November 6, 2013 board packet by Capitol Region Watershed District

Regular Meeting of the Capitol Region Watershed District (CRWD) Board Of Managers, for Wednesday, November 6, 2013 6:00 p.m. at the office of the CRWD, 1410 Energy Park Drive, Suite 4, St. Paul, Minnesota. REGULAR MEETING AGENDA

Materials Enclosed

Call to Order of Regular Meeting (President Joe Collins) A) Attendance C) Review, Amendments and Approval of the Agenda

II.

Public Comment – For Items not on the Agenda (Please observe a limit of three minutes per person.)

III.

Permit Applications and Program Updates (Permit Process: 1) Staff Review/Recommendation, 2) Applicant Response, 3) Public Comment, and 4) Board Discussion and Action.) A) Permit # 13-019 Hamline Station (Kelley) B) Permit # 13-028 Loomis Armored Transport (Kelley) C) Permit # 13-030 Western U Plaza (Kelley) D) Permit # 13-031 US Bank Demolition (Kelley) E) Permit Program/Rules Update (Kelley)

IV.

Special Reports A) Summary and Analysis of Water Quality Data from the Capitol Region Watershed District’s Stormwater Monitoring Program, 2005-2012, Benjamin D.Janke, Ph.D, University of Minnesota B) Statistical Analysis of Lake Data in the Capitol Region Watershed District, Joe Bischoff, Wenck Associates, Inc.

Action Items A) AR: Approve Minutes of the October 16, 2013 Regular Meeting (Sylvander) B) AR: Approve Contract Amendment #4 with Wenck Associates Inc. for the Highland Ravine Project (Eleria) C) AR: Establish the Monitoring, Research and Maintenance Division (Doneux) D) AR: Approve Program Manager III Position (Doneux) E) AR: Approve 2014 Employee Health Insurance Program (Doneux)

VI.

Unfinished Business A. FI: Inspiring Communities Program Update (Eleria and Castro)

VII.

General Information A) Administrator’s Report

VIII. Next Meeting A) Wednesday, November 20, 2013 Meeting Agenda Review IX. Adjournment W:\04 Board of Managers\Agendas\2013\November 6, 2013 Agenda Regular Mtg.docx

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

Capitol Region Watershed District Applicant:

Chris Dettling PPL, Inc. 1035 East Franklin Avenue Minneapolis, MN 55404

Permit 13-019 Hamline Station Consultant: David Bade Westwood Professional Services 7699 Anagram Drive Eden Prairie, Minnesota 55344

Description: Construction of a new Commercial/Residential redevelopment at the former Midway Chevrolet Property at Hamline and University Stormwater Management: Underground infiltration gallery District Rule: C, D, F, Disturbed Area: 2.0 Acres Impervious Area: 1.84 Acres Recommendation: Approve with 5 Conditions 1. Receipt of $9,200 surety and signed maintenance agreement. 2. Submit a copy of NPDES permit. 3. Remove geotextile fabric from bottom of infiltration system detail on Sheet C6. Geotextile shall be placed on top and sides only. 4. Specify non-limestone rock for the clean washed angular aggregate surrounding the StormTech system 5. Revise detail GRD-13 on Sheet C6. The metal posts installed 36â&#x20AC;? deep at the paver interface have potential to punct ure the impermeable liner beneath the structural soil, and dislodge pavers. Provide alternative tree protection fence anchoring device such as sand bags on cross members or other alternative approved by City of St. Paul and CRWD.

Hamline Avenue University Avenue

Permit Location Permit 13-019

Aerial Photo Board Meeting: 11/06/13

Capitol Region Watershed District Permit Report CRWD Permit #:

13-019

Review date:

October 29, 2013

Project Name:

Hamline Station

Applicant:

Chris Dettling PPL, Inc. 1035 East Franklin Ave. Minneapolis, MN 55404

Purpose:

Redevelopment of the former Midway Chevrolet.

Location:

North side of University Avenue between Hamline Ave and Syndicate St.

Applicable Rules:

C, D, and F

Recommendation:

Approve with 5 Conditions

EXHIBITS: 1. Stormwater Management Report, by RLK, dated 10/28/13, recd. 10/28/13. 2. CRWD Volume Control Worksheet, recd. 6/19/13. 3. Declaration for Maintenance of Stormwater Facilities (unsigned), not dated, recd. 6/19/13. 4. Project plans (C1-C6, L1, L2), by ESG and Westwood, dated 10/3/13, recd. 10/28/13. HISTORY & CONSIDERATIONS: None. RULE C: STORMWATER MANAGEMENT Standards  Proposed discharge rates for the 2-, 10-, and 100-year events shall not exceed existing rates.  Developments and redevelopments must reduce runoff volumes in the amount equivalent to an inch of runoff from the impervious areas of the site.  Stormwater must be pretreated before discharging to infiltration areas to maintain the long-term viability of the infiltration area.

W:\07 Programs\Permitting\2013\13-019 Hamline Station\13-019 Permit_Review3.doc

Page 1 of 4

 Developments and redevelopments must incorporate effective non-point source pollution reduction BMPs to achieve 90% total suspended solid removal. Findings 1. A hydrograph method based on sound hydrologic theory is used to analyze runoff for the design or analysis of flows and water levels. 2. Runoff rates for the proposed activity do not exceed existing runoff rates for the 2-, 10-, and 100-year critical storm events. Stormwater leaving the project area is discharged into a well-defined receiving channel or pipe and routed to a public drainage system. 3. Stormwater runoff volume retention is achieved onsite in the amount equivalent to the runoff generated from one inch of rainfall over the impervious surfaces of the development. a. The amount of proposed impervious onsite is 80,355 square feet. b. Volume retention: Volume Retention Required (cu. ft.) Volume Retention Provided (cu. ft.) 6,027 Underground Storage 6,477

c. Banking of excess volume retention is not proposed. d. Infiltration volume and facility size has been calculated using the appropriate hydrological soil group classification and design infiltration rate. e. The infiltration area is capable of infiltrating the required volume within 48 hours. f. Stormwater runoff is pretreated to remove solids before discharging to filtration areas. 4. Alternative compliance sequencing has not been requested. 5. The proposed underground storage system achieves 90% total suspended solids removal from the runoff generated on an annual basis. 6. A recordable executed maintenance agreement has not been submitted. RULE D: FLOOD CONTROL Standards  Compensatory storage shall be provided for fill placed within the 100-year floodplain.  All habitable buildings, roads, and parking structures on or adjacent to a project site shall comply with District freeboard requirements. Findings 1. There is no floodplain on the property according to FEMA. 2. All habitable buildings, roads, and parking structures on or adjacent to the project site comply with CRWD freeboard requirements.

W:\07 Programs\Permitting\2013\13-019 Hamline Station\13-019 Permit_Review3.doc

Page 2 of 4

RULE E: WETLAND MANAGEMENT Standard  Wetlands shall not be drained, filled (wholly or in part), excavated, or have sustaining hydrology impacted such that there will be a decrease in the inherent (existing) functions and values of the wetland.  A minimum buffer of 25 feet of permanent nonimpacted vegetative ground cover abutting and surrounding a wetland is required. Findings 1. There are no known wetlands located on the property. RULE F: EROSION AND SEDIMENT CONTROL Standards  A plan shall demonstrate that appropriate erosion and sediment control measures protect downstream water bodies from the effects of a landdisturbing activity.  Erosion Control Plans must adhere to the MPCA Protecting Water Quality in Urban Areas Manual. Findings 1. Erosion and sediment control measures are consistent with best management practices, as demonstrated in the MPCA manual Protecting Water Quality in Urban Areas. 2. Adjacent properties are protected from sediment transport/deposition. 3. Wetlands, waterbodies and water conveyance systems are protected from erosion/sediment transport/deposition. 4. Project site is greater than 1 acre; an NPDES permit is required. RULE G: ILLICIT DISCHARGE AND CONNECTION Standard  Stormwater management and utility plans shall indicate all existing and proposed connections from developed and undeveloped lands for all water that drains to the District MS4. Findings 1. New direct connections or replacement of existing connections are not proposed. 2. Prohibited discharges are not proposed.

RECOMMENDATION: Approve with 5 Conditions Conditions: 1. Receipt of $9,200 surety and documentation of recorded maintenance agreement. 2. Submit a copy of NPDES permit.

W:\07 Programs\Permitting\2013\13-019 Hamline Station\13-019 Permit_Review3.doc

Page 3 of 4

3. Remove geotextile fabric from bottom of infiltration system detail on Sheet C6. Geotextile shall be placed on top and sides only. 4. Specify non-limestone rock for the clean washed angular aggregate surrounding the StormTech system 5. Revise detail GRD-13 on Sheet C6. The metal posts installed 36â&#x20AC;? deep at the paver interface have potential to puncture the impermeable liner beneath the structural soil, and dislodge pavers. Provide alternative tree protection fence anchoring device such as sand bags on cross members or other alternative approved by City of St. Paul and CRWD.

W:\07 Programs\Permitting\2013\13-019 Hamline Station\13-019 Permit_Review3.doc

Page 4 of 4

LEGEND

UTILITY NOTES

PROPOSED WEST BUILDING FFE=925.0-924.0 (SLOPED FLOOR)

PROPOSED EAST BUILDING FFE=924.0

1309 HOUSING 1311-1337 RETAIL

1305 HOUSING

PROPOSED

EXISTING

Capitol Region Watershed District Applicant:

Permit Application 13-028 Loomis Armored Transport

Herbert Tousley Ironton Management 332 Minnesota Street, Suite W2300 St. Paul, MN 55101

Consultant:

Mike Kettler Sunde Engineering 10830 Nesbitt Avenue Bloomington, MN 55437

Description: Construction of a new building and parking lot within the Beacon Bluff redevelopment. Stormwater Management: Stormwater pretreatment pond and filtration bench District Rule: C, D, and F Disturbed Area: 3.2 Acres Impervious Area: 3.52 Acres

RECOMMENDATION: Approve with 3 Conditions

Forest St

1. Receipt of $17,600 surety and documentation of recorded maintenance agreement. 2. Provide a copy of the NPDES permit. 3. Revise pond outlet #4 in the HydroCAD model. Currently, the filtration draintile is modeled as a 6-inch orifice which results in a flow rate of 1.73 cfs during the 100-year event. Assuming a 1.0 in/hr filtration rate, however, results in a peak â&#x20AC;&#x153;filter flowâ&#x20AC;? of 0.1 cfs based on a filter area of 4,546 square feet. Adjust high water and overflow elevations as necessary.

Ea s

Permit Location Permit Report 13-028

nth e v Se

eet r t S

Aerial Photo November 6, 2013 Board Meeting

Capitol Region Watershed District Permit Report CRWD Permit #:

13-028

Review date:

October 28, 2013

Project Name:

Loomis Armored Transport

Applicant:

Mr. Herbert Tousley Ironton Management 332 Minnesota St, Suite W2300 St. Paul, MN 55401

Purpose:

Construction of new building, parking lot, and filtration pond

Location:

North of the intersection of East Seventh Street and Cypress Street.

Applicable Rules:

C, D, and F

Recommendation:

Approve with 3 Conditions

EXHIBITS: 1. Stormwater Management Calculations, by Sunde Engineering, PLLC., dated 10/28/13, recd. 10/28/13. 2. Schematic Design Plans (sheets C1, C2, C3, C4, C5, C6, and C7), by Sunde Engineering, dated 10/28/13, recd. 10/28/13. HISTORY & CONSIDERATIONS: None. RULE C: STORMWATER MANAGEMENT Standards  Proposed discharge rates for the 2-, 10-, and 100-year events shall not exceed existing rates.  Developments and redevelopments must reduce runoff volumes in the amount equivalent to an inch of runoff from the impervious areas of the site.  Stormwater must be pretreated before discharging to infiltration areas to maintain the long-term viability of the infiltration area.  Developments and redevelopments must incorporate effective non-point source pollution reduction BMPs to achieve 90% total suspended solid removal.

W:\07 Programs\Permitting\2013\13-028 Loomis Amored Transport\13-028 Permit_Review3.doc

Page 1 of 4

Findings 1. A hydrograph method based on sound hydrologic theory is used to analyze runoff for the design or analysis of flows and water levels. 2. Runoff rates for the proposed activity do not exceed existing runoff rates for the 2-, 10-, and 100-year critical storm events. Stormwater leaving the project area is discharged into a well-defined receiving channel or pipe and routed to a public drainage system. 3. Stormwater runoff volume retention is not achieved onsite in the amount equivalent to the runoff generated from one inch of rainfall over the impervious surfaces of the development. a. The amount of proposed impervious onsite is 181,674 square feet. b. Volume retention: Volume Retention Required (cu. ft.) Volume Retention Provided (cu. ft.) 13,625 None, filtration is proposed. c. Filtration is proposed due to contaminated soils: Volume Retention Required (cu. ft.) Volume Retention Provided (cu. ft.) 17,713 18,984 d. Banking of excess volume retention is not proposed. e. Filtration volume and facility size has been calculated using the appropriate hydrological soil group classification and design filtration rate. f. The filtration areas are capable of filtering the required volume within 48 hours. g. Stormwater runoff is pretreated to remove solids before discharging to filtration areas. 4. Alternative compliance sequencing has not been requested. 5. Best management practices achieve 90% total suspended solids removal on an annual basis. 6. A recordable executed maintenance agreement has not been submitted. RULE D: FLOOD CONTROL Standards ď&#x192;&#x2DC; Compensatory storage shall be provided for fill placed within the 100-year floodplain. ď&#x192;&#x2DC; All habitable buildings, roads, and parking structures on or adjacent to a project site shall comply with District freeboard requirements. Findings 1. There is no floodplain on the property according to FEMA. 2. All habitable buildings, roads, and parking structures on or adjacent to the project site comply with CRWD freeboard requirements.

W:\07 Programs\Permitting\2013\13-028 Loomis Amored Transport\13-028 Permit_Review3.doc

Page 2 of 4

W:\07 Programs\Permitting\2013\13-028 Loomis Amored Transport\13-028 Permit_Review3.doc

Page 3 of 4

100-year event. Assuming a 1.0 in/hr filtration rate, however, results in a peak â&#x20AC;&#x153;filter flowâ&#x20AC;? of 0.1 cfs based on a filter area of 4,546 square feet. Adjust high water and overflow elevations as necessary.

W:\07 Programs\Permitting\2013\13-028 Loomis Amored Transport\13-028 Permit_Review3.doc

Page 4 of 4

Capitol Region Watershed District

Applicant:

Permit Application 13-030 Western U Plaza

St. Paul Old Home Plaza, LLC PO Box 727, 366 South Tenth Avenue Waite Park, MN 556387

Consultant:

Robert Wiegert Paramount Engineering 1440 Arcade Street North St. Paul, MN 55106

Description: Redevelopment and reuse of former Old Home property at Western and University Stormwater Management: Underground infiltration District Rule: C,D, and F Disturbed Area: 1.6 Acres Impervious Area: 1.03 Acres

1. Provide documentation that the maintenance agreement has been recorded with Ramsey County. 2. Remove geotextile fabric from bottom of infiltration system detail on Sheets C6 and C7. Geotextile shall be placed on top and sides only. 3. Specify non-limestone rock for the clean washed angular aggregate surrounding the StormTech system. 4. Revise HydroCAD model to include the portion of Area 4 (new building) that is draining to the intersection of University Ave and Virginia Street. 5. Remove the 6â&#x20AC;? drain tile from the underground infiltration system. VOLUME BANK RECOMMENDATION: Approve creation of a volume bank for the Sand Companies and deposit of 4,844 cubic feet of volume reduction credits.

Western Avenue

University Avenue

Permit Location Permit Report 13-030

Aerial Photo November 6, 2013 Board Meeting

Capitol Region Watershed District Permit Report CRWD Permit #:

13-030

Review date:

October 28, 2013

Project Name:

Western U Plaza

Applicant:

St. Paul Old Home Plaza, LLC PO Box 727, 366 South Tenth Avenue Waite Park, MN 56387-0727

Purpose:

Demolition of a portion of existing building and addition of parking structure, apartment complex, and underground infiltration system.

Location:

Southeast corn of the intersection of University Avenue West and Western Avenue.

Applicable Rules:

C, D, E, and F

Recommendation:

Approve with 5 Conditions

Volume Bank Recommendation: Approve creation of a volume bank for the Sand Companies and deposit of 4,844 cubic feet of volume reduction credits. EXHIBITS: 1. Western U Plaza Storm Water Management Plan (includes Narrative, Figure 1.1, HydroCAD model, volume control worksheet, and Geotechnical Evaluation Report by Sand Companies), by MSA Professional Services, dated 9/24/13, recd. 9/25/13. 2. Western U Plaza Storm Water Management Plan, by MSA Professional Services, dated 10/21/13, recd. 10/24/13. 3. Schematic Design Plans (sheets C1, C2, C.3, C4, C5, C6, C7), by Paramount Engineering & Design, dated 10/9/13, recd. 10/24/13. HISTORY & CONSIDERATIONS: Storage in excess of the required volume control is proposed, but no additional phases of development are suggested. If further development on-site is proposed, CRWD will view

W:\07 Programs\Permitting\2013\13-030 Western U Plaza\13-030 Permit_Review_02.doc

Page 1 of 4

it as “common scheme of development” and new impervious area that is subject to Capitol Region Watershed District regulation even though the specific development may be less than one (1) acre of disturbed area. RULE C: STORMWATER MANAGEMENT Standards  Proposed discharge rates for the 2-, 10-, and 100-year events shall not exceed existing rates.  Developments and redevelopments must reduce runoff volumes in the amount equivalent to an inch of runoff from the impervious areas of the site.  Stormwater must be pretreated before discharging to infiltration areas to maintain the long-term viability of the infiltration area.  Developments and redevelopments must incorporate effective non-point source pollution reduction BMPs to achieve 90% total suspended solid removal. Findings 1. A hydrograph method based on sound hydrologic theory is used to analyze runoff for the design or analysis of flows and water levels. 2. Runoff rates for the proposed activity do not exceed existing runoff rates for the 2-, 10-, and 100-year critical storm events. Stormwater leaving the project area is discharged into a well-defined receiving channel or pipe and routed to a public drainage system. 3. Stormwater runoff volume retention is achieved onsite in the amount equivalent to the runoff generated from one inch of rainfall over the impervious surfaces of the development. a. The amount of proposed impervious onsite is 45,041 square feet. b. Volume retention: Volume Retention Required (cu. ft.) Volume Retention Provided (cu. ft.) 3,378 BMP Volume Below Underground 8,222 cf c. Banking of 4,884 cubic feet of excess volume retention has been requested. d. Infiltration volume and facility size has been calculated using the appropriate hydrological soil group classification and design infiltration rate. e. The infiltration area is capable of infiltrating the required volume within 48 hours. f. Stormwater runoff is pretreated to remove solids before discharging to infiltration areas. 4. Alternative compliance sequencing has not been requested. 5. Best management practices achieve 90% total suspended solids removal from the runoff on an annual basis. 6. A recordable executed maintenance agreement has not been submitted.

W:\07 Programs\Permitting\2013\13-030 Western U Plaza\13-030 Permit_Review_02.doc

Page 2 of 4

RULE D: FLOOD CONTROL Standards  Compensatory storage shall be provided for fill placed within the 100-year floodplain.  All habitable buildings, roads, and parking structures on or adjacent to a project site shall comply with District freeboard requirements. Findings 1. There is no floodplain on the property according to FEMA. 2. All habitable buildings, roads, and parking structures on or adjacent to the project site comply with CRWD freeboard requirements. RULE E: WETLAND MANAGEMENT Standard  Wetlands shall not be drained, filled (wholly or in part), excavated, or have sustaining hydrology impacted such that there will be a decrease in the inherent (existing) functions and values of the wetland.  A minimum buffer of 25 feet of permanent nonimpacted vegetative ground cover abutting and surrounding a wetland is required. Findings 1. There are no known wetlands located on the property. RULE F: EROSION AND SEDIMENT CONTROL Standards  A plan shall demonstrate that appropriate erosion and sediment control measures protect downstream water bodies from the effects of a landdisturbing activity.  Erosion Control Plans must adhere to the MPCA Protecting Water Quality in Urban Areas Manual. Findings 1. Erosion and sediment control measures are consistent with best management practices, as demonstrated in the MPCA manual Protecting Water Quality in Urban Areas. 2. Adjacent properties are protected from sediment transport/deposition. 3. Wetlands, waterbodies and water conveyance systems are protected from erosion/sediment transport/deposition. 4. Project site is greater than 1 acre; an NPDES permit is required. RULE G: ILLICIT DISCHARGE AND CONNECTION Standard  Stormwater management and utility plans shall indicate all existing and proposed connections from developed and undeveloped lands for all water that drains to the District MS4.

W:\07 Programs\Permitting\2013\13-030 Western U Plaza\13-030 Permit_Review_02.doc

Page 3 of 4

Findings 1. New direct connections or replacement of existing connections are not proposed. 2. Prohibited discharges are not proposed. RECOMMENDATION: Approve with 5 Conditions Conditions: 1. Provide documentation that the maintenance agreement has been recorded with Ramsey County. 2. Remove geotextile fabric from bottom of infiltration system detail on Sheets C6 and C7. Geotextile shall be placed on top and sides only. 3. Specify non-limestone rock for the clean washed angular aggregate surrounding the StormTech system. 4. Revise HydroCAD model to include the portion of Area 4 (new building) that is draining to the intersection of University Ave and Virginia Street. 5. Remove the 6” drain tile from the underground infiltration system. Note: Storage in excess of the required volume control is proposed, but no additional phases of development are suggested. If further development on site is proposed, CRWD will view it as “common scheme of development” and new impervious area that is subject to Capitol Region Watershed District regulation even though the specific development may be less than one (1) acre of disturbed area. VOLUME BANK RECOMMENDATION Approve creation of a volume bank for the Sand Companies and deposit of 4,844 cubic feet of volume reduction credits.

W:\07 Programs\Permitting\2013\13-030 Western U Plaza\13-030 Permit_Review_02.doc

Page 4 of 4

Capitol Region Watershed District Applicant:

Permit Application 13-031 US Bank Demolition

Scott Belsaas Shepard Development, LLC 1999 Shepard Road St. Paul, MN 55116

Consultant:

Barry Jaeger Jaeger Construction 2317 Waters Drive Mendota Heights, MN 55120

Description: Demolition of the US Bank building at 2751 Shepard Road Stormwater Management: None, Erosion Control Permit Only District Rule: F Disturbed Area: 8.73 Acres Impervious Area: None Proposed

RECOMMENDATION: Approve with 3 Conditions 1. Receipt of $17,460 surety. 2. Provide a copy of the NPDES permit. 3. Identify locations of material stockpiles and required perimeter controls to contain stockpiled materials.

Western Avenue

University Avenue

Permit Location Permit Report 13-031

Aerial Photo November 6, 2013 Board Meeting

Capitol Region Watershed District Permit Report CRWD Permit #:

13-031

Review date:

October 31, 2013

Project Name:

US Bank Demolition

Applicant:

Scott Belsaas Shepard Development, LLC 1999 Shepard Road St. Paul, MN

Purpose:

Demolition of US Bank Building and restoration to vegetation

Location:

2751 Shepard Road, west of Davern Street.

Applicable Rules:

Recommendation:

Approve with 3 Conditions

EXHIBITS: 1. Erosion and Sediment Control Plan by BKBM, dated 10/15/13, recd 10/16/13 HISTORY & CONSIDERATIONS: None.

RULE F: EROSION AND SEDIMENT CONTROL Standards ď&#x192;&#x2DC; A plan shall demonstrate that appropriate erosion and sediment control measures protect downstream water bodies from the effects of a landdisturbing activity. ď&#x192;&#x2DC; Erosion Control Plans must adhere to the MPCA Protecting Water Quality in Urban Areas Manual. Findings 1. Erosion and sediment control measures are consistent with best management practices, as demonstrated in the MPCA manual Protecting Water Quality in Urban Areas. 2. Adjacent properties are protected from sediment transport/deposition.

W:\07 Programs\Permitting\2013\13-031 US Bank Demolition\13-031 Permit_Review_01.doc

Page 1 of 2

3. Wetlands, waterbodies and water conveyance systems are protected from erosion/sediment transport/deposition. 4. Project site is greater than 1 acre; an NPDES permit is required.

RECOMMENDATION: Approve with 3 Conditions Conditions: 1. Receipt of $17,460 surety. 2. Provide a copy of the NPDES permit. 3. Identify locations of materials stockpiles and required perimeter controls to contain stockpiled materials.

W:\07 Programs\Permitting\2013\13-031 US Bank Demolition\13-031 Permit_Review_01.doc

Page 2 of 2

U.S. BANK BUILDING DEMOLITION ST. PAUL, Minnesota

NOT FOR CONSTRUCTION No. Revisions Description

Date

I hereby certify that this plan, specification or report was prepared by me or under my direct supervision and that I am a duly Licensed Professional Engineer under the laws of the state of Minnesota.

Date

10-15-2013

DATE PROJECT # PROJECT STATUS

Eric T. Luth

Lic. No.

50475

10-15-2013 14117 CD

DRAWN BY

ETL

CHECKED BY

KAM

“

EROSION CONTROL PLAN

“

C1.0

” C

2013 BKBM Professional Engineers, Inc. All rights reserved. This document is an instrument of service and is the property of BKBM Professional Engineers, Inc. and may not be used or copied without prior written consent.

