Analysis of Pedernales River Water Quality
Report to the Lower Colorado River Authority
By
Michael E. Barrett, Ph.D., P.E.
Center for Research in Water Resources
Bureau of Engineering Research
University of Texas at Austin
July 31, 1998
ii
TABLE OF CONTENTS
EXECUTIVE SUMMARY............................................................................................... 1
INTRODUCTION............................................................................................................. 4
SCOPE................................................................................................................................ 5
METHODOLOGY............................................................................................................ 6
TEMPORAL TRENDS.......................................................................................................... 6
SPATIAL TRENDS.............................................................................................................. 7
RESULTS........................................................................................................................... 9
DISSOLVED OXYGEN........................................................................................................ 9
Summary Statistics ...................................................................................................... 9
Trend Analysis........................................................................................................... 10
Conclusions ............................................................................................................... 14
SPECIFIC CONDUCTIVITY................................................................................................ 14
Summary Statistics .................................................................................................... 14
Trend Analysis........................................................................................................... 15
Conclusions ............................................................................................................... 17
CHLORIDE ...................................................................................................................... 17
Summary Statistics .................................................................................................... 17
Trend Analysis........................................................................................................... 18
SULFATE......................................................................................................................... 20
Summary Statistics .................................................................................................... 20
Trend Analysis........................................................................................................... 20
NITRATE PLUS NITRITE .................................................................................................. 22
Summary Statistics .................................................................................................... 22
Trend Analysis........................................................................................................... 23
TOTAL KJELDAHL NITROGEN......................................................................................... 24
Summary Statistics .................................................................................................... 24
Trend Analysis........................................................................................................... 24
AMMONIA ...................................................................................................................... 26
Summary Statistics .................................................................................................... 26
Trend Analysis........................................................................................................... 26
TOTAL PHOSPHORUS ...................................................................................................... 27
Summary Statistics .................................................................................................... 27
Trend Analysis........................................................................................................... 27
TOTAL ORGANIC CARBON.............................................................................................. 27
Summary Statistics .................................................................................................... 27
Trend Analysis........................................................................................................... 28
FECAL COLIFORM........................................................................................................... 28
iii
Summary Statistics .................................................................................................... 28
Trend Analysis........................................................................................................... 29
CONCLUSIONS AND RECOMMENDATIONS........................................................ 30
BIBLIOGRAPHY ........................................................................................................... 33
APPENDIX A .................................................................................................................. 34
iv
List of Figures
Figure 1 Oxygen Deficit at Falls Creek ............................................................................ 11
Figure 2 Sample Collection Times at Falls Creek............................................................. 11
Figure 3 Relation between Collection Time and O
2
Deficit ............................................. 12
Figure 4 Average Oxygen Deficits on the Pedernales ...................................................... 13
Figure 5 Specific Conductance at RR 1320 ...................................................................... 16
Figure 6 Comparison of Mean Specific Conductance ...................................................... 16
Figure 7 Chloride Concentrations at RR 1320.................................................................. 18
Figure 8 Chloride Concentrations at RM 962 ................................................................... 19
Figure 9 Average Chloride Concentrations....................................................................... 20
Figure 10 Sulfate Concentrations at RR 1320................................................................... 21
Figure 11 Average Sulfate Concentrations ....................................................................... 22
Figure 12 Average Nitrate plus Nitrite Concentrations .................................................... 24
Figure 13 Total Kjeldahl Nitrogen at Johnson City.......................................................... 25
v
List of Tables
Table 1 Summary Statistics for Dissolved Oxygen .......................................................... 10
Table 2 Summary Statistics for Specific Conductivity ..................................................... 14
Table 3 Summary Statistics for Chloride .......................................................................... 17
Table 4 Summary Statistics for Sulfate............................................................................. 21
Table 5 Summary Statistics for Nitrate plus Nitrite.......................................................... 23
Table 6 Summary Statistics for Total Kjeldahl Nitrogen.................................................. 25
Table 7 Summary Statistics for Ammonia ........................................................................ 26
Table 8 Summary Statistics for Total Phosphorus............................................................ 27
Table 9 Summary Statistics for Total Organic Carbon..................................................... 28
Table 10 Summary Statistics for Fecal Coliform Data ..................................................... 29
Table 11 Regression Statistics for Oxygen Deficit at Falls Creek.................................... 34
Table 12 Regression Statistics for Oxygen Deficit at RR 1320........................................ 34
Table 13 Regression Statistics for Oxygen Deficit at Johnson City ................................. 35
Table 14 Regression Statistics for Oxygen Deficit at Hammett?s Crossing ..................... 35
Table 15 ANOVA Statistics for Oxygen Deficit .............................................................. 36
Table 16 ANOVA Statistics for DO Corrected for Time.................................................. 36
Table 17 Regression Statistics for Specific Conductance at Falls Creek.......................... 37
Table 18 Regression Statistics for Specific Conductance at Johnson City....................... 37
Table 19 Regression Statistics for Specific Conductance at Hammett?s Crossing........... 38
Table 20 Regression Statistics for Specific Conductance at RR 1320.............................. 38
Table 21 ANOVA Statistics for Specific Conductance .................................................... 38
Table 22 Regression Statistics for Chloride at RR 1320................................................... 39
Table 23 Regression Statistics for Chloride at Johnson City............................................ 39
Table 24 Regression Statistics for Chloride at RM 962.................................................... 40
Table 25 Regression Statistics for Chloride at Falls Creek............................................... 40
Table 26 ANOVA Statistics for Chloride ......................................................................... 41
Table 27 ANOVA Statistics for Chloride Normalized for Flow ...................................... 41
Table 28 Regression Statistics for Sulfate at RR 1320 ..................................................... 42
Table 29 Regression Statistics for Sulfate at Johnson City............................................... 42
vi
Table 30 Regression Statistics for Sulfate at RM 962 ...................................................... 43
Table 31 Regression Statistics for Sulfate at Falls Creek ................................................. 43
Table 32 ANOVA Statistics for Sulfate............................................................................ 44
Table 33 ANOVA Statistics for Sulfate Normalized for Flow ......................................... 44
Table 34 Regression Statistics for Nitrate plus Nitrite at RR 1320 .................................. 45
Table 35 Regression Statistics for Nitrate plus Nitrite at Johnson City............................ 45
Table 36 Regression Statistics for Nitrate plus Nitrite at RM 962.................................... 46
Table 37 Regression Statistics for Nitrate plus Nitrite at Falls Creek .............................. 46
Table 38 ANOVA Statistics for Nitrate plus Nitrite......................................................... 47
Table 39 Regression Statistics for TKN at RR 1320 ........................................................ 47
Table 40 Regression Statistics for TKN at Johnson City.................................................. 48
Table 41 Regression Statistics for TKN at RM 962.......................................................... 48
Table 42 Regression Statistics for TKN at Falls Creek .................................................... 49
Table 43 ANOVA Statistics for TKN............................................................................... 50
Table 44 Regression Statistics for Ammonia at RR 1320................................................. 50
Table 45 Regression Statistics for Ammonia at Johnson City.......................................... 50
Table 46 Regression Statistics for Ammonia at RM 962.................................................. 51
Table 47 Regression Statistics for Ammonia at Falls Creek............................................. 51
Table 48 ANOVA Statistics for Ammonia ....................................................................... 52
Table 49 Regression Statistics for Total Phosphorus at RR 1320..................................... 52
Table 50 Regression Statistics for Total Phosphorus at Johnson City.............................. 53
Table 51 Regression Statistics for Total Phosphorus at RM 962...................................... 54
Table 52 Regression Statistics for Total Phosphorus at Falls Creek................................. 54
Table 53 ANOVA Statistics for Total Phosphorus ........................................................... 55
Table 54 Regression Statistics for TOC at RR 1320......................................................... 55
Table 55 Regression Statistics for TOC at Johnson City.................................................. 56
Table 56 Regression Statistics for TOC at RM 962.......................................................... 56
Table 57 Regression Statistics for TOC at Falls Creek..................................................... 56
Table 58 ANOVA Statistics for Total Organic Carbon .................................................... 57
Table 59 Multiple Regression Statistics for Fecal Coliform at RR 1320.......................... 58
Table 60 Multiple Regression Statistics for Fecal Coliform at Johnson City................... 58
vii
Table 61 Multiple Regression Statistics for Fecal Coliform at RM 962........................... 59
Table 62 Multiple Regression Statistics for Fecal Coliform at Falls Creek...................... 59
Table 63 ANOVA Statistics for Fecal Coliform............................................................... 60
1
Executive Summary
The LCRA water quality database for the Pedernales River was analyzed to determine
current conditions and whether there are significant water quality trends. Possible trends
include spatial trends, in which the concentrations vary along the length of the river, and
temporal trends, meaning a variation in concentrations through time at a single
monitoring site.
The data were collected by the LCRA and TNRCC at four sites along the Pedernales
River: RR 1320, Johnson City, RM 962, and upstream of the confluence with Falls Creek
(the lower boundary of this river segment). Although the length of the monitoring period
varied among the sites, the majority of the data were collected between 1984 and 1997.
During this period about 7200 measurements of 24 constituents were made at the
monitoring sites. A subset of these constituents was selected for detailed statistical
analysis. The selected constituents include measures of oxygen content, dissolved solids,
nutrients and bacteria. The constituents analyzed include:
x Dissolved Oxygen
x Specific Conductance
x Sulfate
x Chloride
x Ammonia
x Nitrate + Nitrite
x Total Kjeldahl Nitrogen
x Total Organic Carbon
x Total Phosphorus
x Fecal Coliform
Analysis of the LCRA water quality database for the Pedernales River indicates that
several constituents exhibit a significant spatial trend. All of the constituents that varied
2
had higher concentrations upstream than down. These constituents are dissolved oxygen,
chloride, sulfate, nitrate plus nitrite, and specific conductance (a measure of dissolved
solids). The monitoring data are not sufficient for identifying the reasons for these
changes, which may be natural, manmade, or a combination of the two.
