Cac janyary 15, 2014 meeting packet

Citizen’s Advisory Committee 7:00 PM, Wednesday, January 15, 2014 - Capitol Region Watershed District Office Agenda 7:00

I)

Welcome, Announcements and Updates – Introductions

7:05

II)

Public Comment for issues not on the Agenda (3 minutes per person)

7:08

III)

Approval of the Agenda

7:09

IV)

Approval of Minutes

Materials Enclosed

Approval of the December 11, 2013 Minutes 7:10

V)

District Initiatives A) Statistical Analysis of Lakes Data in the Capitol Region Watershed District, Joe Bischoff, Wenck Associates, Inc. B) Audubon Certification Program. Stepahanie Herbst and Britta Suppes

8:15

VI)

CAC Initiatives A) Develop Outline of 2014 Meetings B) Discuss the Development of CAC Orientation Packet C) Follow up discussion from December 11th CAC meeting

8:45

VII)

Project and Program Updates A) North and East Groundwater Management Area (Doneux)

8:50

VIII) CAC Observer Update

8:55

IX)

Discussion A) B) C)

9:00

X)

New & Old Issues Identify CAC Observer future Board of Managers Meetings December 11, 2013 CAC Agenda Overview

Adjourn

W:\05 Citizens Advisory Committee\Agendas\2014\January 15, 2014 CAC Agenda.docx

Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District.

Draft

Citizen Advisory Committee Meeting Wednesday, December 11, 2013 – 7:00 p.m.

CAC Members Present: Gwen Willems Michelle Ulrich Steve Duerre David Arbeit Bill Barton Ted McCaslin Richard Weil Janna Caywood

Members absent: Katheryn Swanson, w/notice Pat Byrne Mike MacDonald, w/notice Richard Weil, w/notice

Others Present: Mark Doneux, CRWD Michelle Sylvander, CRWD Mary Texer, Board Manager Shirley Reider, Board Manager Joe Collins, Board Manager Seitu Jones, Board Manager Mike Thienes, Board Manager

Welcome, Announcements, and Updates Ms. Willems opened the meeting at 7:00 p.m. with a request for introductions and any announcements.

Public Comments Janna Caywood mentioned that the City of Saint Paul has installed experimental blades on some of the plow trucks. In addition to the experimental blades the City has also installed sensors for detecting the temperature of the pavement.

Approval of Agenda Ms. Willems asked for any additions or changes to the Agenda. No changes were requested.

CAC 13-028 Motion: To approve the CAC December 11, 2013 agenda.

Duerre/Ulrich Unanimously approved Approval of the November 13, 2013 CAC Minutes Ms. Willems requested any changes or corrections to the minutes. There was one correction on page 2.

CAC 13-029 Motion: To approve the CAC November 13, 2013 CAC Minutes with correction.

Arbeit/Duerre Unanimously approved Items for Review and Comment Requested By Board of Managers A)

Review of Survey Results for CAC Initiatives

Administrator Doneux reviewed the survey taken from ideas gathered at the October 16th, 2013 CAC meeting. There was much discussion about the survey results. Many of the ideas will be worked into the schedule for 2014 meetings.

1

CAC Members felt the most important topic of the survey results was the overall recruitment of new CAC Members and develop and the implement of an orientation process with a packet of relevant.

It is very important to the CAC Members that more guest speakers present at CAC meetings and to invite the public to attend. The members of the CAC enjoyed the presentation from the tree guy. Discussion continued on sharing speakers with other groups such as the Fresh Water Society and inviting neighborhood groups.

The CAC Members felt very strongly about more interaction with local governments and their pertinent departments, such as Public Works and Parks and Recreation Department, was warranted.

CAC Members felt it would be very beneficial to sponsor an awards program to recognize outstanding water and soil projects in the district (e.g., a program modeled on the LEAP Awards).

CAC Members felt attending conventions and seminars would be beneficial to help improve their understanding of other pertinent organizations, such as MAWD and BWSR, and to be able to report back to CAC members.

CAC Members would like to attend more tours of projects/features in the CRWD, increasing the number of tours in the watershed to at least two per year with the second tour focused on a particular project or facility.

CAC Members would like to participate in legislative activities that impact the district (e.g. attend MAWD legislative briefing at CRWD or invite local legislators to speak at CAC meetings).

B)

Discussion and Review of CAC Initiatives with Board and CAC Members

Manager Collins recommended that CAC members attend the meetings of other watershed districts. This could help strengthen CRWD by comparing projects and issues to those of other watersheds. Topics of interest could include those such as the water levels in White Bear Lake.

The Members of the CAC felt better communication such as sharing the Board of Managers Meeting Agenda with the members of the CAC. Administrator Doneux discussed a Community Capacity Assessment being done by May Davenport, a Social Scientist with the University of Minnesota. Ms. Davenport is partnering with other watersheds to examine individual actions and behaviors to engage in clean water. Much discussion occurred.

C)

Develop Outline of 2014 Meetings

Discussion on this topic has been moved to the January 15th, 2014 CAC Meeting.

D)

Discuss the Development of CAC Orientation Packet

Discussion on this topic has been moved to the January 15th, 2014 CAC Meeting.

E)

Recommendations for 2014 CAC Reappointments

“Our mission is to protect, manage, and improve the water resources of the Capitol Region Watershed District.�

2

Staff and Program Updates A)

A look ahead to 2014 (Doneux)

Administrator Doneux reviewed the following project and programs planned for 2014.

Rule revisions BMP Database Impervious Surfaces data set New Safety training Aquatic Plant Management at Lake McCarrons Monitoring Program Improvements Curtiss Pond

Highland Ravine Lowertown Ballpark Upper Villa Park Central High School Trout Brook Nature Sanctuary Irrigation for the new Ball Park.

CAC Observer and Board of Managers Update The Minnesota Association of Watershed Districts, Inc. (MAWD) held its annual trade show on December 5-6, 2013 at the Arrowwood Resort in Alexandria, MN. Discussion – A) New & Old Issues There was no discussion.