November 6, 2013 Board Meeting IV. Special Reports—A) Summary of 2005-2012 Monitoring Data by Dr. Ben Janke (Janke)

DATE: TO: FROM: RE:

October 31, 2013 CRWD Board of Managers Britta Suppes, Monitoring Coordinator Summary and Analysis of Water Quality Data from the Capitol Region Watershed District’s Stormwater Monitoring Program, 2005-2012, Benjamin D.Janke, Ph.D, University of Minnesota

Background Since 2005, CRWD has been collecting and analyzing water quality data through the District Monitoring Program. With over eight years of data, CRWD determined that additional analysis of the robust data set was needed to identify long-term trends. In January 2013, CRWD contracted with Dr. Jacques Finlay and Dr. Ben Janke at the University of Minnesota to perform additional analyses of CRWD monitoring data. The final deliverable by Dr. Janke is a comprehensive report titled “Summary and Analysis of Water Quality Data from CRWD’s Stormwater Monitoring Program, 2005-2012”. The objectives of the analyses and report were to: (1) Investigate spatial and seasonal patterns in water yields and concentrations of nutrient and metals (2) Understand the impact of storm even characteristics (e.g. rainfall depth, antecedent dry days or rainfall) on loading of water and nutrients (3) Investigate the impact on water and nutrient loading of differences in land cover and drainage characteristics among monitored sub-watersheds (4) Determine exceedence probabilities of water yields and nutrient loads (5) Quantify probabilities and seasonality of metal toxicity exceedences The primary goals of these analyses were to better understand water and nutrient loading patterns in the watershed, inform the design of future stormwater BMPs, and aid in the development of TMDLs or water quality goals for the CRWD’s lakes and streams. The analyses provide methods that may be used to compare future monitoring seasons to data from the summary period (2005-2012). A summary has also been included of major patterns in spatial and seasonal variability among monitored sub-watersheds, which may help identify seasons and/or specific sub-watersheds or BMPs that may be crucial for managing water quality in the CRWD. Issues Dr. Janke has analyzed the 2005-2012 monitoring data and has completed a final draft report summarizing water quality data and will present and review the report with the Board of Managers. Requested Action None, information only. enc: Final Draft— Summary and Analysis of Water Quality Data from CRWD’s Stormwater Monitoring Program, 2005-2012 (w/o appendices) W:\07 Programs\Monitoring & Data Acquisition\2012 Monitoring\2012 Annual Report\UMN-Ben Janke Report 2012\Brd Memo Ben Janke Report 11-6-13.docx

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

FINAL DRAFT

Prepared for the Capitol Region Watershed District by: Benjamin D. Janke, Ph.D Department of Ecology, Evolution, and Behavior University of Minnesota Saint Paul, MN, USA

Oct 27, 2013

Table of Contents 1. Introduction ........................................................................................................................... 4 List of Analyses .................................................................................................................................... 5

2. Data Collection and Methods ........................................................................................... 7 2.1. Data Collection ............................................................................................................................ 7 2.2. Methods.......................................................................................................................................... 8 2.2.1. Land Cover and Drainage Characteristics ................................................................................8 2.2.2. Stormflow and Baseflow Water Yields ................................................................................... 12 2.2.3. Statistical Methods for Yield and Concentration Data ..................................................... 12 2.2.4. Cumulative Loading and Cumulative Rainfall Frequency .............................................. 14 2.2.5. Metals Toxicity ................................................................................................................................. 15

3. Results ................................................................................................................................... 12 3.1. Characterization of CRWD Sub-watersheds................................................................... 17 3.1.1. Land Cover and Drainage Characteristics ............................................................................. 17 3.1.2. Sub-watershed Stormflow and Baseflow Water Yields................................................... 17 3.1.3. Stormflow Response ...................................................................................................................... 20 3.2. Seasonal and Spatial Patterns in Water, Nutrients, and Metals ............................. 22 3.2.1. Stormflow Concentrations of Nutrients, TSS, Chloride, and Metals........................... 22 3.2.2. Baseflow Concentrations of Nutrients, TSS, Chloride, and Metals ............................. 23 3.2.3. Seasonal Differences in Nutrient and Metal Concentrations ........................................ 23 Stormflow........................................................................................................................................................ 24 Baseflow .......................................................................................................................................................... 25 3.2.4. Cumulative Water Volume and Nutrient Loading -- Stormflow .................................. 30 3.2.1. Cumulative Water Volume and Nutrient Loading -- Baseflow ..................................... 32 Cumulative Baseflow Loading â&#x20AC;&#x201C; Annual .............................................................................................. 36 3.3. Impact of Storm Event Characteristics on Water and Nutrient Loading ............. 37 3.3.1. Cumulative Rainfall Frequency and Runoff Volume......................................................... 37 3.3.2. Cumulative Rainfall Frequency and Nutrient, TSS, and Cl- Loading .......................... 40 3.3.3. Effect of Antecedent Rainfall on Stormwater and Nutrient Loading ......................... 40 3.4. Impact of Land Cover and Drainage Characteristics on Water and Nutrients in Stormflow ........................................................................................................................................... 42 3.5. Exceedence Probabilities of Water Yields and Nutrient Loads............................... 43 3.5.1. Stormflow ........................................................................................................................................... 43 3.5.2. Baseflow.............................................................................................................................................. 44 3.6. Metals Toxicity Exceedences in Stormwater ................................................................. 46 3.6.1. Seasonality of Metals Toxicity.................................................................................................... 47

4. Summary .............................................................................................................................. 53 Part 1: Spatial and Seasonal Patterns in Water, Nutrients, Metals ................................ 53 4.1.1. Baseflow vs. Stormflow ................................................................................................................ 53 4.1.2. Spatial Variation .............................................................................................................................. 53 4.1.3. Seasonality ......................................................................................................................................... 54

CRWD Stormwater Monitoring Data Analysis Report

Part 2: Impact of Storm Event Characteristics on Water and Nutrient Loading ....... 55 4.1.4. Cumulative Rainfall Frequency ................................................................................................. 55 4.1.5. Antecedent Conditions.................................................................................................................. 56 Part 3: Impact of Land Cover and Drainage Characteristics on Water and Nutrients in Stormflow ...................................................................................................................................... 56 Part 4: Exceedence Probabilities of Water Yields and Nutrient Loads ........................ 57 Part 5: Metals Toxicity Exceedences in Stormwater ........................................................... 58

References ................................................................................................................................ 59 Appendix A: Seasonal and Monthly Concentrations of Nutrients, TSS, Chloride, and Metals in Stormflow and Baseflow..................................................................................................... Appendix B: Summary of Regression Parameters (slope, R2, and p-value) for Linear Regression of Stormwater Yield, Nutrients, Total Suspended Solids, Chloride, and Metals against Antecedent Rainfall Parameters ........................................................................... Appendix C: Summary of Regression Parameters (slope, R2, and p-value) for Linear Regression of Stormwater Yield, Nutrients, Total Suspended Solids, Chloride, and Metals against Land Cover and Drainage Characteristics ......................................................... Appendix D: Summary of p-values for Mann-Whitney U test of Seasonal Differences in Metals Toxicity Exceedence Values in Baseflow at CRWD Monitoring Sites. ............... Appendix E: Cumulative Rainfall Frequency Plots for Cumulative Stormwater Volume and Nutrient Loads in CRWD Sub-watersheds ............................................................. Appendix F: Flow-Duration and Load-Duration Curves for Loading of Water, Nutrients, Sediment, and Chloride in CRWD Sub-watersheds ................................................ Appendix G: Observed Concentrations and Toxicity Standards of Metals (Cd, Cr, Cu, Pb, Ni, Zn) as a Function of Total Hardness in Stormflow of CRWD Sub-Watersheds ... Appendix H: Toxicity Exceedence Probability Curves and Observations of Metals Concentrations (Cd, Cr, Cu, Pb, Ni, Zn) in Stormflow of CRWD Sub-Watersheds ............ Appendix I: Cumulative Loading of Water, Nutrients, TSS, and Chloride in Stormflow and Baseflow in CRWD Sub-watersheds ...................................................................

CRWD Stormwater Monitoring Data Analysis Report 3

1. Introduction This report describes the summary and analysis of portions of the extensive data set collected in the Capitol Region watershed (CRWD) from 2005 â&#x20AC;&#x201C; 2012 by the Capitol Region Watershed District as part of its stormwater monitoring program. Monitoring data included continuous flow measurements and water chemistry of samples collected during stormflow and baseflow periods throughout the year at 13 sites (primarily storm drains and outlets of stormwater best management practices). Water samples were analyzed for a suite of nutrients, ions, solids, and metals. The analyses and summaries described in this report are intended to expand on those provided by CRWD in its annual monitoring reports, and can be categorized by objective as follows: (1) investigating spatial and seasonal patterns in yields and concentrations of water, nutrients, and metals, (2) examining the impact of storm event characteristics (e.g. rainfall depth, antecedent conditions) on loading of water and nutrients, (3) investigating the impact on water and nutrient loading of differences in land cover and drainage characteristics among monitored sub-watersheds, (4) determining exceedence probabilities of water yields and nutrient loads, and (5) quantifying probabilities and seasonality of metals toxicity exceedences. A complete list of the analyses is included on the following page. The primary goals of these analyses were to provide a reference that could lead to a better understanding of water and nutrient loading patterns in the watershed, inform the design of future stormwater best management practices (BMPs), and aid in the development of total maximum daily loads (TMDLs) or water quality goals for the CRWD. Several analyses are intended to provide information to assess the appropriateness of the current design storm and to potentially modify it if needed (for example, if the frequency of the design storm is much different than expected or if it results in a different loading than used to size certain BMPs). The analyses also provide several methods that may eventually be used to compare data from future monitoring seasons to data from the summary period (2005-2012). Such a comparison should provide a means of assessment of BMP performance and quantification of progress towards water quality goals in the watershed. A summary has also been included of major patterns in spatial and seasonal variability among monitored sub-watersheds, which may help identify seasons and/or specific sub-watersheds or BMPs that may be especially crucial for managing overall water quality in the CRWD.

CRWD Stormwater Monitoring Data Analysis Report

List of Analyses A complete list of data summaries and analyses is included here, organized by objective. Methods employed in the analyses are described in Section 2. Constituents for most analyses included water, nutrients (total phosphorus, total nitrogen, nitrite-nitrate), total suspended solids, chloride, and metals (cadmium, chromium, copper, lead, nickel, and zinc). (1) Seasonal and spatial patterns in water, nutrients, and metals: (a) Mean and five-number summary (minimum, 1st quartile, median, 3rd quartile, and maximum) of water yield and concentrations of nutrients and metals, by season (spring, summer, and fall for stormflow, all seasons for baseflow). (b) Statistical tests for significant differences among seasonal concentrations of nutrients and metals (stormflow and baseflow) (c) Cumulative water and nutrient loading plots for each site (stormflow) (d) Cumulative discharge and nutrient loading rates for each site (baseflow) (2) Impact of storm event characteristics on water and nutrient loading: (a) Cumulative rainfall frequency plots for rain event count and cumulative stormwater runoff volume (similar to Bannerman et al. 1983, as published in Pitt et al. 1999) (b) Cumulative rainfall frequency plots for nutrient and sediment loads in stormwater (similar to Bannerman et al. 1983, as published in Pitt et al. 1999) (c) Simple linear regression analysis investigating impact of antecedent rainfall characteristics (dry days, days since 0.5-in rainfall, and rainfall in last 7 days) on stormwater yield and nutrient and metals concentrations (3) Impact of land cover and drainage characteristics on water and nutrients in stormflow: (a) Summary of land cover and drainage characteristics for CRWD sub-watersheds for use in the regression analysis and to aid in interpretation of all results (b) Simple linear regression analysis investigating the influence of these land cover and drainage metrics on observed loads and concentrations of nutrients, metals (Cu, Pb, Zn), and water for CRWD sub-watersheds (4) Exceedence probabilities of water yields and nutrient loads: (a) Flow-duration curves for all sites (volume and discharge for stormflow, discharge for baseflow) (b) Load-duration curves for nutrients, sediment, and chloride at all sites (loads for stormflow, loading rates for baseflow)

CRWD Stormwater Monitoring Data Analysis Report 5

(5) Metals toxicity exceedences in stormwater: (a) Toxicity exceedence probability curves for metals (Cd, Cr, Cu, Pb, Ni, Zn) at all sites (stormflow only) (b) Statistical tests for significant differences among seasonal metals toxicity exceedences (stormflow) The data summaries and analyses are presented in the order listed above in the Results. An introduction to the Results is also included in which CRWD sub-watersheds are described in terms of land cover distributions, drainage characteristics, and stormflow and baseflow hydrology, which are referenced in the interpretation of the plots and analyses. A summary of the Results is included at the end of the report.

CRWD Stormwater Monitoring Data Analysis Report

2. Data Collection and Methods 2.1. Data Collection Data used in this work were collected by the Capitol Region Watershed District (CRWD) as part of its stormwater monitoring program over the years 2005 â&#x20AC;&#x201C; 2012. Monitoring sites included major storm drains and outlets of best management practices (BMPs), which were usually monitored from April through November of each year. For sites with baseflow, sampling was also conducted during the interim period (winter and early spring). Collected data included continuous flow rate and chemistry of water samples. Samples were collected during both baseflow and stormflow during the monitoring season using ISCO automatic water samplers, with baseflow sampling during winter and early spring periods conducted using manual grab samples. Precipitation data were also collected across the watershed using both manual and automatic gauges. CRWD water samples were analyzed for a suite of nutrients, solids, ions, and metals by Metropolitan Council Environmental Services (2005-2011) and by Pace Analytical Services Inc. (2012). Of particular interest in this study were total phosphorus (TP), total nitrogen (TN), nitrite and nitrate nitrogen (NO3), total suspended solids (TSS), chloride (Cl-), and cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), nickel (Ni), and zinc (Zn). Data were reported as concentrations: mg/L for nutrients, TSS, and Cl,- and g/L for metals. For some metals (Cd and Cr) and nitrite, measurements were often below the detection limits of the analyses. For the analyses these values were left at the detection limits given the frequent low concentrations of metals (in baseflow especially), and the very small fraction of either stormflow or baseflow TN generally comprised by nitrite. CRWD analyzed the flow data from each monitoring site, correcting errors in the depth and velocity measurements and determining water volumes (in ft3) for baseflow intervals and storm events for the entire monitoring period. Gaps in flow data are present at some sites due to equipment malfunction; most instances in which these gaps could influence the analyses are identified in the Results. A total of 13 CRWD-maintained monitoring sites were included in this work. These sites included storm drains at the outlets of several large sub-watersheds within CRWD: East Kittsondale (EK), Phalen Creek (PC), St. Anthony Park (SAP), Trout Brook East Branch (TBEB), Trout Brook West Branch (TBWB), and Trout Brook Outlet (TBO). Several smaller sites, generally located upstream or downstream of BMPs within CRWD were also included: Arlington-Hamline Underground Stormwater Vault Inlet (AHUG), Villa Park Inlet (VP Inlet), Villa Park Outlet (VP Outlet), Sarita Wetland Outlet (Sarita), and the outlet of a pond at the Como Golf Course (GCP Outlet). Como 7 and Como 3, two sub-watersheds of Como Lake, were also included. CRWD Stormwater Monitoring Data Analysis Report 7

Description of CRWD sub-watersheds, and data collection and processing methods are detailed in the 2012 CRWD monitoring report (CRWD, 2012). Flow and chemistry data used by site is listed in Table 2.1. For the Trout Brook sites, data prior to 2007 was not used due to re-location of the TBEB and TBO sites in spring of 2007. Table 2.1. Flow and water chemistry data intervals used in the analyses, by site. Site

Years of Monitoring Data Used

East Kittsondale

2005 - 2012

Phalen Creek

2005 - 2012

St. Anthony Park

2005 - 2012

Trout Brook - East Branch

2007 - 2012

Trout Brook - West Branch

2007 - 2012

Trout Brook - Outlet

2007 - 2012

Como 7

2007 - 2012

GCP Out

2008 - 2012

Villa Park Outlet

2006 - 2012

Sarita Outlet

2006 - 2012

AHUG

2007 - 2012

Como 3

2009 - 2012

Villa Park Inlet

2006 - 2012*

*no flow data available in 2009 due to equipment malfunction

2.2. Methods 2.2.1. Land Cover and Drainage Characteristics Spatial data was used to determine a wide range of land cover and drainage characteristics for the CRWD sub-watersheds (Table 2.2). Primary data sources included: (1) a high-resolution (roughly 0.6-m) land cover map for assessing canopy coverage in St. Paul, MN, developed by the Forestry Department at the University of Minnesota from 2009 satellite imagery, aerial photography, and LiDAR (Kilberg et al. 2011); and (2) a GIS layer provided by CRWD for impervious cover, including designations for street, alley, several roof types, and miscellaneous impervious cover. ArcMap GIS was used for all spatial data analyses. The two land cover layers were used to determine land cover fractions of the CRWD subwatersheds. Land cover classes included trees, lawn/shrubs, bare ground, open water, rooftop, street, and â&#x20AC;&#x153;otherâ&#x20AC;? impervious (alleys, driveways, and lots). Composite land cover classes included total impervious area and vegetated area (trees + lawn/shrubs). The CRWD impervious layer was used to partition roof area into low-density residential, high-density residential, industrial, commercial, and institutional. Overlay and buffer

CRWD Stormwater Monitoring Data Analysis Report

analyses were used to determine the fraction of street directly covered by vegetation, as well as the fraction of canopy coverage within 5ft, 10ft, and 20ft of the streets. Drainage characteristics included a runoff coefficient, street density (total length of street divided by watershed area), and curb density (total length of curb divided by watershed area). Curb length was determined from calculating the perimeter of the street layer. Street density and curb density were used as surrogates for drainage density, which could not be determined due to the lack of storm drain spatial data at the time of writing. The runoff coefficient is defined as the depth of total runoff normalized by the depth of total rainfall. Pond density, in ponds per km2, was determined from visual inspection of satellite imagery and should be considered a rough approximation of the actual pond density (Ann Krogman, personal comm., March 7, 2012). Note that the watersheds upstream of wetlands (Sarita in SAP) and lakes (i.e. Como Lake and Lake McCarrons in TBWB/TBO) were not included in the calculation of the land cover and drainage characteristics.

CRWD Stormwater Monitoring Data Analysis Report 9

Table 2.2. Land cover and drainage characteristics of CRWD sub-watersheds. Watershed

EK PC SAP TBEB TBWB TBO Como 7 GCP Out VP Outlet Sarita AHUG Como 3 VP Inlet

Area (ac)

Area (km )

Runoff Coeff

1116 1433 2491 808 2379 5036 298 298 708 930 41.5 517 622

4.52 5.80 10.08 3.27 9.63 20.38 1.21 1.21 2.87 3.76 0.17 2.09 2.52

0.373 0.279 0.249 0.248 0.381 0.332 0.052 0.408 0.162 0.067 0.157 0.108 0.168

Drainage Characteristics Street Curb Density Density 2 2 (km/km ) (km/km ) 15.26 14.78 11.59 13.15 8.73 11.13 12.84 12.84 8.45 7.95 13.03 10.25 8.61

Pond Density 2 (ponds/km ) 0.22 1.03 0.60 4.28 3.43 3.24 n/a n/a n/a n/a 0 n/a n/a

26.41 27.18 20.31 22.70 18.32 19.96 24.53 24.53 17.17 n/a 26.71 19.56 17.09

Land Cover Percentages

Watershed EK PC SAP TBEB TBWB TBO Como 7 GCP Out VP Outlet Sarita AHUG Como 3 VP Inlet

Trees

Lawn / Shrubs

Bare

Water

Rooftop

Street

Alley

Other Impervious

Total Impervious

Vegetated

26.8 23.7 23.0 29.9 31.7 26.7 30.5 30.5 45.4 n/a 26.8 31.2 44.0

16.7 17.0 14.4 24.9 25.2 23.5 25.3 25.3 24.8 n/a 21.9 26.7 25.4

0.3 0.5 0.5 0.1 0.8 0.7 0.2 0.2 0.3 n/a 0.3 0.9 0.3

0.0 0.0 0.7 0.4 3.2 1.8 0.4 0.4 1.2 n/a 0.0 0.3 0.9

22.1 22.3 19.0 13.8 13.1 14.2 18.4 18.4 9.2 n/a 24.7 12.0 9.3

16.5 16.9 14.0 16.2 10.5 13.8 13.4 13.4 11.3 n/a 13.3 12.6 11.7

3.3 3.4 1.5 1.3 1.5 1.3 0.5 0.5 0.0 0.1 3.6 1.6 0.0

17.6 19.4 28.3 14.6 15.5 19.3 11.7 11.7 7.8 n/a 12.9 16.3 8.4

56.2 58.7 61.3 44.7 39.2 47.3 43.5 43.5 28.4 n/a 51.0 40.8 29.4

43.5 40.8 37.4 54.8 56.9 50.3 55.9 55.9 70.2 n/a 48.7 57.9 69.4

CRWD Stormwater Monitoring Data Analysis Report

Table 2.2. (Conâ&#x20AC;&#x2122;t). Land cover and drainage characteristics of CRWD sub-watersheds. Rooftop Percentages by Type

Watershed EK PC SAP TBEB TBWB TBO Como 7 GCP Out VP Outlet Sarita AHUG Como 3 VP Inlet

Institutional

Residential, Low Dens.

Residential, High Dens.

Comm.

Industrial

0.9 1.3 0.8 0.3 0.6 0.7 0.9 0.9 0.5 3.5 3.0 0.2 0.6

11.9 10.3 4.6 7.2 6.1 5.6 13.5 13.5 5.6 2.0 16.9 5.1 5.4

1.4 0.9 1.8 1.8 1.5 1.3 0.2 0.2 1.4 3.6 0.1 0.9 1.6

2.2 2.2 1.7 0.3 1.0 1.1 0.3 0.3 0.3 0.6 0.0 1.8 0.3

1.2 2.9 8.0 0.6 1.0 1.8 0.0 0.0 0.0 0.0 0.0 0.7 0.0

Percentage of Street Covered by Canopy Street + Street + Street + Street 5 ft 10 ft 20 ft Buffer Buffer Buffer 30 34 37 41 27 31 34 37 21 24 27 31 22 26 29 34 32 36 39 43 22 25 28 32 43 46 48 51 43 46 48 51 15 19 22 29 n/a n/a n/a n/a 36 40 43 48 31 34 36 40 14 17 21 27

CRWD Stormwater Monitoring Data Analysis Report 11

2.2.1. Stormflow and Baseflow Water Yields Seasonal water yields (in/season) of baseflow and stormflow were calculated for all monitored sub-watersheds. The seasonal period was defined as Apr 1 – Oct 31, which corresponded approximately to the monitoring period of each year. Gaps in flow data were accounted for by linear extrapolation from the interval of existing flow data. Similar to the drainage and land cover characteristics, watersheds of major lakes and wetlands (i.e. Como Lake, Lake McCarrons, and the Sarita wetland) were not included in the contributing areas used for the yield calculations, though these water bodies contribute some flow to their downstream watersheds during both stormflow and baseflow periods. 2.2.2. Statistical Methods for Yield and Concentration Data Concentration data for each site were grouped by month as well as by season: spring (Mar – May), summer (June – Aug), and fall (Sep – Nov) for stormflow data, with winter (Dec – Feb) included for baseflow data. It is acknowledged that these are somewhat arbitrary breakpoints for seasons that do not always correspond to changes in flow regimes, snow cover, or nutrient inputs, but are useful for the purposes of analyzing seasonal changes in runoff concentrations. Mean, median, maximum, minimum, 1st quartile, and 3rd quartile of concentration data were determined by season for each constituent. Volume-weighted mean concentrations by month were also calculated. As is common for water quality data, the concentration data were not normally distributed, instead tending to be positively-skewed due to lack of negative values and occasional high concentrations and outliers (Helsel and Hirsch, 2002). This positive skewness is illustrated in the probability distribution of TP measurements in stormflow at EK (Figure 2.1a). Many methods are available for normality testing. One such method, the Lilliefors test, has been used in previous analyses of stormwater data (e.g. Brezonik and Stadlemann, 2002). This test shows that the TP data at EK are not normally distributed (i.e. the null hypothesis that the data come from a normal distribution is rejected at p = 3.74E-9), and thus transformation of the data was necessary for some analyses. Log transformation, which is commonly used for concentration data (Brezonik and Stadlemann, 2002; Helsel and Hirsch, 2002), improves the fit of the TP data to a normal distribution (Figure 2.1b; p = 0.133 for the Lilliefors test).