The higher levels of dissolved solids, nitrogen, and other ionic species may be derived
from groundwater inflow to the river. Groundwater often contains higher concentrations
of these constituents than surface water. Elevated concentrations of these constituents
also are associated with agricultural activities. Irrigation return flows have higher levels
of dissolved solids and can carry nutrients derived from fertilizers as well as agricultural
pesticides. Measurements of pesticide concentrations were not included in the
monitoring program. Determination of the causes of the higher concentrations should be
the focus of future studies, because dissolved solids, chloride, and sulfate are all listed as
parameters of possible concern in the 1994 LCRA water quality assessment (LCRA,
1994). Concentrations of these constituents are currently below levels that caused them
to be flagged in the 1994 report.
Temporal trends were most evident at the upstream monitoring station at RR 1320, which
generally had the longest period of record. Constituents with significant temporal trends
include specific conductance, chloride, and sulfate. The concentrations of each of these
showed a reduction with time. The monitoring site at RM 962 showed a single parameter
with a temporal trend, chloride, which also had declining concentrations. There was no
significant temporal trend for any constituent at Johnson City or the Falls Creek sites.
These reductions in concentration may be the result of much higher than average rainfall
in 1991 and 1992. Rainfall generally has very low concentrations of these constituents,
causing a dilution in groundwater, which contributes baseflow to the river, as well as in
the river itself through increased surface runoff.
The water quality of the Pedernales River can be characterized as very good and
supportive of all designated beneficial uses. Current concentrations of all major water
quality constituents are generally below levels that would be cause for concern or result
3
in the listing of this river segment as impaired. In addition, this data set indicates that the
concentrations of the analyzed constituents at each monitoring site are relatively constant
or improving. There is no immediate concern that changes in land use or other human
activities threaten the water quality of the Pedernales River; however, the source of
higher concentrations of dissolved solids and nutrients in the upstream reach of the river
should be identified. The change from undeveloped to agricultural land use occurred
many years before the beginning of any water quality monitoring programs and may be
responsible for higher constituent concentrations in this portion of the watershed.
Despite the generally high quality of the Pedernales River water, eight fish kill episodes
have been reported in the river, including five since 1990. Approximately half of the
kills have been the result of illegal dumping of toxic substances. These episodes
highlight the importance of an effective public education/outreach program. Such a
program can make citizens more aware of the environmental impacts of improper
disposal of waste materials. It is especially important to target owners of small
businesses, which often need to dispose of significant quantities of spent solvents,
lubricants, paint and other toxic materials.
The remaining fish kills were the result of wastewater treatment plant (WWTP)
discharges to the Pedernales near Johnson City, resulting in low dissolved oxygen
concentrations. Conventional water quality monitoring programs are not effective for
identifying episodic events resulting from equipment malfunction or other causes;
however, wastewater discharges may be responsible for the trend of decreasing dissolved
oxygen concentrations from upstream to downstream. The number of fish kills related to
wastewater discharges suggests that a review of the permit requirements and adequacy of
the Johnson City WWTP should be a high priority.
4
Introduction
The LCRA has been collecting periodic water quality data from a number of sites along
the Colorado River and it?s tributaries since the early 1980?s. Geographically, the sites
range from upstream of San Saba to Matagorda Bay. One of the main functions of data
collection is to detect long term changes in water quality that could indicate possible
causes and provide a quantitative basis for management actions. Changes in water
quality may reflect the impacts of urbanization of other changes in land use patterns.
Because of the size and complexity of the data analysis required to determine current
conditions and trends, a pilot study was determined to be the best way to evaluate the
potential problems and time required to complete a study of the entire lower Colorado
River watershed. The Pedernales River was selected as the site for initial analysis,
because it was deemed representative of river system analysis, while having a much
smaller data set for analysis.
The Pedernales also has been the site of five reported fish kills since 1990 that were
caused primarily by illegal dumping or by wastewater treatment plant discharges.
However, a general decline in water quality of this segment could have contributed to
these episodes and this is an additional reason to select the Pedernales River for analysis
of water quality trends.
5
Scope
Sufficient water quality data for analyzing temporal and spatial trends of water quality in
the Pedernales River have been collected at fours sites. From upstream to downstream,
these sites are RR 1320 (Site 150), Johnson City (Site 75), RM 962 (Site 25), and just
upstream of the confluence with Falls Creek (Site 15). Samples were collected between
1984 and 1997 by the LCRA and the Texas Natural Resource Conservation Commission,
although the period of record varies for individual constituents. The data allow the
determination of water quality changes that have occurred since 1984.
There are two primary questions addressed in this pilot study. First, does the data exhibit
discernible trends through time within the given subwatershed? Second, does the data
exhibit discernible trends through space along the length of the river? This study answers
these questions and provides a template for further analysis of water quality data for the
LCRA service area.
The constituents analyzed include:
x Dissolved Oxygen
x Specific Conductance
x Sulfate
x Chloride
x Ammonia
x Nitrate + Nitrite
x Total Kjeldahl Nitrogen
x Total Organic Carbon
x Total Phosphorus
x Fecal Coliform
6
Methodology
There are numerous statistical methods for analyzing temporal and spatial trends in water
quality data and their appropriateness often depends on the underlying distribution of the
data. Many analyses (parametric tests) assume that the data are normally distributed;
however, environmental data often does not follow this distribution. Nonparametric
statistical tests are used when the distribution of the data is unknown and although they
may not yield as much information, they are more robust. Consequently, many of the
analyses were done with both tests, where appropriate, in order to yield the strongest
results possible.
Flow rate of the Pedernales was not recorded at each location at the time of sampling.
Since this is such an important parameter, average daily flow at the U.S. Geological
Survey gauge at Johnson City was used to characterize conditions at the time of
sampling. Although the absolute value is only correct for the Johnson City monitoring
site, the numbers offer a quantitative way to differentiate between high and low flow
sampling conditions.
Many of the measurements are censored; that is, they are reported as less than or greater
than some value associated with the detection limit of the method. There are numerous
methods for treating censored data by assuming arbitrary values (the detection limit or
zero, for instance) or by identifying the underlying distribution of the data and estimating
the true value. It is far better to perform statistical analyses with the actual measured
concentrations even though they fall below the instrument or method detection limit;
however, laboratories rarely report results in this form. For this analysis, all censored
values were assumed to have the same concentration as the detection limit.
Temporal Trends
Regression analyses are commonly used to identify temporal trends in water quality data.
If plots of data versus time suggest a simple linear increase or decrease over time, a linear
regression of the variable against time may be fit to the data. A t test may be used to test
7
that the true slope is not different from zero. This t test can be misleading if seasonal
cycles are present, the data are not normally distributed, and/or the data are serially
correlated. In these situations, the t test may indicate a significant slope when the true
slope actually is zero (Gilbert, 1987).
Multiple linear regression is an especially useful approach if other variables such as flow
rate or temperature also affect parameter values. Since flow rate is such an important
factor, especially as it relates to storm runoff and baseflow, the data at each site was first
analyzed for temporal trends using multiple linear regression. The statistical software
package, Minitab for Windows: Release 12, was used for these analyses.
For the constituents that appeared to exhibit a significant temporal trend in the multiple
linear regression tests, the data also were analyzed using a nonparametric test, the Mann
Kendall test. This procedure is particularly useful since missing values are allowed and
the data need not conform to any particular distribution. Also, data reported as trace or
less than the detection limit can be used by assigning them a common value that is
smaller than the smallest measured valued in the data set. The MannKendall test can be
viewed as a nonparametric test for zero slope of the linear regression (Gilbert, 1987).
The test consists of a comparison of the difference of all possible pairs of values and
indicates whether the values are generally increasing or decreasing, but gives no
indication of the rate of change. This test is not commonly available in commercial
software packages, so it was implemented as a spreadsheet.
Spatial Trends
Analysis of variance (ANOVA) was the statistical technique used to determine whether
there are spatial trends in the water quality data (e.g., whether the mean concentrations at
the sites are different). ANOVA is similar to regression in that it is used to investigate
and model the relationship between a response variable and one or more independent
variables. However, analysis of variance differs from regression in two ways: the
independent variables are qualitative (sampling location), and no assumption is made
about the nature of the relationship (i.e. the model does not include coefficients for
8
variables). In effect, analysis of variance extends the twosample ttest for testing the
equality of two population means to a more general null hypothesis of comparing the
equality of more than two means, versus them not all being equal. Minitab for Windows:
Release 12 was used for the ANOVA calculations.
For selected constituents, the data were corrected for changes in sample collection time or
flow rate and then the ANOVA analysis was performed. This correction consisted of
normalizing the data at each site to a consistent time or flow basis. This was
accomplished by performing a linear regression against the influencing variable and
calculating the average value for an arbitrary time or discharge rate. The residual error
for each measurement was then added to the average value and the ANOVA test was then
performed on the new data set.
9
Results
Dissolved Oxygen
Summary Statistics
The analysis of temporal and spatial trends in dissolved oxygen concentrations is
especially difficult because of the number of factors that affect this parameter. Of
particular importance is temperature, depth of sample and time of day. Samples were
often collected from a series of depths at each site. There is a correlation between sample
depth and oxygen deficit, with higher deficits occurring near the base of the channel.
Other than samples collected at the surface, there were not a sufficient number of samples
to perform a trend analysis. Consequently, only those samples collected at the surface
were used to evaluate trends in the data.
The saturation concentration for dissolved oxygen was calculated for each of the samples
using the FairGeyer expression. This expression states that:
)T(
)Cl(
C
S
35
1005
where C
S
is DO saturation in mg/L, Cl is chlorinity in parts per thousand and T is
temperature in degrees Celsius. Chlorinity was taken to be zero for this analysis.
The value of the sample results was subtracted from the saturation value to determine the
oxygen deficit at the time the sample was taken. A negative value for the oxygen deficit
indicates that the measured value was greater than the saturation value. There are several
possible physical reasons that the water could be supersaturated; consequently, these
values were retained in the data set. The data was then analyzed using oxygen deficit as
the parameter of interest. The site locations and summary statistics are shown in Table 1.