B) Identify CAC Observer for December 18th Board of Managers Meeting and the January 8th, 2014 Board of Managers Meeting The Annual Meeting and Regular Board of Managers Meeting will be held on December 18th, with a social hour from 5:00pm to 6:00pm. All CAC members are welcome to attend, there will be a special recognition for Jerome Wagner.

There were no volunteers for the January 8th Board of Managers Meeting.

C) January 15, 2014 CAC Agenda Overview At the January 15, 2014 CAC meeting, Joe Bischoff from Wenck Associates, Inc. will be presenting his Statistical Analysis of Lake Data in the Capitol Region Watershed District.

Adjourn – CAC 13-030 Motion: To adjourn.

Caywood/Ulrich Unanimously approved The meeting was adjourned at 9:15 PM. Respectfully submitted, Michelle Sylvander W:\05 Citizens Advisory Committee\Minutes\2013\December 11 2013 Draft Minutes.doc

“Our mission is to protect, manage, and improve the water resources of the Capitol Region Watershed District.”

3

January 15, 2014 CAC Meeting V. District Initiatives - A) CRWD Lakes Statistical Analysis, Joe Bischoff, Wenck Associates

DATE: TO: FROM: RE:

January 9, 2014 CRWD CAC Members Anna Eleria, Water Resource Project Manager Statistical Analysis of Lakes Data in CRWD

Background In early January 2013, CRWD hired Wenck Associates, Inc. to conduct a more in-depth analysis of the four CRWD lakes water quality data collected by Ramsey County to better understand temporal, seasonal and climatic trends and the factors driving these trends. Specifically, CRWD sought answers to several questions for each of the lakes including: 1) Is the lake water quality data generally getting better or worse; 2) What are the trends; and 3) What factors are driving these trends.

Issues Wenck Associates, Inc. has completed a statistical and graphical analysis of CRWD lake water quality data, trend analysis of selected water quality parameters, and a qualitative assessment of potential trend drivers. Enclosed for the CAC’s review and comment is the technical memorandum summarizing the results and recommendations for further lake analysis and monitoring.

Action Requested None, for your information only

enc: Technical Memorandum of Statistical Analysis of CRWD Lakes Data

W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis - Wenck\Board Memos\CAC Memo CRWD Lakes Analysis 01-15-14.docx

Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District.

Wenck Associates, Inc. 1800 Pioneer Creek Center P.O. Box 249 Maple Plain, MN 55359‐0249

800‐472‐2232 (763) 479‐4200 Fax (763) 479‐4242 wenckmp@wenck.com www.wenck.com

TECHNICAL MEMORANDUM

TO: Anna Eleria, Capitol Region Watershed District

FROM: Joe Bischoff, Wenck Associates, Inc.

DATE: September 18, 2013

SUBJECT: Statistical Analysis of Lake Data in the Capitol Region Watershed District

Purpose

The purpose of this technical memorandum is to present results from a statistical analysis of lake data in the Capitol Region Watershed District. The intent of the statistical analysis is to answer the following questions:

 Can the water quality of CRWD lakes be described as generally getting better or worse than was recorded in the past?  What trends in water quality exist? Can these trends be verified through statistical methods?  What factors are driving the trends in water quality among the different lakes?  What qualitative statements can be made regarding the causes and effects in the observed water quality trends?

To answer these questions, Wenck employed a number of statistical analyses including trend analysis, hypothesis testing, and general descriptive statistics. Results of the analyses for each lake are presented below.

Approach CRWD provided Wenck with water quality and biological data for the four lakes to be assessed (Table 1). After review, the project team decided to focus on the water quality parameters (TP, chlorphyll-a, and Secchi) first, and use the biological data where possible to provide context for the water quality data. Fairly long records of phytoplankton and zooplankton data are available for Como, Crosby, and McCarron Lake.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Table 1. Available data for the lake statistical analyses.

Data Description

Como

Aquatic vegetation and species survey 2012 Como Lake Turtle Study

Crosby

Loeb

McCarrons

2012

2012

2012

1999‐2007

2003‐2007

1988‐2007

2005

2010

2011

Crosby Lake Sediment Data Daphnia Size

Little Crosby

2010 1984‐2007

DNR Fisheries‐Lake Management Plan Lake Elevations

1978‐2012

2003‐2004, 2006‐2012 1924‐2012

Lake Sampling Data

1982, 1984‐2012

1999‐2012

2003‐2012

1988‐2012

Macrophyte Surveys

2005, 2010

2009

2005

2005

Phytoplankton Data Zooplankton Data

1984‐2011 1984‐2011

1999‐2011 1999‐2011

2003‐2011 2003‐2011

1988‐1998, 2000‐2011 1988‐1998, 2000‐2011

2011‐2012

To evaluate trends in lake water quality, Wenck employed a series of statistical tests for the period of record. Wenck conducted the following steps in the statistical analysis of the lake data: 1. Evaluate the normality of the data including the residuals and log‐transformed data and residuals. Levene’s test was used to assess equal variance among the years and the Shapiro‐ Wilks test was used to test for normality of the entire data set as well as each year. These tests are critical to ensure statistical test assumptions are not violated. Analyses can be conducted on the data, residuals, log‐transformed data, or log‐transformed residuals.

2. Run pairwise comparisons among the years using either ANOVA (parametric test if assumptions are met) or Kruskall‐Wallace (non‐parametric test if assumptions are not met) tests to assess difference among the years. Post‐hoc testing was completed using the Bonferonni test at a 0.1 significance level.

3. Visually plot data sets using time series and box plots to identify potential trends, seasonality, or other exogenous factors that may be influencing the data set.

4. Evaluate potential exogenous variables for their influence on the data set. An exogenous variable is an outside variable that may demonstrate trends that will influence the analysis variable. For example, lake water quality data may be influenced by precipitation patterns causing the analyst to interpret precipitation trends as water quality trends.

5. Monthly plots to evaluate the potential for seasonality in the data set.

6. Autocorrelograms to determine the level of autocorrelation in the data set. Autocorrelograms lag the data sets to evaluate correlation between sequentially collected samples. So, at lag 1, two sequentially collected samples are compared for correlation. At lag 2, the first and third samples in a series are compared for correlation and so on.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

7. Trend analysis for the data set corrected for autocorrelation and seasonality of necessary. The Mann Kendall‐Tau test was used in most cases which performs the trend assessment on the ranks of the data sets.

