Silver Creek - Division of Water Quality - Utah.gov

3.0 WATER QUALITY DATA
3.1 Sources of Data
Silver Creek Watershed TMDL Final Report
In order to assess the quality of the water in Silver Creek and to quantify the impairment of the
stream with respect to zinc and cadmium, several sources of data were considered. These data
sources were collected by different government agencies and are summarized below and in
Appendix A of this report.
STORET
STOrage and RETrieval (STORET) is a repository for water quality, biological, and physical
data, and it is used by state environmental agencies, EPA and other Federal agencies,
universities, private citizens, and many others. This data was collected by the Utah Division of
Water Quality over a twelve-year period between 1990 and 2002, and covers the reach of Silver
Creek from the Weber River at Wanship upstream to a station located near Bonanza Drive in
Park City (see Figure 5). Not all of the sampling stations were sampled consistently throughout
this period.
USGS
USGS conducted two separate studies on Silver Creek, one in 2000 and another in 2002. The
USGS sampling locations cover the same reach of the stream as do the STORET stations.
USEPA
In the Year 2000, USEPA sampled during the Spring, Summer, and Autumn periods in the reach
of the stream from the vicinity of Richardson Flats upstream to the headwaters of Silver Creek.
3.2 Data Limitations
As with most studies of this nature, there has not been continuous sampling conducted
throughout the watershed over the 13 year time period analyzed. The sampling has included
different time spans, non-uniform sampling within the time spans, and inconsistent flow
measurements. Sometimes flow measurements were made concurrently with water quality
sampling, and at other times no flow measurements were made. There do not appear to be any
data points where only flow measurements were made.
Figure 6 shows the sampling performed for dissolved zinc at the STORET locations. Only two
sampling locations have data for the entire time span of the study. Most locations have data
limited to shorter time periods.
Generally there are small populations of data for most time periods. This necessitated the
clustering of the individual data points. The purpose of the clustering was to be able to compute
statistically reliable parameters for each time interval within the year. Because the standard error
of estimate of the mean value for populations is approximately proportional to the inverse of the
square root of the number of data points, it is important to have a minimum number of data
points in order to reasonably estimate the mean value for the population. Therefore, the time
interval for clustering was expanded until such time as the minimum number of data points per
interval was in the range of 4 to 5. In order to accomplish this objective, it was necessary to
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