10
Trend Analysis
Analysis of all samples collected at the water surface at Falls Creek indicates a significant
improvement with time in the dissolved oxygen conditions at this site (Figure 1).
However, there is also a systematic trend in the time of day the samples were collected.
Samples collected near the beginning of the sampling program were taken earlier in the
day (Figure 2) and there is a significant correlation between time of sample collection and
the oxygen deficit. The deficits are significantly higher earlier in the day when
photosynthesis has not replenished dissolved oxygen in the river (Figure 3).
Table 1 Summary Statistics for Dissolved Oxygen
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/84 ? 10/97 2/84  10/97 4/84 ? 10/97 2/84 ? 5/90
# of Samples 114 73 113 72
Average DO, mg/L 9.19 9.42 8.62 8.3
Median DO, mg/L 9.00 9.30 8.59 8
DO Std Deviation 1.77 1.94 1.47 1.7
Avg O
2
Deficit, mg/L 0.11 0.20 0.46 0.74
Median O
2
Def., mg/L 0.24 0.04 0.48 0.7
Deficit Std Dev 1.09 1.38 0.79 1.14
11
y = 0.0007x + 22.956
R
2
= 0.1531
6.0
5.0
4.0
3.0
2.0
1.0
0.0
1.0
2.0
3.0
4.0
7/3/83 11/14/84 3/29/86 8/11/87 12/23/88 5/7/90 9/19/91
Date
D
e
f
i
c
i
t (m
g
/
L
)
Figure 1 Oxygen Deficit at Falls Creek
y = 0.0009x  17.984
R
2
= 0.3506
8
9
10
11
12
13
14
15
7/3/83 11/14/84 3/29/86 8/11/87 12/23/88 5/7/90 9/19/91
Date
S
a
m
p
le
C
o
lle
c
t
io
n
T
i
m
e
Figure 2 Sample Collection Times at Falls Creek
12
y = 0.4748x + 6.4762
R
2
= 0.1803
6.0
5.0
4.0
3.0
2.0
1.0
0.0
1.0
2.0
3.0
4.0
9 101112131415
Collection Time
O
xygen D
e
f
i
ci
t
(
m
g/
L)
Figure 3 Relation between Collection Time and O
2
Deficit
The subtle shift in sampling protocol at this site creates such a strong signal in the data
that it becomes extremely difficult to detect a correlation with land use changes or other
events in the watershed. A multiple regression analysis was performed using oxygen
deficit of samples collected at the surface as the dependent variable and time of day and
date as the independent variables. The results are summarized in Table 11 and they
indicate no significant change in oxygen deficit at the 90% confidence level.
A similar analysis was performed on the data collected at RR 1320. The sample
collection at this site also changed systematically, with more recent samples collected
earlier in the day. This made it appear that there was strong trend of reduced oxygen
concentrations. A multiple linear regression analysis was conducted using date and time
of day as the independent variables. This analysis indicated a slight trend of reduced
oxygen concentrations even when time of sampling was taken into account. However,
this trend was not significant at the 95% confidence level. The multiple regression
statistics are shown in Table 12. The effect of season was also investigated at RR1320;
however, this proved to be a completely random variable. Similar analyses were
performed on the data collected at Johnson City and Hammett?s Crossing. The results of
13
the regression analyses are shown in Table 13 and Table 14. There was no significant
longterm trend in oxygen deficit at either of these sites.
An ANOVA test was performed on the pooled raw data from the Pedernales, which
indicated a significant spatial trend in oxygen deficit at a greater than 99% confidence
level. The small difference between the mean deficits at RR 1320 and Johnson City and
the mean deficits at RR 962 and Falls Creek are not significantly different. The deficits
at RR 962 and Falls Creek are significantly higher than at either of the upstream stations.
Table 15 contains the ANOVA statistics, while a bar graph of the average deficits is
shown in Figure 4.
2
1.5
1
0.5
0
0.5
1
RR 1320 Johnson City RM 962 Falls Creek
D
O
D
e
fi
c
i
t (m
g
/
L
)
Raw Data Time Corrected
Figure 4 Average Oxygen Deficits on the Pedernales
The ANOVA analysis also was performed on the oxygen deficit data with a correction
for sampling time. The data at each site was normalized to a common sampling time of
noon. The test statistics for the normalized data shown in Table 16 indicate a more
significant spatial trend than the raw data. The average value at each site based on a
common sampling time is also shown in Figure 4.
14
Conclusions
Dissolved oxygen data from the Pedernales River collected between 1984 and 1997
indicate no significant longterm trends; however, the identification of changes in the
dissolved oxygen concentrations has been hampered by systematic changes in the way
the data have been collected. It is interesting to note, however, that 7 of the 8 highest
oxygen deficits recorded on the Pedernales were measured during 1984. The data do
indicate a trend of increasing oxygen deficit between Johnson City and the river segment
boundary at Falls Creek. The dissolved oxygen conditions in the river are generally very
good, even at the sites with higher deficits.
The large dissolved oxygen surplus measured at Johnson City could indicate a potential
problem area. Large surpluses can be associated with algal blooms, which produce
oxygen during the day via photosynthesis. Conversely, algal blooms can result in
extremely low oxygen concentrations at night. Consequently, it is important to identify
the reason for the high daytime readings at this site.
Specific Conductivity
Summary Statistics
The summary statistics for all the specific conductance data are shown in Table 2.
Table 2 Summary Statistics for Specific Conductivity
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/84 ? 10/97 2/84  10/97 4/84 ? 10/97 2/84 ? 5/90
# of Samples 114 73 113 72
Average Sp. Cond 682 648 540 553
Median Sp. Cond 690 623 546 546
Std Deviation 128 153 98 109
15
Trend Analysis
A temporal trend analysis was performed on the data set for each of the four monitoring
sites. At two of the sites, the conductance was highly correlated with river discharge as
measured at Johnson City. Consequently, a multiple linear regression was performed
using date and flow as the independent variables. The regression statistics for each of the
sites are shown in Table 17 through Table 20.
The regression equations indicate no significant temporal trend at Falls Creek and RM
962; however, Johnson City and RR 1320 sites both showed improvements in water
quality during the monitoring period. This trend is driven mainly by very high
conductance readings during the drought of 1984.
The data from Johnson City and RR 1320 were then analyzed using the MannKendall
test. This test confirms the downward trend in conductance at RR 1320, with a Z statistic
of 2.39 indicating a probability of less than 0.008 that the trend could have occurred by
chance. The analysis indicated no significant statistical relationship between date and
conductance at Johnson City, where the Z statistic was 0.76 indicating a probability of
0.22 that the differences are the result of random fluctuations. A plot of the data
collected at RR 1320 is shown in Figure 5.
An ANOVA test for spatial variation in conductance was conducted using the data from
the four monitoring sites. The results of the test are shown in Table 21, which indicates
that there is a significant spatial trend. The mean concentrations for the four sites are
shown graphically in Figure 6 where the trend towards decreasing concentrations
downstream is apparent.
16
y = 0.0194x + 1317.9
R
2
= 0.0474
0
200
400
600
800
1000
1200
2/18/82 11/14/84 8/11/87 5/7/90 1/31/93 10/28/95 7/24/98
Date
S
p
e
c
i
f
i
c
C
o
nduc
t
a
nc
e
(
mh
o
s
/
c
m)
Figure 5 Specific Conductance at RR 1320
0
100
200
300
400
500
600
700
800
RR 1320 Johnson City RM 962 Falls Creek
Location
S
p
eci
f
i
c C
onduct
a
nce
Figure 6 Comparison of Mean Specific Conductance
17
Conclusions
Conductance is clearly related to river discharge with higher readings occurring during
low flow periods. This is a common relationship, since low flows are mainly created by
groundwater inflows, which are generally higher in dissolved solids than storm runoff.
Only one site, RR1320, exhibited a statistically significant trend in specific conductance;
however, there is a strong spatial trend in dissolved solids. The readings are highest at
the upstream site and gradually decline to near the RM 962 site. This is likely the result
of dilution by the dissolved solids concentrations by inflows between RR 1320 and RM
962. The high dissolved solids concentrations upstream may be the result of natural
factors, but could also be due in part to human activities. High dissolved solids
concentrations are often encountered in agricultural areas and can be caused by irrigation
return flows. Further investigation is warranted to identify the causes, since total
dissolved solids are listed as a constituent of possible concern in the LCRA Water
Quality Assessment.
Chloride
Summary Statistics
Chloride is listed as a constituent of possible concern in the 1994 LCRA water quality
assessment, which indicates that a concentration of 105 mg/L is considered a problem
level. The summary data shown in Table 3 shows that the average concentrations at all
four sites is well below this value.
Table 3 Summary Statistics for Chloride
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 96 72 23 73
Average (mg/L) 66.2 62.5 37.3 40.7
Median (mg/L) 64.5 54 37 39
Std Deviation 22.8 32.3 11.2 20.5
18
Trend Analysis
Multiple linear regression was used initially to identify possible trends in the chloride
data. The independent variables were selected as date and flow rate to account for higher
salinity, which commonly is associated with low flow conditions. The regression
statistics, which are shown in Table 22 through Table 25, indicate a trend of decreasing
concentrations at RR 1320, Johnson City, and RM 962. The data at these sites was then
subjected to the MannKendall test. This test confirmed the significance of the trend at
RR 1320 and RM 962, with Z statistics of 1.94 and 2.19 respectively, which corresponds
to confidence levels of 0.027 and 0.014. For Johnson City, the calculated Z statistic was
0.57, which corresponds to a P value of 0.28. The data for RR 1320 and RM 962 are
plotted in Figure 7 and Figure 8.
y = 0.0047x + 218.08
R
2
= 0.0701
0
20
40
60
80
100
120
140
2/18/82 11/14/84 8/11/87 5/7/90 1/31/93 10/28/95 7/24/98
Date
C
h
l
o
r
i
de (
m
g/
L)
Figure 7 Chloride Concentrations at RR 1320
19
y = 0.0057x + 232.64
R
2
= 0.1217
0
10
20
30
40
50
60
70
1/3/90 1/3/92 1/2/94 1/2/96 1/1/98
Date
C
h
l
o
r
i
d
e
(
m
g/
L
)
Figure 8 Chloride Concentrations at RM 962
An ANOVA test was performed on the pooled data from all four sites to determine
whether spatial trends were present. The test statistics, which are shown in Table 26,
indicate that a significant decrease in concentration occurs between Johnson City and RM
962. This decrease is evident in the graph shown in Figure 9.
Since chloride concentrations at many of the sites are significantly correlated with flow
rate, the concentrations were normalized to the Pedernales median flow rate, 50 cfs. The
ANOVA analysis was then performed on the normalized data. The normalized data
indicate an even more statistically significant spatial trend. The averages for the
normalized data set are also shown in Figure 9.