CRWD Stormwater Monitoring Data Analysis Report

Figure 2.1. (a) Probability density of stormflow TP concentrations at EK, and (b) Probability density of log-transformed stormflow TP concentrations at EK. Significant differences in nutrient concentrations and metals toxicity exceedences between pairs of seasons (within sites) were assessed using the Mann-Whitney U test, a non-parametric pairwise test appropriate for use on non-normally distributed data (Helsel and Hirsch, 2002). The null hypothesis of this rank-sum test is that an observation from one group has a 50% probability of being larger than that from the second group. The null hypothesis is rejected if this probability is not 50% (i.e. observations from one group tend to be higher or lower than those from the second group), meaning that the groups differ in their medians. Differences were considered significant at p < 0.05. Simple linear regression was used to investigate the effect of antecedent rainfall conditions on stormflow water yield (in) and stormwater nutrient (TP, TN, NO3), TSS, Cl-, and metals (Cd, Cr, Cu, Pb, Ni, Zn) concentrations. For all events in the data set of each site, these water yield and chemistry variables were regressed against three antecedent rainfall characteristics: days since last measureable rainfall (â&#x20AC;&#x153;dry daysâ&#x20AC;?), days CRWD Stormwater Monitoring Data Analysis Report 13

since last storm of 0.5 inch depth or greater (“days since 0.5-inch”), and total rainfall depth in the previous 7 days (“weekly rain”). All data were log-transformed for this analysis as recommended by Helsel and Hirsch (2002), and correlations were considered significant at p < 0.05. Simple linear regression was also used to investigate the influence of land cover and drainage variables on mean values of stormwater volume and nutrients, TSS, Cl-, and metals. For this analysis, the non-BMP sites were used (AHUG, EK, PC, SAP, TBEB, and TBWB). The BMP outlet sites were not included in the analysis due to a less definite link between the land surface and monitored stormwater (due to internal processing of nutrients or increased hydrologic residence times), and TBO was excluded because it is not independent of TBEB and TBWB. Como 3 was excluded due to large gaps in its relatively short data record. Land cover and drainage metrics used as explanatory variables are shown in Table 2.2. Dependent variables included event mean concentration and mean seasonal yield of nutrients (TP, TN, NO3), TSS, Cl-, and selected metals (Cu, Pb, Zn). The other metals (Cd, Cr, and Ni) were not included due to few observed toxicity exceedences and generally lower concentrations. Data were not log-transformed due to the use of mean quantities and because of the small number of sites (6), which also limited the ability to interpret results. R was used for all statistical analyses, as well as to generate most of the plots for presentation of the data and analyses. Microsoft Excel was used for some plots and basic statistical summaries. 2.2.3. Cumulative Loading and Cumulative Rainfall Frequency Nutrient loads (lb) were calculated by multiplying observed concentrations by observed water volumes for each event (stormflow) or flow interval (baseflow). For un-sampled intervals, loads were calculated by using a volume-weighted mean concentration for the month in which the volume interval occurred (determined from the whole set of samples at a site for that month; see Tables A.3 and A.4). This monthly mean approach was used in order to capture seasonality of nutrient concentrations and because flow-concentration relationships were generally poor. Loads were normalized by watershed area to produce yields (lb/ac) that allowed for comparisons among watersheds of varying size. Cumulative loading curves for water and nutrients were developed for each site, with separate curves for baseflow and stormflow. Snowmelt was included in baseflow intervals from 2005-2010 (and rarely sampled directly), but CRWD identified snowmelt events in 2011 and 2012 at most sites. Snowmelt intervals are therefore not included in cumulative loading curves developed for 2011 and 2012, but are included in curves developed from earlier data. Loading was normalized by the total load for the monitoring season, and each year of available data is shown along with a mean seasonal (Apr – Oct) 14

CRWD Stormwater Monitoring Data Analysis Report

loading line for all years, which was determined by taking the average across years of the fraction of the cumulative loading added each day. Cumulative rain count and cumulative water and nutrient loads were plotted as a function of increasing rainfall depth for all sites, referred to for the purposes of this report as cumulative rainfall frequency plots. These plots are similar to those constructed by Bannerman et al. (1983), as shown in Pitt et al. (1999). This analysis first required matching rainfall depths with associated runoff volumes for each sub-watershed. Precipitation data utilized in this analysis was collected at a station maintained on the University of Minnesota’s St. Paul campus by the Department of Soil, Water, and Climate, as well as at six sites maintained by CRWD, including manual gauges at the CRWD office, Villa Park, and Westminster-Mississippi stormwater pond, and automatic gauges at Highland Park, the St. Paul Fire Station, and Trout Brook East Branch. Gauge locations are shown in CRWD (2012). Mean precipitation depth for each storm was determined using an inverse squared distance relationship, as in Brezonik and Stadlemann (2002):

å( P d ) åd i ij ij

where Pi is the precipitation depth measured at gauge i, and dij is the inverse of the square of the distance from gauge i to monitoring site j at the outlet of the watershed, i.e. dij = (distance from gauge i to site j)-2. Once runoff volumes (and nutrient loads) were matched to rainfall depths, the plots were constructed by sorting the data records by increasing rainfall depth. For all sites, flow-duration curves were developed for runoff and load-duration curves were developed for nutrients (TP, TN, NO3), TSS, and Cl- in both stormflow and baseflow. Event water volume (ft3), flow rate (cfs), and nutrient loads (lb) were used for the stormflow plots, while loading rates (cfs for runoff, and lb/h for nutrients) were used for the baseflow plots due to the dependence of baseflow loads on the length of the sampling intervals. Following the recommendations of Helsel and Hirsch (2002), the Weibull plotting parameter (plotting position, i = n / N+1) was used for these plots, where n = rank and N = number of events or intervals. 2.2.4. Metals Toxicity The toxicity of a metal is a function of water hardness. For CRWD watersheds, the chronic toxicity standard was used, as defined in Minnesota Rules 7050.0222 for each of the 6 metals (Cr, Cd, Cu, Pb, Ni, and Zn). Toxicity is assessed only for stormflow, given the generally low concentrations of metals and high water hardness in baseflow, which leads to very few toxicity exceedences. Equations for the chronic standard (CS) for each CRWD Stormwater Monitoring Data Analysis Report 15

metal in g/L, as a function of total water hardness (TH) in mg/L, are listed below as well as in CRWD (2012): Cadmium:

CSCd = exp(0.7852[ln(TH)] – 3.490)

Chromium:

CSCr = exp(0.819[ln(TH)] + 1.561)

Copper:

CSCu = exp(0.620[ln(TH)] – 0.570)

Lead:

CSPb = exp(1.273[ln(TH)] – 4.705)

Nickel:

CSNi = 297 g/L, for TH > 212 mg/L CSNi = exp(0.846[ln(TH)] + 1.1645), for TH < 212 mg/L

Zinc:

CSZn = exp(0.8473[ln(TH)] + 0.7615)

Toxicity exceedence curves were developed by sorting hardness concentration data by decreasing concentration, then applying the toxicity standard to the hardness data. Corresponding observed metal concentrations were also plotted on these curves. Toxicity exceedence was defined as the difference between the observed metal concentration and the toxicity standard, which is a function of the observed hardness. Positive values of exceedences, which were not normally distributed, were assessed for seasonality using the Mann-Whitney U test (similar to the nutrient concentration data). All negative exceedence values (i.e. non-exceedences) were discarded, resulting in sample sizes that varied considerably among sites and among seasons.

CRWD Stormwater Monitoring Data Analysis Report

3. Results 3.1. Characterization of CRWD Sub-watersheds To aid in explanation and interpretation of the results, differences in land cover, drainage characteristics, and hydrology of the monitored sub-watersheds are described here. Methods used to determine the land use and drainage metrics and to calculate stormflow and baseflow water yields are described in Section 2. 3.1.1. Land Cover and Drainage Characteristics A summary of land cover metrics and drainage characteristics of all monitored subwatersheds is shown in Table 2.2. Some variation in land cover is present among subwatersheds. For example, total impervious area varies from 39% (TBWB) to 59% (PC), with much smaller percentages (28%, 29%) at the VP Inlet and Outlet sites, while total vegetated area (tree canopy + lawn and shrubs) varies from 37% (SAP) to 70% (VP Outlet). Street area varies only from 10% (TBWB) to 17% (PC), with roughly 14% (VP Inlet) to 43% (Como 7) of this street area directly shaded by overhanging canopy. Among roof types, low-density residential was the most common, as expected given the dominance of this land use in the watersheds, ranging from 5.4% (VP Inlet) to 17% (AHUG). Drainage characteristics also showed some variability among sites. Runoff coefficients (RC) ranged from 0.052 to 0.408, with the lowest values at the Como and BMP sites (excepting GCP Outlet, which had the highest runoff coefficient due to water pumped in from outside the watershed via Gottfriedâ&#x20AC;&#x2122;s Pit). The highest values of RC for non-BMP sites were observed at EK, TBWB, and TBO. Street and curb density were both lowest at VP Outlet, and highest at EK and PC. The amount of surface water in CRW also varied considerably among sub-watersheds, and was anticipated to have an impact on water yields. Open water area, though relatively insignificant in terms of total area, was greatest in TBWB, TBO, Villa Park, and SAP (even neglecting the area of the Sarita wetland and Como Lake and Lake McCarrons). In addition, a rough count of stormwater ponds in five sub-watersheds using aerial photography showed the greatest density in TBEB (approximately 4.28 ponds per km2 watershed area) and TBWB (3.43 ponds/m2), with lower densities (0.22 â&#x20AC;&#x201C; 1.02 ponds/km2) in EK, PC, and SAP (Ann Krogman, personal comm., March 7, 2012). Potential implications of differences in drainage characteristics for stormflow and baseflow are addressed below and throughout the Results. 3.1.2. Sub-watershed Stormflow and Baseflow Water Yields Mean seasonal water yields (in/season) of baseflow and stormflow for all monitored sites are shown in Figure 3.1a. The percentage of the combined seasonal water yield due to CRWD Stormwater Monitoring Data Analysis Report 17

(a)

Seasonal Water Yield, in

baseflow is also shown. The seasonal period was defined as Apr 1 – Oct 31, which corresponds approximately to the monitoring period of each year. Note that watersheds of upstream lakes (e.g. Como Lake and Lake McCarrons for TBWB) or wetlands (e.g. Sarita for SAP) are not included in the contributing area for the yield calculations.

62%

Stormflow

67%

61%

Baseflow

56% 25% 44%

31%

28%

G U AH

C om

C G

C om

Sa r

O ut VP

VP VP In

TB O TB O

B W TB

SA SA

PC PC

TB E

EK EK

Seasonal Stormwater Yield, in

(b) 12

10 8 6 4 2

G AH U

P C G

o7 om

Sa r

VP O ut

B TB W

B TB E

Figure 3.1. (a) Mean seasonal (Apr – Oct) stormflow and baseflow water yields (inches) for CRWD sub-watersheds during the monitoring period (2005-2012), and (b) Mean and standard error of seasonal (Apr – Oct) stormflow yields (inches). In (a), percentages indicate the baseflow portion of total seasonal water yield. While variation in stormwater yields from year to year was relatively small at most sites (i.e. small standard errors; Figure 3.1b), considerable variation was present among sites in 18

CRWD Stormwater Monitoring Data Analysis Report

seasonal stormwater yields. The lowest yields were generally observed for the BMP sites (VP Inlet, VP Outlet, and Sarita) as well as the Como sites (Como 3, Como 7, and AHUG), which have a relatively large number of BMPs present that should reduce water yields. The high water yields at GCP Outlet are probably due to pumping from Gottfriedâ&#x20AC;&#x2122;s Pit, which is outside the GCP/Como 7 watershed. With this exception, the highest stormwater yields were observed at the non-BMP sites, including at EK, which has very little surface water (i.e. few ponds and no open water; Table 2.2), and thus likely has little storage capacity relative to the other sites. High stormwater yields at TBWB and TBO (and to a lesser extent SAP) might be supplemented by flow from upstream lakes and wetlands present in these sub-watersheds (the area of which is not included in the yield calculations). Frequency of large events should vary from year to year, which may also explain the higher standard errors at these sites. For the non-BMP sites with baseflow (EK, PC, SAP, and the Trout Brook sites), appreciable variation was present in combined seasonal water yields. This variation was driven primarily by differences in baseflow yield, as stormflow yields were similar among these sites (see Figure 3.1b). Baseflow was especially important at the largest sites, including PC, SAP, TBWB, and TBO, where 56% to 67% of combined seasonal water yield was delivered by baseflow. For several sites (EK, PC, SAP, TBEB, TBWB, and TBO), year-round flow data was collected from 2010 - 2012. These results are summarized in Table 3.1. While some gaps exist in these data, they illustrate the even greater importance of baseflow on an annual scale, as baseflow comprises 32% (EK) to 71% (PC) of combined annual volume. The substantial contribution of baseflow to combined water yield at several sites is noteworthy, as it represents a considerable flux of water that is often not monitored, and rarely treated or considered in BMP development. Table 3.1. Annual water yields for six CRWD sub-watersheds, averaged over 2010 to 2012 and separated by flow type (baseflow, stormflow, and snowmelt). Note that snowmelt volumes were only available for 2011 and 2012; in 2010 these volumes are included in the baseflow volumes and thus may slightly inflate baseflow estimates.

Site

Baseflow

Stormflow

Snowmelt

Combined

Baseflow as % of Combined

5.93

11.11

1.41

18.46

32%

23.15

8.37

1.20

32.72

71%

SAP

6.59

3.71

0.29

10.59

62%

TBEB

7.80

6.42

0.85

15.07

52%

TBWB

9.75

6.93

0.50

17.19

57%

TBO

11.50

5.62

1.35

18.46

62%

CRWD Stormwater Monitoring Data Analysis Report 19

In CRWD, two primary baseflow sources are assumed to be present: (1) groundwater seepage into storm drains that were constructed below the water table, and (2) outflow from surface water (lakes, ponds, and wetlands) that is connected to storm drains. Groundwater is presumed to be the dominant baseflow source in all sub-watersheds due to generally high water tables and sandy or loamy soils (Kanivetsky and Cleland 1992, Meyer 2007), in particular for the larger watersheds with extensive or deeper storm drain networks (e.g. SAP, TBO). For several watersheds with a large number of lakes, ponds, and wetlands, and in particular those with known outflows from major lakes or wetlands to the storm drain network (e.g. Sarita Wetland in SAP, Como Lake and Lake McCarrons in TBWB), surface water may contribute a small but important fraction of baseflow. The developmental history of the watershed may be important in explaining baseflow variation among sites. For example, the main trunks of the storm drains in PC and the Trout Brook watersheds were constructed in existing stream channels beginning in the late 1800â&#x20AC;&#x2122;s (Brick 2008). Water tables are especially high in the vicinity of these drains (Barr Engineering 2010), and this concentration of shallow groundwater may cause high seepage rates into the aging storm drains, which would explain the high baseflow yields for TBWB/TBO and PC in particular. Extent of the storm drain is also likely important, as EK and TBEB, which had the smallest baseflow yields of the non-BMP sites, are the smallest of these watersheds and have relatively small, shallow storm drain networks that may be located mostly above the water table. The importance of baseflow for water and nutrient loading, and the potential influence of groundwater vs. surface water for baseflow nutrient chemistry has been investigated for the 2005-2011 CRWD monitoring data set by Janke et al. (2013). 3.1.3. Stormflow Response Inspection of hydrographs further illustrates the differences in stormflow response among the monitored sub-watersheds, and in particular the influence of major BMPs. A relatively large-scale, fast-moving frontal storm occurring on July 31, 2009 producing 0.60 in of rain was used for this illustration. Normalized hydrographs for this event are shown for most sites in Figure 3.2. Note that no flow data was collected at VP Inlet during 2009, and water level was used in place of flow rate for Sarita due to errors in velocity data for that storm. As expected, the outflow hydrographs for the BMP sites (VP Outlet, GCP Outlet, and Sarita) were considerably different than for the other sites. The BMPs stored much of the rainfall-runoff from this event and released it slowly over the next day, with peak outflow rates occurring several hours after rainfall had ended. By contrast, hydrographs for EK, PC, AHUG, and Como 7 were typical of very impervious watersheds with little surface water for detention capacity: very early runoff peaks and short hydrographs (i.e. small times of concentration). SAP, Como 3, and the Trout Brook watersheds had much longer 20

CRWD Stormwater Monitoring Data Analysis Report

hydrographs and later peak flows. In the case of SAP and the Trout Brook sites this is likely evidence of considerable surface water (especially detention ponds) present in these watersheds that delays the movement of stormwater, as observed at the BMP sites. For Como 3, the large amount of park and golf course area in the watershed may also serve to slow stormwater movement. 1.2

1.0

0.5

SAP 0.8

TBEB TBWB

TBEB 0.6

1.5

TBO Precip

0.4

2 EK

TBO SAP

0.2

2.5

TBWB

Precip (cm, per 15min interval)

Dimensionless Flow (Q/Qpeak)

PC 3 23:00

0:00

1:00

2:00

3:00

4:00

5:00

6:00

Dimensionless Flow (Q/Qpeak)

1.2

1.0

0.5 VP Outlet

0.8 GCP Outlet

0.6

AHUG

VP Outlet

Como 3

Sarita (Lvl)

Como 7

GCP Outlet

1.5

Precip 0.4

2 Sarita

0.2

2.5

Precip (cm, per 15min interval)

0.0 22:00

Como 3 0.0 22:00

AHUG 23:00

Como 7 3 0:00

1:00

2:00

3:00

4:00

5:00

6:00

Figure 3.2. Observed hydrographs at CRWD sub-watersheds for a spatially extensive, 0.60-in storm on July 31, 2009. Main sites are shown in the top plot, with smaller sites and BMPs shown in the bottom plot. Note that VP Inlet is not included due to lack of flow data in 2009, and level data is plotted at Sarita due to errors in velocity data.

CRWD Stormwater Monitoring Data Analysis Report 21

3.2. Seasonal and Spatial Patterns in Water, Nutrients, and Metals Concentration data are summarized in terms of mean, median, minimum, maximum, 1st quartile, and 3rd quartile by season for all monitoring sites in Appendix A for stormflow (Table A.1) and for baseflow (Table A.2). Concentrations of most constituents appear to have right-skewed distributions common in these type of data (Helsel and Hirsch 2002), with median concentrations considerably smaller than mean concentrations, the latter of which can be influenced by a few samples with very high concentrations. Monthly mean volume-weighted concentrations of nutrients, TSS, and Cl- are shown in Table A.3 for stormflow and in Table A.4 for baseflow. 3.2.1. Stormflow Concentrations of Nutrients, TSS, Chloride, and Metals The highest median TP and TN concentrations were observed at EK, PC, Como 7, and AHUG. At EK and PC, high TN and TP may be due to high stormwater yields at these sites (Figure 3.1b), which may result in the transport of more particulate N and P relative to sites with smaller stormwater yields. The highest median NO3 concentrations were observed at PC, SAP, TBWB, and TBO, which might be explained by mixing of stormwater with NO3-rich baseflow at these sites (Table A.2). Median TSS concentrations were highest at EK, PC, TBWB, and Como 7. For EK, PC, and TBWB this again may be due to high stormwater yields (and runoff coefficients) for these watersheds, but an explanation for high TSS at Como 7, which has very low stormwater yields, is unclear. By contrast, the lowest median TP, TN, and TSS concentrations were logically observed at the BMP sites (Sarita, VP Inlet, VP Outlet, and GCP Outlet), suggesting that these BMPs were effective in removing some particulate nutrients from stormwater relative to the larger, non-BMP sites. The smallest median NO3 concentrations were also generally observed at these sites, suggesting that NO3 uptake or denitrification may be occurring in the ponds and wetlands present at these sites. Median stormflow Cl- concentrations did not vary much among sites, and were well below the Minnesota Pollution Control Agency (MPCA) water quality standard of 230 mg/L at all sites. The highest concentrations were observed at VP Inlet, VP Outlet, GCP Outlet, and TBEB, and were driven by high values during spring. It is unclear why these sites have higher spring Cl- concentrations than the others, but a high density of stormwater ponds are present in TBEB and the other sites are located at outlets of wetland and pond BMPs, suggesting that winter accumulation of road salt in the ponds from snowmelt may be flushing out during early spring rains. Cr, Cd, and Ni concentrations tended to be very low in stormwater, with Cr and Cd in particular often below the detection limit of the analyses. Median Cu, Pb, and Zn concentrations were highest in EK, PC, and SAP, which have the greatest total 22

CRWD Stormwater Monitoring Data Analysis Report

impervious area of all monitored sub-watersheds, suggesting that these may be primary source areas of metals. Cu, Pb, and Zn concentrations were generally several times lower at the BMP sites (Sarita, VP Outlet, GCP Outlet, and VP Inlet), suggesting that the BMPs were capturing metals through particle settling, similar to particulate nutrients. 3.2.2. Baseflow Concentrations of Nutrients, TSS, Chloride, and Metals For those sites with baseflow (EK, PC, SAP, TBEB, TBWB, TBO, VP Inlet, and VP Outlet), nutrient chemistry (Table A.2) was generally much different than in stormflow. For metals, concentrations in baseflow were frequently below the detection limit for most sites and constituents, and rarely exceeded toxicity standards (see Appendix D), and therefore are not presented here. For the non-BMP sites (EK, PC, SAP, TBEB, TBWB, and TBO), median TP concentrations in baseflow were roughly 15% - 30% of values in stormflow, consistent with the expectation that most P is delivered in stormflow due to mobility of particulates in stormwater. Accordingly, median TSS concentrations were roughly 10-50 times higher in stormflow than in baseflow at the non-BMP sites. While median TN concentrations tended to be similar among baseflow and stormflow, the form of N varied considerably: median NO3 concentrations were much higher in baseflow than in stormflow across all sites, with the greatest difference at PC, where NO3 was 4-5 times higher in baseflow than in stormflow. Higher NO3 in baseflow relative to stormflow is sensible if much of the baseflow in these larger drains is contributed by groundwater, which should be much higher in dissolved than particulate N forms. Median Cl- concentrations were generally several times higher in baseflow than in stormflow across the non-BMP sites, including an order of magnitude higher in baseflow at EK. Median Cl- concentrations at TBEB and EK exceed the MPCA water quality standard of 230 mg/L during all seasons, and maximum concentrations at most of the other sites exceed the standard for all seasons except summer. Given that groundwater is the likely source of baseflow for these sites, the results suggest that road salt applications during winter months are polluting shallow groundwater in these watersheds. For the VP sites, TP, TN, NO3, and TSS concentrations were remarkably similar between stormflow and baseflow, suggesting that the BMP is effectively capturing suspended solids as well as reducing NO3 export. For Cl-, the slightly lower median concentrations in stormflow are probably the result of dilution by a larger water volume during storms. It is also worth noting that median Cl- concentrations at both VP sites exceed the MPCA standard during winter months (Dec â&#x20AC;&#x201C; Feb). 3.2.3. Seasonal Differences in Nutrient and Metal Concentrations Nutrient and metal concentrations were tested for statistically significant differences among seasons, both in stormflow and in baseflow. Pairwise testing was conducted using CRWD Stormwater Monitoring Data Analysis Report 23

the Mann-Whitney test, with differences considered significant for p < 0.05. Results are shown for stormwater in Table 3.2a (nutrients and metals), and for baseflow in Table 3.2b (nutrients only). Note that no stormwater samples were collected during winter months (Dec â&#x20AC;&#x201C; Feb), and therefore this period was not included in the stormflow tests. Stormflow For TP, relatively few statistically significant differences (p < 0.05) existed among seasons for any of the sites. At PC, SAP, and TBEB, differences between summer and fall TP were significant, and in all cases fall concentrations were lower than summer, suggesting a depletion of TP sources in the watershed. However, there are generally fewer samples collected during fall (Sep â&#x20AC;&#x201C; Nov) than during summer (June â&#x20AC;&#x201C; Aug), and the monitoring period may end before leaf fall has finished, and therefore a potentially large input of phosphorus is not reflected in these results. In addition, TP was significantly lower during spring at VP Outlet and significantly higher during summer at VP Inlet. Seasonality of TP in this BMP, which is present to a greater extent in the baseflow TP concentration data (Table 3.2b), does not have an obvious explanation but may be related to processing or inputs, the latter of which may be greater in summer storms. Seasonality was much more prevalent in the nitrogen concentration data (TN and NO3) than in the TP data. For most non-BMP sites (EK, PC, SAP, TBEB, and TBWB), TN concentrations were significantly lower during fall than in the spring and summer, suggesting a depletion of TN sources in the watersheds. As in the case of TP, most samples were likely taken before leaf fall, and thus a large N input is probably not included. NO3 concentrations showed a strong seasonality for nearly all sites, with concentrations generally decreasing from spring to fall, and significant differences present among all seasons at SAP, VP Outlet, and GCP Outlet. NO3 depletion by algal uptake over the summer in relatively abundant surface water in these watersheds may partially explain seasonal variation of NO3 concentrations. NO3 was not a large component of stormwater TN at the non-BMP sites in general, and therefore seasonality of TN concentrations were likely being controlled by seasonal dynamics of the organic and particulate components, which may be largely contributed by lawns and trees. Few patterns were readily apparent in the seasonal differences of TSS concentrations. No significant seasonal differences were present in TSS in TBWB, TBO, or Sarita; for the latter site this is unsurprising as it is located at a wetland outlet and settling of solids is likely occurring upstream. For the other non-BMP sites (EK, PC, SAP, TBEB, and AHUG), fall concentrations of TSS were significantly lower than summer and sometimes spring as well. Higher TSS in summer may be due to high erosion rates during summer storms, which tend to be more intense than during other seasons, while higher TSS in spring (at EK and TBEB) may be due to flushing of winter-applied sand or erosion of lawns by spring rains before grass is fully established. 24

CRWD Stormwater Monitoring Data Analysis Report

Cl- concentrations showed strong seasonality for all sites except Sarita, with spring concentrations significantly different from those observed in summer and/or fall. Additionally, median spring concentrations at all sites were higher than in either summer or fall. This result is consistent with the expectation that spring rains flush road salt applied during winter months. In addition, due to solubility of Cl-, the BMP sites do very little to remove it from runoff. For all monitored metals, significant seasonal differences were present mostly at the nonBMP sites, again highlighting the ability of BMPs to allow metals to settle out and maintain relatively consistent concentrations in outflow throughout the year. Seasonal differences tended to be similar among sites for the six metals, which may be evidence of more uniform sources and delivery mechanisms among watersheds. Accordingly, the greatest seasonality was present for the sites with the most impervious area (EK, PC, SAP, and TBEB). Mean fall concentrations of most metals tended to be lower than in spring at these sites, suggesting a winter build up on impervious surfaces followed by a flushing that occurs over the warm season. Baseflow Grab samples were collected during the winter months at all sites with baseflow, and while the number of samples is few relative to the other periods, the winter season was considered in the tests for significant seasonal differences in nutrient concentrations. Metals were not considered due to the generally low concentrations year-round. For the non-BMP sites (EK, PC, SAP, TBEB, TBWB, and TBO), the strongest seasonality was present for the Trout Brook sites. This seasonality could be evidence of the influence of surface water, which may be more susceptible to seasonal nutrient dynamics than groundwater. While groundwater is likely the largest baseflow water source for all of the non-BMP sites, surface water is present in storm drain baseflow in the Trout Brook watersheds due to connections to upstream lakes (TBWB/TBO) and a large number of ponds (TBEB). Of note, median TP concentration at TBEB was higher in summer than during the rest of the year, and was significantly different from the other seasons; seasonal differences in TP were not significant in any of the other non-BMP sites. TN concentrations showed some seasonality at SAP, TBEB, TBWB, and TBO, which was similar but not identical to the seasonality in NO3 concentrations. Fall TN was significantly lower than spring TN at all four of these sites, perhaps a result of N depletion during summer in drain-connected surface waters, as a similar trend was not present in the NO3 data. At all four sites, summer NO3 was significantly lower than during spring, and lower than during winter (with the exception of TBEB). This pattern suggests that NO3-rich groundwater, which may explain high winter NO3 concentrations, might be diluted by NO3-poor outflow from ponds and wetlands in these watershed during summer. CRWD Stormwater Monitoring Data Analysis Report 25

By contrast, EK and PC, watersheds with very few BMPs or surface water, showed few significant differences among seasons for TP, TN, and NO3. This result is unsurprising as groundwater is presumed to dominate baseflow at these sites given the lack of surface water, and nutrient concentrations are not expected to vary as much throughout the year in groundwater as in surface water. One exception is TN, which was significantly lower during winter at EK; an explanation for this trend is not apparent, but due to the lower proportion of NO3 relative to PC, the pattern may be evidence of the depletion of sources of organic (non-nitrate) N during cold months. For the two VP sites, more seasonal variability was present for nutrients and TSS than in the other sub-watersheds, most likely because these sites are located in a BMP heavily influenced by surface inputs. Significant seasonal differences in nutrients and TSS were similar but not identical to those observed in stormflow. TP and TSS were significantly lower in spring than in summer and fall at both VP sites, suggesting that TP and TSS are predominantly from surface runoff inputs, which would be larger during summer and fall. While TN was not strongly seasonal, NO3 was significantly different between winter and both summer and fall, and between spring and summer. Median NO3 in winter at both sites was several times higher than in any other season; the cause is uncertain, but may result from NO3-rich shallow groundwater inputs that are not diluted by surface runoff in winter, or from the decay of vegetation within the wetland. Strong seasonality of Cl- in baseflow was present at all sites, especially between spring and summer or fall. Significant differences among nearly all seasons were observed for the two VP sites, with the lowest p values observed between winter and summer/fall and between spring and summer, a trend similar to what was observed in stormflow data for these two sites. In addition, significant differences were observed at all non-BMP sites between winter and summer. Taken together, these results strongly suggest that road salt applications during winter and spring (Nov â&#x20AC;&#x201C; Apr) may be polluting both surface water and shallow groundwater, the latter of which is likely present in all of the large non-BMP watersheds.

