مرکز منطقه ای اطلاع رساني علوم و فناوري -

چكيده لاتين :

Multivariate statistical techniques were applied for evaluation of temporal/ spatial variations and interpretation ofa large complexwater-qualitydata set ofShiroud River that discharges to southern part ofCaspian Sea, Iran. TotalIy 16parameters of water quality were monitored during 12 months at 8 sites in mountainous, flat and estuary areas. Factor analysis (FA) results showed that the first factor explained 25.76% of the total variance [comprise ofelectrical conductivity (EC), total dissolved solids (TDS), total hardness, calcium ion and water temperature levels]. The second factor calIed water quality indicator factor explained 13.99% [comprise ofsilicate, dissolved oxygen (DO) and pH levels], and the third factor calIed phosphate pollutant factor explained 10.72% (comprise of orthophosphate and total phosphorus (TP)). Additional factors were affected by part of nutrient, flow rate and general water quality, each of them recorded variance less than I0%. Discriminate analysis (DA) gave the best results for both spatial and temporal analysis. It has provided an important data reduction as it uses only fourparameters (mean river depth, DO,NH4+, and EC). Thus, DAalloweda reductionin the dimensionalityofthe large data set, explaining a fewindicatorparameters responsible for large variations in water quality. The present study shows the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and identifies probable source components in order to explain the pollution ofShiroud River.