20
0
10
20
30
40
50
60
70
80
RR 1320 Johnson City RM 962 Falls Creek
C
h
l
o
r
i
de (
m
g/
L)
Raw Data Flow Corrected
Figure 9 Average Chloride Concentrations
Sulfate
Summary Statistics
Sulfate is another constituent that the LCRA has identified of being of possible concerns
because of high concentrations. The critical concentration for this constituent is 50 mg/L.
The summary statistics for the four sites are shown in Table 4. The average values are
much lower than the critical concentration.
Trend Analysis
Multiple linear regression, with date and flow as the independent variables, was used to
identify temporal trends at each site. The regression statistics are shown in Table 28
through Table 31. According to the regression analysis, the only site with a significant
temporal trend in RR 1320. The data from this site was also tested for significance using
21
the MannKendall test. The Z statistic was 2.59, which corresponds to a P value of
0.005, confirming the temporal trend. The data from RR 1320 is shown in Figure 10.
Table 4 Summary Statistics for Sulfate
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 95 72 23 73
Average (mg/L) 32.2 36.6 26.0 27.4
Median (mg/L) 33 33 26 27
Std Deviation 8.6 28.0 6.4 11.2
y = 0.0017x + 86.548
R
2
= 0.0636
0
10
20
30
40
50
60
1/4/83 1/3/86 1/2/89 1/2/92 1/1/95 12/31/97
Date
S
u
l
f
at
e
(
m
g/
L
)
Figure 10 Sulfate Concentrations at RR 1320
The ANOVA analysis was then used to determine whether there were significant
differences among the sites. The ANOVA statistics are shown in Table 32 and they
indicate that the concentrations at Johnson City are significantly higher than at the two
downstream monitoring stations. The concentrations at RR 1320 are also higher than the
22
downstream sites; however, the difference is not significant. The average concentrations
at the sites are shown in Figure 11.
The ANOVA analysis was also performed with data normalized to the median flow rate
of 50 cfs. This data set also had a significant spatial variation, which had a higher degree
of confidence than the raw data. The average values for the normalized data are also
presented in Figure 10.
0
5
10
15
20
25
30
35
40
45
RR 1320 Johnson City RM 962 Falls Creek
S
u
l
f
at
e (
m
g/
L)
Raw Data Flow Corrected
Figure 11 Average Sulfate Concentrations
Nitrate plus Nitrite
Summary Statistics
Nutrients are listed as a constituent of concern in the LCRA 1994 Water Quality
Assessment and the nitrogen concentrations are relatively high compared to many surface
water bodies. The average concentrations and other summary statistics for the four
monitoring sites are shown in Table 5. The average values are much higher than the
23
median values compared to other constituents indicating that the underlying distribution
is skewed.
Table 5 Summary Statistics for Nitrate plus Nitrite
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8410/95 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 92 72 13 73
Average (mg/L) 0.36 0.28 0.21 0.19
Median (mg/L) 0.18 0.095 0.16 0.08
Std Deviation 0.43 0.32 0.23 0.21
Trend Analysis
Multiple linear regression, using flow and date as the independent variables, was used to
test for a temporal trend at each of the monitoring sites. The regression statistics for each
of the sites are shown in Table 34 through Table 37. The only site with a statistically
significant trend was RR 1320, which showed a decrease in concentration through time.
The data at this site was then analyzed using the MannKendall test. The calculated Z
statistic was 1.19, which corresponds to a P value of 0.117 and indicates that the trend is
not statistically significant.
An ANOVA analysis was performed on the data to determine whether there were
differences among the sites and the results are shown in Table 38. The analysis indicated
a significant difference at the 0.009 confidence level. A plot of the average concentration
at each site is shown in Figure 12 and the trend to decreasing concentrations downstream
is readily apparent.
This reduction in concentration could be the result of uptake of the nutrients in the river
or dilution by inflows with lower nitrogen concentrations. The fact that specific
conductance shows this same trend suggests that the reduction is due primarily to
24
dilution. The higher concentrations upstream could be caused by naturally high levels of
nitrogen in groundwater contributing baseflow to the river, use of fertilizers in
agricultural areas, or discharge from wastewater treatment plants.
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
RR 1320 Johnson City RM 962 Falls Creek
Site
N
i
t
r
at
e +
N
i
t
r
i
t
e (
m
g/
L)
Figure 12 Average Nitrate plus Nitrite Concentrations
Total Kjeldahl Nitrogen
Summary Statistics
Another important for of nitrogen is total Kjeldahl nitrogen (TKN), which includes
ammonia plus organic nitrogen. The summary statistics for each of the sites is shown in
Table 6.
Trend Analysis
Multiple linear regression, using flow and date as the independent variables, was used to
test for a temporal trend at each of the monitoring sites. The regression statistics for each
25
of the sites are shown in Table 39 through Table 42. The regression analysis indicates
that the only significant trend occurs at Johnson City, where the concentrations are
decreasing with time (Figure 13). The data from Johnson City were then examined with
the MannKendall test. The Z statistic for this test was 1.61, which corresponds to a P
value of 0.054, and indicates that the slope is not statistically significant at the 95%
confidence level.
Table 6 Summary Statistics for Total Kjeldahl Nitrogen
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 96 72 23 73
Average (mg/L) 0.58 0.69 0.53 0.73
Median (mg/L) 0.49 0.535 0.277 0.54
Std Deviation 0.44 0.50 0.75 0.79
y = 0.0002x + 8.271
R
2
= 0.0993
0
0.5
1
1.5
2
2.5
3
3.5
7/3/83 11/14/84 3/29/86 8/11/87 12/23/88 5/7/90 9/19/91
Date
TK
N (
m
g
/
L)
Figure 13 Total Kjeldahl Nitrogen at Johnson City
26
An ANOVA test was conducted on the TKN data and the results are shown in Table 43.
Although there is a general trend towards decreasing concentrations in the downstream
direction, the differences are not statistically significant (P = 0.354).
Ammonia
Summary Statistics
Ammonia can be toxic to aquatic life at low concentrations and therefore is a critical
water quality parameter. The high dissolved oxygen concentrations in the Pedernales are
oxidize the ammonia to nitrate, reducing the concentration of ammonia. The average
concentrations and other summary statistics are shown in Table 7.
Table 7 Summary Statistics for Ammonia
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 94 72 23 73
Average (mg/L) 0.054 0.070 0.058 0.069
Median (mg/L) 0.02 0.035 0.04 0.03
Std Deviation 0.10 0.117 0.062 0.097
Trend Analysis
Multiple linear regression, with flow and date as the independent variables, was used to
detect the presence of temporal trends. The regression statistics shown in Table 44
through Table 47 indicated no significant trend at any of the sites.
An ANOVA analysis was used to detect differences in ammonia concentrations among
the sites. The ANOVA statistics, which are shown in Table 48, indicate no significant
differences in concentration.
27
Total Phosphorus
Summary Statistics
The summary statistics for phosphorus are shown in Table 8 and they indicated low
median concentrations at all monitoring sites.
Table 8 Summary Statistics for Total Phosphorus
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 96 72 23 73
Average (mg/L) 0.046 0.148 0.071 0.033
Median (mg/L) 0.02 0.05 0.03 0.02
Std Deviation 0.08 0.61 0.141 0.035
Trend Analysis
Multiple linear regression, using flow and date as the variables indicated a significant
trend only at Johnson City. The regression statistics for this analysis are shown in Table
49 through Table 52. The MannKendall test was performed on the data from Johnson
City to confirm the trend. The value of the Z statistic was 0.81, which corresponds to a P
value of 0.209, indicating no significant trend.
Total Organic Carbon
Summary Statistics
The summary statistics shown in Table 9 demonstrate the relatively low concentrations of
Total Organic Carbon (TOC) present in the Pedernales River.
28
Table 9 Summary Statistics for Total Organic Carbon
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 96 72 23 73
Average (mg/L) 3.69 4.02 3.12 3.29
Median (mg/L) 3 3 3 3
Std Deviation 1.81 2.40 1.34 1.51
Trend Analysis
Multiple linear regression, using date and flow as the independent variables, indicates
that the only statistically significant temporal occurs at Johnson City. The statistics for
the linear regression test are shown in Table 54 through Table 57. The data were
analyzed with the MannKendall test to confirm the trend. The Z statistic for this test
was 1.01, which corresponds to a P value of 0.156, indicating that the slope is not
significant.
The ANOVA analysis indicated no significant differences in concentration among the
stations. The ANOVA statistics are shown in Table 58.
Fecal Coliform
Summary Statistics
The summary statistics for the fecal coliform data at the four monitoring sites are shown
in Table 10. The large difference between the average and median values for all the sites
indicates that the underlying distribution is not normal. Consequently, the median is a
better representation of the normal conditions in the river than the average value. All of
the median values are well below standards for contact recreation.