8. A multivariate analysis of lake Trophic Status Index to evaluate drivers of lake water quality.

Data Description The first step is to describe the data set focusing on the assumptions for each potential statistical test. For example, most parametric statistical hypothesis tests such as ANOVA require the data have a normal distribution and equal variances among groups. In the case where this is not true, alternative nonparametric hypothesis tests such as the Kruskall-Wallace test can to be used.

Because parametric testing is more powerful in determining differences among groups or trends, it is worthwhile to check the data and residuals as well as the log transformed data and residuals for the assumptions of equal variance and normality.

Data Visualization The second step is to visualize the data set to develop a general understanding of potential trends in the data set or other factors that may be causing trends in the data set. Many potential trends can be recognized using data visualization techniques such as notched box plots, histograms, scatter plots and other plots of the data or residuals of the data. Once any trends are identified at this level, they can be further evaluated using the appropriately selected statistical test. Wenck developed notched box plots by year and month to evaluate trends and statistical differences among the years. The notches in the box plots represent the 95% confidence internal around the mean, so when the notches overlap, there is no statistical difference in the means of the individual data sets. If they do not overlap, the means are likely statistically different.

Trend Assessment To evaluate trends, Wenck first evaluated the necessary statistical assumptions for using trend analysis including normality of the data set and equal variance over time. In almost all cases, the data sets were determined to be non-normal. The Mann-Kendall Tau test for trends is nonparametric and is therefore appropriate where the data are non-normal although it still requires equal variance over time. The Mann-Kendall Tau test can also be adjusted for serial autocorrelation, the condition where a previous sample in time is correlated to the current sample, and seasonality.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Differences Among Years The data set was also evaluated for differences among the years to identify groups of years that may be similar. The groupings can then be evaluated for similar conditions such as rainfall or fish abundance to evaluate potential causes. For this analysis, the grouping was completed; however a detailed review of other factors was outside the scope of this assessment.

Multivariate Assessment using the Lake Trophic Status Index The interrelationship between simultaneously collected variables can be used to identify conditions in a lake that affect those measured variables. One way this can be done is by evaluating the differences among TSI values for each of the three collected variables (Carlson 1992). Theoretically, the empirical relationships between TP, chlorophyll-a, and Secchi should result in the same TSI value. Because these empirical relationships are derived from regressions that have error terms, some variability can be expected. However, in some situations the differences are not random and can be used to identify factors interfering with the relationship.

The figure below represents a plot of the TSI differences with 4 primary zones for interpretation.

Table 2 provides some interpretation of the data in each zone. If points fall below the x axis, chlorophyll-a is under predicted suggesting that P is not limiting algal growth, rather algal growth is limited by light availability, nitrogen limitation or zooplankton grazing. Points lying to the right of the y axis indicate better clarity than expected which may be a result of larger algae such as aphanizomenon, a colony forming blue-green algae. Points to the left of the y-axis suggest smaller particles dominate suggesting water color or turbidity is a critical factor. Points lying along the diagonal and to the left of the axis suggest that P and clarity are correlated, but the expected chlorophyll response is not demonstrated. This suggest non-algal turbidity such as clay is controlling water clarity and keeping the P unavailable for algal production.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Carlson and Simpson 1996.

Following is a discussion of the results of the statistical analysis for each lake.

LAKE MCCARRON

Descriptive Statistics

Total phosphorus, chlorophyll‐a and Secchi depth were assessed for basic statistical assumptions such as normality, equal variance, and central tendencies (Table 2). None of the data sets as a whole are normal or lognormal, although Secchi depth demonstrates a lognormal distribution in all but one year.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Table 2. General statistical description of Lake McCarrons water quality data.

Statistic No. of observations Minimum Maximum 1st Quartile Median 3rd Quartile Mean Variance (n-1) Standard deviation (n-1) Skewness (Pearson) Kurtosis (Pearson) Standard error of the mean Geometric mean Geometric standard deviation

TP (mg/L) 177 0.009 0.175 0.016 0.026 0.039 0.031 0.001 0.025 3.258 14.539 0.002 0.026

Chl-a (µg/L) 177 0.317 74.800 2.780 6.500 13.370 9.760 107.056 10.347 2.856 12.298 0.787 6.197

Secchi (m) 177 0.700 8.400 1.700 2.750 4.000 2.952 2.199 1.483 0.697 0.206 0.114 2.580

1.862

2.686

1.715

Summer average phosphorus, chlorophyll‐a and Secchi depth were plotted for Lake McCarrons (Figure 1). Both TP and chlorophyll‐a demonstrate a decreasing trend in concentration with Secchi depth demonstrating an increasing trend in water clarity. It is important to note that an alum treatment was performed on the lake in 2004 which essentially breaks the data set into two distinct periods: pre‐ and post‐alum application. Long term notched box plots demonstrate an improving trend in water quality (Figure 2). Pre‐alum variability was quite high with extreme values in TP and chlorophyll‐a. After the alum treatment the spread of the data decreased significantly for chlorophyll‐a and TP. It is also interesting to note that the lake appears to have taken a few years after the alum treatment to reach the maximum effectiveness (2007‐2010). The most recent two years demonstrate a broader spread in the data suggesting that the effectiveness of the alum treatment may be weakening.

Annual Pairwise Comparisons

Data and residuals, including log transformations, for Lake McCarrons was evaluated to test for normality and equal variance among the sample years (Table 3). To use parametric testing such as an ANOVA to test for differences among years, the test groups must be normally distributed and have equal variance. Although some of the Secchi depth data was normally distributed or had equal variances among years, none occurred in the same grouping. Therefore, the nonparametric Kruskall‐Wallace test was selected with a Bonferonni post‐hoc pairwise comparison.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Table 3. Evaluation results for tests of normality and equal variance among groups.

Parameter Total Phosphorus Chlorophylla Secchi Depth

Data

Residuals1

Logs of Data Equal Variance?

Normally Distributed?

Equal Variance?

