisionally named as Fe, As, Cr, Pb, Zn, Hg, conductivity, salinity and turbidity, explains 72.17% of the total variance of the data set. Significant seasonal variation also was observed in the trace metals distribution. Higher cumulative of total variance was recorded during Southwest Monsoon (73.91%) compared to the Northeast Monsoon (68.52%). For ANN computation, the most significant variable extracted from rotating PCA was selected and used in ANN model. The developed approaches were trained and tested using 80% and 20% of the data, respectively. The coefficient of determination (R2) was executed to calculate the model performances. Results showed that only As and Cr from historical data set has achieved the acceptable coefficients of determination for ANN models. Generally, this study illustrates the usefulness of environmetric techniques for analysis and interpretation of complex data sets and understanding the temporal and spatial variations in the Kuantan River for effective river water management.