29
Table 10 Summary Statistics for Fecal Coliform Data
Parameter RR 1320 Johnson City RM 962 Falls Creek
Period of Record 2/8412/96 2/848/90 10/9012/96 2/84 ? 5/90
# of Samples 96 72 23 73
Average Count/100 ml 280 332 311 328
Median Count/100 ml 43 75 36 16
Std Deviation 680 1190 803 1698
Trend Analysis
Multiple linear regression was used to identify significant temporal trends in the water
quality data. The independent variables were time and flow rate. Flow rate was selected
to try to distinguish between conditions of baseflow and storm runoff; however, flow was
not statistically significant at any of the sites. The regression analysis indicated that there
was no temporal trend at any of the sites. The regression statistics for fecal coliform at
the four sites are shown in Table 59 through Table 62.
ANOVA test for difference in Fecal Coliform means for all sites on the Pedernales
indicate no statistically significant spatial trend. The ANOVA statistics are shown in
Table 63.
30
Conclusions and Recommendations
The LCRA water quality sampling program for the Pedernales River has focused
primarily on the quality of ambient, baseflow conditions. Of the 264 samples collected
and analyzed for Fecal coliform and other common constituents, only 18 (7%) were
collected during peak flow conditions caused by stormwater runoff. The current
sampling program is best suited for identifying long term changes in water quality caused
by continuous point source discharges and by significant changes in groundwater quality.
Reduction in groundwater quality resulting from land use changes would have to be
widespread or very severe to cause statistically significant changes in the quality of the
Pedernales and other rivers in the LCRA service area. In general, agricultural land uses
have a greater impact on groundwater quality than urban land uses. Consequently, one
would expect the most commonly identified impacts to be associated with agricultural
activities and be reflected in higher concentrations of dissolved solids and nutrients.
Urbanization of a watershed generally affects the water quality of the river during
ambient conditions by increased discharges from wastewater treatment facilities. These
discharges are often associated with a reduction in dissolved oxygen concentrations.
Urbanization also can result in reduction of baseflow because the increased impervious
cover prevents rainfall from infiltrating; however, the urban area would have to cover a
large portion of the watershed for the changes to be obvious.
Analysis of the LCRA water quality database for the Pedernales River indicates that
several constituents exhibit a significant spatial trend. All of the constituents that varied
had higher concentrations upstream than down. These constituents are dissolved oxygen,
chloride, sulfate, nitrate plus nitrite, and specific conductance. The monitoring data are
not sufficient for identifying the reasons for these changes, which may be natural,
manmade, or a combination of the two.
The higher levels of dissolved solids, nitrogen, and other ionic species may be derived
from groundwater inflow to the river. Groundwater often contains higher concentrations
31
of these constituents than surface water. Elevated concentrations of these constituents
also are associated with agricultural activities. Irrigation return flows have higher levels
of dissolved solids and can carry nutrients derived from fertilizers as well as agricultural
pesticides. Measurements of pesticide concentrations were not included in the
monitoring program. Determination of the causes of the higher concentrations should be
the focus of future studies, because dissolved solids, chloride, and sulfate are all listed as
parameters of possible concern in the 1994 LCRA water quality assessment (LCRA,
1994). Concentrations of these constituents are currently below levels that caused them
to be flagged in the 1994 report.
Temporal trends were most evident at the upstream monitoring station at RR 1320, which
generally had the longest period of record. Constituents with significant temporal trends
include specific conductance, chloride, and sulfate. The concentrations of each of these
showed a reduction with time. The monitoring site at RM 962 showed a single parameter
with a temporal trend, chloride, which also had declining concentrations. There was no
significant temporal trend for any constituent at the Johnson City and Falls Creek sites.
These reductions in concentration may be the result of much higher than average rainfall
in 1991 and 1992. Rainfall generally has very low concentrations of these constituents,
causing a dilution in groundwater, which contributes baseflow to the river, as well as in
the river itself through increased surface runoff.
The water quality of the Pedernales River can be characterized as very good and
supportive of all designated beneficial uses. Current concentrations of all monitored
water quality constituents are generally below levels that would be cause for concern or
result in the listing of this river segment as impaired. In addition, this data set indicates
that the concentrations of the analyzed constituents at each monitoring site are relatively
constant or improving. There is no immediate concern that changes in land use or other
human activities threaten the water quality of the Pedernales River; however, the source
of higher concentrations of dissolved solids and nutrients in the upstream reach of the
river should be identified. The change from undeveloped to agricultural land use
32
occurred many years before the beginning of any water quality monitoring programs and
may be responsible for higher constituent concentrations in this portion of the watershed.
A consistent sampling protocol is required to reduce the noise inherent in the dissolved
oxygen and other environmental data. For dissolved oxygen, important variables in the
sampling program are collection time and sampling depth. In order to avoid a situation
where sampling time changes systematically during the monitoring period or where
sampling times differ systematically between monitoring stations, collection times should
be randomized.
Despite the generally high quality of the Pedernales River water, eight fish kill episodes
have been reported in the river, including five since 1990. Approximately half of the
kills have been the result of illegal dumping of toxic substances. These episodes
highlight the importance of an effective public education/outreach program. Such a
program can make citizens more aware of the environmental impacts of improper
disposal of waste materials. It is especially important to target owners of small
businesses, which often need to dispose of significant quantities of spent solvents,
lubricants, paint and other toxic materials.
The remaining fish kills were the result of wastewater treatment plant (WWTP)
discharges to the Pedernales near Johnson City, resulting in low dissolved oxygen
concentrations. Conventional water quality monitoring programs are not effective for
identifying episodic events resulting from equipment malfunction or other causes and
samples collected within a few weeks of the events did not have particularly low
dissolved oxygen concentrations. Wastewater discharges may be a factor in the trend of
decreasing dissolved oxygen concentrations from upstream to downstream. The number
of fish kills related to wastewater discharges suggests that a review of the permit
requirements and adequacy of the Johnson City WWTP should be a high priority.
33
Bibliography
Gilbert, R.O., 1987, Statistical Methods for Environmental Pollution Monitoring, Van
Nostrand Reinhold Company, New York.
LCRA, 1994, 1994 Water Quality Assessment of the Colorado River Basin.
Minitab Inc, 1998, Minitab for Windows: Release 12, State College, PA.
34
Appendix A
Table 11 Regression Statistics for Oxygen Deficit at Falls Creek
Predictor Coef StDev T P
Constant 16.981 6.635 2.56 0.013
DATE 0.0003847 0.0002371 1.62 0.109
Time 0.3322 0.1484 2.24 0.028
S = 1.027 RSq = 21.0% RSq(adj) = 18.8%