CRWD Stormwater Monitoring Data Analysis Report

Table 3.2a. Summary of p-values for Mann-Whitney U test of seasonal differences in nutrient, TSS, Cl-, and metals concentrations (mg/L) in stormflow at CRWD monitoring sites. Seasonal differences significant at p < 0.05 are highlighted in blue. Seasonal Comparison

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Sarita Outlet

Villa Park Outlet

Como 7

GCP Outlet

Como 3

AHUG

Villa Park Inlet

Total Phosphorus spring-summer

3.0E-01

5.3E-02

4.5E-01

5.6E-01

2.0E-01

9.3E-01

8.3E-01

3.0E-05

2.4E-01

2.2E-01

7.8E-03

7.0E-01

7.9E-06

spring-fall

1.4E-01

4.4E-01

9.5E-02

3.9E-01

7.0E-01

7.1E-01

6.2E-01

1.0E-02

5.8E-02

1.6E-01

5.8E-02

2.0E-01

8.1E-01

summer-fall

5.4E-01

5.0E-03

1.6E-03

2.0E-02

7.6E-02

5.1E-01

4.2E-01

1.0E-01

1.9E-01

6.6E-01

6.3E-01

1.1E-01

2.0E-06

Total Nitrogen spring - summer

1.4E-02

7.6E-01

6.7E-01

1.0E-01

6.7E-01

5.6E-02

4.3E-01

8.1E-02

5.8E-01

1.6E-01

8.1E-03

9.8E-01

1.3E-01

spring - fall

2.4E-04

3.3E-03

1.0E-04

7.2E-04

2.7E-02

1.6E-02

3.2E-02

1.4E-01

1.1E-01

1.8E-02

8.3E-03

2.0E-02

1.2E-04

summer - fall

2.7E-02

2.3E-04

1.5E-05

2.7E-03

1.8E-02

9.1E-02

4.8E-02

9.0E-01

3.3E-01

2.8E-01

7.9E-02

5.3E-03

1.4E-04

spring - summer

4.9E-01

3.4E-02

2.2E-02

5.6E-01

2.1E-01

1.3E-01

3.1E-01

1.8E-05

3.6E-01

4.9E-04

3.6E-01

8.8E-01

1.3E-01

spring - fall

6.1E-03

1.2E-03

1.4E-04

5.7E-04

6.7E-03

4.3E-04

1.8E-01

2.6E-03

6.5E-05

4.4E-05

5.8E-02

1.9E-03

1.5E-01

summer - fall

1.2E-02

9.4E-02

4.4E-03

2.6E-04

1.6E-02

1.8E-03

2.4E-03

4.8E-02

2.0E-04

1.6E-02

8.5E-03

2.3E-04

8.1E-01

Nitrate-Nitrite

Total Suspended Solids spring - summer

8.3E-02

1.6E-02

2.5E-01

2.7E-01

9.6E-01

6.5E-01

9.2E-01

2.0E-01

1.1E-01

3.6E-01

1.2E-02

6.1E-02

7.2E-01

spring - fall

1.6E-03

6.6E-01

1.2E-01

3.7E-03

2.5E-01

1.7E-01

9.8E-02

2.3E-02

9.6E-01

7.9E-03

1.4E-02

9.1E-01

4.6E-03

summer - fall

1.3E-02

1.7E-03

1.4E-03

2.5E-03

9.7E-02

2.0E-01

1.1E-01

3.4E-01

1.1E-01

6.8E-03

5.6E-01

3.2E-02

3.0E-03

Chloride spring - summer

1.0E-05

5.0E-05

2.8E-09

2.3E-08

4.1E-08

1.9E-07

1.6E-01

1.8E-06

3.2E-03

9.2E-02

3.8E-03

2.3E-05

1.6E-07

spring - fall

1.5E-02

5.4E-03

3.4E-08

9.9E-05

1.7E-05

9.4E-05

7.2E-01

7.6E-03

5.1E-01

4.6E-02

1.0E-01

9.9E-04

3.8E-06

summer - fall

1.5E-01

5.3E-01

2.0E-01

7.9E-01

7.6E-01

8.2E-01

8.2E-02

5.4E-01

9.5E-02

4.8E-01

6.1E-01

9.1E-01

2.2E-01

CRWD Stormwater Monitoring Data Analysis Report 27

Table 3.2a (conâ&#x20AC;&#x2122;t). Seasonal Comparison

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Sarita Outlet

Villa Park Outlet

Como 7

GCP Outlet

Como 3

AHUG

Villa Park Inlet

Cadmium spring - summer

4.0E-01

2.7E-03

3.1E-02

7.8E-01

8.9E-01

1.0E-01

8.7E-01

1.2E-01

2.8E-01

2.4E-01

4.5E-01

6.0E-01

spring - fall

4.4E-02

1.8E-03

1.0E-01

3.9E-05

1.7E-01

3.1E-01

7.7E-05

1.2E-01

5.6E-02

7.3E-03

1.3E-02

5.3E-04

3.2E-02

summer - fall

2.5E-02

3.1E-01

5.8E-01

1.4E-02

1.0E-01

2.1E-01

7.3E-04

1.3E-01

3.4E-01

3.7E-02

6.5E-02

6.4E-04

3.9E-02

Chromium spring - summer

3.2E-04

3.2E-01

3.3E-01

7.2E-02

6.9E-01

8.7E-02

6.5E-01

7.9E-01

5.4E-01

9.3E-01

1.6E-02

6.8E-01

6.7E-01

spring - fall

4.7E-06

4.7E-02

2.8E-03

2.8E-02

1.1E-01

1.9E-01

5.2E-01

3.5E-01

5.8E-01

7.0E-01

7.7E-02

6.5E-02

9.4E-01

summer - fall

1.3E-02

1.1E-03

5.7E-03

3.7E-01

6.3E-02

9.9E-01

6.7E-01

4.0E-01

8.9E-01

6.5E-01

9.3E-01

7.2E-02

8.7E-01

spring - summer

4.3E-03

1.1E-02

6.4E-01

3.8E-02

9.8E-01

1.7E-01

8.7E-01

1.5E-01

2.6E-01

7.8E-01

5.8E-02

9.9E-01

3.4E-02

spring - fall

3.5E-04

4.1E-01

1.1E-01

4.6E-03

5.3E-02

1.3E-01

9.1E-01

8.1E-01

4.8E-01

2.8E-01

1.5E-01

1.3E-01

1.3E-02

summer - fall

9.1E-02

4.2E-04

2.5E-03

2.0E-01

8.8E-03

4.6E-01

7.7E-01

1.8E-01

6.3E-01

5.1E-01

8.7E-01

4.8E-02

7.3E-01

Copper

Lead spring - summer

1.6E-01

1.2E-02

1.3E-01

6.6E-01

1.8E-01

4.6E-01

6.6E-01

8.8E-01

1.2E-01

2.4E-01

5.1E-02

9.4E-01

spring - fall

3.5E-03

4.7E-01

4.2E-01

6.3E-03

2.1E-01

1.7E-01

1.3E-01

5.8E-02

9.1E-01

2.7E-01

8.0E-03

6.4E-01

3.4E-01

summer - fall

9.0E-03

2.3E-04

1.1E-03

5.7E-03

8.3E-03

3.0E-01

3.4E-01

5.3E-02

1.6E-01

8.6E-01

5.0E-01

1.2E-01

3.1E-01

Nickel spring - summer

3.8E-02

1.5E-02

1.7E-01

1.8E-02

7.7E-01

3.2E-01

7.1E-01

2.7E-02

2.4E-01

5.5E-01

5.4E-02

7.0E-01

1.1E-03

spring - fall

5.7E-03

4.9E-01

8.0E-02

3.4E-02

1.1E-01

2.9E-01

6.9E-01

5.6E-01

4.9E-01

7.1E-01

1.8E-01

3.7E-01

2.9E-03

summer - fall

1.3E-01

2.4E-03

3.2E-04

5.9E-01

2.1E-02

6.7E-01

9.4E-01

1.8E-01

8.1E-01

3.1E-01

8.3E-01

1.2E-01

8.7E-01

Zinc spring - summer

9.6E-03

8.8E-02

3.8E-01

1.7E-03

5.3E-01

1.1E-01

3.4E-02

3.9E-01

5.2E-01

2.3E-03

1.3E-02

6.7E-01

1.1E-01

spring - fall

1.0E-04

1.4E-01

4.1E-01

2.1E-05

2.7E-02

8.2E-02

1.2E-03

1.0E+00

9.8E-01

1.8E-03

2.1E-02

4.5E-02

1.9E-02

summer - fall

2.0E-02

4.6E-04

6.2E-03

1.2E-02

1.7E-02

3.8E-01

1.8E-01

4.3E-01

5.2E-01

1.5E-01

7.3E-01

5.2E-02

1.8E-01

CRWD Stormwater Monitoring Data Analysis Report

Table 3.2b. Summary of p-values for Mann-Whitney U test of seasonal differences in nutrient, TSS, and Cl- concentrations in baseflow at CRWD monitoring sites. Seasonal differences significant at p < 0.05 are highlighted in blue. Seasonal Comparison

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Villa Park Outlet

Villa Park Inlet

spring-summer

7.5E-01

9.8E-01

Total Phosphorus 4.0E-01 3.7E-02

4.8E-01

4.1E-01

2.8E-09

1.1E-06

spring-fall

4.4E-01

6.4E-01

9.3E-02

9.2E-01

2.3E-01

2.5E-01

1.7E-07

5.1E-04

summer-fall

1.8E-01

5.0E-01

3.8E-01

2.3E-03

5.9E-01

2.7E-02

3.5E-02

1.9E-01

winter-spring

1.5E-01

3.5E-01

1.9E-01

7.2E-01

9.9E-01

9.6E-01

2.7E-01

winter-summer

1.7E-01

2.8E-01

4.4E-01

7.3E-03

7.2E-01

3.2E-01

1.3E-05

1.8E-06

winter-fall

6.2E-02

8.7E-02

9.6E-01

6.8E-01

6.6E-01

5.1E-01

1.1E-04

1.6E-04

spring-summer

2.7E-01

1.4E-01

Total Nitrogen 1.4E-03 5.5E-02

1.3E-03

1.5E-02

5.4E-01

1.5E-01

spring-fall

4.1E-01

3.4E-01

1.4E-02

6.4E-03

1.5E-02

1.9E-02

7.0E-01

6.2E-01

summer-fall

9.2E-01

5.6E-01

8.7E-02

3.0E-01

6.2E-01

8.2E-01

2.8E-01

3.7E-01

winter-spring

6.3E-03

2.7E-01

2.6E-01

8.7E-04

4.4E-01

4.9E-01

7.9E-02

6.1E-01

winter-summer

3.4E-02

9.4E-01

7.6E-02

5.2E-02

1.4E-03

2.1E-01

1.9E-02

8.0E-02

winter-fall

3.1E-02

5.2E-01

3.6E-01

1.3E-02

2.1E-01

1.6E-01

2.9E-01

spring-summer

1.1E-01

5.8E-02

Nitrate-Nitrite 1.3E-03 2.5E-04

1.8E-03

7.3E-04

1.3E-03

1.5E-02

spring-fall

2.9E-01

3.8E-01

1.3E-01

1.4E-02

3.6E-02

5.4E-02

2.5E-03

3.4E-01

summer-fall

9.8E-01

5.2E-01

8.5E-02

6.9E-01

1.7E-01

2.4E-01

8.9E-01

8.3E-02

winter-spring

7.5E-01

9.8E-01

4.7E-01

1.1E-02

9.0E-01

5.8E-01

5.6E-02

4.8E-03

winter-summer

5.5E-01

1.5E-01

4.2E-03

4.6E-01

5.8E-03

6.7E-03

1.9E-06

1.6E-08

winter-fall

7.8E-01

6.9E-01

6.6E-02

8.8E-01

3.9E-02

6.7E-02

7.6E-06

1.5E-05

spring-summer

4.6E-01

Total Suspended Solids 5.0E-01 9.8E-01 1.4E-01 4.2E-01

6.0E-01

1.4E-04

1.7E-02

spring-fall

4.4E-02

5.7E-02

1.7E-01

2.1E-01

2.9E-01

4.7E-02

3.9E-07

3.1E-02

summer-fall

1.2E-01

1.4E-01

1.7E-01

5.9E-03

4.7E-02

7.8E-02

6.9E-02

7.8E-01

winter-spring

1.1E-01

4.4E-01

9.0E-01

8.0E-01

1.8E-01

7.9E-01

2.3E-01

1.3E-01

winter-summer

2.0E-02

8.1E-01

9.2E-01

5.9E-01

6.0E-02

2.9E-01

8.9E-02

3.6E-03

winter-fall

3.4E-03

5.0E-01

1.9E-01

3.4E-01

4.0E-01

4.6E-02

4.9E-03

6.3E-03

spring-summer

4.1E-07

1.5E-01

Chloride 1.7E-01 4.6E-05

1.1E-03

8.9E-03

2.0E-07

9.4E-07

spring-fall

3.1E-05

5.2E-01

1.9E-02

8.0E-03

3.6E-04

3.6E-01

2.8E-02

6.8E-02

summer-fall

5.4E-01

1.8E-02

1.9E-05

2.8E-01

6.5E-01

1.5E-01

1.2E-03

5.3E-05

winter-spring

4.4E-01

9.3E-02

6.4E-03

9.1E-02

8.1E-01

4.6E-02

1.5E-03

1.3E-03

winter-summer

5.9E-04

4.8E-03

1.8E-05

5.3E-05

2.1E-03

1.1E-03

2.7E-07

4.1E-08

winter-fall

2.5E-03

1.9E-01

1.3E-01

8.5E-04

4.8E-04

2.1E-02

5.7E-06

1.0E-06

CRWD Stormwater Monitoring Data Analysis Report 29

3.2.4. Cumulative Water Volume and Nutrient Loading -- Stormflow Plots of cumulative seasonal loading of stormwater, nutrients, TSS, and Cl- are shown for all years at each site in Appendix I-1. Note that significant gaps in flow or chemistry data can exaggerate the contribution of all sampled events to cumulative loading (e.g. PC in 2007, SAP in 2008). Figure 3.4 shows the mean loading curves for the sites, grouped by main sites and secondary sites, with separate plots for each constituent (volume and TP in Figure 3.4a, TN and NO3 in Figure 3.4b, and TSS and Cl- in Figure 3.4c). Cumulative stormwater loading for most sites (Figure 3.4a) followed a slight S-shaped curve, with the largest increases from mid-summer through early fall, when some of the larger, more intense storms tend to occur. This seasonality appears especially true of some of the BMP sites (e.g. Sarita, GCP Outlet, VP Outlet), where these larger events cannot be completely detained and more outflow may occur than in other times of the year. For the non-BMP sites, in particular EK, PC, TBEB, and TBWB, the largest increases in stormwater loads tended to occur in fall, perhaps due to the effect of a few large fall storm events, or because of the loss of rainfall abstraction by vegetation as leaf fall occurs. The largest watersheds, TBO and SAP, had more uniform seasonal stormwater volume loading than the other sites, perhaps due to the substantial presence of BMPs and surface water in both watersheds that at large scale might serve to smooth out stormwater loading. The nutrient loading plots are intended to illustrate the combined effect of seasonality in both runoff yields and nutrient concentrations. Loading of nutrients (TP, TN, NO3) at most sites was similar to stormwater, with perhaps slightly larger increases in nutrient loads (relative to increases in stormwater volume) during summer and early autumn, which may be related to event size. Some non-BMP sites (e.g. EK, PC, TBW, TBO) showed substantial increases in TN and TP loads in early summer that could perhaps be related to early-season inputs of leaves, seeds, and flowers as trees leaf out. However, the similarity of nutrient and stormwater loading suggests that while some nutrient concentrations do vary significantly among seasons during the monitoring period (Section 3.2.3), these differences are not enough to substantially impact seasonal loading (though extreme loading events may still be a concern during seasons with generally higher nutrient concentrations). Instead, nutrient loading appears to be controlled primarily by the seasonality of stormwater loads. Seasonal patterns of cumulative TSS loading also tended to follow patterns in water loading, though most sites showed much larger increases in TSS than in stormwater in late summer and early fall, especially at the BMP sites. This late season TSS flux is presumably due to larger or more intense storms occurring during this part of the year, which may tend to cause greater erosion rates and carry more sediment into storm drains. In the case of the BMP sites, the large or intense late summer storms may be pushing 30

CRWD Stormwater Monitoring Data Analysis Report

sediment-laden water from the BMPs, which are better able to detain the smaller or lessintense events that tend to occur during the rest of the year. The cumulative loading curves for Cl- were generally dissimilar to the stormwater loading curves at the non-BMP sites because of the significantly higher spring Clconcentrations at these sites. In particular, EK, SAP, TBEB, TBWB, and TBO showed large increases in Cl- loading in late spring and early summer, with nearly uniform (linear) loading the rest of the monitoring season. This is unsurprising for stormwater since early season rains are expected to flush winter road salt applications from impervious surfaces, and once this source has been depleted, stormwater concentrations become more uniform as background sources (e.g. groundwater mixing, outflow from ponds and wetlands) become the dominant contributors of Cl-.

CRWD Stormwater Monitoring Data Analysis Report 31

Figure 3.4. (a) Mean cumulative seasonal stormwater volume loading at main sites (top left) and secondary sites (top right), and mean cumulative seasonal stormwater TP loading at main sites (bottom left) and secondary sites (bottom right).

CRWD Stormwater Monitoring Data Analysis Report

Figure 3.4. (b) Mean cumulative seasonal stormwater TN loading at main sites (top left) and secondary sites (top right), and mean cumulative seasonal stormwater NO3 loading at main sites (bottom left) and secondary sites (bottom right).

CRWD Stormwater Monitoring Data Analysis Report 33

Figure 3.4. (c) Mean cumulative seasonal stormwater TSS loading at main sites (top left) and secondary sites (top right), and mean cumulative seasonal stormwater Cl- loading at main sites (bottom left) and secondary sites (bottom right). 34

CRWD Stormwater Monitoring Data Analysis Report

3.2.1. Cumulative Water Volume and Nutrient Loading -- Baseflow In general, loading of water and nutrients by baseflow (Appendix I-2) was much more uniform than by stormwater due to the less dynamic nature of baseflow water sources, which is likely groundwater at most sites. The exception to this was the two VP sites, which are dominated by surface water in the upstream ponds and wetlands and therefore exhibited some seasonal variation in nutrient and water loading. Cumulative water loading was very uniform throughout the monitoring season for all sites (the non-BMP sites in particular), as exhibited by the linear loading curves (Appendix I-2). The Trout Brook sites in particular were remarkably constant over the season, even showing small variation year-to-year. This suggests a consistent source of baseflow, which in these watersheds is mostly groundwater that may be potentially enhanced by the presence of buried streams. As in the case of stormwater, cumulative nutrient loading (TP, TN, and NO3) was tied strongly to hydrology, and was therefore relatively constant throughout the year on average, especially for the non-BMP sites (EK, PC, SAP, TBEB, TBWB, and TBO). For the VP sites, NO3 loading appears to be relatively more intense during spring than the rest of the monitoring period (with a similar pattern for TN at VP Outlet), which is explained by the significantly higher NO3 concentrations observed at both sites during winter and spring relative to summer (Table 3.2b). This could be the result of build-up of NO3 during winter (perhaps due to decay of wetland vegetation) that is flushed out by storms and baseflow in spring, or perhaps due to the dominance of potentially NO3-rich groundwater during winter and early spring, when the upstream ponds and wetlands are mostly frozen. TSS, which is found in much lower concentrations in baseflow than in stormflow, showed some seasonality in cumulative loading. In particular, a regular late spring â&#x20AC;&#x201C; early summer increase in loading was present at PC, and both VP sites showed relatively sharp increases in TSS loading during fall. At the VP sites, this fall increase in TSS loading may be caused by flushing of summer-deposited sediment from the wetland during autumn rains, especially as macrophytes senesce and potentially reduce the ability of the wetland to filter out and retain sediment. This explanation is also supported by the much larger increases in fall TSS loading at VP Outlet vs. VP Inlet. Cumulative baseflow loading of Cl- was more variable among sites than for nutrients and TSS. Spring peaks in Cl- loading were apparent at the VP sites and to a lesser extent EK; this is a logical observation for the BMP sites (VP) as road salt accumulated in the ponds and wetlands of this BMP during winter are flushed out in spring outflow. An explanation for EK is more difficult, but results suggest that shallow groundwater is the primary baseflow component at EK. Some flushing of this reservoir may thus occur during late spring, with more consistent loading of Cl- (which is above the MPCA water CRWD Stormwater Monitoring Data Analysis Report 35

quality standard year-round) during the rest of the season. At the other sites, the Trout Brook sites in particular, Cl- loading is relatively constant throughout the monitoring season as well as among years. Cumulative Baseflow Loading – Annual Annual flow data was collected for the non-BMP sites (EK, PC, SAP, TBEB, TBWB, and TBO) during 2010, 2011 and 2012, allowing cumulative baseflow loading curves to be developed for the entire year rather than just the Apr – Oct monitoring period. These plots are shown in Appendix I-3. Note that in all years, the monitoring interval at SAP is shorter than a year (Mar – Dec in 2010, Apr – Dec in 2011, parts of June and Nov in 2012) due to equipment issues. Note that while major snowmelt intervals were identified by CRWD for 2011 and 2012 and are not included in these plots, some snowmelt input is probably reflected in the loading curves. As expected, baseflow water loading was relatively constant throughout the year at these sites, especially at the Trout Brook sites. Annual water loading was more variable at EK, with an increase in loading rates in early spring 2011 and 2012, and during summer of 2010. The cause of these patterns is uncertain, but may be related to seasonality of flow rates of shallow groundwater, which is assumed to be the primary baseflow source in this watershed. Over the annual time scale, nutrient loading was very similar to water loading for these sites. Much of TN is in dissolved form as NO3 in these large drains, and therefore the annual loading curves for TN and NO3 were very similar for all sites and generally followed patterns in water yields. Some site-to-site variability was observed for TP; while loading was uniform over much of the year at PC, TBWB, and TBO, small increases in loading rates were present in spring and again in fall for TBWB and TBO. As baseflow in the Trout Brook watersheds is influenced by outflow from upstream lakes (Como and McCarrons), increases in TP, especially in fall, may be related to seasonality of both terrestrial and aquatic vegetation inputs. The spring TP increases occur simultaneously with increases in TN, TSS, and Cl- (especially in 2012), suggesting inputs from snowmelt or early season rainfall, which would influence outflow from upstream lakes in the TBWB and TBO watersheds. Note that the sharp increases in TP during late fall at TBEB in 2010 and at EK in 2011 are likely caused by single, high TP concentrations being applied to long-duration loading intervals due to less frequent sampling during this time of year, and thus may not reflect actual changes in loading rates. TSS loading varied among sites and between years when considered on an annual time scale, and did not appear to follow the relatively uniform patterns of water yield. For example, increased loading rates were observed in July, Aug or Sep at EK, with similar peaks observed for PC in Feb-Mar and May-June. All three Trout Brook sites showed large increases in loading rates in Feb-Mar of 2011 and 2012 but not in 2010. The early 36

CRWD Stormwater Monitoring Data Analysis Report

spring peaks are likely related to small snowmelt events, which would be expected to flush sediment (likely from winter road deicing applications) into the drains and would be higher in TSS than groundwater during baseflow periods. Spring of 2011 in particular would have involved more snowmelt as snowfall was far above average during the winter of 2010-2011. For Cl- loading, patterns similar to those of TSS were observed for all sites, suggesting that early season TSS (and Cl-) inputs may be due in part to flushing of sand and salt applied to roads during winter. In 2011, all sites showed large increases in Cl- loading rates in early spring (beginning in Feb or Mar), in particular at PC and EK, which have less surface water than the Trout Brook sites. Smaller spring increases in Cl- loading rates were observed in 2012, and especially in 2010; springs in both of these years followed much warmer and drier winters than 2011. Interestingly, while peak loading rates of Clwere also observed in spring in the cumulative loading curves for the Apr-Oct monitoring period, the annual data shows that the onset of Cl- loading peaks may be much earlier than the start of the monitoring period, and also that, while data are limited, loading rates may be highly dependent on antecedent winter conditions (e.g. snowfall, snowpack depth, temperature).

