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An overview of trend monitoring and analysis in water resources, focusing on the identification and measurement of trends in water quality parameters. various methods for visualizing trends, selecting appropriate statistical tests, and calculating non-parametric statistics. It also discusses issues to consider when doing trend monitoring, such as data quality, time frame, and exogenous variables.
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Time of Day
Percent Total Concentration
Trend Monitoring
What is it and why do we do it?
Trend monitoring looks for changes in environmental
parameters over time periods (E.g. last 10 years) or in space
(e.g. as you move downstream)
***** Created with StatPlus™ Software**
How to find a trend
Visual-
Good News... Graphing or mapping data for people to see is the
easiest way to communicate trends, especially to a non-technical
crowd.
Bad News… No way of “measuring” that there is a trend or how
big it is.
Statistical-
Good News…Can identify hard to see trends and gives a number
that is defensible and repeatable.
Bad News…Easy to do wrong and hard to figure out.
Be vewy, vewy quiet…I’m hunting fow a twend
Visual methods for displaying trends
Time/area series scatter plot Bar Graphs
Time series smoothed scatter plot Time/area series box plot of statistics*
Techniques of Water-Resources Investigations of the USGS Book 4. Chapter A
p. 287
(^1 ) (^3 ) 5 (^7 ) 9 10
May
June
July
August
Sept
October
0
500
1000
1500
2000
2500
The Trouble with Graphs
changes
in a parameter.
http://dnr.metrokc.gov/wlr/waterres/streams/northtrend.htm
Statistical Trend Analysis Methods
Type of statistic depends on data characteristics- To test if an existing data
set is “normally” distributed you may (a) plot a histogram of the results; or (b) conduct
tests for normality like the Shapiro-Wilk W test, the Filliben’s statistic, or the
studentized rage test (EPA, 2000, p. 4-6).
Parametric- Statistics for normally distributed data.
Includes regression of parameter against time or spatial
measure, like river mile. Parametric statistics are rarely
appropriate for environmental samples without massaging
data. See the USGS guide by Helsel and Hirsch for
descriptions of using regression.
Nonparametric- Statistics that are not as dependent on
assumptions about data distribution. Generally the safer
statistics to use, but are not as readily available. Test
include the Kendall test for presence of consistent trend,
Sen slope test for measure of magnitude of slope, and
Wilcoxon-Mann-Whitney step trend analysis.
Things to watch out for with statistical analysis
*** From Helsel D.R. and R.M. Hirsch. 1991 Statistical Methods**
in Water Resources. Techniques of Water-Resources
Investigations of the USGS Book 4. Chapter A3 p.
and met. Failure to do so, may lead to misleading results
appropriate.
test are not readily available and can be computationally
demanding.
find the trend.
methods often requires
relearning fairly complicated
procedures every year. If
you do use a statistical
package, keep excellent
notes of what you do and
why.
Four OLS regression charts with the same R
2 , slope,
and intercept*
How to Calculate Non-Parametric Statistics
Kendall Test to determine if a significant trend exists see EPA
guide QA/G-9 pages 4-16 to 4-
XY Plot of data vs time
Year Units
2000 5
2001 6
2002 11
2003 8
2004 10
Sen Slope or Kendall-Theil line to measure the magnitude of
the trend see USGS Statistical Methods for Water Resources
pages 266 - 267
What type of trend analysis is right for you to use?
What would you need for temperature trend monitoring? Is there an
exogenous variable?
What about changes in other water quality parameters?
How could changes in monitoring schedule impact trends?
Example Bob has been monitoring DO in the morning at a site for 3 years. He adds
4 new sites to his route and now visits his old site in the afternoon every visit. Now
samples are collected in the pm. What impact will this have on your ability to track
trends? What could you do to correct the problem?
DO Saturation in Willamette R. at Portland S.P. & S. Railroad Bridge
2 / 12 / 19906 / 27 / 199111 / 8 / 19923 / 23 / 19948 / 5 / 1995 Date
50
60
70
80
90
50
60
70
80
90
OWQI...month OWQI...annual
ComparisonofTrends:Annualvs.MonthlyData
WillametteRiveratNewbergBridge
Issues to consider when doing trend monitoring
1
sampling frequency (i.e., constant number of samples per period, equally spaced
across the period) to minimize variance.
tests by changing variance.
outliers
time and space).
impacted by exogenous parameters, like stream discharge or time of day,
respectively. Changes in these exogenous variables may impact trends you
measure in the parameter of interest. To remove these impacts develop a
regression between the two variables. Calculate the residuals (the difference
between the measured value and value predicted by the regression) and then run
the trend analysis on the residuals.
statistic into thinking concentrations are decreasing (make sure you have a way to
statistically handle changing detection limits}.
p. 146