Residuals of Logs1

Equal Variance?1

Normally Distributed?2

Normally Distributed?

Equal Variance?

Normally Distributed?

No

No

Yes

No

No

No

Yes

No

No

No

Yes

No

No

No

Yes

No

Yes

No

No

Yes

Yes

No

No

Yes

1

Levene’s test Shapiro‐Wilks test

2

The Kruskall‐Wallace and Bonferonni tests demonstrated significant differences among the years for all three parameters (Attachment 1). A total of 81 pairs were significantly different than one another for TP. Most of the years prior to the alum treatment were significantly higher in TP than those years after the treatment except for 1989, 1992, 1994, and 1998 with 2008 and 2009 significantly lower than all the other years.

Only 27 pairs of years were significantly different than one another for chlorophyll‐a. The most recent two years are statistically similar than almost all the other years, although based on visual inspection (Figure 2) the spread of the data is tighter in more recent years. The fact that the most recent years of chlorophyll‐a data are similar to most years suggests that other factors may be affecting mean algal abundance or that the effectiveness of the alum treatment is diminishing. Overall, the post‐alum treatment chlorophyll‐a abundance is significantly lower. However, the reduced phosphorus concentrations appear to have reduced significant algal blooms (decreased spread in the data).

Only 2008, when Secchi depth was at its highest, demonstrated a significant difference than most of the pre‐alum treatment period. This is slightly surprising given the significant reductions in chlorophyll‐a and total phosphorus. Other factors are likely controlling Secchi depth at these lower chlorophyll‐a concentrations and 2008 likely presents the best achievable Secchi depth when addressing only phosphorus and chlorophyll‐a.

Trend Assessment

Based on the visual assessment of water quality data in Lake McCarrons it is clear that there are two distinct periods to evaluate trends including the pre‐ and post‐alum treatment periods. An assessment of trends needs to focus on these two periods.

Exogenous Variables

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Before evaluating trends in a lake data set, exogenous variables that may be causing a pattern in the data must be evaluated and removed if present. An exogenous variable is a variable other than time that may have considerable influence on the response variable. These variables are usually natural such as rainfall, temperature or stream flow. For lakes, especially those with long residence times such as Lake McCarron, the most common potential exogenous variable is rainfall.

To test for rainfall as a factor, monthly total precipitation was regressed against monthly average TP concentrations for the period of record (Figure 3). No relationship between TP and monthly precipitation totals was found for the data or the logs of the data. Consequently, it was concluded that rainfall totals does not need to be accounted for in the trend analysis.

Seasonality and Autocorrelation

Two other factors that need to be accounted for in any trend analysis including serial autocorrelation and seasonality. Seasonality is important in lakes since they demonstrate a clear growing season along with a dormant season. However, most of the monitoring data were collected during the growing season meaning that years to year comparisons are not likely to include much seasonality in the data.

Monthly notched box plots confirm this assumption (Figure 4). Only Secchi depth for one month (August) demonstrated a significant difference among the months. Based on this assessment, using the seasonally adjusted Kendall Tau trend test is not necessary.

Lake data tend to be serially autocorrelated due to long residence times. To evaluate serial autocorrelation, correlograms were developed for each of the three parameters (Figure 5).

Autocorrelograms evaluate autocorrelation using time lags in the data. For our analysis, we chose a lag period of 12 to account for annual data. Typical sampling in Lake McCarrons was 7 samples over the summer growing season. However, a lag period of 12 allows for evaluation of autocorrelation within a sampling year and between years. All three parameters demonstrated autocorrelation within any given year but not between years. Consequently, autocorrelation must be accounted for in the trend analysis.

Trend Assessment

Because a major event (alum treatment) occurred in Lake McCarron, the trend assessment must account for both the pre‐ and post‐alum conditions. Total phosphorus conditions before and after the alum treatment were statistically different (Figure 6).

No trends were detected in either the pre‐ or post‐alum treatment data sets using the Mann‐Kendall trend test with a significance value of 0.05. Trends tests on the overall data set do demonstrate an improving trend in water quality although this is solely a result of the alum treatment conducted in 2004.

Multi‐Variate Assessment

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

The multivariate TSI comparison for Lake McCarrons did not present a great deal of information about the lake (Figure 7). Essentially, Lake McCarrons appears to be a typically P limited lake. Much of the data do fall right of the y‐axis suggesting that larger particles such as Aphanizomenon dominate water clarity. This is further corroborated by the lack of significant improvements in water clarity after the alum treatment where algae were reduced but the water clarity was already relatively good.

Potential Divers of Water Quality

Lake McCarrons Conclusions

1. Water quality in Lake McCarrons after the alum treatment was statistically better than the pre‐ alum water quality for all three parameters. Water quality appears to have peaked in 2008 through 2010 and may be trending poorer in the past two years. However, it is impossible to tell if this is just annual variability and visual observations of the data suggest that the alum treatment is still effective.

2. Prior to the alum treatment, peak total phosphorus concentrations were typically observed in the spring (April‐May) samples suggesting high runoff loads during these periods.

3. No statistical trends were detected in water quality data for either pre‐ or post‐alum conditions in Lake McCarrons. However, recent spread in total phosphorus and Secchi depth data suggest that water quality may be changing and the alum treatment effectiveness may be weakening.

However, other data such as sediment cores are needed to evaluate current sediment release.

4. Other than 2008 and 2009, mean chlorophyll‐a data after the alum treatment was statistically similar to many of the pre‐treatment years suggesting there was not a great overall reduction in algal abundance in the lake. However, mean algal abundance has been reduced and it does appear to have eliminated significant algae blooms in the lake.

5. Water clarity overall did increase significantly after the alum treatment. However, year to year comparisons suggest that the clarity is not significantly different than many of the previous years. It is important to note that the year to year tests have less statistical power due to the lower sample size in each given year. So, water clarity was improved for much of the year, but some years still may demonstrate water clarity similar to past years even though overall algal abundance is lower. 2008 is likely the best achievable Secchi depth by controlling phosphorus alone.