Analysis of Variance
Source DF SS MS F P
Regression 2 19.415 9.708 9.20 0.000
Residual Error 69 72.836 1.056
Total 71 92.252
Source DF Seq SS
DATE 1 14.125
Time 1 5.290
Table 12 Regression Statistics for Oxygen Deficit at RR 1320
Predictor Coef StDev T P
Constant 0.018 2.725 0.01 0.995
DATE 0.00012079 0.00006925 1.74 0.084
time 0.34966 0.08567 4.08 0.000
Season 0.04620 0.08257 0.56 0.577
S = 0.9904 RSq = 20.3% RSq(adj) = 18.1%
Analysis of Variance
Source DF SS MS F P
Regression 3 27.1926 9.0642 9.24 0.000
Residual Error 109 106.9077 0.9808
Total 112 134.1003
Source DF Seq SS
DATE 1 10.5199
Time 1 16.3656
Season 1 0.3071
35
Table 13 Regression Statistics for Oxygen Deficit at Johnson City
Predictor Coef StDev T P
Constant 7.917 6.192 1.28 0.205
DATE 0.0000683 0.0001923 0.36 0.724
Time_(d) 0.6022 0.1711 3.52 0.001
S = 1.289 RSq = 15.6% RSq(adj) = 13.2%
Analysis of Variance
Source DF SS MS F P
Regression 2 21.445 10.722 6.45 0.003
Residual Error 70 116.351 1.662
Total 72 137.796
Source DF Seq SS
DATE 1 0.850
Time_(d) 1 20.595
Table 14 Regression Statistics for Oxygen Deficit at Hammett?s Crossing
Predictor Coef StDev T P
Constant 0.307 2.384 0.13 0.898
DATE 0.00004533 0.00006302 0.72 0.474
Time_d 0.11427 0.03820 2.99 0.003
S = 0.7344 RSq = 15.7% RSq(adj) = 14.2%
Analysis of Variance
Source DF SS MS F P
Regression 2 11.0656 5.5328 10.26 0.000
Residual Error 110 59.3270 0.5393
Total 112 70.3927
Source DF Seq SS
DATE 1 6.2402
Time_d 1 4.8254
36
Table 15 ANOVA Statistics for Oxygen Deficit
Source DF SS MS F P
Factor 3 43.96 14.65 10.07 0.000
Error 372 541.44 1.46
Total 375 585.40
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++

Falls Cr 73 0.741 1.140 (*)
RM 962 114 0.546 1.237 (*)
Johnson 74 0.202 1.383 (*)
RR 1320 115 0.108 1.089 (*)
+++

Pooled StDev = 1.206 0.00 0.50 1.00
Table 16 ANOVA Statistics for DO Corrected for Time
Analysis of Variance
Source DF SS MS F P
Factor 3 236.463 78.821 79.92 0.000
Error 367 361.956 0.986
Total 370 598.418
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev ++++

1320noon 113 0.3900 0.9918 (*)
johnoon 73 1.4900 1.2724 (*)
962noon 113 0.4200 0.7295 (*)
fcnoon 72 0.7800 1.0320 (*)
++++

Pooled StDev = 0.9931 1.60 0.80 0.00 0.80
37
Table 17 Regression Statistics for Specific Conductance at Falls Creek
Predictor Coef StDev T P
Constant 383.0 642.3 0.60 0.553
DATE 0.00556 0.02021 0.28 0.784
Flow (cf 0.03527 0.02589 1.36 0.178
S = 108.6 RSq = 2.7% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 22461 11231 0.95 0.391
Residual Error 69 813739 11793
Total 71 836200
Source DF Seq SS
DATE 1 583
Flow (cf 1 21878
Table 18 Regression Statistics for Specific Conductance at Johnson City
The regression equation is
CONDUCTANCE (UMHOS/CM @ 25C) = 2102  0.0446 DATE  0.240 Flow (cfs)
Predictor Coef StDev T P
Constant 2101.7 680.9 3.09 0.003
DATE 0.04465 0.02135 2.09 0.040
Flow (cf 0.24019 0.08798 2.73 0.008
S = 143.8 RSq = 14.1% RSq(adj) = 11.6%
Analysis of Variance
Source DF SS MS F P
Regression 2 237438 118719 5.74 0.005
Residual Error 70 1446592 20666
Total 72 1684030
Source DF Seq SS
DATE 1 83408
Flow (cf 1 154031
38
Table 19 Regression Statistics for Specific Conductance at Hammett?s Crossing
Predictor Coef StDev T P
Constant 493.6 217.3 2.27 0.025
DATE 0.001824 0.006636 0.27 0.784
Flow (cf 0.07132 0.03288 2.17 0.032
S = 97.03 RSq = 4.1% RSq(adj) = 2.4%
Analysis of Variance
Source DF SS MS F P
Regression 2 44381 22190 2.36 0.100
Residual Error 109 1026228 9415
Total 111 1070608
Source DF Seq SS
DATE 1 87
Flow (cf 1 44294
Table 20 Regression Statistics for Specific Conductance at RR 1320
Predictor Coef StDev T P
Constant 1361.1 268.1 5.08 0.000
DATE 0.020420 0.008190 2.49 0.014
Flow (cf 0.04861 0.04700 1.03 0.303
S = 123.4 RSq = 6.8% RSq(adj) = 5.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 121217 60608 3.98 0.021
Residual Error 110 1673716 15216
Total 112 1794933
Source DF Seq SS
DATE 1 104944
Flow (cf 1 16273
Table 21 ANOVA Statistics for Specific Conductance
39
Source DF SS MS F P
Factor 3 1483597 494532 33.32 0.000
Error 368 5461561 14841
Total 371 6945158
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev ++++

RR 1320 114 682.1 127.8 (*)
Johnson 73 647.8 152.9 (*)
RM 962 113 539.9 98.8 (*)
Falls C 72 553.0 108.5 (*)
++++

Pooled StDev = 121.8 540 600 660 720
Table 22 Regression Statistics for Chloride at RR 1320
The regression equation is
CHLORIDE (MG/L AS CL) = 229  0.00473 DATE  0.0659 FLOW
Predictor Coef StDev T P
Constant 228.55 46.73 4.89 0.000
DATE 0.004730 0.001438 3.29 0.001
FLOW 0.065859 0.009561 6.89 0.000
S = 18.10 RSq = 38.4% RSq(adj) = 37.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 19001.9 9501.0 29.02 0.000
Residual Error 93 30451.7 327.4
Total 95 49453.6
Source DF Seq SS
DATE 1 3465.0
FLOW 1 15536.9
Table 23 Regression Statistics for Chloride at Johnson City
The regression equation is
40
CHLORIDE (MG/L AS CL) = 444  0.0117 DATE  0.0765 FLOW
Predictor Coef StDev T P
Constant 444.3 162.1 2.74 0.008
DATE 0.011685 0.005095 2.29 0.025
FLOW 0.07649 0.01722 4.44 0.000
S = 28.10 RSq = 26.7% RSq(adj) = 24.5%
Analysis of Variance
Source DF SS MS F P
Regression 2 19817.9 9909.0 12.55 0.000
Residual Error 69 54488.1 789.7
Total 71 74306.0
Source DF Seq SS
DATE 1 4241.9
FLOW 1 15576.0
Table 24 Regression Statistics for Chloride at RM 962
The regression equation is
CHLORIDE (MG/L AS CL) = 272  0.00670 DATE  0.0372 FLOW
Predictor Coef StDev T P
Constant 271.87 96.90 2.81 0.011
DATE 0.006700 0.002814 2.38 0.027
FLOW 0.03722 0.01189 3.13 0.005
S = 9.021 RSq = 41.1% RSq(adj) = 35.2%
Analysis of Variance
Source DF SS MS F P
Regression 2 1134.01 567.00 6.97 0.005
Residual Error 20 1627.52 81.38
Total 22 2761.53
Source DF Seq SS
DATE 1 336.18
FLOW 1 797.83
Table 25 Regression Statistics for Chloride at Falls Creek
41
The regression equation is
CHLORIDE (MG/L AS CL) =  35 + 0.00244 DATE  0.0109 FLOW
Predictor Coef StDev T P
Constant 34.9 117.4 0.30 0.767
DATE 0.002444 0.003696 0.66 0.511
FLOW 0.010858 0.004771 2.28 0.026
S = 20.01 RSq = 7.3% RSq(adj) = 4.7%
Analysis of Variance
Source DF SS MS F P
Regression 2 2207.6 1103.8 2.76 0.070
Residual Error 70 28033.0 400.5
Total 72 30240.6
Source DF Seq SS
DATE 1 133.1
FLOW 1 2074.5
Table 26 ANOVA Statistics for Chloride
Analysis of Variance for CHLORIDE
Source DF SS MS F P
STATION 3 38190 12730 21.11 0.000
Error 260 156762 603
Total 263 194952
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++
15 73 40.70 20.49 (*)
50 23 37.37 11.20 (*)
75 72 62.51 32.35 (*)
150 96 66.26 22.82 (*)
+++
Pooled StDev = 24.55 36 48 60
Table 27 ANOVA Statistics for Chloride Normalized for Flow
42
Analysis of Variance
Source DF SS MS F P
Factor 3 49378 16459 34.87 0.000
Error 264 124602 472
Total 267 173980
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev ++++

150 97 71.70 18.92 (*
75 _ 73 68.66 28.74 (*)
50 24 41.20 9.74 (*)
15 74 42.70 19.79 (*)
++++

Pooled StDev = 21.73 36 48 60 72
Table 28 Regression Statistics for Sulfate at RR 1320
The regression equation is
SULFATE (MG/L AS SO4) = 89.7  0.00169 DATE  0.0189 FLOW
95 cases used 1 cases contain missing values
Predictor Coef StDev T P
Constant 89.74 19.50 4.60 0.000
DATE 0.0016945 0.0005998 2.83 0.006
FLOW 0.018911 0.003970 4.76 0.000
S = 7.511 RSq = 24.9% RSq(adj) = 23.3%
Analysis of Variance
Source DF SS MS F P
Regression 2 1720.20 860.10 15.24 0.000
Residual Error 92 5190.71 56.42
Total 94 6910.91
Source DF Seq SS
DATE 1 439.68
FLOW 1 1280.52
Table 29 Regression Statistics for Sulfate at Johnson City
43
The regression equation is
SULFATE (MG/L AS SO4) =  153 + 0.00607 DATE  0.0283 FLOW
Predictor Coef StDev T P
Constant 152.9 158.9 0.96 0.339
DATE 0.006073 0.004993 1.22 0.228
FLOW 0.02833 0.01688 1.68 0.098
S = 27.54 RSq = 5.8% RSq(adj) = 3.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 3242.6 1621.3 2.14 0.126
Residual Error 69 52330.3 758.4
Total 71 55572.9
Source DF Seq SS
DATE 1 1105.1
FLOW 1 2137.5
Table 30 Regression Statistics for Sulfate at RM 962
The regression equation is
SULFATE (MG/L AS SO4) = 101  0.00214 DATE  0.0155 FLOW
Predictor Coef StDev T P
Constant 101.16 64.59 1.57 0.133
