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Our Mission is to protect, manage and improve the water resources of 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
I. 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.
V. 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
Materials Enclosed
Capitol Region Watershed District Permit 13-019 Hamline Station
Permit 13-019 Board Meeting: 11/06/13
Aerial Photo
Applicant: Chris Dettling Consultant: David Bade PPL, Inc. Westwood Professional Services 1035 East Franklin Avenue 7699 Anagram Drive Minneapolis, MN 55404 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
Permit Location
University Avenue
Ham
line Avenue
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 36” 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.
W:\07 Programs\Permitting\2013\13-019 Hamline Station\13-019 Permit_Review3.doc Page 1 of 4
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 2 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 3 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 land-disturbing 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 4 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 36” 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.
PROPOSED WEST BUILDINGFFE=925.0-924.0 (SLOPED FLOOR)
PROPOSED EAST BUILDINGFFE=924.0
1309 HOUSING1311-1337 RETAIL
1305 HOUSING
UTILITY NOTES
LEGEND EXISTINGPROPOSED
Capitol Region Watershed District Permit Application 13-028 Loomis Armored Transport
Permit Report 13-028 November 6, 2013 Board Meeting
Aerial Photo
Applicant: Herbert Tousley Consultant: Mike Kettler Ironton Management Sunde Engineering 332 Minnesota Street, Suite W2300 10830 Nesbitt Avenue St. Paul, MN 55101 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
Permit Location
East Seventh Street
For
est S
t
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 “filter flow” 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 1 of 4
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 2 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 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\13-028 Loomis Amored Transport\13-028 Permit_Review3.doc Page 3 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 land-disturbing 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 3 Conditions Conditions:
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
W:\07 Programs\Permitting\2013\13-028 Loomis Amored Transport\13-028 Permit_Review3.doc Page 4 of 4
100-year event. Assuming a 1.0 in/hr filtration rate, however, results in a peak “filter flow” of 0.1 cfs based on a filter area of 4,546 square feet. Adjust high water and overflow elevations as necessary.
Capitol Region Watershed District Permit Application 13-030 Western U Plaza
Permit Report 13-030 November 6, 2013 Board Meeting
Aerial Photo
Applicant: St. Paul Old Home Plaza, LLC Consultant: Robert Wiegert PO Box 727, 366 South Tenth Avenue Paramount Engineering Waite Park, MN 556387 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
Permit Location
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. VOLUME BANK RECOMMENDATION: Approve creation of a volume bank for the Sand Companies and deposit of 4,844 cubic feet of volume reduction credits.
University Avenue
Wes
tern
Ave
nue
W:\07 Programs\Permitting\2013\13-030 Western U Plaza\13-030 Permit_Review_02.doc Page 1 of 4
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 2 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 3 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 land-disturbing 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 4 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.
Capitol Region Watershed District Permit Application 13-031 US Bank Demolition
Permit Report 13-031 November 6, 2013 Board Meeting
Aerial Photo
Applicant: Scott Belsaas Consultant: Barry Jaeger Shepard Development, LLC Jaeger Construction 1999 Shepard Road 2317 Waters Drive St. Paul, MN 55116 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
Permit Location
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.
University Avenue
Wes
tern
Ave
nue
W:\07 Programs\Permitting\2013\13-031 US Bank Demolition\13-031 Permit_Review_01.doc Page 1 of 2
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: F 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 A plan shall demonstrate that appropriate erosion and sediment control
measures protect downstream water bodies from the effects of a land-disturbing 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.
W:\07 Programs\Permitting\2013\13-031 US Bank Demolition\13-031 Permit_Review_01.doc Page 2 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.
“
“ ”
DATE
PROJECT #
PROJECT STATUS
DRAWN BY
CHECKED BY
2013 BKBM Professional Engineers, Inc.All rights reserved.This document is an instrument of service and is the property of BKBMProfessional Engineers, Inc. and may not be used or copied withoutprior written consent.
C
I hereby certify that this plan, specification orreport was prepared by me or under mydirect supervision and that I am a dulyLicensed Professional Engineer under thelaws of the state of Minnesota.
Date Lic. No.
