Assessment Of Seasonal Variations In Stream Water By Principal Component Analysis
Price
Free (open access)
Transaction
Volume
106
Pages
10
Published
2007
Size
420 kb
Paper DOI
10.2495/ECO070511
Copyright
WIT Press
Author(s)
M. M. Taboada-Castro, M. L. Rodríguez-Blanco & M. T. Taboada-Castro
Abstract
Assessment of seasonal changes in surface water is an important aspect for the interpretation of hydrochemical data. Thirteen physical and chemical parameters monitored at four sampling stations along the Corbeira stream, NW Spain, were analyzed during a three-year period. The Corbeira stream drains a rural catchment (16 Km2) with low population density. The land use consists mainly of forested and agricultural land. The geological material is basic schist. A total of 51 samples were collected from each station. The principal component analysis (PCA) technique was used to evaluate the seasonal correlations of water quality parameters. Four principal components, accounting for 88.7 and 83.3% of the total variances of information contained in the original dataset for spring and winter, respectively, were obtained. In summer and autumn, three principal components accounted for 80.3 and 81.1% of the total variance, respectively. The results revealed that conductivity, chloride, magnesium, sulphate and nitrate were always the most important variables contributing to water physical-chemical properties in the stream for all seasons. The first three can be interpreted as a mineral component of the stream water. This clustering of variables points to a common origin for these minerals, most likely from an alteration of schist, whereas nitrates may be interpreted as representing influences from natural (decomposition of organic matter from soils) and anthropogenic inputs. Autumn and winter (periods with high water discharge) showed a strong influence of dissolved organic carbon (DOC) and total nitrogen (Kjeldahl), respectively. This finding could be due to surface runoff. Keywords: hydrochemistry, surface water, principal component analysis, seasonal variation.
Keywords
hydrochemistry, surface water, principal component analysis, seasonal variation.