6. Based on the multi‐variate assessment of the Trophic Status Index, Lake McCarrons appears to be a typical P‐limited lake where larger particles dominate and zooplankton grazing likely plays a factor is algal abundance.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Como Lake Descriptive Statistics

Total phosphorus, chlorophyll‐a and Secchi depth were assessed for basic statistical assumptions such as normality, equal variance, and central tendencies (Table 4). Chlorophyll‐a had a wide range of values resulting a large standard deviation.

Table 4. General statistical description of Lake McCarrons water quality data.

Statistic No. of observations Minimum Maximum 1st Quartile Median 3rd Quartile Mean Variance (n-1) Standard deviation (n-1) Skewness (Pearson) Kurtosis (Pearson) Standard error of the mean Geometric mean Geometric standard deviation

TP (mg/L) 307 0.031 0.970 0.089 0.129 0.228 0.182 0.023 0.150 2.358 6.879 0.009 0.142

Chl-a (ug/L) 307 0.1 223.3 6.8 20.1 49.4 32.8 1261.7 35.5 1.9 4.8 2.1 16.5

Secchi (m) 307 0.20 4.20 0.70 1.20 2.20 1.58 1.09 1.05 0.86 -0.31 0.06 1.26

1.974

3.9

2.00

A visual review of the summer average total phosphorus concentrations for Como Lake suggest a somewhat cyclical patter of several years of high phosphorus concentrations followed by a few years of lower concentrations (Figure 8 and Figure 9). Both response variables follow similar patterns. The patterns may reflect cyclical life cycles of fish, particularly panfish, which can follow boom‐bust patterns.

The fishery may ultimately affect zooplankton grazing and chlorophyll‐a abundance. Although there appears to be a cyclical pattern, there is no apparent trend in the data or major shift at any point in time.

Annual Pairwise Comparisons

Data and residuals, including log transformations, for Como Lake were evaluated to test for normality and equal variance among the sample years (Table 5). To use parametric testing such as an ANOVA to test for differences among years, the test groups must be normally distributed and have equal variance.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

No of the groups followed these assumptions. Therefore, the nonparametric Kruskall‐Wallace test was selected with a Bonferonni post‐hoc pairwise comparison.

Table 5. Evaluation results for tests of normality and equal variance among groups.

Parameter Total Phosphorus Chlorophylla Secchi Depth

Data

Residuals1

Logs of Data Equal Variance?

Normally Distributed?

Equal Variance?

Residuals of Logs1

Equal Variance?1

Normally Distributed?2

Normally Distributed?

Equal Variance?

Normally Distributed?

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

1

Levene’s test Shapiro‐Wilks test

2

Pairwise comparisons for Como Lake TP suggest that there are not many significant differences from year to year since only 22 pairs demonstrated statistically significant differences and where most differences were between extreme years. These results suggest that although there appears to be differences in the spread of the data among years, average conditions are not significantly different.

Both chlorophyll‐a and Secchi follow a similar cyclical pattern, however they demonstrate more difference among pairs, especially Secchi depth (Figure 9). The fact that more differences were not picked up in chlorophyll‐a is likely a result of the high variances in many of the years. For Secchi, there were 70 statistically different pairs. The greater number differences among years for water clarity suggest that water clarity is controlled by multiple factors and not just TP and chlorophyll‐a abundance.

Further exploration of the cyclical patterns in the lake data may reveal other factors affecting water clarity such as changes in the fish community, patterns of vegetation change, and potential climatic patterns.

Trend Assessment

Exogenous Variables

Precipitation was evaluated as a potential factor affecting water quality trends in Como Lake (Figure 10).

No relationship was found between monthly TP concentrations and monthly precipitation totals.

Seasonality and Autocorrelation

Box plots of monthly data suggest some seasonality in the data collected for Como Lake (Figure 11). It is important to note that the majority of the data were collected in the summer months. Because so few 11 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

of the data are collected outside of the summer months, seasonality in the trend assessment can be ignored.

The data do present autocorrelation, especially in those data collected in that same year (Figure 12).

Data collected between years do not appear to be autocorrelated which is expected since the residence time of Como Lake is likely relatively short. Serial autocorrelation was accounted for in the trend assessment.

Trend Assessment

Total phosphorus in Como Lake did demonstrate a significant decreasing trend, although it was not significant if seasonality is included. Based on the relatively small data set outside of the summer season, the non‐seasonally adjusted test is acceptable. A trend test on the summer average TP did not result in a significant trend in the data. Neither chlorophyll‐a or Secchi depth resulted in a significant trend.

Multi‐Variate Assessment

The multivariate assessment resulted in a number insights about Como Lake including:

1. phosphorus is not limiting algal growth, and that a phosphorus surplus may exist in the lake 2. Zooplankton grazing plays a large role in controlling water clarity in Como Lake. This is similar to conclusions by Noonan (1998) who determined cyclical patters in lake water quality are a result of complex interactions between submerged aquatic vegetation, zooplankton grazing, nutrient cycling and fish abundance.

3. Vegetation in Como Lake is currently sparse (CRWD 2012) correlating to lower daphnia abundance (Figure 14) and poorer water quality.

Potential Drivers of Water Quality

Como Lake Conclusions

1. Cyclical patterns in water quality suggest that outside factors that follow cyclical patterns may be affecting water quality in Como Lake. Noonan (1998) concluded that although “bottom‐up” nutrient controls play a factor in Como Lake, other factors such as plant abundance, fisheries, and zooplankton abundance are also critical in controlling water quality.

2. Secchi depth demonstrated many more statistically different years than either chlorophyll‐a or TP, suggesting that other factors may be affecting water clarity. Some potential factors include wind resuspension of sediment, changes in zooplankton abundance, TSS inflow, or rough fish activity.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

3. A statistically significant decreasing trend in TP was detected in Como Lake, although a trend test on the summer average data was not significant. However, statistical differences among the years in TP did not pick up significant patterns, confounding the results. It appears that TP is possibly decreasing in Como Lake, but more data will improve the prediction.

4. Based on the data, management of water quality in Como Lake should focus on the submerged aquatic vegetation community as well as nutrient reductions. Fish abundance is also an important factor.