NOT FORCONSTRUCTION
ST. PAUL, Minnesota
14117CD
U.S. BANKBUILDINGDEMOLITION
50475
Revisions
No.
Description Date
Eric T. Luth
10-15-2013
ETL
KAM
10-15-2013
EROSIONCONTROL PLAN
C1.0
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District
DATE: October 31, 2013
TO: CRWD Board of Managers
FROM: Britta Suppes, Monitoring Coordinator
RE: 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
November 6, 2013 Board Meeting
IV. Special Reports—A) Summary
of 2005-2012 Monitoring Data by
Dr. Ben Janke (Janke)
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
2 CRWD Stormwater Monitoring Data Analysis Report
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 – 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 3
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 ...................................................................
4 CRWD Stormwater Monitoring Data Analysis Report
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 – 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 5
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, 3
rd 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)
6 CRWD Stormwater Monitoring Data Analysis Report
(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 7
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 – 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.
8 CRWD Stormwater Monitoring Data Analysis Report
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 sub-
watersheds. Land cover classes included trees, lawn/shrubs, bare ground, open water,
rooftop, street, and “other” 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 9
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.
10 CRWD Stormwater Monitoring Data Analysis Report
Table 2.2. Land cover and drainage characteristics of CRWD sub-watersheds.
Watershed Area (ac) Area (km2)
Drainage Characteristics
Runoff Coeff
Street Density
(km/km2)
Curb Density
(km/km2)
Pond Density
(ponds/km2)
EK 1116 4.52 0.373 15.26 26.41 0.22
PC 1433 5.80 0.279 14.78 27.18 1.03
SAP 2491 10.08 0.249 11.59 20.31 0.60
TBEB 808 3.27 0.248 13.15 22.70 4.28
TBWB 2379 9.63 0.381 8.73 18.32 3.43
TBO 5036 20.38 0.332 11.13 19.96 3.24
Como 7 298 1.21 0.052 12.84 24.53 n/a
GCP Out 298 1.21 0.408 12.84 24.53 n/a
VP Outlet 708 2.87 0.162 8.45 17.17 n/a
Sarita 930 3.76 0.067 7.95 n/a n/a
AHUG 41.5 0.17 0.157 13.03 26.71 0
Como 3 517 2.09 0.108 10.25 19.56 n/a
VP Inlet 622 2.52 0.168 8.61 17.09 n/a
Watershed
Land Cover Percentages
Trees Lawn / Shrubs
Bare Water Rooftop Street Alley Other
Impervious Total
Impervious Vegetated
EK 26.8 16.7 0.3 0.0 22.1 16.5 3.3 17.6 56.2 43.5
PC 23.7 17.0 0.5 0.0 22.3 16.9 3.4 19.4 58.7 40.8
SAP 23.0 14.4 0.5 0.7 19.0 14.0 1.5 28.3 61.3 37.4
TBEB 29.9 24.9 0.1 0.4 13.8 16.2 1.3 14.6 44.7 54.8
TBWB 31.7 25.2 0.8 3.2 13.1 10.5 1.5 15.5 39.2 56.9
TBO 26.7 23.5 0.7 1.8 14.2 13.8 1.3 19.3 47.3 50.3
Como 7 30.5 25.3 0.2 0.4 18.4 13.4 0.5 11.7 43.5 55.9
GCP Out 30.5 25.3 0.2 0.4 18.4 13.4 0.5 11.7 43.5 55.9
VP Outlet 45.4 24.8 0.3 1.2 9.2 11.3 0.0 7.8 28.4 70.2
Sarita n/a n/a n/a n/a n/a n/a 0.1 n/a n/a n/a
AHUG 26.8 21.9 0.3 0.0 24.7 13.3 3.6 12.9 51.0 48.7
Como 3 31.2 26.7 0.9 0.3 12.0 12.6 1.6 16.3 40.8 57.9
VP Inlet 44.0 25.4 0.3 0.9 9.3 11.7 0.0 8.4 29.4 69.4
CRWD Stormwater Monitoring Data Analysis Report 11
Table 2.2. (Con’t). Land cover and drainage characteristics of CRWD sub-watersheds.
Watershed
Rooftop Percentages by Type Percentage of Street Covered by Canopy
Instit-utional
Residential, Low Dens.
