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RELATING TRENDS OF PRINCIPAL COMPONENTS TO TRENDS OF WATER‐QUALITY CONSTITUENTS 1
Author(s) -
Yu YunSheng,
Zou Shimin
Publication year - 1993
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1993.tb03239.x
Subject(s) - principal component analysis , water quality , environmental science , hydrology (agriculture) , drainage basin , sampling (signal processing) , principal (computer security) , geology , geography , statistics , ecology , mathematics , cartography , engineering , geotechnical engineering , filter (signal processing) , computer science , electrical engineering , biology , operating system
The seasonal Kendall test is used for detecting water‐quality trend or lack of trend for monthly data of 15 water‐quality constituents at 15 sampling stations in the Arkansas River, the Neosho River, and the Verdigris River basins. Trends of individual constituents and the trends of the first four principal components for the correlation matrix of water‐quality data at each station are determined, and the relationships between the trends of constituents and the trends of principal components are established. Using the principal components not only reduces the high dimensionality of the original data to a few principal components, but also presents an overall picture of water‐quality trend of these river basins.