3.3. Impact of Storm Event Characteristics on Water and Nutrient Loading Cumulative rainfall frequency plots for rain count, cumulative runoff volume, and cumulative loads of nutrients and sediment were determined for all monitored subwatersheds. In addition, a simple linear regression analysis was used to determine the importance of antecedent conditions (e.g. days since last measurable rainfall, total rainfall in previous 7 days) on runoff volume and nutrient, TSS, Cl-, and metal concentrations. 3.3.1. Cumulative Rainfall Frequency and Runoff Volume Cumulative rainfall frequency plots (exceedence probability distributions for runoff volume and rainfall events versus rainfall depth) are given for all sites in Appendix E-1. Results for EK are also shown in Figure 3.4a as an example. As is generally the case for all monitored sites, the cumulative runoff volume frequency distribution has a similar shape to the rain event frequency distribution, but they are not coincident. As a result, the median rainfall depth for EK is 0.46 inches, but rainfall events of this depth and smaller only account for 21% of the total runoff volume; half of the runoff volume occurs for events 0.81 inches and smaller. A 1-inch rainfall event, which is commonly used to size BMPs, is in the 87th percentile for EK, but events at or below this depth contribute only 63% of total runoff volume. These results show that the largest storms comprise the majority of the total runoff volume for this site, an unsurprising result given that very little area of this watershed is devoted to surface water storage or BMPs. By contrast, the CRWD Stormwater Monitoring Data Analysis Report 37

smallest events, which are the most frequent, are mostly captured by the watershed and may not be of great concern in BMP design.

Figure 3.4. Cumulative rainfall frequency plots of rain event count and cumulative stormwater runoff volume at (a) East Kittsondale (EK) and at (b) Villa Park Outlet. A second example of rainfall and runoff volume exceedence probabilities is shown in Figure 3.4b for VP Outlet. Both the rain event count and runoff volume curves are more vertical and shifted slightly towards greater rainfall depth relative to EK because larger rainfall events are completely captured by the wetland system compared to the EK watershed. As a result, the median rainfall depth is much greater for VP Outlet (0.69 in) than for EK (0.46 in). Events at and below this depth constitute 24% of the total runoff volume from VP Outlet, while half the total runoff volume occurs for rainfall depths of 38

CRWD Stormwater Monitoring Data Analysis Report

1.11 inches and smaller -- considerably larger than at EK (0.81 in). A 1-inch storm is in the 74th percentile by rainfall depth and 45st percentile for cumulative runoff volume. These results illustrate the effect of BMPs to restrict runoff to greater rainfall depths, especially relative to watersheds (such as EK) with very little surface storage or few BMPs. Rainfall and runoff exceedence probability characteristics are summarized for all sites in Table 3.3. The BMP sites (GCP Outlet, VP Outlet, Sarita) have the largest median rainfall depths and largest rainfall depths corresponding to median cumulative runoff volumes, likely due to the ability of BMPs to store runoff from smaller events. Rainfall depths of 1 inch or less contributed 32% - 42% of the total runoff volume at these sites, suggesting that the BMPs were designed for storms smaller than 1-inch, or that other factors (e.g. rainfall intensity, antecedent conditions, variable watershed area) are increasing water loads to these BMPs. Similarly, among the non-BMP sites, those with upstream connections to lakes (e.g. TBWB) or with relatively large numbers of ponds and wetlands (e.g. TBEB, SAP) had higher median rainfall depths and/or greater rainfall depths corresponding to median cumulative runoff volume when compared to sites such as EK and PC, which have less surface water and fewer BMPs. Table 3.3. Summary of rainfall and runoff frequency characteristics of CRWD subwatersheds. Median Rainfall by Count Site

Depth

Cmltv Vol

(in)

(fraction)

0.43

PC SAP

Rainfall Depth at Median Cmltv Vol

1-inch Rainfall

Median Event Vol by Count

Cmltv Vol

Rainfall

(in)

(fraction)

Percentile

(ft )

0.20

0.82

0.62

0.87

534,105

0.50

0.21

0.86

0.55

0.84

596,768

0.55

0.23

0.85

0.59

0.84

1,195,920

TBEB

0.59

0.24

1.01

0.50

0.77

358,771

TBWB

0.53

0.19

1.13

0.45

0.80

1,147,130

TBO

0.51

0.25

0.80

0.59

0.82

2,955,970

Como7

0.31

0.12

1.13

0.48

0.89

10,768

GCP

0.72

0.19

1.24

0.42

0.73

257,416

VP Out

0.74

0.25

1.26

0.41

0.70

268,419

Sarita

0.65

0.14

1.50

0.32

0.74

69,328

Como 3

0.28

0.11

1.05

0.47

0.84

53,914

AHUG

0.32

0.12

0.87

0.59

0.90

6,331

VP Inlet

0.56

0.23

0.94

0.54

0.79

224,831

Note that some of the smaller sites (e.g. AHUG, Como 3) have smaller median rainfall event depths than the larger watersheds. This is likely the result of including in the CRWD Stormwater Monitoring Data Analysis Report 39

analysis only those events that produce runoff. In the smaller watersheds, less rainfall is required to produce runoff that is above the sampling threshold (“trigger”) for the autosamplers; at the larger sites the trigger is set higher so that changes in baseflow rates are not sampled as storm events. It is also possible that at the larger sites, especially those with significant amount of surface storage, smaller events are mostly contained on the watershed, resulting in little detectable effect on flow at the watershed outlet. 3.3.2. Cumulative Rainfall Frequency and Nutrient, TSS, and Cl - Loading Cumulative rainfall frequency curves for loads of nutrients, TSS, and Cl- are shown for all sites in Appendix E-2. In general, cumulative loading curves for TP, TN, NO3, and TSS are very similar to each other, and to the cumulative stormwater volume curves (shown also in the nutrient loading plots for reference). This suggests, much as in the case of the seasonal cumulative loading curves (Appendix I-1), that hydrology is controlling stormwater loading of nutrients and TSS. For Cl-, the loading curves fall slightly above the other curves at most sites due to a larger percentage of total Cl- loading being associated with smaller rainfall events. This is perhaps caused by the high solubility of Cl-, which makes it mobile in even the smallest rainfall-runoff events. The differences in Cl- loading are especially apparent at EK and PC, which have less BMPs and surface water than most of the other sites, and therefore less ability to retain water, even for small events. It should be noted that March rainfall events were left out of these analyses due to their scarcity at most sites. This prevents confounding of results among sites due to release of Cl- in snowmelt; the few early spring rainfall-snowmelt events that exist in the record at all sites generally have very high Clconcentrations and loads, even for small rainfall events, which may tend to exaggerate the Cl- curves even further. With a greater sample size, these events could potentially be examined on their own to determine the impact of early spring rains on flushing of nutrients, and Cl- in particular. 3.3.3. Effect of Antecedent Rainfall on Stormwater and Nutrient Loading Stormflow water yield (in) and stormwater nutrient (TP, TN, NO3), TSS, Cl-, and metal (Cd, Cr, Cu, Pb, Ni, Zn) concentrations were regressed against three antecedent rainfall characteristics, including days since last measureable rainfall (“dry days”), days since last storm of 0.5 inch depth or greater (“days since 0.5-inch rain”), and total rainfall depth in the previous 7 days (“antecedent weekly rain”). Results are shown in Appendix B. For stormwater yield, antecedent weekly rain was a statistically significant predictor (i.e., p < 0.05) for all sites. This is perhaps a logical result, as slope was positive for antecedent weekly rainfall; positive slope suggests that as more rainfall occurs in the week before an event, the watershed has less ability to capture water via infiltration or surface storage, resulting in greater runoff. The other antecedent parameters were generally not significant, except at SAP and VP Outlet, where both dry days and days since 0.5-inch 40

CRWD Stormwater Monitoring Data Analysis Report

rain were significant. These sites are dissimilar in terms of size and land cover composition and thus the correlations may be spurious, but stormwater yields from both may be influenced to a significant degree by antecedent conditions. For TP and TN, all three antecedent parameters were statistically significant predictors of nutrient concentration at most sites; of these, antecedent weekly rainfall appeared to be a slightly better predictor than the other two parameters for TN and TP, as it generally explained more variance (higher R2). A notable exception to this is at several of the smaller sites: none of the antecedent parameters were useful predictors of TP concentration for VP Inlet or of TN concentration for Sarita or Como 3. These differences, at least for VP Inlet and Sarita, may result from the large BMPs at these sites that capture particulate N and P, potentially reducing the impact of antecedent rainfall. In addition, for all sites, regressions of TP and TN concentration had negative slopes with antecedent weekly rainfall, which was opposite the trend for stormwater yield. This suggests that N and P source dilution may be occurring as antecedent rainfall and/or stormwater volume increases. For TSS, fewer significant correlations existed with antecedent parameters at most of the sites. For the significant relationships, positive slopes associated with dry days and days since 0.5-inch rainfall and negative slopes associated with 7-day antecedent rainfall suggest that TSS may be subject to build-up and wash-off. This effect could explain the strong correlations of TP and TN with antecedent rainfall parameters, as N and especially P tend to be transported as particulates in stormwater (e.g. Waschbusch et al. 1999, Easton and Petrovic 2008). The significant effect of all three antecedent conditions on TSS concentrations at TBWB, TBO, and GCP Outlet suggests that in addition to build-up and wash-off, flushing of sediment from abundant surface water in these watersheds may be occurring, as concentrations of TSS could increase with drier antecedent conditions (e.g. due to evaporation). NO3 was correlated with almost none of the antecedent rainfall parameters at any sites. While atmospheric deposition may be a potentially important source of NO3 in urban watersheds, if it were the dominant source it would be expected to have greater correlation with antecedent rainfall (evidence of build-up and wash-off). NO3 is a relatively small component of stormwater TN at most sites, and the dominant source is likely fertilizer, pet waste, and/or vegetation rather than dry deposition. Cl- concentration in runoff was significantly correlated with antecedent rainfall parameters at most sites, particularly for antecedent weekly rainfall and days since last 0.5-inch rainfall. An explanation for these trends is not readily apparent given the seasonality of Cl- in storm runoff, but dry deposition on impervious surfaces between events may play a role in enhancing Cl- concentrations. For example, as in the case of TN and TP, all slopes for Cl- vs. antecedent weekly rainfall are negative, suggesting that as CRWD Stormwater Monitoring Data Analysis Report 41

more rainfall occurs prior to an event, less Cl- is available and/or it is being diluted by larger stormwater volumes. All metals were significantly correlated with antecedent rainfall parameters at most sites (with perhaps fewer total significant correlations present for Cu and Cd), though the amount of variance explained (R2) was generally low overall. Similar to TSS, among significant relationships the slopes associated with dry days and days since 0.5-inch rainfall were positive and those associated with 7-day antecedent rainfall were negative, suggesting build-up and wash-off as the primary transport mechanism for metals. Finally, none of the antecedent parameters appeared to be more frequently significantly correlated with metals concentration than the others, although R2 was usually higher for weekly antecedent rainfall than for the other parameters.

3.4. Impact of Land Cover and Drainage Characteristics on Water and Nutrients in Stormflow Simple linear regression was used to investigate correlations of stormflow nutrients and metals with 21 land cover and drainage characteristics of several of the non-BMP subwatersheds (AHUG, EK, PC, SAP, TBEB, and TBWB). A complete list of land cover factors is shown in Table 2.2. Dependent variables included stormwater yield, and event mean concentration and event yield of nutrients (TP, TN, NO3), TSS, Cl-, and selected metals (Cu, Pb, Zn). Linear regression parameters from the analysis (slope, R2, and pvalue) are summarized in Appendix C. In general, very few useful relationships emerged from this analysis for parameters expected to be good predictors of nutrient and metal concentrations (e.g. total impervious area, street density, lawn). Of the explanatory variables, canopy over street, ‘other’ impervious, alley, and several roof types (institutional, high-density residential, commercial, and industrial) were the only factors that were statistically significant (p < 0.05) predictors of nutrient concentration. Of these, the most sensible factors are probably canopy over street and ‘other’ impervious area (parking lots, alleys, and driveways). Alley area and the specific roof types are generally scarce in the monitored watersheds (with the exception of low-density residential), and thus most of those correlations are likely spurious. Relationships of nutrient concentrations with canopy over and near the street were positive, and significant for TP and TSS, suggesting that this near-street tree cover may enhance TP concentrations, perhaps by leaching nutrients from leaves or through washoff of atmospheric deposition onto the street surface. However, if litterfall was a major source of nutrients, TN would also be expected to be significantly correlated with near42

CRWD Stormwater Monitoring Data Analysis Report

street canopy cover, and TSS is the only other nutrient for which a near-street canopy is a statistically significant predictor. NO3 concentration was significantly and positively correlated with â&#x20AC;&#x2DC;otherâ&#x20AC;&#x2122; impervious area. This is a sensible result if atmospheric deposition is a primary source of NO3, as these areas may serve as collectors of deposition. However, if impervious areas were also primary pathways of transport, factors such as street density or total impervious area should also be correlated with NO3, but none of these parameters are significant predictors of either NO3 concentration or yield. Very few factors were significant predictors of water, nutrient, sediment, or metal yields. This is a surprising result, especially for water yield, given that impervious surfaces in particular are expected to be primary conveyances of water and nutrients. The near lack of correlations for yields suggests that water and nutrient sources in CRWD may be relatively diverse, and that a single source or transport factor is not primarily responsible for nutrient and metal loading. The watershed areas used to calculate yields may also be inaccurate, particularly for the watersheds with upstream lakes and wetlands (SAP, TBWB/TBO), as these upstream areas were not included in the yields despite possibly contributing some water and nutrients during storm events.

3.5. Exceedence Probabilities of Water Yields and Nutrient Loads Flow-duration curves were constructed for runoff, and load-duration curves for nutrients (TP, TN, NO3), TSS, and Cl- in both stormflow and baseflow. All flow-duration curves are shown for stormflow and baseflow in Appendices F-1 and F-3, respectively, and loadduration curves are shown in Appendix F-2 for stormflow and in Appendix F-4 for baseflow. 3.5.1. Stormflow Flow-duration curves for stormflow showed the expected S-shaped patterns for volume and flow rate at most sites (e.g. EK in Figure 3.5a). Stormwater volumes and flow rates varied over 3 or 4 orders of magnitude at several of the smaller non-BMP sites (e.g. AHUG, Como 3, and EK), as well as at two of the BMP outlet sites (GCP Outlet and Sarita). For the non-BMP sites, these ranges may be related to lower sampling thresholds for the auto-samplers (some small events go undetected at the larger sites) or less capacity for surface water storage relative to the larger sites, thus causing more small events to be included in the analysis for these sites. By contrast, flatter loading curves were observed for the larger watersheds, in particular SAP and the Trout Brook sites, which may be related to upstream lakes, ponds, and wetlands in these watersheds that tend to moderate flow rates of larger or more intense storms. CRWD Stormwater Monitoring Data Analysis Report 43

As in the case of the cumulative loading plots, the nutrient, TSS, and Cl- loading exceedence curves for a given site were similar in shape to each other. Likewise, for most sites, load-duration curves followed similar patterns as their respective flow-duration curves, with some exceptions, particularly for small events, that might be related to the smaller data sets used for the load-duration curves (i.e., samples were not collected for all events for which flow was measured.) However, the results generally support the conclusion that hydrology has a stronger influence than nutrient or sediment sources on stormwater loading in CRWD watersheds. Some discrepancies existed between the load-duration curves for TSS and the other constituents. For example, at several sites, including PC, TBEB, TBO, and VP Inlet, TSS curves appeared to have slightly steeper slopes overall than the other loading curves. This is due to greater amounts of sediment being mobilized for the larger (i.e. low exceedence probability) storms, but these increases do not appear to also correlate to higher nutrient and Cl- loads for these sites. In addition, at some sites (TBEB, PC and to a lesser extent AHUG, SAP, and TBO) TSS loading decreased more than the other constituents for smaller (high exceedence probability) events, which may be related to low mobility of sediment for small storms at these sites. 3.5.2. Baseflow Baseflow flow-duration curves were much flatter and much less variable than those for stormflow at a given site (e.g. for EK in Figure 3.5b) due to relatively uniform flow rates throughout the monitoring season at those sites with baseflow. At all sites except EK and the VP sites, baseflow rate generally varied over less than an order of magnitude. For TBWB and VP Inlet/Outlet, the loading curves were similar among nutrients, TSS, and Cl-, with similar shapes to their respective flow-duration curves resulting from relatively uniform nutrient concentrations and baseflow rates. At the remaining sites, some variation was present among constituents. For example, at TBEB, TP, TSS, and Clloading were less uniform, particularly at the extreme low- and high- exceedence probabilities. The higher loading rates may perhaps be explained by the influence of snowmelt or the receding limbs of storm events. This may also be the case at SAP and EK, where some higher loading rates are present in Cl- and TSS in particular. At PC, a large range in loading rates are present at the extreme low- and high- exceedence probabilities, which is somewhat surprising given the nearly steady baseflow rates and relatively linear cumulative loading curves (Appendix I). This suggests a large but infrequent change in nutrient concentrations, perhaps due to snowmelt (for Cl-) or input of water with low nutrient content, although the source of such an input is unknown.

CRWD Stormwater Monitoring Data Analysis Report

1,000.0

1,000,000

100.0

100,000

10.0

10,000

1.0

Storm Event Flow Rate (cfs)

Storm Event Volume (cu ft)

10,000,000

Volume Flow Rate 1,000 0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

0.1 1.00

Probability of Exceedence 100.000

Baseflow Rate (cfs)

10.000

1.000

0.100

0.010

0.001 0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Probability of Exceedence

Figure 3.5. Flow-duration curves for the East Kittsondale (EK) site, for (a) stormflow and (b) baseflow.

CRWD Stormwater Monitoring Data Analysis Report 45

3.6. Metals Toxicity Exceedences in Stormwater Plots of metals concentrations vs. hardness along with the chronic toxicity standard for 6 metals (Cr, Cd, Cu, Pb, Ni, and Zn) are shown for all sites in Appendix G. Toxicity exceedence probability curves based on the toxicity standard and water hardness data are shown in Appendix H. Only stormflow is considered, as metals concentrations in baseflow are low and toxicity exceedences are rare. Figure 3.6 shows an example of toxicity and metal concentration vs. hardness for Cu and Zn measurements at TBEB. These plots show that the toxicity standards increase nonlinearly for increases in hardness. For Zn, it is apparent that a few storm events at TBEB exceed the toxicity standard (mostly at lower hardness), while for Cu roughly half of the events exceed the toxicity standard for a range of hardness values. The corresponding toxicity exceedence probability plots for Cu and Zn at TBEB are shown in Figure 3.7. For Zn, the few toxicity exceedences were mostly for lower hardness values, which correspond to lower values of the toxicity standard (and a higher exceedence probability) at this site. For Cu, toxicity exceedences were distributed across the whole range of hardness values (and toxicity exceedence probabilities).

Figure 3.6. Observed stormflow metal concentrations in g/L and toxicity standards at TBEB as a function of observed total hardness mg/L for zinc (left) and copper (right).

CRWD Stormwater Monitoring Data Analysis Report

Figure 3.7. Toxicity exceedence probability curves at TBEB for zinc (left) and copper (right). Observations of metals concentrations (in g/L) are also shown. 3.6.1. Seasonality of Metals Toxicity For many sites, Cu, Pb, and Zn frequently exceeded chronic toxicity standards. The seasonality of these exceedences was investigated to determine if certain times of year were more likely to have exceedences than others, which might aid in the design of future BMPs where metals toxicity is an issue. The percentage of samples in each season (spring, summer, fall) that exceed the standard, as well as the mean value of the exceedences are summarized in Table 3.4 by metal and by site. Only stormflow results are included here; the corresponding table for baseflow is shown in Appendix D. No toxicity exceedences were observed in stormflow at any of sites for Cr or Ni, while exceedence percentages for Cd, Cu, Pb, and Zn varied considerably among sites, and among seasons within some sites. For Cd, most non-BMP sites had fewer than 20% exceedences across seasons; exceedences of greater than 28% were present during summer and fall at the Como sites (Como 7, GCP Outlet, Como 3, and AHUG). For Cu and Pb, all sites except the VP sites had toxicity exceedences of roughly 60% or higher for all seasons. The most among-site variability in exceedence percentages was observed for Zn: exceedences were highest (60% to 100%) at EK, Como 7, Como 3, and AHUG, and lowest or non-existent at the VP Sites. On average, the percentage of events exceeding standards did not vary much among seasons, with a few exceptions where considerable variability was observed, such as at AHUG, Sarita, Como 7, and GCP Outlet for Cd, and at most sites for Zn. At the main sites, summer Zn exceedences were more common than in spring or fall, while spring exceedences were more common at many of the smaller sites. Toxicity exceedence values, defined as the difference between the observed concentration and the toxicity standard for the observed hardness, also showed some CRWD Stormwater Monitoring Data Analysis Report 47

variability among sites and among seasons (Table 3.4). For Cu, Pb, and Zn, exceedence values were generally largest at EK, PC, and SAP, with the smallest values observed at the BMP sites (Sarita, GCP Outlet, VP Outlet). The largest Cd exceedences were found at TBO, but were an order of magnitude higher than at any other site, suggesting an error in the data or presence of a point source (the large exceedences were found only in the spring). Exceedences generally decreased in value from spring to fall at most sites, suggesting that spring or summer may be the most important time of year for metals toxicity management. Toxicity exceedence values in stormflow were tested for statistically significant differences among seasons using the Mann-Whitney test. Table 3.5 summarizes p-values for all sites and metals. Very few statistically significant differences among seasons (at p < 0.05) were found for Cd and Zn, in which the percentage of exceedences among seasons appeared to vary the most. One exception is EK, in which Zn exceedences were significantly lower in fall and decreased throughout the year from spring to fall, suggesting source depletion of Zn (or an increase in water hardness) over the season. Similar trends, while not statistically significant, were present at a few other sites (TBEB, TBWB, and AHUG). Statistically significant seasonal differences in Cu and Pb toxicity exceedences were present at all of the main sites except TBO. Due to lower Cu and Pb exceedence values in the fall, differences between summer and fall toxicity exceedences were nearly all significant at these sites, with several spring-fall differences significant as well. As in the case of Zn at EK, this may be related to source depletion or an increase in water hardness (which would increase the toxicity standard), though a uniform increase in water hardness across sites is less likely than a depletion of Cu and Pb sources to stormwater. As streets and impervious surfaces could be considered the primary collectors and vectors for metals transport (by providing substrate for atmospheric deposition and connecting directly to storm drains), it is possible that summer and fall rains deplete this source at a faster rate than deposition recharges it, leading to low exceedences in the fall and higher exceedences in spring and summer. This conclusion is supported in part by the metals concentration data; concentrations of Cu and Pb in particular decline over the spring and/or summer seasons in stormwater at many sites (Table A.1), and many of these decreases were found to be statistically significant, especially at the main sites (Table 3.2a).