Crosby Lake

Total phosphorus, chlorophyll‐a and Secchi depth were assessed for basic statistical assumptions such as normality, equal variance, and central tendencies (Table 6). None of the parameters were normally or log‐normally distributed.

Table 6. General statistical description of Lake McCarrons water quality data.

Statistic No. of observations Minimum Maximum Range 1st Quartile Median 3rd Quartile Mean Variance (n-1) Standard deviation (n-1) Skewness (Pearson) Kurtosis (Pearson) Standard error of the mean Geometric mean Geometric standard deviation

TP (mg/L) 87 0.010 0.330 0.320 0.032 0.051 0.091 0.066 0.002 0.050 2.415 8.414 0.005 0.053 1.895

Chl-a (µg/L) 87 0.2 47.0 46.8 2.8 4.7 8.8 8.0 75.6 8.7 2.2 5.0 0.9 5.1

Secchi (m) 87 0.50 4.90 4.40 1.63 2.00 2.88 2.26 0.85 0.92 0.55 -0.23 0.10 2.07

2.6

1.55

Plots of the summer mean water quality for Crosby Lake show a decrease in water quality over the past five years with increasing TP and chlorophyll‐a concentrations and decreasing water clarity (Figure 15). It is important to note that although chlorophyll‐a demonstrates an increase over the past 8 years, the concentrations still remain below the state standard of 20 µg/L as a summer average. Secchi disk transparency has decreased over the years but still remains greater than the state standard of greater than 1 meter.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Notched box plots for water quality suggest that water quality may be degrading with the most recent period showing greater extremes and spread in the data especially for TP and chlorophyll‐a (Figure 16).

TP demonstrated statistically significant increases in the past three years.

Annual Pairwise Comparisons

Data and residuals, including log transformations, for Crosby Lake were evaluated to test for normality and equal variance among the sample years (Table 7). To use parametric testing such as an ANOVA to test for differences among years, the test groups must be normally distributed and have equal variance.

None of the parameters had normal distributions or equal variance among the groups. Therefore, the nonparametric Kruskall‐Wallace test was selected with a Bonferonni post‐hoc pairwise comparison.

Table 7. Evaluation results for tests of normality and equal variance among groups.

Parameter Total Phosphorus Chlorophylla Secchi Depth

Data

Residuals1

Logs of Data Equal Variance?

Normally Distributed?

Equal Variance?

Residuals of Logs1

Equal Variance?1

Normally Distributed?2

Normally Distributed?

Equal Variance?

Normally Distributed?

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

No

1

Levene’s test Shapiro‐Wilks test

2

Pairwise comparisons for TP show the last three years being statistically higher than most other years 2001, 2002, 2005 and 2006. So, although the last three years are higher, these TP levels in the lake are not unprecedented. Chlorophyll‐a doesn’t follow the same patter as TP with 2012 statistically similar to all other years and only 2010 and 2011 being statistically higher than the lowest of the previous years.

Secchi depth follows chlorophyll‐a patterns suggesting that algal abundance is likely the primary driver for water clarity in Crosby Lake.

Trend Assessment

Exogenous Variables

Precipitation was evaluated as a potential factor affecting water quality trends in Crosby Lake (Figure 17). No relationship was found between monthly TP concentrations and monthly precipitation totals.

Seasonality and Autocorrelation

The majority of data collected for Crosby Lake were collected in the summer months which did not demonstrate statistical differences for TP or chlorophyll‐a but did have some differences for Secchi 14 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

(Figure 18). Because the three parameters are related, a non‐seasonally adjusted Kendall Tau is appropriate, but both should be evaluated for Secchi.

Crosby Lake demonstrated serial autocorrelation in any given year’s data set, but not between years (Figure 19). Consequently, serial autocorrelation needs to be accounted for in the trend assessment.

Trend Assessment

A Mann‐Kendall Tau test was positive for all three parameters with increasing trends in both TP and chlorophyll‐a and a seasonally adjusted decreasing trend in Secchi depth. The trend was also significant for the annual average data for all three parameters. Crosby Lake is trending toward poorer water quality.

One factor that may be affecting water quality for Crosby Lake is interaction with the Mississippi River.

Table 8 shows the number of days by year that the Mississippi River was at an elevation that would discharge to Crosby Lake (Elev. 697 feet). Although the Mississippi River interacts with Crosby Lake periodically over the past 15 years, the lake has received inputs from the River for the past 4 years with the Lake being flooded for 103 days in 2011. Similarly, in 2001 and the following year, water quality was poor following 63 days of inundation by the River. It appears likely that inundation from the Mississippi River is a significant factor affecting water quality in Crosby Lake.

Table 8. Annual days the Mississippi River is at an elevation that interacts with Crosby Lake (Wenck 2012).

Year Number of Days Mississippi River Interacts with Crosby Lake 1999 14 2000 0 2001 63 2002 0 2003 0 2004 0 2005 0 2006 19 2007 0 2008 0 2009 15 2010 36 2011 103 2012 10 15 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Multi‐Variate Assessment

The multivariate TSI approach suggests that Crosby Lake is not typically limited by P, but may be limited by other factors such as light or P‐availability (Figure 20). The graph suggests that not all of the TP in the water column is available for algal production and may be adhered to small particles such as clay or other TSS components. TP may be increasing in the lake, but it does not appear to all be readily available for algal production. Because there is a P surplus, other factors need to be considered in managing Crosby Lake including fisheries and submerged aquatic vegetation abundance.

Potential Divers of Water Quality

Crosby Lake Conclusions

1. Water quality in Crosby Lake’s three most recent years demonstrates an increase in total phosphorus and a decrease in water clarity. Algal abundance is high in 2010 and 2011, although water quality in 2012 was typical of previous years even though TP was higher. This suggests that water quality in Crosby Lake is degrading but that algal abundance is not necessarily controlled directly by TP (some fraction of phosphorus may be unavailable or zooplankton grazing may play a role).

2. Water clarity appears to be primarily driven by algal abundance.

3. Statistical trend testing verifies that water quality in Crosby Lake is trending poorer with increases in total phosphorus and chlorophyll‐a and decreases in water clarity. However, this may be a function of inundation by the Mississippi River which occurred for 164 days over the past 4 years.