DATE 0.002136 0.001876 1.14 0.268
FLOW 0.015491 0.007921 1.96 0.065
S = 6.012 RSq = 18.9% RSq(adj) = 10.8%
Analysis of Variance
Source DF SS MS F P
Regression 2 168.76 84.38 2.33 0.123
Residual Error 20 722.94 36.15
Total 22 891.70
Source DF Seq SS
DATE 1 30.52
FLOW 1 138.23
Table 31 Regression Statistics for Sulfate at Falls Creek
44
The regression equation is
SULFATE (MG/L AS SO4) = 51.7  0.00072 DATE  0.00653 FLOW
Predictor Coef StDev T P
Constant 51.66 63.75 0.81 0.420
DATE 0.000725 0.002006 0.36 0.719
FLOW 0.006533 0.002590 2.52 0.014
S = 10.86 RSq = 8.6% RSq(adj) = 6.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 775.4 387.7 3.29 0.043
Residual Error 70 8260.1 118.0
Total 72 9035.5
Source DF Seq SS
DATE 1 24.5
FLOW 1 750.8
Table 32 ANOVA Statistics for Sulfate
Analysis of Variance for SULFATE
Source DF SS MS F P
STATION 3 3863 1288 4.61 0.004
Error 259 72411 280
Total 262 76274
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++
15 73 27.40 11.20 (*)
50 23 25.99 6.37 (*)
75 72 36.63 27.98 (*)
150 95 32.19 8.57 (*)
+++
Pooled StDev = 16.72 24.0 30.0 36.0
* NOTE * N missing = 1
Table 33 ANOVA Statistics for Sulfate Normalized for Flow
Analysis of Variance
Source DF SS MS F P
Factor 3 4621 1540 5.85 0.001
45
Error 259 68138 263
Total 262 72759
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++
+
150 _ 95 33.70 7.75 (*)
75 _ 72 38.89 27.44 (*
50 23 27.60 5.92 (*)
15 73 28.60 10.72 (*)
+++
+
Pooled StDev = 16.22 24.0 30.0 36.0 42.0
Table 34 Regression Statistics for Nitrate plus Nitrite at RR 1320
The regression equation is
NITRITE PLUS NITRATE, TOTAL 1 D = 2.79 0.000077 DATE +0.000511 FLOW
91 cases used 5 cases contain missing values
Predictor Coef StDev T P
Constant 2.787 1.236 2.25 0.027
DATE 0.00007706 0.00003825 2.01 0.047
FLOW 0.0005113 0.0002224 2.30 0.024
S = 0.4189 RSq = 9.3% RSq(adj) = 7.2%
Analysis of Variance
Source DF SS MS F P
Regression 2 1.5787 0.7893 4.50 0.014
Residual Error 88 15.4414 0.1755
Total 90 17.0201
Source DF Seq SS
DATE 1 0.6514
FLOW 1 0.9273
Table 35 Regression Statistics for Nitrate plus Nitrite at Johnson City
The regression equation is
46
NITRITE PLUS NITRATE, TOTAL 1 D = 0.37 0.000005 DATE +0.000490 FLOW
Predictor Coef StDev T P
Constant 0.374 1.766 0.21 0.833
DATE 0.00000501 0.00005549 0.09 0.928
FLOW 0.0004897 0.0001876 2.61 0.011
S = 0.3061 RSq = 9.0% RSq(adj) = 6.4%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.63893 0.31946 3.41 0.039
Residual Error 69 6.46367 0.09368
Total 71 7.10260
Source DF Seq SS
DATE 1 0.00054
FLOW 1 0.63839
Table 36 Regression Statistics for Nitrate plus Nitrite at RM 962
The regression equation is
NITRITE PLUS NITRATE, TOTAL 1 D =  5.19 +0.000159 DATE  0.00076 FLOW
13 cases used 10 cases contain missing values
Predictor Coef StDev T P
Constant 5.187 4.018 1.29 0.226
DATE 0.0001586 0.0001176 1.35 0.207
FLOW 0.000763 0.001267 0.60 0.561
S = 0.2317 RSq = 15.5% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.09828 0.04914 0.92 0.431
Residual Error 10 0.53671 0.05367
Total 12 0.63499
Source DF Seq SS
DATE 1 0.07885
FLOW 1 0.01943
Table 37 Regression Statistics for Nitrate plus Nitrite at Falls Creek
The regression equation is
NITRITE PLUS NITRATE, TOTAL 1 D =  0.07 +0.000008 DATE +0.000090 FLOW
47
Predictor Coef StDev T P
Constant 0.066 1.192 0.06 0.956
DATE 0.00000751 0.00003752 0.20 0.842
FLOW 0.00009006 0.00004844 1.86 0.067
S = 0.2032 RSq = 4.8% RSq(adj) = 2.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.14571 0.07285 1.76 0.179
Residual Error 70 2.88967 0.04128
Total 72 3.03538
Source DF Seq SS
DATE 1 0.00301
FLOW 1 0.14270
Table 38 ANOVA Statistics for Nitrate plus Nitrite
Analysis of Variance for NITRITE + NITRATE
Source DF SS MS F P
STATION 3 1.348 0.449 3.96 0.009
Error 245 27.793 0.113
Total 248 29.141
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++

15 73 0.1895 0.2053 (*)
50 13 0.2149 0.2300 (*)
75 72 0.2783 0.3163 (*)
150 91 0.3674 0.4349 (*)
+++

Pooled StDev = 0.3368 0.12 0.24 0.36
* NOTE * N missing = 15
Table 39 Regression Statistics for TKN at RR 1320
The regression equation is
NITROGEN, KJELDAHL, TOTAL, (MG/ = 1.00 0.000013 DATE +0.000147 FLOW
95 cases used 1 cases contain missing values
Predictor Coef StDev T P
48
Constant 0.995 1.163 0.86 0.394
DATE 0.00001310 0.00003584 0.37 0.716
FLOW 0.0001470 0.0002316 0.63 0.527
S = 0.4382 RSq = 0.6% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.1028 0.0514 0.27 0.766
Residual Error 92 17.6633 0.1920
Total 94 17.7661
Source DF Seq SS
DATE 1 0.0255
FLOW 1 0.0773
Table 40 Regression Statistics for TKN at Johnson City
The regression equation is
NITROGEN, KJELDAHL, TOTAL, (MG/ = 8.31 0.000238 DATE 0.000518 FLOW
Predictor Coef StDev T P
Constant 8.312 2.687 3.09 0.003
DATE 0.00023752 0.00008445 2.81 0.006
FLOW 0.0005184 0.0002854 1.82 0.074
S = 0.4657 RSq = 14.0% RSq(adj) = 11.5%
Analysis of Variance
Source DF SS MS F P
Regression 2 2.4437 1.2219 5.63 0.005
Residual Error 69 14.9671 0.2169
Total 71 17.4108
Source DF Seq SS
DATE 1 1.7282
FLOW 1 0.7155
Table 41 Regression Statistics for TKN at RM 962
The regression equation is
NITROGEN, KJELDAHL, TOTAL, (MG/ =  9.77 +0.000302 DATE  0.00025 FLOW
49
21 cases used 2 cases contain missing values
Predictor Coef StDev T P
Constant 9.765 9.506 1.03 0.318
DATE 0.0003024 0.0002771 1.09 0.289
FLOW 0.000252 0.001046 0.24 0.812
S = 0.7903 RSq = 6.7% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.8065 0.4032 0.65 0.536
Residual Error 18 11.2432 0.6246
Total 20 12.0497
Source DF Seq SS
DATE 1 0.7703
FLOW 1 0.0362
Table 42 Regression Statistics for TKN at Falls Creek
The regression equation is
NITROGEN, KJELDAHL, TOTAL, (MG/ = 7.45 0.000210 DATE 0.000112 FLOW
72 cases used 1 cases contain missing values
Predictor Coef StDev T P
Constant 7.445 4.660 1.60 0.115
DATE 0.0002102 0.0001466 1.43 0.156
FLOW 0.0001119 0.0001882 0.59 0.554
S = 0.7891 RSq = 3.5% RSq(adj) = 0.7%
Analysis of Variance
Source DF SS MS F P
Regression 2 1.5390 0.7695 1.24 0.297
Residual Error 69 42.9598 0.6226
Total 71 44.4988
Source DF Seq SS
DATE 1 1.3188
FLOW 1 0.2203
50
Table 43 ANOVA Statistics for TKN
Analysis of Variance for NITROGEN TKN
Source DF SS MS F P
STATION 3 1.172 0.391 1.09 0.354
Error 256 91.725 0.358
Total 259 92.898
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev ++++
15 72 0.7417 0.7917 (*)
50 21 0.5678 0.7762 (*)
75 72 0.6879 0.4952 (*)
150 95 0.5905 0.4347 (*)
++++
Pooled StDev = 0.5986 0.32 0.48 0.64 0.80
* NOTE * N missing = 4
Table 44 Regression Statistics for Ammonia at RR 1320
The regression equation is
NITROGEN, AMMONIA, TOTAL (MG/L =  0.192 +0.000008 DATE +0.000078 FLOW
78 cases used 18 cases contain missing values
Predictor Coef StDev T P
Constant 0.1921 0.2863 0.67 0.504
DATE 0.00000756 0.00000877 0.86 0.392
FLOW 0.00007808 0.00006656 1.17 0.244
S = 0.1035 RSq = 2.6% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.02153 0.01076 1.01 0.371
Residual Error 75 0.80314 0.01071
Total 77 0.82467
Source DF Seq SS
DATE 1 0.00679
FLOW 1 0.01474
Table 45 Regression Statistics for Ammonia at Johnson City
The regression equation is
51
NITROGEN, AMMONIA, TOTAL (MG/L = 1.19 0.000035 DATE 0.000055 FLOW
62 cases used 10 cases contain missing values
Predictor Coef StDev T P
Constant 1.1876 0.7517 1.58 0.119
DATE 0.00003457 0.00002359 1.47 0.148
FLOW 0.00005512 0.00007728 0.71 0.478
S = 0.1227 RSq = 4.3% RSq(adj) = 1.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.04001 0.02001 1.33 0.272
Residual Error 59 0.88756 0.01504
Total 61 0.92757
Source DF Seq SS
DATE 1 0.03236
FLOW 1 0.00765
Table 46 Regression Statistics for Ammonia at RM 962
The regression equation is
NITROGEN, AMMONIA, TOTAL (MG/L =  0.048 +0.000004 DATE 0.000080 FLOW
21 cases used 2 cases contain missing values
Predictor Coef StDev T P
Constant 0.0482 0.8562 0.06 0.956
DATE 0.00000351 0.00002475 0.14 0.889
FLOW 0.00008036 0.00008899 0.90 0.378
S = 0.06511 RSq = 5.0% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.004045 0.002023 0.48 0.628
Residual Error 18 0.076306 0.004239
Total 20 0.080351
Source DF Seq SS
DATE 1 0.000588
FLOW 1 0.003457
Table 47 Regression Statistics for Ammonia at Falls Creek
