Understanding the water quality within a watershed is vital to the proper management of
that watershed. This requires monitoring frequencies that observe variations in water
quality over a variety of time scales, and analytical techniques that effectively interpret
the resulting data sets. The following study assesses the use of high frequency, in situ
sensors and discreet grab sampling along with Principal Component Analysis (PCA) for
watershed management. PCA of the water quality parameters produced graphical
representations of the data that captured between 73.0% and 88.6% of the variability in
the data sets analyzed. These figures were useful for showing changes in water quality
over different time periods and for describing the relationships between different water
quality parameters in the data sets. The monitoring scheme used was effective for tracing
changes in water quality over a wide range of temporal scales, and showed the
importance of flow to the water quality of Minnehaha Creek. This type of monitoring has economic and analytical limitations, however, that must be addressed to make it viable on a watershed management scale.
University of Minnesota M.S. thesis. February 2011. Major: Civil Engineering. Advisor: William Arnold. 1 computer file (PDF); viii, 68 pages, appendices A-C.
Erickson, Kevin Anders.
Temporal variations in urban stream water quality and the use of high frequency sampling for watershed management.
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