CRWD Stormwater Monitoring Data Analysis Report

Table 3.4. Seasonality of metals toxicity exceedences in stormflow of CRWD sub-watersheds. Season

Parameter

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Sarita Outlet

Villa Park Outlet

Como 7

GCP Outlet

Como 3

AHUG

Villa Park Inlet

summer

spring

Cadmium No. of Samples

Exceedences (%)

11.5

0.0

4.5

73.7

8.3

0.0

37.5

9.1

0.0

30.4

0.0

Mean Exc. (ug/L)

0.103

N/A

0.148

0.686

0.083

N/A

0.186

0.036

N/A

0.141

N/A

Exceedences (%)

13.2

10.5

7.0

7.5

6.5

7.3

29.2

0.0

33.3

28.1

32.0

50.0

3.0

Mean Exc. (ug/L)

0.219

0.571

0.595

0.649

0.245

0.594

0.094

N/A

0.129

0.115

0.123

0.128

1.204

Exceedences (%)

25.8

15.4

3.7

4.0

4.8

0.0

45.8

0.0

29.4

50.0

40.0

90.5

4.2

Mean Exc. (ug/L)

0.297

1.316

0.014

0.059

N/A

0.301

N/A

0.046

0.148

0.160

0.183

0.111

No. of Samples

Exceedences (%)

0.0

Mean Exc. (ug/L)

N/A

No. of Samples

fall

No. of Samples

fall

summer

spring

Chromium

Exceedences (%)

0.0

Mean Exc. (ug/L)

N/A

No. of Samples

Exceedences (%)

0.0

Mean Exc. (ug/L)

N/A

CRWD Stormwater Monitoring Data Analysis Report 49

Table 3.4 (conâ&#x20AC;&#x2122;t). Seasonality of metals toxicity exceedences in stormflow of CRWD sub-watersheds. Season

Parameter

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Sarita Outlet

Villa Park Outlet

Como 7

GCP Outlet

Como 3

AHUG

Villa Park Inlet

summer

spring

Copper No. of Samples

Exceedences (%)

100.0

95.2

87.5

79.2

81.8

66.7

91.7

0.0

100.0

63.6

100.0

4.2

Mean Exc. (ug/L)

36.9

14.9

15.4

8.3

15.8

16.8

4.3

N/A

15.5

2.1

15.6

12.1

0.4

Exceedences (%)

98.5

94.7

75.4

77.4

90.3

83.6

81.3

0.0

97.9

65.6

96.0

98.0

4.5

Mean Exc. (ug/L)

26.3

23.9

19.8

8.1

15.5

11.8

4.8

N/A

12.7

9.4

8.9

12.6

10.0

Exceedences (%)

100.0

84.6

77.8

64.0

81.0

65.0

91.7

0.0

94.1

50.0

100.0

95.2

0.0

Mean Exc. (ug/L)

21.9

13.5

12.9

4.2

8.4

13.0

3.3

N/A

9.6

1.6

9.3

7.9

N/A

Exceedences (%)

100.0

93.8

83.3

90.9

77.8

100.0

0.0

100.0

90.9

100.0

8.3

Mean Exc. (ug/L)

46.7

36.2

22.4

10.8

18.7

22.4

12.2

N/A

19.4

3.2

25.8

17.6

3.9

Exceedences (%)

97.1

96.5

80.7

92.5

98.4

90.9

95.8

9.1

100.0

93.8

100.0

10.6

Mean Exc. (ug/L)

48.1

53.7

27.2

11.4

22.4

21.6

11.9

2.1

18.0

1.6

13.6

20.5

7.3

Exceedences (%)

100.0

92.3

77.8

72.0

95.2

90.0

100.0

16.7

100.0

92.9

100.0

8.3

Mean Exc. (ug/L)

28.4

31.0

18.9

4.9

13.4

17.7

9.3

1.5

14.0

1.4

10.1

15.5

0.8

No. of Samples

fall

No. of Samples

summer

spring

Lead No. of Samples

No. of Samples

fall

No. of Samples

CRWD Stormwater Monitoring Data Analysis Report

Table 3.4 (conâ&#x20AC;&#x2122;t). Seasonality of metals toxicity exceedences in stormflow of CRWD sub-watersheds. Season

Parameter

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Sarita Outlet

Villa Park Outlet

Como 7

GCP Outlet

Como 3

AHUG

Villa Park Inlet

fall

summer

spring

Nickel No. of Samples

Exceedences (%)

0.0

Mean Exc. (ug/L)

N/A

No. of Samples

Exceedences (%)

0.0

Mean Exc. (ug/L)

N/A

No. of Samples

Exceedences (%)

0.0

Mean Exc. (ug/L)

N/A

No. of Samples

Exceedences (%)

100.0

76.2

50.0

12.5

40.9

25.9

83.3

0.0

95.8

27.3

92.3

95.7

0.0

Mean Exc. (ug/L)

146.4

69.1

63.3

43.3

60.3

44.6

11.7

N/A

83.8

5.0

58.5

64.0

N/A

Exceedences (%)

95.6

87.7

66.7

26.4

54.8

29.1

41.7

0.0

93.8

3.1

84.0

96.0

4.5

Mean Exc. (ug/L)

102.1

93.1

81.5

25.0

45.1

47.8

15.8

N/A

60.8

2.8

32.9

56.5

101.8

Exceedences (%)

93.5

50.0

48.1

4.0

33.3

25.0

16.7

0.0

76.5

0.0

60.0

90.5

0.0

Mean Exc. (ug/L)

68.5

63.0

61.7

7.8

23.7

56.5

14.1

N/A

54.8

N/A

40.4

36.3

N/A

summer

spring

Zinc

No. of Samples

fall

No. of Samples

CRWD Stormwater Monitoring Data Analysis Report 51

Table 3.5. Summary of p-values for Mann-Whitney U test of seasonal differences in metals toxicity exceedence values in stormflow at CRWD monitoring sites. Seasonal differences significant at p < 0.05 are highlighted in blue. Seasonal Comparison

Kittsondale

Phalen Creek

St. Anthony Park

Trout Brook East

Trout Brook West

Trout Brook Outlet

Sarita Outlet

Villa Park Outlet

Como 7

GCP Outlet

Como 3

AHUG

Villa Park Inlet

Cadmium spring-summer

1.0E+00

8.1E-01

N/A

7.1E-01

2.9E-01

N/A

1.0E+00

N/A

spring-fall

9.2E-01

1.2E-03

6.5E-01

1.0E+00

1.4E-01

7.7E-01

N/A

9.3E-02

5.0E-01

N/A

3.1E-01

1.6E-01

summer-fall

9.2E-01

3.9E-01

8.0E-01

1.0E+00

2.2E-01

3.4E-01

N/A

1.8E-01

3.9E-01

7.3E-01

7.5E-02

6.7E-01

Chromium spring-summer

N/A

spring-fall

N/A

summer-fall

N/A

9.5E-02

6.1E-01

N/A

Copper spring-summer

5.8E-02

8.4E-03

1.8E-01

4.6E-01

9.0E-01

8.5E-02

5.3E-01

N/A

2.7E-01

5.3E-01

spring-fall

6.3E-03

5.4E-01

9.9E-01

5.2E-02

4.9E-02

2.6E-01

6.1E-01

N/A

8.6E-01

3.2E-01

1.7E-01

5.1E-01

N/A

summer-fall

2.5E-01

9.1E-04

1.6E-02

1.3E-01

1.7E-02

8.2E-01

8.4E-02

N/A

4.9E-01

1.6E-01

1.0E+00

7.4E-02

N/A

Lead spring-summer

5.0E-01

2.5E-02

1.3E-01

5.8E-01

3.5E-01

5.6E-01

7.1E-01

N/A

2.1E-01

4.4E-01

4.8E-02

6.7E-02

8.9E-01

spring-fall

1.7E-02

1.9E-01

7.8E-01

1.6E-02

2.1E-01

1.3E-01

1.4E-01

N/A

6.7E-01

3.1E-01

6.5E-03

7.4E-01

3.3E-01

summer-fall

9.7E-03

1.1E-04

3.7E-02

3.1E-02

1.2E-02

1.7E-01

1.8E-01

7.3E-01

1.3E-01

4.3E-01

3.6E-01

1.3E-01

5.0E-01

Nickel spring-summer

N/A

spring-fall

N/A

summer-fall

N/A

Zinc spring-summer

8.9E-02

1.8E-01

3.5E-01

8.9E-02

3.4E-01

8.2E-01

6.2E-01

N/A

7.8E-01

N/A

4.8E-02

9.4E-01

N/A

spring-fall

1.2E-03

6.5E-01

5.0E-01

1.4E-01

8.8E-01

5.4E-01

N/A

6.3E-01

N/A

4.4E-01

1.6E-01

N/A

summer-fall

2.2E-02

9.8E-02

2.7E-01

7.3E-01

2.2E-01

7.8E-01

1.0E+00

N/A

4.8E-01

N/A

4.4E-01

1.2E-01

N/A

CRWD Stormwater Monitoring Data Analysis Report

4. Summary Part 1: Spatial and Seasonal Patterns in Water, Nutrients, Metals 4.1.1. Baseflow vs. Stormflow Appreciable differences existed between stormflow and baseflow in the loading of water, nutrients, and metals. Baseflow water yields were quite variable among sites, and with the exception of EK, were substantial, comprising 56% to 67% of combined seasonal volume at PC, TBEB, TBWB, and TBO. These percentages are even greater when considered on an annual scale. TP concentrations were much higher in stormflow as expected, but TN concentrations were roughly similar between stormflow and baseflow, suggesting that baseflow is potentially important for N loading. For metals (Cd, Cr, Cu, Pb, Ni, Zn), baseflow concentrations were very low, often below the detection limit and very rarely exceeded toxicity standards; stormflow concentrations were generally much higher, and in particular for Cu, Pb, and Zn, frequently exceeded toxicity standards. For Cl-, stormwater concentrations were generally much lower than in baseflow, and never exceeded the MPCA standard of 230 mg/L; baseflow Cl- exceeded the standard at TBEB and EK. 4.1.2. Spatial Variation Spatial (i.e. site-to-site) variation was present to some extent in the water and nutrient data for stormflow. As expected, the BMP sites (Sarita, VP Inlet/Outlet, GCP Outlet) tended to have steadier flow regimes (flatter hydrographs, lowest stormflow water yields and runoff coefficients) and the lowest median TP, TN, and TSS concentrations, which logically suggests that the BMPs are effective in reducing nutrient export by detaining water and capturing particulates. By contrast, non-BMP watersheds with very little surface water (ponds, lakes, or wetlands) or BMPs, including EK and PC, had the flashiest hydrographs and the highest stormwater yields, runoff coefficients, and TP, TN, and TSS concentrations, consistent with expectations for highly urbanized watersheds. Sites with some surface water in their watersheds (SAP and the Trout Brook sites) tended to have longer hydrographs and variable stormflow water yields and nutrient concentrations, likely the result of a relative diversity of water and nutrient sources and transport pathways in these watersheds. For metals, in particular Cu, Pb, and Zn, median concentrations were highest in the watersheds with the greatest total impervious area (EK, PC, and SAP), suggesting that these surfaces may be both sources and vectors of metals transport.

CRWD Stormwater Monitoring Data Analysis Report 53

4.1.3. Seasonality Seasonal patterns were present in concentrations and loads of nutrients and metals in CRWD watersheds, with considerable site-to-site variability present in these seasonal trends. These patterns are summarized separately for stormflow and baseflow. Stormflow In stormflow, very few statistically significant (p < 0.05) differences among seasons existed at any of the sites for TP concentration. Summer and fall differences in TP at PC, SAP, and TBEB were significant, with lower concentrations observed in the fall, suggesting source depletion over the summer (likely due to the establishment of lawns, which may prevent erosion, and to the seasonal maturing of trees and plants, causing less plant material to enter the sewers). However, it is possible that extending the monitoring season into the early winter to capture the effect of leaf fall would lead to a sharp increase in TP in the autumn, as it is a potentially large TP input that is likely not reflected in the results. Stronger seasonality was present in the TN data, with significantly lower concentrations of TN observed in the fall at several of the non-BMP sites (EK, PC, SAP, TBEB, and TBWB). A similar explanation to the TP data is likely; the monitoring season may not always capture events after leaf fall. Leaf fall would be expected to produce a large flux of TN to the landscape following a summer depletion of organic and particulate N, which is generally derived from soil and vegetation, and comprises the majority of TN at most sites. Cumulative N, P, and TSS loading curves at most sites tended to follow patterns in cumulative stormwater volume, with the largest increases in loading rates generally occurring in late summer and early fall. This suggests that while significant seasonality is present in stormwater nutrient concentrations at some sites, nutrient loading is primarily driven by hydrology. Cl- concentrations were higher in the spring at most sites, and statistically different from the other seasons (fall and summer), consistent with the expectation that spring rains flush winter applications of road salt. As a result, loading curves for Cl- tended to show large increases in spring, with more uniform loading the rest of the season. For all monitored metals, significant seasonal differences were present mostly at the nonBMP sites, again suggesting that BMPs are capturing metals and particulates. Seasonal differences tended to be similar among sites for the six metals, which may be evidence of more uniform sources and delivery mechanisms among watersheds for metals.

CRWD Stormwater Monitoring Data Analysis Report

Baseflow In baseflow, very few significant differences existed among seasons in nutrient and TSS concentrations at EK and PC. This is a sensible result given that the two sites are likely dominated by groundwater, for which nutrient chemistry is not expected to change as dynamically as surface water. At the remaining non-BMP sites (SAP, TBEB, TBWB, and TBO), which all have storm drain connections to surface water, some seasonality was present in TP, TN, and NO3. However, no consistent patterns emerged other than significantly lower fall TN relative to spring TN at these four sites. At the VP sites, seasonal variability was more prevalent in baseflow than at the other sites due to the logical influence of surface water at these sites. The most noteworthy differences were observed for TP and TSS, which were significantly higher in summer and fall than in spring (suggesting a surface runoff or internal source), and for NO3, which was several times higher in winter than any other season, suggesting an influx of NO3-rich groundwater undiluted by stormwater or an internal source such as decay of vegetation within the wetland. Cl- concentrations were significantly different between winter/spring and summer at most sites in baseflow (and significantly different among nearly all seasons at the VP sites), with concentrations generally highest in winter and lowest in the summer. These results strongly suggest that road salt applications during winter and spring (Nov â&#x20AC;&#x201C; Apr) may be polluting both surface water and shallow groundwater, the latter of which is likely present in all of the large non-BMP watersheds. Cumulative loading curves for nutrients and TSS in baseflow were generally much more linear than in stormflow, due to much more uniform loading rates of water. The Trout Brook sites were especially constant over the season and among years. For Cl-, loading curves were less linear, though primarily for the VP sites, which had sharp increases in spring loading rates similar to stormflow Cl- loading curves.

Part 2: Impact of Storm Event Characteristics on Water and Nutrient Loading 4.1.4. Cumulative Rainfall Frequency Some variability existed in rainfall-runoff characteristics of the main sub-watersheds. Among the non-BMP sites, the rainfall depth corresponding to median cumulative runoff volume ranged from 0.80 in (TBO) to 1.13 in (TBWB), while the 1-inch rainfall corresponded to a range in cumulative volume fractions of 0.45 (TBWB) to 0.62 (EK) and ranged in depth from 77th percentile at TBEB to 87th at EK. Therefore slightly more than half of the total stormwater volume from most watersheds is contributed by events of 1-inch and smaller. In addition, the smallest 50 percent of rainfall events (by count) contribute only 19% (TBWB) to 25% (TBO) of total runoff volume at the major subwatersheds. This logically suggests that the larger, less common rainfall events are CRWD Stormwater Monitoring Data Analysis Report 55

disproportionately important in terms of stormwater loading. A design storm larger than 1-inch may be needed to further reduce stormwater (and nutrient) loading by BMPS in some watersheds. BMPs shift importance to larger rainfall events by design, and rainfall-runoff results from the BMP sites (GCP Outlet, VP Outlet, Sarita) show this to be the case. Median rainfall depths are higher for these sites relative to the non-BMP sites, and the rainfall depth corresponding to median cumulative runoff volume is also much higher for the BMP sites. These results suggest that the BMPs monitored by CRWD are effective in controlling runoff volume to some degree, and that placing such BMPs in other watersheds might further reduce runoff volumes in those watersheds. 4.1.5. Antecedent Conditions Antecedent conditions were important for stormwater yield and concentrations of TN, TP, and Cl-. In particular, the amount of rainfall occurring in the week prior to an event appeared to be important for explaining variance in these quantities, producing generally higher R2 than the other two parameters. In addition, as antecedent weekly rainfall increased, stormwater yield increased (positive slope) and TN, TP, and Cl- concentrations decreased (negative slope), suggesting that source depletion or dilution may be occurring for greater antecedent rainfall and/or increasing stormwater volume. Fewer significant correlations with antecedent rainfall parameters were observed for TSS, though significant relationships showed positive slopes for dry days and days since 0.5inch rainfall and negative slopes for 7-day antecedent rainfall, suggesting that build-up and wash-off may be a dominant transport process in stormwater. Additionally, TN and TP, which are predominantly found in particulate form in stormwater in CRWD (Janke et al. 2013) are well-correlated with antecedent rainfall, and therefore may also be subject to build-up and wash-off. By contrast, the near lack of significant correlations between NO3 and antecedent rainfall suggests that the dominant source of NO3 is perhaps fertilizer, pet waste, or vegetation, rather than dry deposition. No obvious patterns emerged for metals and antecedent rainfall. Cu and Cd were perhaps less commonly significantly correlated with antecedent parameters than the other metals, and none of the antecedent parameters appeared to be a better predictor of metal concentration than the others.

Part 3: Impact of Land Cover and Drainage Characteristics on Water and Nutrients in Stormflow Very few land cover and drainage characteristics were found to be sensible or useful predictors of concentration of nutrients and metals in CRWD sub-watersheds in the linear regression analysis. Of the explanatory variables, almost none were significantly 56

CRWD Stormwater Monitoring Data Analysis Report

correlated with nutrient, metal, or stormwater yields, while canopy over street, ‘other’ impervious, alley, and several roof types were the only statistically significant (p < 0.05) predictors of nutrient concentration. Of these explanatory variables, the most sensible factor is tree canopy over street. The positive slope of the regression of TP with tree canopy suggests that near-street tree cover may enhance TP concentrations, perhaps through litterfall inputs or wash-off of atmospheric deposition. In addition, NO3 concentration was significantly and positively correlated with ‘other’ impervious area, suggesting that atmospheric deposition, which may collect on these surfaces, is a potentially significant source of NO3. Overall, the general lack of statistically significant correlations between nutrients and land cover or drainage metrics in the single linear regression analysis suggests the presence of multiple sources and transport pathways in the CRWD watersheds. However, very little should be concluded from this regression analysis for several reasons: (1) the large size of many sub-watersheds might have obscured some source signals; (2) the relatively uniform land use (i.e. residential) for many of the watersheds, particularly at large scale, resulted in small ranges of the land cover metrics; and (3) the small number of sub-watersheds (6) used reduced the statistical power of the analysis.

Part 4: Exceedence Probabilities of Water Yields and Nutrient Loads Flow-duration curves showed the expected S-shaped patterns for volume and flow rate in stormflow at most sites. Flatter curves were observed for the larger watersheds (e.g. SAP and the Trout Brook sites), likely reflecting the presence of surface water and/or BMPs in these watersheds that help to reduce flow rates for large storms and detain most of the runoff from smaller storms. By contrast, flow rates and volumes varied over several orders of magnitude at many of the smaller non-BMP sites. The nutrient, TSS, and Cl- load-duration curves for a given site were similar in shape to each other and to their respective flow-duration curve. Some exceptions exist for the high exceedence probability events, which are small events that are often monitored for flow but not sampled for nutrients. However, as in the case of the cumulative loading curves, the results suggest that hydrology rather than nutrient or sediment sources dominate stormwater loading in these watersheds. Baseflow loading tended to be more uniform than stormflow, in particular due to relatively constant baseflow rates; at all but EK and the VP sites, baseflow rates varied by less than an order of magnitude. However, some unexpected variability was observed in the load-duration curves at a few sites (PC and TBEB, and to a lesser extent EK and SAP). In particular, Cl- and TSS loading rates varied at the extreme low- and high-

CRWD Stormwater Monitoring Data Analysis Report 57

exceedence probabilities, perhaps due to the influence of snowmelt events or the receding limbs of storm events that were treated as baseflow.

Part 5: Metals Toxicity Exceedences in Stormwater Due to relatively lower concentrations of metals and much higher water hardness in baseflow, chronic toxicity standards as defined by Minnesota Rules 7050.0222 were very rarely exceeded in baseflow for the six metals sampled by CRWD (Cd, Cr, Cu, Pb, Ni, Zn). In stormflow, no toxicity exceedences were observed for Cr or Ni, while for Cd fewer than 20% of sampled events exceeded standards at most sites, with the exception of the Como sites, which had much higher exceedence percentages (28% or greater). More frequent exceedences were observed for Cu and Pb (60% or higher at all sites except VP), while the most variability among sites occurred for Zn: greater than 60% to 100% of events exceeded standards at EK, Como 7, Como 3, and AHUG, with almost no exceedences at the VP sites. Cu, Pb, and Zn are therefore likely the metals of greatest interest in terms of management due to the frequency of toxicity exceedences. Toxicity exceedence values of Cu, Pb, and Zn were generally largest at EK, PC, and SAP, and smallest at the BMP outlet sites. Exceedence values tended to decrease in value from spring to fall at most sites, suggesting the effect of source depletion or dilution over the summer. Concentration data showed that Cu, Pb, and Zn concentrations decreased from spring to fall, and these seasonal differences were statistically significant (p < 0.05) at many sites. Accordingly, exceedence values of Zn were statistically lower during fall than in other seasons at EK, while fall exceedence values of Cu and Pb were significantly lower at most sites. These results suggest that spring or summer may be the most important time of year for metals toxicity management, though the percentage of events exceeding standards does not vary much (on average) among seasons except for Zn.

CRWD Stormwater Monitoring Data Analysis Report

References

Bannerman RT, Baun K, Bohn M, Hughes PE, Graczyk DA (1983). Evaluation of Urban Nonpoint Source Pollution Management in Milwaukee County, Wisconsin. Vol 1. PB 84-114164. EPA Water Planning Division. Barr Engineering (2010). Evaluation of groundwater and surface-water interaction: guidance for resource assessment, Twin Cities Metropolitan Area, Minnesota. June 2010. 27 pp. http://www.metrocouncil.org/Wastewater-Water/Publications-AndResources/Evaluation_of_Groundwater_and_Surface_Water_Intera.aspx. Accessed 12 Sep 2013 Brick G (2008). Historic waters of the capitol region watershed district, Ramsey County, Minnesota. In: Capitol Region Watershed District 2010 watershed management plan. Capitol Region Watershed District (CRWD) (2012) Capitol region watershed district 2012 monitoring report. 195 pp. Easton ZM, Petrovic AM (2008). Determining phosphorus loading rates based on land use in an urban watershed. In: Nett MT, Carroll MJ, Horgan BP, Petrovic MA (eds) The fate of nutrients and pesticides in the urban environment. American Chemical Society, Washington, D.C. pp 43-62. Fissore C, Hobbie SE, King JY, McFadden JP, Nelson KC, Baker LA (2011). The residential landscape: fluxes of elements and the role of household decisions. Ecol App 15:1-18. Helsel DR and Hirsch RM (2002). Statistical Methods in Water Resources Techniques of Water Resources Investigations, Book 4, Chapter A3. U.S. Geological Survey. 522 pages. Janke BD, Finlay JC, Hobbie SE, Baker LA, Sterner RW, Nidzgorski D, Wilson BN (2013). Contrasting influences of stormflow and baseflow pathways on nitrogen and phosphorus export from an urban watershed. Submitted to: Biogeochemistry, Jan 2013. Kanivetsky R and Cleland JM (1992). Geologic Atlas of Ramsey County: Surficial Hydrogeology. County Atlas Series, Atlas C-7, Plate 6. Minnesota Geological Survey. Kilberg D, Martin M, Bauer M (2011). Digital classification and mapping of urban tree cover: City of St. Paul. University of Minnesota. Jan 2011. 17 pp. Meyer GN (2007). Surficial Geology of the Twin Cities Metropolitan Area, Minnesota. Miscellaneous Map Series, Map M-178. Minnesota Geological Survey. CRWD Stormwater Monitoring Data Analysis Report 59

Pitt R, Lilburn M, Durrans SR, Burian S, Nix S, Vorhees J, Martinson J (1999). Guidance Manual for Integrated Wet Weather Flow (WWF) Collection and Treatment Systems for Newly Urbanized Areas (New WWF Systems). U.S. Environmental Protection Agency, Urban Watershed Management Branch, Edison, New Jersey. Waschbusch RJ, Selbig WR, Bannerman RT (1999). Sources of Phosphorus in Stormwater and Street Dirt From Two Urban Residential Basins in Madison, Wisconsin, 1994-95. USGS WRI 99-4021, 47 pp., U.S. Geological Survey, Washington, D.C.

CRWD Stormwater Monitoring Data Analysis Report

November 6, 2013 Board Meeting IV. Special Report - B) CRWD Lakes Statistical Analysis

DATE: TO: FROM: RE:

October 31, 2013 CRWD Board of Managers Anna Eleria, Water Resource Project Manager Statistical Analysis of Lake 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 Boardâ&#x20AC;&#x2122;s review and comment is a draft technical memorandum summarizing the results and recommendations for further analysis and monitoring. Action Requested None, for your information only

enc: Draft Technical Memorandum of Statistical Analysis of CRWD Lakes Data

W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis - Wenck\Board Memos\BM CRWD Lakes Analysis Presentation 11-0613.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 Lake, Crosby Lake, and Lake McCarrons. W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

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

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. 2 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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. 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 3 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

4 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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. 5 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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. Chl‐a Statistic TP (mg/L) (µg/L) Secchi (m) No. of observations 177 177 177 Minimum 0.009 0.317 0.700 Maximum 0.175 74.800 8.400 1st Quartile 0.016 2.780 1.700 Median 0.026 6.500 2.750 3rd Quartile 0.039 13.370 4.000 Mean 0.031 9.760 2.952 Variance (n‐1) 0.001 107.056 2.199 Standard deviation (n‐1) 0.025 10.347 1.483 Skewness (Pearson) 3.258 2.856 0.697 Kurtosis (Pearson) 14.539 12.298 0.206 Standard error of the mean 0.002 0.787 0.114 Geometric mean 0.026 6.197 2.580 Geometric standard deviation 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. 6 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

Data Equal Varianc e?1 No

Logs of Data Normally Normally Equal Distribut Variance Distribute d? ed?2 ? No Yes No

Residuals1 Residuals of Logs1 Normally Normally Equal Equal Varianc Distribut Varianc Distribut ed? e? ed? e? No No Yes No

Total Phosphorus Chlorophyll No No Yes No No No Yes No ‐a Secchi Yes No No Yes Yes No No Yes Depth 1 Levene’s test 2 Shapiro‐Wilks test 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.

7 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

8 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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 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 Drivers 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. 9 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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. 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 TP (mg/L) Chl‐a (ug/L) Secchi (m) No. of observations 307 307 307 Minimum 0.031 0.1 0.20 Maximum 0.970 223.3 4.20 1st Quartile 0.089 6.8 0.70 Median 0.129 20.1 1.20 3rd Quartile 0.228 49.4 2.20 Mean 0.182 32.8 1.58 Variance (n‐1) 0.023 1261.7 1.09 Standard deviation (n‐1) 0.150 35.5 1.05 Skewness (Pearson) 2.358 1.9 0.86 Kurtosis (Pearson) 6.879 4.8 ‐0.31 Standard error of the mean 0.009 2.1 0.06 Geometric mean 0.142 16.5 1.26 Geometric standard deviation 1.974 3.9 2.00 A visual review of the summer average total phosphorus concentrations for Como Lake suggest a somewhat cyclical pattern of several years of high phosphorus concentrations followed by a few years of 10 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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. None 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

Data Equal Varianc e?1 No

Logs of Data Normally Normally Equal Distribut Variance Distribute d? ed?2 ? No No No

Residuals1 Residuals of Logs1 Normally Normally Equal Equal Varianc Distribut Varianc Distribut ed? e? ed? e? No No No No

Total Phosphorus Chlorophyll No No No No No No No No ‐a Secchi No No No No No No No No Depth 1 Levene’s test 2 Shapiro‐Wilks test 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. 11 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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 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. 12 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

13 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 Table 6. General statistical description of Lake McCarrons water quality data. Chl‐a Statistic TP (mg/L) (µg/L) Secchi (m) No. of observations 87 87 87 Minimum 0.010 0.2 0.50 Maximum 0.330 47.0 4.90 Range 0.320 46.8 4.40 1st Quartile 0.032 2.8 1.63 Median 0.051 4.7 2.00 3rd Quartile 0.091 8.8 2.88 Mean 0.066 8.0 2.26 Variance (n‐1) 0.002 75.6 0.85 Standard deviation (n‐1) 0.050 8.7 0.92 Skewness (Pearson) 2.415 2.2 0.55 Kurtosis (Pearson) 8.414 5.0 ‐0.23 Standard error of the mean 0.005 0.9 0.10 Geometric mean 0.053 5.1 2.07 Geometric standard deviation 1.895 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. 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. 14 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 Table 7. Evaluation results for tests of normality and equal variance among groups. Parameter

Data Equal Varianc e?1 No

Logs of Data Normally Equal Normally Distribut Variance Distribute ed?2 ? d? No No No

Residuals1 Residuals of Logs1 Equal Normally Equal Normally Varianc Distribut Varianc Distribut e? ed? e? ed? No No No No

Total Phosphorus Chlorophyll No No No No No No No No ‐a Secchi No No No No No No No No Depth 1 Levene’s test 2 Shapiro‐Wilks test 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 pattern 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 (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. 15 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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 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 16 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

17 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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 TP (mg/L) Chl‐a (ug/L) Secchi (m) No. of observations 70 70 70 Minimum 0.012 1.1 1.90 Maximum 0.093 21.8 4.60 Range 0.081 20.7 2.70 1st Quartile 0.017 2.4 2.80 Median 0.022 3.4 3.35 3rd Quartile 0.027 6.3 3.80 Mean 0.024 4.5 3.29 Variance (n‐1) 0.000 10.5 0.45 Standard deviation (n‐1) 0.012 3.2 0.67 Skewness (Pearson) 3.166 2.5 ‐0.25 Kurtosis (Pearson) 14.803 10.1 ‐0.75 Standard error of the mean 0.001 0.4 0.08 Geometric mean 0.022 3.7 3.22 Geometric standard deviation 1.459 1.9 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.