Residential, High Dens.
Comm. Industrial Street Street +
5 ft Buffer
Street + 10 ft
Buffer
Street + 20 ft
Buffer
EK 0.9 11.9 1.4 2.2 1.2 30 34 37 41
PC 1.3 10.3 0.9 2.2 2.9 27 31 34 37
SAP 0.8 4.6 1.8 1.7 8.0 21 24 27 31
TBEB 0.3 7.2 1.8 0.3 0.6 22 26 29 34
TBWB 0.6 6.1 1.5 1.0 1.0 32 36 39 43
TBO 0.7 5.6 1.3 1.1 1.8 22 25 28 32
Como 7 0.9 13.5 0.2 0.3 0.0 43 46 48 51
GCP Out 0.9 13.5 0.2 0.3 0.0 43 46 48 51
VP Outlet 0.5 5.6 1.4 0.3 0.0 15 19 22 29
Sarita 3.5 2.0 3.6 0.6 0.0 n/a n/a n/a n/a
AHUG 3.0 16.9 0.1 0.0 0.0 36 40 43 48
Como 3 0.2 5.1 0.9 1.8 0.7 31 34 36 40
VP Inlet 0.6 5.4 1.6 0.3 0.0 14 17 21 27
12 CRWD Stormwater Monitoring Data Analysis Report
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 13
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 (“dry days”), days
14 CRWD Stormwater Monitoring Data Analysis Report
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)
CRWD Stormwater Monitoring Data Analysis Report 15
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):
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
P =Pidij( )ådijå
16 CRWD Stormwater Monitoring Data Analysis Report
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 17
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 sub-
watersheds is shown in Table 2.2. Some variation in land cover is present among sub-
watersheds. 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 Gottfried’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 – 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
18 CRWD Stormwater Monitoring Data Analysis Report
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.
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
0
2
4
6
8
10
12
EK
PC
SAP
TBEB
TBW
B
TBO
VPIn
VPOut
Sar
Com
o7
GCP
Com
o3
AHUG
Seaso
nal S
torm
wa
ter
Yie
ld,
in
(b)
0
5
10
15
20
25
EK
PC
SAP
TBEB
TBW
B
TBO
VPIn
VPOut
Sar
Com
o7
GCP
Com
o3
AHUG
Sea
so
na
l W
ate
r Y
ield
, in
Stormflow
Baseflow
25%
67%
56%
44%
62%
61%
31% 28%
(a)
CRWD Stormwater Monitoring Data Analysis Report 19
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
Gottfried’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
EK 5.93 11.11 1.41 18.46 32%
PC 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%
20 CRWD Stormwater Monitoring Data Analysis Report
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 1800’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
CRWD Stormwater Monitoring Data Analysis Report 21
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.
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.
0
0.5
1
1.5
2
2.5
3 0.0
0.2
0.4
0.6
0.8
1.0
1.2
22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 6:00
Pre
cip
(c
m,
pe
r 1
5m
in i
nte
rva
l)
Dim
en
sio
nle
ss F
low
(Q
/Qp
ea
k)
EK
PC
SAP
TBEB
TBWB
TBO
Precip
EK
TBWB
TBEB
PC
SAP TBO
0
0.5
1
1.5
2
2.5
3 0.0
0.2
0.4
0.6
0.8
1.0
1.2
22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 6:00
Pre
cip
(cm
, p
er
15m
in in
terv
al)
Dim
en
sio
nle
ss F
low
(Q
/Qp
ea
k)
AHUG VP Outlet
Como 3 Sarita (Lvl)
Como 7 GCP Outlet
Precip
AHUG
GCP Outlet
VP Outlet
Como 7
Como 3
Sarita
22 CRWD Stormwater Monitoring Data Analysis Report
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
CRWD Stormwater Monitoring Data Analysis Report 23
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 – 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
24 CRWD Stormwater Monitoring Data Analysis Report
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 – 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 – Nov) than during summer (June – 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.
CRWD Stormwater Monitoring Data Analysis Report 25
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 non-
BMP 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.
26 CRWD Stormwater Monitoring Data Analysis Report
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 – 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 27
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
Kittson-dale
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
Nitrate-Nitrite
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
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
28 CRWD Stormwater Monitoring Data Analysis Report
Table 3.2a (con’t).