Loeb Lake

Total phosphorus, chlorophyll‐a and Secchi depth were assessed for basic statistical assumptions such as normality, equal variance, and central tendencies (Table 9). Secchi depth is normally distributed for Loeb Lake. TP and chlorophyll‐a were not normally or log‐normally distributed. Variance for all three parameters was low.

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Table 9. General statistical description of Lake McCarrons water quality data.

Statistic No. of observations Minimum Maximum Range 1st Quartile Median 3rd Quartile Mean Variance (n-1) Standard deviation (n-1) Skewness (Pearson) Kurtosis (Pearson) Standard error of the mean Geometric mean Geometric standard deviation

TP (mg/L) 70 0.012 0.093 0.081 0.017 0.022 0.027 0.024 0.000 0.012 3.166 14.803 0.001 0.022 1.459

Chl-a (ug/L) 70 1.1 21.8 20.7 2.4 3.4 6.3 4.5 10.5 3.2 2.5 10.1 0.4 3.7 1.9

Secchi (m) 70 1.90 4.60 2.70 2.80 3.35 3.80 3.29 0.45 0.67 -0.25 -0.75 0.08 3.22 1.24

Loeb Lake does not demonstrate much variability in water quality between years (Figure 21 and 22).

2003 appears to have the worst water in the data record although the lake still met state water quality standards.

Annual Pairwise Comparisons

Data and residuals, including log transformations, for Loeb Lake was evaluated to test for normality and equal variance among the sample years (Table 8). To use parametric testing such as an ANOVA to test for differences among years, the test groups must be normally distributed and have equal variance.

Secchi depth was normally distributed in all years and demonstrated equal variance. Chlorophyll‐a was log‐normally distributed and logs had equal variance among the years. TP residuals were normally distributed and had equal variance among the groups. Therefore, the parametric GLM (ANOVA) test was selected with a Bonferonni post‐hoc pairwise comparison.

Table 8. Evaluation results for tests of normality and equal variance among groups.

Parameter Total Phosphorus

Data

Residuals1

Logs of Data

Equal Variance?1

Normally Distributed?2

Yes

No

Equal Variance?

Yes

Normally Distributed?

No

Equal Variance?

Yes

Residuals of Logs1 Normally Distributed?

Yes

Equal Variance?

Normally Distributed?

Yes

No

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

Chlorophylla Secchi Depth

Yes

No

Yes

Yes

Yes

No

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

1

Levene’s test Shapiro‐Wilks test

2

Pairwise comparisons for Loeb Lake suggest that there is some variability from year to year especially in TP, but water quality generally has remained consistent over the past 9 years. 2003, 2006, and 2012 were higher in TP than most other years but no differences were identified in chlorophyll‐a concentrations.

Trend Assessment

Exogenous Variables

Precipitation was evaluated as a potential factor affecting water quality trends in Loeb Lake (Figure 23).

No relationship was found between monthly TP concentrations and monthly precipitation totals.

Seasonality and Autocorrelation

The majority of data collected for Loeb Lake were collected in the summer months but there is some variability (Figure 24). Consequently, a seasonally adjusted Mann‐Kendall Tau should be applied.

Crosby Lake demonstrated serial autocorrelation in TP, but not in Secchi or chlorophyll‐a data (Figure 25). Autocorrelation is accounted for in TP, but not the other parameters.

Trend Assessment

No water quality trends were detected in Loeb Lake.

Multivariate Assessment

The multivariate TSI assessment for Loeb Lake suggests that the lake is typically P‐limited although zooplankton grazing may play a role in expected algal abundance (Figure 26).

Potential Drivers of Water Quality

Loeb Lake Conclusions

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Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

1. Water quality is fairly consistent in Loeb Lake with no trends detected in TP, chlorophyll‐a or Secchi depth.

2. Comparisons among years yield few differences with only TP showing some differences among years.

3. The multivariate TSI assessment suggests that Loeb Lake is a fairly typical P‐limited lake.

SUMMARY

Following is a summary of the results of the analysis.

Can the water quality of CRWD lakes be described as generally getting better or worse than was recorded in the past?

In general, water quality in CRWD lakes is fairly stable with a few demonstrating signs of eutrophication.

Lake McCarron demonstrates improved water quality as a direct result of the alum treatment conducted in 2004. Although the alum treatment visually demonstrates some signs of weakening, no statistical trends were identified suggesting that water quality is degrading. Como Lake demonstrates a cyclical pattern in water quality that is likely directly tied to changes in submerged aquatic vegetation and zooplankton abundance. Total phosphorus concentrations in Como Lake appear to be improving. Water quality in Crosby Lake appears to be degrading with higher TP and chlorophyll‐a concentrations resulting in decreased water clarity. Water quality in Loeb Lake appears to be stable with relatively good water quality.

What trends in water quality exist? Can these trends be verified through statistical methods?

Statistical methods applied to CRWD lake water quality demonstrated relatively stable water quality in the lakes except for Crosby Lake. Lake McCarrons had no significant trends prior to or after the alum treatment suggesting that water quality is stable in the lake. Detecting statistical trends in water quality in Como Lake is very difficult due to the complex interactions of vegetation and zooplankton on water quality. Although statistical results were weak, total phosphorus concentrations appear to be improving suggesting that other factors are controlling water clarity. Crosby Lake demonstrates a statistically significant trend toward poorer water quality with increased phosphorus and chlorophyll‐a concentrations and decreased water clarity. Loeb Lake remains stable.

What factors are driving the trends in water quality among the different lakes?

The lakes demonstrated a variety of factors controlling water quality. Both Lake McCarrons and Loeb Lake appear to be phosphorus limited lakes where nutrient controls remain the best approach for controlling eutrophication. Both Crosby Lake and Como Lake are more typical shallow lakes that 19 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

demonstrate other factors affecting water quality including vegetation, zooplankton and fish abundance. Crosby Lake is further complicated by its connection to the Minnesota River which has the potential to bring in large quantities of sediment and nutrients during flood periods. The degrading water quality trend in Crosby Lake is most likely attributed to flooding frequency since there are no apparent changes in the watershed that lead to additional nutrient loading.