18 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 Table 8. Evaluation results for tests of normality and equal variance among groups. Parameter

Data Equal Varianc e?1 Yes

Logs of Data Normally Equal Normally Distribut Variance Distribute ed?2 ? d? No Yes No

Residuals1 Residuals of Logs1 Equal Normally Equal Normally Varianc Distribut Varianc Distribut e? ed? e? ed? Yes Yes Yes No

Total Phosphorus Chlorophyll Yes No Yes Yes Yes No Yes Yes ‐a Secchi Yes Yes Yes Yes Yes Yes Yes Yes Depth 1 Levene’s test 2 Shapiro‐Wilks test 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. 19 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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 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 McCarrons 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 20 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013 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 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 Mississippi and Minnesota Rivers. 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 Mississippi and Minnesota Rivers 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 Lake McCarrons. The long term effectiveness of Lake McCarrons 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. 21 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

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

22 W:\07 Programs\Monitoring & Data Acquisition\Lakes\2013 Lakes Analysis ‐ Wenck\Technical Memo\Technical Memo FINAL\Lake Trend Assessment Technical Memo FINAL CRWD comments.docx

November 6, 2013 Board Meeting V. Action Item A) Approve Minutes of October 16, 2013 DRAFT Regular Board Meeting (Sylvander)

Regular Meeting of the Capitol Region Watershed District (CRWD) Board of Managers, for Wednesday, October 16, 2013 6:08 p.m. at the office of the CRWD, 1410 Energy Park Drive, Suite 4, St. Paul, Minnesota. REGULAR MEETING I.

Call to Order of Regular Meeting (President Joe Collins) A) Attendance Joe Collins Mike Thienes Shirley Reider Seitu Jones Mary Texer â&#x20AC;&#x201C; absent w/notice

Others Present Mark Doneux, CRWD Michelle Sylvander, CRWD Forrest Kelley, CRWD Anna Eleria, CRWD Lindsay VanPatten, CRWD Elizabeth Beckman, CRWD

Public Attendees Todd Shoemaker, Wenck

Review, Amendments and Approval of the Agenda

President Collins asked for additions or changes to the agenda. Administrator Doneux stated that representatives from Hamline University will deliver proto types of the education display designs. After a discussion with the board, item VI. A) Education Display Designs Update could be elevated to an action item. Motion 13-187: Approve the October 16, 2013 Agenda. The consensus of the board approved the October 16, 2013 Agenda. II.

Public Comments â&#x20AC;&#x201C; For Items not on the Agenda There were no public comments.

III.

Permit Applications and Program Updates A)

Permit # 13-026 Associated Bank (Kelley)

Mr. Kelley, reviewed Permit #13-026 Associated Bank Project. The applicant is Associated Bank. The permit is for demolition and construction of a new bank at the corner of Snelling and Dayton. The applicable rules are Stormwater Management (Rule C), Flood Control (Rule D), Erosion and Sediment Control (Rule F). The disturbed area of this project is 1.5 Acres and .93 Acres impervious surface. Motion 13-188: To approve Associated Bank Permit #13-026 with 4 conditions: 1. 2.

Receipt of $4,650 surety and maintenance agreement. Provide a copy of the NPDES permit. Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District

Increase filtration volume to provide at least 3,949 cf of storage between the outlet invert elevation and the top of the sand. Currently, 1,993 cf is provided between elevation 926.3 and 925.56. Clarify placement of the 4” draintile. Detail B on sheet C8-02 states the 4” draintile shall be on the sides and outlet, but sheet C5-01 indicates it is a 6” draintile.

Reider/Thines Unanimously approved B)

Permit # 13-029 Island Station Demolition (Kelley)

Mr. Kelley, reviewed Permit #13-029 Island Station Demolition. The applicant is Frattalone. The permit is for the demolition of Island Station Power Plant. The applicable rule is Sediment Control (Rule F). This project has 3.5 Acres of disturbed area and no impervious surface. Motion 13-189: To approve Island Station Demolition Permit 13-029 with nine conditions: 1. 2. 3. 4. 5.

6. 7. 8. 9.

Receipt of $7,000 surety. Provide a copy of the NPDES permit. Revise construction limits, perimeter controls, and revegetation areas to encompass the temporary parking area.. Provide native seed mix appropriate for the river corridor and floodplain such as Mn/DOT 300 series. Provide a note on the plans that stockpiles, equipment and other demolition materials shall not be placed within the 100 yr floodplain, and that the floodplain shall be fenced or flagged to prevent encroachment. Identify and provide protection for catch basins on Randolph Avenue. Provide a flood response plan to minimize floodwater contact with demolition materials and exposed soils. Quantify the net change in floodplain storage and provide compensatory storage for any fill within 100yr floodplain. Provide final plans signed by a professional engineer per the Minnesota Board of AELSLAGID.

Reider/Thienes Unanimously approved President Collins asked for clarification on item number 8. Mr. Kelley replied that in a floodplain, to prevent a change in elevation, projects can not add fill. C)

Permit #13-030 Western U Plaza (Kelley)

Mr. Kelley reviewed permit #13-030 Western U Plaza. The applicant is St. Paul Old Home Plaza. The permit is for redevelopment and reuse of former Old Home property at Western and University. The applicable rules are Stormwater Management (Rule C), Flood Control (Rule D), Erosion and Sediment Control (Rule F). This project has 1.6 Acres of disturbed area and 1.03 Acres of impervious surface. Motion 13-190: Table the permit application for Western U Plaza Permit 13-030 with 10 Conditions: 1. Receipt of $5,150 surety and maintenance agreement. 2. Provide a copy of the NPDES permit. 3. Provide plans signed by a professional engineer per the Minnesota Board of AELSLAGID. Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District

4. Place inlet protection on curb catch basins on University Avenue. 5. Show location of existing storm sewer for catch basins at corner of University Avenue and Western Avenue. Two catch basins appear to be detached from storm sewer system. 6. Remove geotextile fabric from bottom of the rock reservoir, provide on top and sides only 7. Revise grading plan so that, in the event the underground StormTech system outlet manhole overflows, runoff flows to the west and into the street. The current grading promotes runoff flowing into the parking garage ramp. 8. Revise plans, drainage area map, and HydroCAD to correspond: a) Specify within the plan set or include a detail to show the elevation of underground StormTech system. Confirm the values correspond with the HydroCAD model. b) Area 4 (new building) is draining to the underground facility in HydroCAD, but there is a storm sewer inlet on the east side of the building on sheet C5. c) Porch area is draining to the underground facility in HydroCAD, but a separate storm sewer for the porch is on plan sheet C5. 9. Define location and dimension for the pretreatment system for the StormTech underground infiltration system. Isolator row is selected as pretreatment in plan set but location and orientation is not defined in the plan set. 10. Identify whether the existing storm sewer in Lot 2 will be removed. Removal is not specified on sheet C5. 11. Revise plans to show pavement replacement where existing storm sewer is being disconnected and removed. Thienes/Reider Unanimously approved Manager Jones abstained from voting due to possible conflict of interests. D)

Permit Program/Rules Update (Kelley)

There will be three permit applications at the November 6th meeting. IV.

Special Reports

No Special Reports

Action Items A) AR: Approve Minutes of the October 2, 2013 Regular Meeting (Sylvander)

Motion 13-191: Approve Minutes of the October 2, 2013 Regular Meeting. Jones/Reider Unanimously approved B)

AR: Approve Accounts Payable/Receivables for September 2013 (Sylvander)

Motion 13-192: Approve Accounts Payable/Receivables for September 2013 Thienes/Reider Unanimously approved Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District

AR: Approve letter of support for CCLRT GLGI (Eleria)

Ms. Eleria reviewed at the October 2, 2013 Board meeting, the City of Saint Paul presented its work and findings over the past two years on shared, stacked-function green infrastructure (SSGI) as a tool for more robustly achieving transit-oriented redevelopment in the Green Line corridor (formerly known as the Central Corridor). The City has prepared a draft final project report titled “Strategic Stormwater Solutions for Transit Oriented Development” and is seeking stakeholder comments until October 18, 2013. CRWD staff have prepared a draft comment letter and detailed memorandum on the draft final report for the Board’s review and approval. The letter and memorandum include the Board’s verbal comments to the City at the Oct. 2nd meeting as well as CRWD staff comments. Motion 13-193: Approve the comment letter and detailed memorandum to the City of Saint Paul for the draft final report titled, “Strategic Stormwater Solutions for Transit-Oriented Development”. Thienes/Jones Unanimously approved Motion 13-194: Approve Resolution for Shared, Stacked-Function Green Infrastructure. Therefor be it resolved that CRWD Board of Managers support the incorporation of shared, stacked-function green infrastructure into (re) development projects when doing so would result in economic, environmental and social benefits to the community. Be it further resolved, CRWD will support the implementation of shared, stackedfunction green infrastructure by: 1. Providing education materials of shared, stacked-function green infrastructure; 2. Encouraging consideration of shared, stacked-function green infrastructure in pre-development discussions. 3. Considering regulatory measures to facilitate shared, stacked-function green infrastructure. 4. Considering conducting pilot studies to better understand and refine the shared, stacked-function green infrastructure framework. 5. Considering integration of shared, stacked-function green infrastructure where prudent in CRWD-led and CRWD-funded projects. Thienes/Reider Unanimously approved VI.

Unfinished Business A.

Education Display Designs Update (Beckman)

Ms. Beckman reviewed in July of 2011 the Board of Managers authorized staff to explore options for creating education displays. In September 2012, a committee consisting of Managers Jones and Texer and CRWD staff selected Hamline University’s Center for Global and Environmental Education (CGEE) to design and fabricate the displays. The Board of Managers reviewed the proto types of the Education Displays. Overall the Board was very pleased with the displays. A few modifications were requested by Administrator Doneux, the Board of Managers and the committee. Motion 13-195: Motion to begin fabrication of the Educational Displays with recommended changes. Jones/Reider Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District

Unanimously approved Manager Thienes asked if the displays would be ready to share at the December 6th, 2013 MAWD meeting. Ms. Beckman felt that was enough time for the modifications to be made and the final fabrications to be made for one display. B.

CAC Revitalization Update (Reider)

Ms. Reider attended the October 9th, 2013 CAC meeting. The focus of the meeting was about strengthening the roles of the CAC. Former State Senator Ellen Anderson was the facilitator. Ms. Reider felt the ideas that the CAC had were very similar to ideas from the Board of Managers. The CAC showed an interest in more social events that would involve more opportunities to interact and meet the staff of CRWD. The attendance of the meetings continues to average around 50% of the total membership. VII.

General Information A.

CAC Update and identify a Board Member Attendee for November 13 th CAC Meeting

Ms. Reider will attend the November 13th CAC meeting. B.

Administrator’s Report

Administrator Approved or Executed Agreements General updates including recent and upcoming meetings and events Staff attended and Administrator Doneux presented at the Ramsey County State of the Waters meeting on September 26, 2013. CRWD Staff, Mark Doneux, Bob Fossum, Forrest Kelley and Nate Zwonitzer attended the WEF TEC conference in Chicago that was held from 10/7/13 – 10/9/13. Lake McCarron’s Shoreline Residents Meeting, 6:00 PM, Thursday, October 3rd, Roseville City Hall Council Chambers. – Twenty-nine lakeshore residents, five agency staff and Managers Thienes, Texer, and Collins attend this meeting. The meeting generated many questions about managing aquatic plants in Lake McCarrons especially along the shallow western shore. CRWD will be starting a process to develop a plan to manage aquatic plants in the lake. The focus of the plan will be less on invasive species and more specific to navigation and aesthetics. Administrator Doneux felt the meeting went very well with a good exchange of information. The Neighbors thanked the Board Members and Administrator for their time and explaining the problems of Lake McCarron’s. CRWD Staff will be participating in the Minnesota Water Resources Conference in Saint Paul, October 15 – 16. Ms. Eleria and Mr. Fossum will both be presenters at the conference. A Partner Grant committee will need to meet and review applications. Applications are due October 25, 2013. Managers Reider and Jones will meet on November 6th at 4:30 to review the applications. 1)

Upcoming events and meetings a) Metro MAWD Meeting is Tuesday, October 15, 2013 at 7:00 PM. Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District

b) Next Board Meeting is Wednesday, November 6, 2013 at 6:00 pm. c) Next CAC Meeting is Wednesday November 13, 2013 from 7:00-9:00 pm. d) MAWD Annual Meeting and Trade Show, December 5-7, 2013, Arrowwood Resort, Alexandria. The Villa Park Wetland Restoration Project is one of the featured presentations at this conference. 2)

Project Updates a) Villa Park Wetland Restoration Project Dredging at Villa Park is complete and all dried sediment has been removed. Frattalone is now completing the site restoration phase and will be done by the end of October. b) TBI â&#x20AC;&#x201C; Cayuga Relocation Project The TBI Realignment Project at 35E/Cayuga is substantially completed. The new TBI alignment has been fully constructed and is on-line. Over the next couple of weeks, the old TBI alignment will be abandoned.

VIII. Next Meeting A) Wednesday, November 6, 2013 Meeting Agenda Review IX.

Adjournment

Motion 13-196: Adjournment of the October 16, 2013 regular Board Meeting at 7:03 p.m. Reider/Jones Unanimously Approved Respectfully submitted, Michelle Sylvander

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

November 6, 2013 Board Meeting V. Action Item â&#x20AC;&#x201C; B) Contract Amendment for Engineer for Highland Ravine Project (Eleria)

DATE: TO: FROM: RE:

October 31, 2013 CRWD Board of Managers Anna Eleria, Water Resource Project Manager Approve Contract Amendment #4 for Engineer for Highland Ravine Stabilization Project

Background In early November 2012, CRWDâ&#x20AC;&#x2122;s Board of Managers approved Wenck Associates as the engineer for the Highland Ravine Stabilization Project for an original contract amount of $45,476. To date, CRWD has approved three contract amendments for additional engineering work at cost of $8,110 for a total engineering budget of $53,586. The additional work included stabilization designs for ravines discovered during field work, addressing another round of comments, and covering other design changes that were outside the original scope of work. Issues Due to the expanding scope of the project and the complexities of working with private property owners, Wenck has exceeded the engineering budget and seeks additional funds to cover portion of the unpaid expenses to date and the remaining tasks including finalizing the stabilization plans for all ravines, completing the contract documents, assisting CRWD with easements/agreements, and bidding. Wenck has incurred over $17,000 to date since their last paid invoice and anticipates spending another $17,000 for the remaining tasks with a majority of that combined amount used to convert the plans to CAD. Wenck is willing to assume a significant portion of the outstanding and future engineering costs and is requesting $7,634 to complete the engineering work. See enclosed Wenck memo. Currently, the Wenck contract deadline is December 31, 2013, which needs to be extended through 2014. CRWD staff anticipates all plans will be completed and easements/agreements secured in February 2014. The project will go out for bid in March 2014 and construction will commence in summer 2014. CRWD staff believes the budget request by Wenck is justified and recommends the Board approve a Wenck contract amendment to increase the budget by $7,634 and extend the contract deadline to December 31, 2014. Action Requested Approve Contract Amendment #4 for Wenck Associates, Inc. for the Highland Ravine Stabilization Project in an amount not to exceed $7,634.00 for a total budget not to exceed $61,220 and a contract deadline of December 31, 2014. enc:

Wenck Memo dated October 28, 2013

W:\06 Projects\Highland Ravine\Board-CAC Memos\BM Highland Ravine Engineer Contract Amendment #4 11-06-13.docx

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

Wenck Associates, Inc. 1802 Wooddale Drive Suite 100 Woodbury, MN 55125‐2937 (651) 294‐4580 Fax (651) 228‐1969 wenckmp@wenck.com www.wenck.com

MEMORANDUM TO: Anna Eleria, Capitol Region Watershed District FROM: Todd Shoemaker, PE, CFM DATE: October 28, 2013 SUBJECT: Scope of work change #5 for Highland Ravine Stabilization Project INTRODUCTION The purpose of this memorandum is to request additional compensation to finalize the project plans and specifications. BACKGROUND Capitol Region Watershed District (CRWD) contracted with Wenck Associates, Inc. (Wenck) to provide stabilization plans for multiple ravines adjacent to Highland Park in St. Paul. Wenck has completed preliminary plans which have been reviewed by CRWD staff, City of St. Paul staff, and affected property owners. Wenck and CRWD staff recently met to discuss the project status, pending tasks, and future schedule. CRWD staff advised Wenck to submit this memorandum to document anticipated future costs to finalize the plans and specifications. As this project has grown in size and scope, Wenck has notified CRWD staff and requested the scope and project budget be revised accordingly. Below are the four changes in scope for the project that have been approved by CRWD’s Board of Managers: 1. Add design plans, profiles and calculations for Ravine 2 (formerly known as the Stolpestad Ravine); 2. Revise the plans per comments submitted by CRWD, City of St. Paul and affected property owners; 3. Stabilize an eroding slope on 1590 Edgcumbe Rd; and 4. Include the eroding slope at 1626 Edgcumbe Rd in the stabilization plans. SCOPE OF WORK CHANGE #5 Wenck is requesting a fifth change to accomplish the necessary tasks for finalizing the Highland Ravine plans and specifications, which include:  Finalize sanitary sewer design based on City of St. Paul comments.  Revise plans based on CRWD comments.  Finalize project manual and assist CRWD with bidding. W:\06 Projects\Highland Ravine\Design and Engineering\Wenck Scope of Work and Budget\Design Scope Changes\M ‐ Eleria Anna re Scope Change #5 FINAL.docxC:\Documents and Settings\anna\Local Settings\Temporary Internet Files\Content.Outlook\BELLGC1X\M ‐ Eleria Anna re Scope Change #5.docx

Technical Memo Scope of work change #5 Highland Ravine Stabilization Project October 28, 2013  Finalize easements with homeowners and agreement with Deer Park. The table below indicates the Wenck staff members that will accomplish the remaining tasks. (The task ID’s and task description headings have been maintained from our original proposal.) The total estimated cost for this change in budget is $7,634.00. This amount includes 8 hours for the Wenck Project Manager to manage the additional tasks. TASK ID

TASK DESCRIPTION

TASK 1

Data Collection and Review

TASK 2

Field Work and Site Evaluation

Wenck Staff Matthiesen Shoemaker Jonett Title Sr. Engineer PM/WR Eng LA Hourly Rate $179 $144 $101 $ TASK 01 TOTAL: $0.00

TASK 02 TOTAL:

$ $0.00

TASK 3 A B C D

Project Design Sanitary sewer design and meeting with St. Paul Revise plans based on City and CRWD comments Receive comments from City, DP, and CRWD Finalize plans based on homeowner, City and CRWD comments TASK 03 TOTAL:

$ $1,808.00 $977.00 $288.00 $977.00 $4,050.00

TASK 4 A B C D E F

Construction Bidding Revise and resubmit project manual to CRWD for review Finalize project manual Pre-bid meeting Respond to bidder questions Attend bid opening Advise CRWD of lowest, qualified bidder and draft memo TASK 04 TOTAL:

$ $490.00 $1,048.00 $462.00 $288.00 $462.00 $432.00 $2,000.00

TASK 5 A B C

Technical Support for Easement Agreements Provide plans and easements to Deer Park (DP) homeowners Finalize easements with homeowners and agreement with Deer Park Board approval of homeowner easements and Deer Park agreement TASK 05 TOTAL:

$ $144.00 $144.00 $0.00 $288.00

TASK 6 A

Permitting Resubmit plans to City for site plan review

TASK 06 TOTAL:

$ $144.00 $144.00

TASK 07 TOTAL:

$ $1,152.00 $1,152.00

PROJECT TOTALS

$7,634.00

TASK 7 A

Project Coordination and Meetings Project coordination

1 1

6 2 2 2

2 4 3 2 3 3

Boell CAD Admin Expenses $144 $93

7 2

$20

2 4

$100 $30 $30

1 1

2 W:\06 Projects\Highland Ravine\Design and Engineering\Wenck Scope of Work and Budget\Design Scope Changes\M ‐ Eleria Anna re Scope Change #5 FINAL.docxC:\Documents and Settings\anna\Local Settings\Temporary Internet Files\Content.Outlook\BELLGC1X\M ‐ Eleria Anna re Scope Change #5.docx

$200

April 3, 2013 Board Meeting V. Action Item – C) Establish Monitoring, Research and Maintenance Division (Doneux)

DATE: TO: FROM: SUBJECT:

October 31, 2013 CRWD Board of Managers Mark Doneux, Administrator Establish Monitoring, Research and Maintenance Division

Background Minnesota Statue 103D.325, Subdivision 1 provides the District with employment authority and states that the CRWD Board of Managers may employ a chief engineer, professional assistants, and other employees, and provide for their qualifications, duties, and compensation. CRWD Board of Managers first hired professional staff in 2003 and currently employs 14 Full Time Equivalents (FTE). The District recognizes the need to regularly evaluate and assess staff size, skills and structure. Since the District first started hiring employees with the Administrator position in 2003, the staff organizational structure has been flat. All employees report directly to the Administrator. Issues Over time staff organized around the monitoring and BMP maintenance has grown in numbers with 5.5 FTE working in this area currently. Because of this growth and need to provide more direct supervision for these staff, I believe there is benefit in establishing functional Divisions as an organizational tool to provide enhanced and more direct staff supervision, training and mentoring. In addition to the District benefit, staff desires the opportunity to grow and gain management experience at CRWD. Establishing functional units (Division) within the District’s staff structure recognizes the benefit for both staff and the District to provide professional advancement for staff to strengthen the organization, reduce turnover and maintain high employee satisfaction. To clarify how this would work I have drafted an organizational chart that illustrates both the proposed 2013 implementation of the Monitoring, Research and Maintenance Division as well as hypothetical future structure. I would like to emphasize that staff structure beyond establishing the Monitoring, Research and Maintenance Division is not known and the organizational chart provided is something that will need to be regularly reviewed and evolve overtime with our programs, projects and staffing requirements. This plan has been reviewed with the Personnel Committee and the Board of Managers. I recommend the Board of Managers create and establishes the Division of Monitoring, Research and Maintenance. I would also recommend that the Board of Managers regularly evaluate the District’s staff structure to ensure an efficient and effective structure that harnesses staff skills, abilities and professional development goals. Requested Action Adopt Resolution Creating and Establishing the Monitoring, Research and Maintenance Division enc:

2020 Organization Chart Draft Resolution Creating and Establishing the Monitoring, Research and Maintenance Division

W:\03 Human Resources\Staff Structure\Board Memo- Monitoring, Research and Maintenance Division 10-31-13.docx

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

CAPITOL REGION WATERSHED DISTRICT

Citizens

2020 ORGANIZATIONAL CHART

Ramsey County Commissioners

CAC

October 31, 2013 Board of Managers

Implement in 2013

Administrator

Implementation (TBD) Engineer

Program Manager Monitoring, Research & Maintenance

Monitoring Coordinator

Maintenance Coordinator

Program Manager Regulatory Program

Water Resource Technician (.25 FTE)

Water Resource Technician (.75 FTE)

Water Resource Technician

Technician

Attorney

Program Manager

Capitol Improvements and TBI

Education & Outreach

Grants & BMPs

Water Resource Specialist

Education Assistant (.50 FTE)

Technician

Office Manager

Technician

Administrative Assistant (.50 FTE)

Education Assistant

Water Resource Technician

Currently same person performing two roles Water Resoure Technician (Seasonal)

Technician

Future Position

Future implementation of this Organizational strucutre will be regularly evalutated by the Board of Managers. Divisions, staff positions and titles to the right of the red dashed line are for illustration purposes only. These positions are not established until they are reviewed, updated adopted by the Board of Managers.