52
The regression equation is
NITROGEN, AMMONIA, TOTAL (MG/L =  0.428 +0.000016 DATE 0.000026 FLOW
Predictor Coef StDev T P
Constant 0.4279 0.5710 0.75 0.456
DATE 0.00001579 0.00001797 0.88 0.382
FLOW 0.00002633 0.00002320 1.13 0.260
S = 0.09731 RSq = 2.8% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.018826 0.009413 0.99 0.375
Residual Error 70 0.662806 0.009469
Total 72 0.681633
Source DF Seq SS
DATE 1 0.006632
FLOW 1 0.012194
Table 48 ANOVA Statistics for Ammonia
Analysis of Variance for Ammonia
Source DF SS MS F P
STATION 3 0.0235 0.0078 0.69 0.562
Error 213 2.4370 0.0114
Total 216 2.4605
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++
+
15 56 0.0870 0.1048 (*)
50 21 0.0630 0.0634 (*)
75 62 0.0794 0.1233 (*)
150 78 0.0628 0.1035 (*)
+++
+
Pooled StDev = 0.1070 0.030 0.060 0.090
0.120
* NOTE * N missing = 47
Table 49 Regression Statistics for Total Phosphorus at RR 1320
53
The regression equation is
PHOSPHORUS, TOTAL, WET METHOD ( =  0.250 +0.000009 DATE +0.000031 FLOW
Predictor Coef StDev T P
Constant 0.2504 0.2083 1.20 0.233
DATE 0.00000902 0.00000641 1.41 0.163
FLOW 0.00003072 0.00004263 0.72 0.473
S = 0.08067 RSq = 2.6% RSq(adj) = 0.5%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.016202 0.008101 1.24 0.293
Residual Error 93 0.605264 0.006508
Total 95 0.621465
Source DF Seq SS
DATE 1 0.012822
FLOW 1 0.003380
Table 50 Regression Statistics for Total Phosphorus at Johnson City
The regression equation is
PHOSPHORUS, TOTAL, WET METHOD ( = 7.23 0.000221 DATE 0.000349 FLOW
Predictor Coef StDev T P
Constant 7.228 3.449 2.10 0.040
DATE 0.0002211 0.0001084 2.04 0.045
FLOW 0.0003493 0.0003663 0.95 0.344
S = 0.5978 RSq = 6.9% RSq(adj) = 4.2%
Analysis of Variance
Source DF SS MS F P
Regression 2 1.8197 0.9099 2.55 0.086
Residual Error 69 24.6560 0.3573
Total 71 26.4757
Source DF Seq SS
DATE 1 1.4948
FLOW 1 0.3249
54
Table 51 Regression Statistics for Total Phosphorus at RM 962
The regression equation is
PHOSPHORUS, TOTAL, WET METHOD ( = 0.20 0.000004 DATE +0.000116 FLOW
Predictor Coef StDev T P
Constant 0.204 1.579 0.13 0.899
DATE 0.00000424 0.00004587 0.09 0.927
FLOW 0.0001161 0.0001937 0.60 0.556
S = 0.1470 RSq = 1.9% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.00834 0.00417 0.19 0.826
Residual Error 20 0.43226 0.02161
Total 22 0.44060
Source DF Seq SS
DATE 1 0.00057
FLOW 1 0.00777
Table 52 Regression Statistics for Total Phosphorus at Falls Creek
The regression equation is
PHOSPHORUS, TOTAL, WET METHOD ( = 0.202 0.000005 DATE 0.000002 FLOW
Predictor Coef StDev T P
Constant 0.2022 0.2087 0.97 0.336
DATE 0.00000530 0.00000657 0.81 0.422
FLOW 0.00000189 0.00000848 0.22 0.824
S = 0.03556 RSq = 1.0% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 0.000905 0.000453 0.36 0.700
Residual Error 70 0.088539 0.001265
Total 72 0.089444
Source DF Seq SS
DATE 1 0.000842
FLOW 1 0.000063
55
Table 53 ANOVA Statistics for Total Phosphorus
Analysis of Variance for TOTAL PHOSPHOROUS
Source DF SS MS F P
STATION 3 0.589 0.196 1.85 0.139
Error 260 27.627 0.106
Total 263 28.216
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++
15 73 0.0334 0.0352 (*)
50 23 0.0714 0.1415 (*)
75 72 0.1482 0.6107 (*)
150 96 0.0466 0.0809 (*)
+++
Pooled StDev = 0.3260 0.000 0.080 0.160
Table 54 Regression Statistics for TOC at RR 1320
The regression equation is
CARBON, TOTAL ORGANIC (MG/L AS = 10.3 0.000203 DATE 0.000140 FLOW
95 cases used 1 cases contain missing values
Predictor Coef StDev T P
Constant 10.329 4.682 2.21 0.030
DATE 0.0002030 0.0001440 1.41 0.162
FLOW 0.0001405 0.0009498 0.15 0.883
S = 1.794 RSq = 2.1% RSq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 2 6.459 3.230 1.00 0.371
Residual Error 92 296.254 3.220
Total 94 302.713
Source DF Seq SS
DATE 1 6.389
FLOW 1 0.070
56
Table 55 Regression Statistics for TOC at Johnson City
The regression equation is
CARBON, TOTAL ORGANIC (MG/L AS = 39.6  0.00111 DATE  0.00131 FLOW
Predictor Coef StDev T P
Constant 39.63 13.28 2.98 0.004
DATE 0.0011138 0.0004173 2.67 0.009
FLOW 0.001305 0.001410 0.93 0.358
S = 2.301 RSq = 10.4% RSq(adj) = 7.8%
Analysis of Variance
Source DF SS MS F P
Regression 2 42.418 21.209 4.00 0.023
Residual Error 69 365.407 5.296
Total 71 407.824
Source DF Seq SS
DATE 1 37.881
FLOW 1 4.537
Table 56 Regression Statistics for TOC at RM 962
The regression equation is
CARBON, TOTAL ORGANIC (MG/L AS =  19.6 +0.000658 DATE + 0.00108 FLOW
Predictor Coef StDev T P
Constant 19.60 14.20 1.38 0.183
DATE 0.0006577 0.0004124 1.59 0.126
FLOW 0.001077 0.001742 0.62 0.543
S = 1.322 RSq = 12.0% RSq(adj) = 3.2%
Analysis of Variance
Source DF SS MS F P
Regression 2 4.777 2.389 1.37 0.278
Residual Error 20 34.942 1.747
Total 22 39.719
Source DF Seq SS
DATE 1 4.110
FLOW 1 0.668
Table 57 Regression Statistics for TOC at Falls Creek
57
The regression equation is
CARBON, TOTAL ORGANIC (MG/L AS = 17.7 0.000454 DATE +0.000122 FLOW
Predictor Coef StDev T P
Constant 17.704 8.792 2.01 0.048
DATE 0.0004543 0.0002767 1.64 0.105
FLOW 0.0001225 0.0003572 0.34 0.733
S = 1.498 RSq = 3.8% RSq(adj) = 1.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 6.230 3.115 1.39 0.256
Residual Error 70 157.121 2.245
Total 72 163.351
Source DF Seq SS
DATE 1 5.966
FLOW 1 0.264
Table 58 ANOVA Statistics for Total Organic Carbon
Analysis of Variance for Total Organic Carbon
Source DF SS MS F P
STATION 3 26.22 8.74 2.48 0.062
Error 259 913.61 3.53
Total 262 939.83
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev ++++

15 73 3.289 1.506 (*)
50 23 3.122 1.344 (*)
75 72 4.022 2.397 (*)
150 95 3.717 1.795 (*)
++++

Pooled StDev = 1.878 2.40 3.00 3.60 4.20
* NOTE * N missing = 1
58
Table 59 Multiple Regression Statistics for Fecal Coliform at RR 1320
The regression equation is
FECAL COLIFORM,MEMBR FILTER,MF = 1774  0.0483 DATE + 0.540 FLOW
95 cases used 1 cases contain missing values
Predictor Coef StDev T P
Constant 1774 1750 1.01 0.313
DATE 0.04831 0.05388 0.90 0.372
FLOW 0.5397 0.3579 1.51 0.135
S = 675.8 RSq = 3.2% RSq(adj) = 1.1%
Analysis of Variance
Source DF SS MS F P
Regression 2 1405229 702615 1.54 0.220
Residual Error 92 42013081 456664
Total 94 43418311
Source DF Seq SS
DATE 1 366726
FLOW 1 1038503
Table 60 Multiple Regression Statistics for Fecal Coliform at Johnson City
The regression equation is
FECAL COLIFORM,MEMBR FILTER,MF = 6320  0.194 DATE + 1.31 FLOW
Predictor Coef StDev T P
Constant 6320 6768 0.93 0.354
DATE 0.1936 0.2127 0.91 0.366
FLOW 1.3077 0.7189 1.82 0.073
S = 1173 RSq = 5.6% RSq(adj) = 2.9%
Analysis of Variance
Source DF SS MS F P
Regression 2 5667955 2833978 2.06 0.135
Residual Error 69 94937923 1375912
Total 71 100605879
Source DF Seq SS
DATE 1 1115080
FLOW 1 4552875
59
Table 61 Multiple Regression Statistics for Fecal Coliform at RM 962
The regression equation is
FECAL COLIFORM,MEMBR FILTER,MF = 5317  0.150 DATE + 1.46 FLOW
22 cases used 1 cases contain missing values
Predictor Coef StDev T P
Constant 5317 9222 0.58 0.571
DATE 0.1504 0.2673 0.56 0.580
FLOW 1.461 1.055 1.38 0.182
S = 792.4 RSq = 11.8% RSq(adj) = 2.6%
Analysis of Variance
Source DF SS MS F P
Regression 2 1601635 800817 1.28 0.302
Residual Error 19 11928952 627840
Total 21 13530587
Source DF Seq SS
DATE 1 398784
FLOW 1 1202850
Table 62 Multiple Regression Statistics for Fecal Coliform at Falls Creek
The regression equation is
FECAL COLIFORM,MEMBR FILTER,MF = 3589  0.106 DATE + 0.598 FLOW
71 cases used 2 cases contain missing values
Predictor Coef StDev T P
Constant 3589 10037 0.36 0.722
DATE 0.1063 0.3158 0.34 0.737
FLOW 0.5984 0.4040 1.48 0.143
S = 1694 RSq = 3.2% RSq(adj) = 0.4%
Analysis of Variance
Source DF SS MS F P
Regression 2 6518103 3259051 1.14 0.327
Residual Error 68 195198893 2870572
Total 70 201716996
Source DF Seq SS
DATE 1 221718
FLOW 1 6296384
60
Table 63 ANOVA Statistics for Fecal Coliform
Source DF SS MS F P
STATION 3 144190 48063 0.03 0.992
Error 255 359167039 1408498
Total 258 359311229
Individual 95% CIs For Mean
Based on Pooled StDev
Level N Mean StDev +++

15 70 328 1709 (*)
50 22 311 803 (*)
75 72 332 1190 (*)
150 95 280 680 (*)
+++

Pooled StDev = 1187 0 300 600
* NOTE * N missing = 5