What qualitative statements can be made regarding the causes and effects in the observed water quality trends?

Lakes in the CRWD watershed have relatively stable water quality; however both Como Lake and Crosby Lake are sensitive to factors other than nutrient loading including submerged vegetation, zooplankton and fish abundance. Crosby Lake has the additional pressures of nutrient and sediment loading from the Minnesota River. Monitoring and managing biological conditions in these two lakes is critical to successfully improving and maintain water quality. For Crosby Lake, managing the input of sediment and nutrients from the Minnesota River could stabilize water quality, although managing flood water inputs is very difficult. It may take direct management such as alum addition or other phosphorus inactivation to be effective. Long term nutrient load management is effective for both Loeb and McCarrons Lake. The long term effectiveness of the McCarrons Lake alum treatment poses the greatest risk for water quality degradation in the lake.

What monitoring recommendations can be made to improve assessing lake conditions in the CRWD? How should lake health be assessed moving forward?

For the two deep lakes, continuing the current monitoring (TP, chlorophyll‐a, and Secchi plus field parameters) is sufficient for assessing the health of the lake. Monitoring of the phytoplankton and zooplankton communities provide some insight into the health of the lake too, but are not critical. For the shallow lakes, the standard water quality parameters are important, but so is the submerged aquatic vegetation community. The best measure of healthy shallow lake is the clarity of the water and the diversity and robustness of the submerged aquatic vegetation community. So, annual (or every few years) vegetation surveys are critical in assessing lake health. Zooplankton, phytoplankton, and fish surveys can be useful in assessing mechanisms controlling water quality.

Following is a description of the analytical results for each of the lakes.

Lake McCarrons

Lake McCarrons is a deep lake that received an alum treatment in 2004. Watershed BMPs have also been introduced over the periods of record, specifically the Villa Parks wetland complex. Water quality improved significantly after the alum treatment with reduced TP and chlorophyll‐a and increased Secchi depth. Prior to the alum treatment, no trends were identified in water quality suggesting that conditions were fairly stable. After the alum treatment, water quality improved greatly over a 3 to 4 year period; 20 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013

however recent data is demonstrating that the effectiveness of the alum treatment may be diminishing although no water quality trend was detected.

Como Lake

Como Lake, a shallow lake, demonstrates a cyclical pattern in water quality that may be related to other factors such as a boom‐bust fishery. The pattern should be explored further in relation to fish and zooplankton data. Como Lake did have a significant decreasing trend in TP, although statistical testing among years could not pick up the differences. There may be a long term, slow decrease in TP concentrations, albeit a very small one. Water clarity appears to be affected by factors beyond algal abundance, but the lake is phosphorus limited.

Crosby Lake

Although water quality in Crosby Lake is fairly good, water quality is decreasing in the lake over the past 13 years. Total phosphorus and chlorophyll‐a had significant increasing trends while Secchi depth had a significant decreasing trend. Water clarity followed a similar trend as algal abundance suggesting algal abundance is the primary factor controlling water clarity.

Loeb Lake

Overall, Loeb Lake demonstrated consistent water quality over the period of record with little to no variation in chlorophyll‐a or Secchi depth. Loeb Lake appears to be a P‐limited lake that has not experienced any major changes in water quality in the past 9 years.

REFERENCES

Wenck Associates Inc. 2012. Crosby Lake Management Plan. Report to the Capitol Region Watershed District.

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January 15, 2014 CAC Meeting V) District Initiatives B) Audubon Certification Program (Herbst)

DATE: TO: FROM: RE:

January 15, 2013 CRWD Board of Managers Stephanie Herbst, Water Resources Technician 2013 Audubon Monitoring Purpose, Procedure, and Results

Background The Audubon Cooperative Sanctuary Program for Golf (ACSP) is an education and certification program developed by Audubon International that seeks to minimize the potentially harmful impacts of golf course operations. Golf courses that choose to partake in the program are held responsible to implement a plan that will address key environmental components. As members of the Sanctuary Program, Como Golf Course and Highland Golf Course are responsible for implementing a set of environmental management practices that target six key areas: environmental planning, wildlife and habitat management, chemical use reduction and safety, water conservation, water quality management, and outreach and education.

Documentation is required, and designation as a Certified Audubon Cooperative Sanctuary is awarded by Audubon International upon meeting environmental management standards in each area.

In 2012, Capitol Region Watershed District (CRWD) entered verbal agreements with the Highland Golf Course and the Como Golf Course stating that CRWD would lead efforts for the golf courses’ water quality monitoring programs. A Guide to Environmental Stewardship on the Golf Course, the official guide for the Audubon Cooperative Sanctuary Program, describes the purpose and procedure of water quality monitoring. As outlined in the guide, CRWD collected samples once a month for four months (JuneSeptember) that were analyzed for physical characteristics and nutrient concentrations.

Issues Based on the 2013 data, the parameter of greatest concern for both golf courses is total phosphorus (TP). Total phosphorus relates to dissolved oxygen (DO) because an excessive amount of TP could lead to eutrophication, a process in which excessive aquatic growth depletes oxygen supply.

According to A Guide to Environmental Stewardship on the Golf Course, baseline testing should be conducted four times per year during the first two years. 2013 marks the end of the baseline testing. For future years, sampling twice a year is considered sufficient, unless problems such as algae blooms, fish kills, or unusual wildlife behavior arise.

Action Requested None. Information only. enc:

Final Draft – Como Golf Course Audubon Monitoring 2013 (w/appendix) Final Draft – Highland Golf Course Audubon Monitoring 2013 (w/appendices)

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Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District.

Capitol Region Watershed District Citizen Advisory Committee 2014 Agenda Plan CAC Meeting Date

Action Items and Items for Review/Comment Requested by Board of Managers

Project and Program Updates

January 15, 2014 February 12, 2014 March 12, 2014 April 9, 2014 May 14, 2014 June 11, 2014 July 16, 2014 August 13, 2014 September 10, 2014 October 8, 2014 November 12, 2014 December 10, 2014 Updated: December 11, 2013

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