Resolution

Resolution # 13-194 Date Adopted: November 6, 2013

Capitol Region Watershed District In the matter pertaining to: Establishing the Monitoring, Maintenance and Research Division Board Member __________ introduced the following resolution and moved its adoption, seconded by Board Member ________. WHEREAS, Minnesota Statue 103D.325, Subdivision 1 provides the District with employment authority; and WHEREAS, The CRWD Board of Managers may employ a chief engineer, professional assistants, and other employees, and provide for their qualifications, duties, and compensation; and WHEREAS, CRWD Board of Managers first hired professional staff in 2003 and currently employ 14 Full Time Equivalents (FTE); and WHEREAS, CRWD Board of Managers recognizes the need to regularly evaluate and assess staff size, skills and structure; and WHEREAS, CRWD Board of Managers recognizes the benefit of establishing functional Divisions as an organizational tool to provide enhanced and more direct staff supervision, training and mentoring; and WHEREAS, CRWD Board of Managers recognizes that staff desire the opportunity to grow and gain management experience at CRWD; and WHEREAS, CRWD Board of Managers recognizes the benefit for both staff and the District to provide professional advancement for staff to strengthen the organization, reduce turnover and maintain high employee satisfaction; and THEREFORE BE IT RESOLVED, that CRWD Board of Managers creates and establishes the Division of Monitoring, Research and Maintenance. BE IT FURTHER RESOLVED, CRWD Board of Managers will regularly evaluate the Districtâ&#x20AC;&#x2122;s staff structure to ensure an efficient and effective structure that harnesses staff skills, abilities and professional development goals. Manager Yeas* Nays Absent Abstain Collins Texer Jones Thienes Reider TOTAL *Approval must receive minimum of 3 Yeas Vote: Approved/Denied

Requested By: Recommended for Approval: Approved by Attorney: Funding Approved:

Mark Doneux N/A N/A

Resolution Adoption Certified By the Board of Managers: By: ______________________________________ Date: November 6, 2013

W:\04 Board of Managers\Motions\Resolutions 2013\Resolution 13-xx-xx Establishing Monitoring, Research and Maintenance Division 10-29-13.docx

November 6, 2013 Board Meeting V. Action Item – D) Approve Program Manager III Position (Doneux)

DATE: TO: FROM: SUBJECT:

October 31, 2013 CRWD Board of Managers Mark Doneux, Administrator Approve Program Manager III Position

Background Over time the number of staff organized around the monitoring and BMP maintenance has grown with 5.5 FTE working in this area currently. Because of this growth and a need to provide more direct supervision for these staff, I believe there is benefit in establishing a Program Manager to manage the Monitoring, Research and Maintenance Division in order to provide enhanced and more direct staff supervision, training and mentoring. In addition, staff desires the opportunity to grow and gain management experience at CRWD. Establishing a Program Manager within the District’s staff structure recognizes the benefit for both staff and the District to provide professional advancement for staff to strengthen the organization, reduce turnover and maintain high employee satisfaction. Issues Currently the District does not have a Program Manger III position. I have drafted a position description and have reviewed it with the Personnel Committee. The Primary Objective of this position is to manage the Monitoring, Research and Maintenance Division. In addition, this position will perform skilled to highly skilled duties providing water resource management, protection and planning as it relates to the implementation of District’s Watershed Management Plan and annual work plan. The Program Manager coordinates the implementation of their Division’s area of responsibility within the District’s Watershed Management Plan. Major areas of accountability and essential job functions include: program and project Management, Fiscal management and employee supervision. In addition to creating the Program Manager III position, I am requesting Board approval to promote Bob Fossum into this position. Bob Fossum has been with the District since 2004 and has been instrumental in implementing many major projects and programs with the District including, Rules, the 2010 Watershed Management Plan and the Arlington Pascal project. Most recently Bob Fossum has brought his leadership and management skills to help stabilize the Monitoring and BMP Maintenance programs of the District after significant staff turnover. In accordance with the District Salary Administration Policy, the Personnel Committee must approve any change in Grade for an existing employee. The Personnel Committee has met and supports this promotion and is seeking Board Approval of this action. Requested Action 1) Approve Program Manager III Position and Position Description 2) Approve Promotion of Bob Fossum to Grade 11 and to fill Program Manager III Position. enc:

Draft Program Manager Position Description

W:\03 Human Resources\POSITIONS\Program Manager\Board Memo- Program Manger III 10-31-13 #2.docx

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

Board Adopted: November 6, 2013 GRADE:

JOB CLASSIFICATION: Program Manager III POSITION TITLE:

Program Manager – Monitoring, Research and Maintenance Division

REPORTS TO:

Administrator

PRIMARY OBJECTIVE: Perform skilled to highly skilled duties providing water resource management, protection and planning as it relates to the implementation of District’s Watershed Management Plan and annual work plan. POSITION OBJECTIVE: The Program Manager coordinates the implementation of their Division’s area of responsibility within the District’s Watershed Management Plan. The Program Manager is responsible for the development and implementation of District projects and programs, and the oversight of capital projects. The Program Manager is responsible for implementing projects that address water quality issues. This position will coordinate watershed management activities involving other local units of government, City Departments, agencies, and private and non-profit sectors in the Watershed. MAJOR AREAS OF ACCOUNTABILITY/ESSENTIAL JOB FUNCTIONS Program and Project Management: Engages the Division’ direct reports in the portions of the comprehensive Watershed Management Plan and the area’s Annual Program Work Plan. Develops corresponding budgets, secures Administrator’s approval for, and oversees the implementation of, the above plans. Identifies goals and corresponding strategies to address the watershed plan content areas and annual work plans. Ensure that the plans reflect best practices and fulfill all requirements as outlined in MN Statute 103B. Ensure their Division’s compliance with the District’s practices and policies. Fiscal Management: Involve direct reports in contributing data to be considered for inclusion in the budget. Formalize final budgets for their Division. Obtain Administrator and/or Board approval. Tracks program expenditures and monitors activities against budget. Secure Administrator and/or Board approval for expenditures outside of established budgets. Identifies, provides corresponding rationale, and advocates for appropriate staffing levels, material resources and professional development for direct reports to perform their jobs. Comply with all financial reporting requirements, as documented in the CRWD Policies and Procedures Manual.

Board Adopted: November 6, 2013 Supervision: Supervise staff as assigned by Administrator in accordance with CRWD Organizational structure established by the Board of Managers. Manage the hiring process and decisions related to the selection, promotion, and transfer of assigned personnel. Has authority to terminate program area personnel, interns, and contractors as long as the Administrator has been apprised of the situation and the details are documented according to the organization’s progressive disciplinary process, outlined in the Employee Handbook. Provide clear, specific, and timely directions. Delegate without removing assistance or accountability. Works with direct reports to develop their annual Work Plans in a timely manner; approves Individual Work Plans and ensures they are in response to the Watershed Management Plan, support the area’s Annual Program Work Plan, and link to the Individual Performance Goals. Monitors deadlines and takes the appropriate actions to ensure that all goals/projects stay on track. Adjusts deadlines when the unexpected occurs, or per Administrator or Board directive. Ensures direct reports receive ongoing training/education and certification to perform their existing jobs, increase skills and knowledge, improve current performance, and/or develop new competencies for other assignments/positions. Provides regular formal performance reviews. Responsible for making salary adjustments based on Policies and subject to the approval of the Administrator. Contract Management: Manage the selection of contractors, creation of contract documents, and management of contracted services and personnel consistent with District policies, subject to the approval of the Administrator and/or Board of Managers. Orient contracted personnel to the organization’s policies and procedures. Communicate, both verbally and in writing, performance specifications and expectations. Monitors the work performance of contracted personnel on a continual basis, provides timely feedback, and if applicable, takes corrective action. Administer the organization’s policies and procedures as related to contractor selection, payment, contract deliverables and corresponding schedule, applicable amendments, and closeout. ADDITIONAL FUNCTIONS: 1. Provides technical support to District programs. 2. Represent the District on special committees. 3. Effectively represent water and watershed issues at meetings, conferences, before the media, and to other local units of government, City Departments, the Board of Managers, partner organizations and the public. 4. Coordinate watershed-related activities in the District, and activities involving other governmental agencies and private and non-profit entities.

Board Adopted: November 6, 2013 (The examples given above are intended only as illustrations of various types of work performed and are not necessarily all-inclusive. This position description is subject to change as the needs of the employer and requirements of the position change.) SALARY Grade 11, depending on qualifications and experience, plus benefits. MINIMUM QUALIFICATIONS Degree and/or experience appropriate for the position. Experience with stream hydrology and water quality monitoring and chemistry are essential. Minimum of eight years professional experience including project management is preferred. Appropriate advance degree and/or certificates are preferred. Good communication and computer skills are required. KNOWLEDGE, SKILLS and ABILITIES 1.

2. 3.

4. 5. 6. 7. 8. 9. 10. 11. 12. 13.

14.

15.

16.

Knowledge of watershed management, surface and groundwater hydrology, natural resource management, soils and biology. Demonstrated knowledge and working experience related to local, state, and federal programs and requirements. Effective communication skills, both oral and written. Ability to develop effective cooperative relationships with technical and policy staff, state and local government officials, and private entities and citizens. Ability to effectively lead teams of technical and policy staff, including those of partner and stakeholder organizations. Demonstrated ability in team building and effective coaching. Demonstrated knowledge of budget preparation and contract development. Demonstrated knowledge of procurement, permitting and other processes, and design and construction contracting. Extensive knowledge of project management techniques. Extensive negotiating skills. Ability to analyze technical reports and construction diagrams. Proven ability to achieve goals, ability to work successfully with considerable independence. Excellent analytical, conflict management, interpersonal, and leadership skills. Ability to write successful grant requests, including knowledge of grant writing requirements. Proficiency with a personal computer (PC) and Microsoft software packages for word processing, spreadsheet, database management and computer generated graphics. Specifically, but not limited to, Microsoft Office, Excel, Word, Access, PowerPoint. Ability to effectively use email and internet applications and other common software applications. Ability to take direction, work independently with a minimum of supervision, use good time management practices, possess the ability to set priorities and balance large volumes of diverse work. Ability to develop and maintain effective working relationships with, the Administrator, CRWD Board of Managers, Citizens Advisory Committee, Ramsey SWCD staff, Ramsey County staff, City and agency staff, members of the public, and other interested parties. Must have valid Minnesota driverâ&#x20AC;&#x2122;s license and have vehicle available for periodic business use on a mileage reimbursement basis. The vehicle must have insurance approved by the District.

Board Adopted: November 6, 2013 RESPONSIBILITY FOR PUBLIC CONTACT High level of public contact requiring tact, courtesy and good judgment. EMPLOYMENT CLASSIFICATION: Standards Act.

Salaried, exempt from the provisions of the Fair Labor

NON-DISCRIMINATION POLICY The Capitol Region Watershed District will not discriminate against or harass any employee or applicant for employment because of race, color, creed, religion, national origin, sex, disability, age, marital status, sexual orientation, or status with regard to public assistance. PROGRAM MANAGER PHYSICAL DEMANDS AND JOB DESCRIPTION SUPPLEMENT WORK ENVIRONMENT 1.) Normal shift = eight (8) hours for five (5) consecutive days. 2.) Work location normally in controlled environment. 3.) Stress level varies from low to very high. PHYSICAL DEMANDS Type of Activity Walking/standing:

Frequency M

Sitting:

Standing in One Place:

Climbing:

Pulling/Pushing:

Crawling/Kneeling/Squatting:

Bending/Stooping:

Twisting/Turning:

Repetitive movement:

Lifting waist to shoulder:

Lifting knee to waist:

M M

Lifting floor to knee: S = Significant

M = Moderate

O= Occasional

November 6, 2013 V. Action Items E) Approve 2014 Employee Benefit Program (Doneux)

DATE: TO: FROM: RE:

October 31, 2014 Board of Managers Mark Doneux 2014 Employee Benefit Program

Background Since 2003, Bearence (formally TC Fields) has provided insurance to the District. During late 2011 the District looked at other options for benefits for employees. Staff worked with Bearence to review and determine a new benefits package with the goal of attempting to meet the following objectives: 1. Realize a cost savings for the District and District employees. 2. Obtain similar benefit coverage’s to those currently available to District employees through Ramsey County. The District has purchased health benefit package from Health Partners through Bearance for 2012 and 2013. The District purchased dental and other ancillary coverage’s (Life, Short Term and Long Term Disability) from Ramsey County. The District is now ready to take the next step and obtain all benefit coverage through Bearance. Issues Staff has obtained benefit quotes from Bearance for health, dental and ancillary coverage’s. Bearance obtains quotes from at least three vendors when soliciting benefit quotes. The action requested by the Board of Managers is to set the employee contribution rates for 2014. Table 1 below summarizes Table 1- Current 2013 and Proposed 2014 Monthly Health Insurance Coverage Contributions Current 2013 Health Coverage 2013 Employee 2013 District Total Cost Single Health Insurance $11.66 $290.94 -$312.74 $302.60 - $324.40 Family Health Insurance $68.12 $537.08 - $1,329.48 $605.20 - $1,397.60 Proposed 2014 Health Coverage Single Health Insurance Single + 1 Insurance Family Health Insurance**

2014 Employee $40.00 $80.00 $120.00

2014 District* $299.41 $606.11 $815.71 - $1,314.91

Total Cost* $339.41 $686.11 $935.71 - $1,434.90

*2014 District and Total Costs are average based on all age groups and assume the same enrollment for 2014 ** 2014 District and Total Costs are based on using 20-29 age with spouse and 1 child for low end of range, 40-49 age, spouse and 3 children for high end of range.

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

Table 2 - Current 2013 and Proposed 2014 Monthly Dental Insurance Coverage Contributions Current 2013 Dental Coverage 2013 Employee 2013 District Total Cost Single Dental Insurance $16.18 $28.27 $44.45 Family Dental Insurance $43.43 $55.57 $99.00 Proposed 2014 Dental Coverage Single Dental Insurance Single + 1 Dental Insurance Family Dental Insurance

2014 Employee $10.00 $20.00 $40.00

2014 District $30.85 $61.29 $82.55

Total Cost $40.85 $81.29 $122.55

Staff has reviewed potential changes to the benefits with the Employee Committee (Managers Texer and Collins) and the committee is bringing forward the recommendation listed below. Requested Action Approve the 2014 Employee Benefit Program as follows: 1) 2) 3) 4)

Effective January 1, 2014, the District move all employee benefit programs from Ramsey County to those offered through the Districtâ&#x20AC;&#x2122;s Insurance Company, the Bearence Management Group. The District requires a monthly employee contribution of $40.00 for single, $80.00 for Single Plus One and $120.00 for Family health insurance, effective December 1, 2013. The District requires a monthly employee contribution of $10.00 for single, $20.00 for Single Plus One and $40.00 for Family dental insurance, effective January 1, 2013. The District will continue to provide ancillary employee benefits including life, short term disability and long term disability insurance. These programs and the employee/District contributions will be consistent to those offered by Ramsey County. The District will continue to provide Life Insurance and Long Term Disability coverage consistent with the Ramsey County Program and allow employees to purchase additional coverage at their cost. The District provide payroll deductions and employee contributions to Health Care Flexible Spending Accounts and Dependent Care Spending Accounts.

W:\03 Human Resources\Benefits\2014 Benefits\Board Memo- 2014 Employee Benefit Program 10-31-13.docx

November 6, 2013 VI. Unfinished Business A)

Inspiring Communities Program Updates (Eleria, Castro)

DATE: TO: FROM: RE:

October 31, 2013 CRWD Board of Managers Anna Eleria, Project Manager Gustavo Castro, Water Resource Specialist Inspiring Communities Program Updates (Former Neighborhood Stabilization Program)

Background Since August 2011, CRWD has partnered with the City of Saint Paul’s Planning and Economic Development (PED) Department on creating water-friendly landscapes on single-family residential properties that the City is acquiring and redeveloping through its Neighborhood Stabilization Program (NSP). For each NSP property, CRWD has prepared a landscape plan that includes stormwater BMP(s) (i.e., rain gardens, swales, etc.) to provide proper drainage away from the property, minimize stormwater runoff from the property, enhance the property’s aesthetics and improve water quality of the Mississippi River. Issues The Neighborhood Stabilization Program, now called Inspiring Communities Program has been undergoing some changes. Up to now, CRWD has been working directly with the City of St Paul, and they have been implementing many of the rehabs of vacant single family buildings over the last couple of years. Moving forward, the program is shifting to a developer driven model that allocates property and subsidy through an open bid process to developers. To that end, the City released an RFP in early October with around 77 properties, which includes a mix of owner occupied and rental, as well as vacant building rehabs and new construction. In this new format, the developer is ultimately responsible for initiating work with CRWD. The enhancement of the RFP properties to achieve water quality benefits is still a requirement of the program, however, developers are not required to work with CRWD. Nevertheless, CRWD will continue to offer a free landscape design and rebates, generally ranging from $500 - $1,000, for the installation of rain gardens. In cases where CRWD identifies a unique opportunity for the installation of other management practice, higher rebates could be considered. Action Requested No action requested. This is intended to be only an update to the board members on the undergoing changes in the program’s format. enc: Map of current and future project locations \\CRwDC01\company\07 Programs\Stewardship Grant Program\Saint Paul NSP\Board Memos\BM Inspiring Communities Program Updates.docx

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

MENDOTA ST

EARL ST

FRANK ST

FOREST ST

PAYNE AVE

CLARENCE ST

WALSH ST WEIDE ST ARCADE ST

BRADLEY ST

DESOTO ST

EDGERTON ST

WESTMINSTER ST

ARKWRIGHT ST

RR D

WA R

EARL ST

BURR ST

JACKSON ST

SYLVAN ST

ABELL ST

PARK ST

AGATE ST

JESSIE ST

SYLVAN

RICE ST

JACKSON ST N

MISSISSIPPI ST

ELFELT ST

OLIVE ST

WESTERN AVE N

MCMENEMY ST N

PACIFIC ST

WA R

M IL

GROTTO ST S

AVON ST S

RR D

DRAKE ST

VICTORIA ST S

LORIENT ST INTERSTATE 35E

VIRGINIA ST

GALTIER ST

KENT ST

DALE ST N

PARK ST

MARION ST

KENT ST

ARUNDEL ST

GROTTO ST N

SAINT ALBANS ST N

AVON ST N

CHURCHILL ST

OXFORD ST N

MONT CALM PL LEXINGTON PKWY S

GRIGGS ST S

SYNDICATE ST S

VIEW ST

ALBERT ST S

HAMLINE AVE S

MACKUBIN ST

AGLEN ST

VICTORIA ST N

LINDY AVE LEXINGTON AVE N

PL A AI D

GRIGGS ST N

DUNLAP ST N

SYNDICATE ST N

ALBERT ST N

ASBURY ST

PASCAL ST S

SNELLING AVE S

MACALESTER ST

WILSON AVE

WEST SEVENTH BAY ST

ALBERT ST N

HAMLINE AVE N HAMLINE AVE N

ALDINE ST

WHEELER ST N

WHEELER ST S

DAVERN ST

FAIRVIEW AVE S

BL V

SUE PL

4TH ST E

FORSTER ST

OTTO AVE

HI GH

W AY

Crosby Lake

CLEVELAND AVE S

VD BL

iv i R

FINN ST S

6TH ST E

ip p

CRETIN AVE S

L KE

s sis Mi s

MOUNT CURVE BLVD

E AV

DOWNTOWN

GRACE ST

BEECH ST

E AT ST

VE TA AR R D EW R D ST EPA SH

! ! !! !!

GOODRICH AVE PA HE ST S F IF CL

GOODHUE ST MICHIGAN ST

BUSH AVE

BEECH ST

TUSCARORA AVE

RAMSEY ST

GOODRICH-WESTERN

T 10

PHALEN BLVD

FRED ST NORTH ST

M O

CASE AVE

T IN E AV N ELWAY ST

MUNSTER AVE

R ME

VE L A RETURN CT

SHERIDAN AVE

JUNO AVE

JENKS AVE

TE BA

U PA

EDGCUMBE RD

COLVIN AVE

DAVERN

INT

MONTREAL AVE

YORKSHIRE AVE

ID HOLLY AVE MA

BOHLAND PL

PALACE AVE

IO N ST

COOK AVE E

MINNEHAHA AVE E

CROSBY

IVY AVE E

BUSH AVE

HIGHLAND PKWY

IA AVE PENNSYLVAN COMO AVE

DAYTON AVE

PORTLAND AVE

JEFFERSON AVE

TO M AR

YORK AVE

CAY UG A ST

! !

LAWSON AVE E

SAINT CLAIR AVE

EB I94

LAUREL AVE

ASHLAND AVE

EAST KITTSONDALE

INTERSTATE 35E

SCHEFFER AVE

CONCORDIA AVE

SELBY AVE

LINCOLN AVE

JULIET AVE

NILES AVE

EDMUND AVE

MARSHALL AVE

PORTLAND AVE

HARTFORD AVE

LAFOND AVE

THOMAS AVE

FULLER AVE

STANFORD AVE

ROME AVE

BLAIR AVE

SIMS AVE

SYCAMORE ST W

! ! ! ! ! ! ! ! ! ! !! ! !! ! ! !! !HILL ! ! ! ! ST. ANTHONY ! ! ! ! ! ! !! ! ! ! ! St. Paul ! !! ! ! ! ! !

HAGUE AVE

RANDOLPH AVE

WAYZATA ST MILFORD ST ATWATER ST

JUNO AVE

HATCH AVE

IOWA AVE E

! ! ! ! !! !!! !! ! ! ! !! ! ! ! ! !!! !! ! !! ! !!! ! !! ! ! ! ! ! ! PHALEN CREEK ! !! ! ! ! ! ! !! ! ! ! ! ! ! ! ! !! ! ! ! ! ! ! !! !! !! ! ! !! URBAN ! ! !! !

PALACE AVE

TOPPING ST

COOK AVE W

Riv er Mississip pi

JEFFERSON AVE

FRONT AVE

MINNEHAHA AVE W

INTERSTATE 94

DAYTON AVE

L RD

! ! !! ! ! ! !

LAWSON AVE W

SHERBURNE AVE

GRAND AVE

BERKELEY AVE

PINEHURST AVE

HUBBARD AVE

MARYLAND AVE W

ASHLAND AVE

MISSISSIPPI RIVER BLVD

ELEANOR AVE

M IL

AV E

IVY AVE W

ORANGE AVE W

BL SI

O SE PL

AY D

HAGUE AVE

BURGESS ST

CARROLL AVE

LINCOLN AVE GOODRICH AVE

JAMES AVE

ORCHARD AVE HATCH AVE FRONT AVE

SAINT ANTHONY AVE

DAYTON AVE

ARLINGTON AVE E

TROUT BROOK

MO NTR

DEWEY ST FAIRVIEW AVE N

SHIELDS AVE

SUMMIT AVE

HIDDEN FALLS

PASCAL ST N

UNIVERSITY AVE W

ROSE AVE W

COMO AVE

OXFORD ST N

ARONA ST

PASCAL ST N

FRY ST

UNDERWOOD ST N

SNELLING AVE N

SIMPSON ST

TATUM ST

FIELD AVE N

TATUM ST

ER TA VE

FINN ST N

WEST KITTSONDALE

Loeb Lake

ARLINGTON AVE W

LARPENTEUR AVE E WHEELOCK PKWY E

AL W

E AV

CRETIN AVE N

GIL B

TAYLOR AVE TAYLOR AVE HEWITT AVE

E AV

IS OT

P LE

HA VE

JESSAMINE AVE W

ENGLEWOOD AVE

Como Lake

DOWNS AVE E

TE M

NEBRASKA AVE W

MO AVE

ENERGY LN

FRY ST

WA B

TRANSFER RD

EA VE

PIERCE BUTLER RTE

PRIOR AVE N

GORTNER AVE

HYTHE ST RD

IOWA AVE W

PARKVIEW AVE

BREDA AVE

ST. ANTHONY PARK

VANDALIA ST

LI FF

AV E

MY RT L

ALBANY AVE

COMO AVE

CLEVELAND AVE N WILDER ST N MOORE ST

EUSTIS ST

PELHAM BLVD

CURFEW ST

W YC

E AV

COMO

Lake MC McCarrons CA RR ON SB WAGNER ST LV

SKILLMAN AVE E

R MA

O YM RA

CLEVELAND AVE N ECKLES AVE

ST LO

HOWELL ST N

EUSTIS ST CARL ST

EUSTIS ST

TO N LL HI

IDAHO AVE W

HOYT AVE W

ELMER ST

FOLWE LL AVE HOYT AVE W

GARDEN AVE

Maplewood

COUNTY ROAD B E

BURKE AVE W

Propos oposeedd B BM MP P Lo Lo ca cattio io nn Pr

AD IST

Falcon Heights

LARPENTEUR AVE W

KES

DRAPER AVE

ROSELAWN AVE W

MINNESOTA AVE WAY 36 W

SKILLMAN AVE W

AV ALT

Lauderdale

E AV DE

BURKE AVE W PARKER AVE

SHRYER AVE W

HIG H

MCCARRONS LAKE

VICTORIA ST N

Roseville

LOVELL AVE

COPE AVE W

SHERREN ST

Capitol Region Watershed District

Inspiring Communities Program | Project Locations

! !

2013 Sites

2011-2012 Sites Major Highways

Major Waterbodies Parks

CRWD

Subwatersheds 0

0.3 0.6

1.2

1.8

2.4

Miles

DISCLAIMER: This map is neither a legally recorded map nor a survey, and is not intended to be used as one. This map is a compilation of records, information anddata located in various city, county, state and federal offices and other sources regarding the area shown, and is to be used for reference purposes only.

DATE: TO: FROM: RE:

October 31, 2013 CRWD Board of Managers and Staff Mark Doneux, Administrator November 6, 2013 Administratorâ&#x20AC;&#x2122;s Report

Administrator Approved or Executed Agreements Stewardship Grant Agreement with Great River Greening for a fall intern. - $1,500. Board Approved or Executed Agreements TBI Work Order No. 5 Amendment No. 2 with Barr Engineering for additional rail monitoring program. Not to exceed $56,500 for a total work order amount of $992,865 General updates including recent and upcoming meetings and events

Upcoming events and meetings a) Next CAC Meeting is Wednesday November 13, 2013 from 7:00-9:00 pm. b) Next Board Meeting is Wednesday, November 20, 2013 at 6:00 pm. c) MAWD Annual Meeting and Trade Show, December 5-7, 2013, Arrowwood Resort, Alexandria. The Villa Park Wetland Restoration Project is one of the featured presentations at this conference. The deadline to register for lodging is November 15, 2013. The deadline to register for the Annual Conference is November 20, 2013.

Project Updates a) Villa Park Wetland Restoration Project Dredging at Villa Park is complete and all dried sediment has been removed. Frattalone is now completing the final site restoration phase. b) TBI â&#x20AC;&#x201C; Cayuga Relocation Project The TBI Realignment Project at 35E/Cayuga is completed. The new TBI alignment has been fully constructed and is on-line. The old TBI alignment is now abandoned.

W:\04 Board of Managers\Correspondence\Administrator's Report 2013\Administrator's Report 11-6-13.docx

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