WIT Press


Assessment Of Seasonal Variations In Stream Water By Principal Component Analysis

Price

Free (open access)

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.