Seasonal Comparison
Kittson-dale
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 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
Copper
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
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 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 29
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
Kittson-dale
Phalen Creek
St. Anthony
Park
Trout Brook East
Trout Brook West
Trout Brook Outlet
Villa Park
Outlet
Villa Park Inlet
Total Phosphorus
spring-summer 7.5E-01 9.8E-01 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 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
Total Nitrogen
spring-summer 2.7E-01 1.4E-01 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 3.6E-01 1.3E-02 2.1E-01 1.6E-01 2.9E-01
Nitrate-Nitrite
spring-summer 1.1E-01 5.8E-02 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
Total Suspended Solids
spring-summer 4.6E-01 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
Chloride
spring-summer 4.1E-07 1.5E-01 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
30 CRWD Stormwater Monitoring Data Analysis Report
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
CRWD Stormwater Monitoring Data Analysis Report 31
sediment-laden water from the BMPs, which are better able to detain the smaller or less-
intense 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 Cl-
concentrations 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-.
32 CRWD Stormwater Monitoring Data Analysis Report
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 33
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).
34 CRWD Stormwater Monitoring Data Analysis Report
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).
CRWD Stormwater Monitoring Data Analysis Report 35
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 – 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
36 CRWD Stormwater Monitoring Data Analysis Report
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
CRWD Stormwater Monitoring Data Analysis Report 37
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 Cl-
were 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 sub-
watersheds. 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
38 CRWD Stormwater Monitoring Data Analysis Report
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
CRWD Stormwater Monitoring Data Analysis Report 39
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 sub-
watersheds.
Site
Median Rainfall by Count Rainfall Depth at
Median Cmltv Vol
1-inch Rainfall Median Event Vol by Count
Depth Cmltv Vol Cmltv Vol Rainfall
(in) (fraction) (in) (fraction) Percentile (ft3)
EK 0.43 0.20 0.82 0.62 0.87 534,105
PC 0.50 0.21 0.86 0.55 0.84 596,768
SAP 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
40 CRWD Stormwater Monitoring Data Analysis Report
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 auto-
samplers; 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 Cl-
concentrations 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
CRWD Stormwater Monitoring Data Analysis Report 41
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
42 CRWD Stormwater Monitoring Data Analysis Report
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 sub-
watersheds (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 p-
value) 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 wash-
off 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 near-
CRWD Stormwater Monitoring Data Analysis Report 43
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 ‘other’ 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 load-
duration 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.
44 CRWD Stormwater Monitoring Data Analysis Report
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 Cl-
loading 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 45
Figure 3.5. Flow-duration curves for the East Kittsondale (EK) site, for (a) stormflow
and (b) baseflow.
0.1
1.0
10.0
100.0
1,000.0
1,000
10,000
100,000
1,000,000
10,000,000
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
Sto
rm E
ven
t F
low
Rate
(cfs
)
Sto
rm E
ve
nt
Vo
lum
e (
cu
ft)
Probability of Exceedence
Volume
Flow Rate
0.001
0.010
0.100
1.000
10.000
100.000
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
Bas
efl
ow
Rate
(c
fs)
Probability of Exceedence
46 CRWD Stormwater Monitoring Data Analysis Report
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 non-
linearly 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 47
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
48 CRWD Stormwater Monitoring Data Analysis Report
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 49
Table 3.4. Seasonality of metals toxicity exceedences in stormflow of CRWD sub-watersheds.
Season Parameter Kittson-
dale 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
sp
ring
No. of Samples 26 21 16 24 22 26 12 17 24 11 13 23 24
Exceedences (%) 11.5 0.0 0.0 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 N/A N/A 0.148 0.686 0.083 N/A 0.186 0.036 N/A 0.141 N/A
su
mm
er No. of Samples 68 57 57 53 62 55 48 55 48 32 25 50 66
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
fall
No. of Samples 31 26 27 25 21 20 24 24 17 14 10 21 24
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 0.059 N/A 0.301 N/A 0.046 0.148 0.160 0.183 0.111
Chromium
sp
ring
No. of Samples 26 21 16 24 22 27 12 17 24 11 13 23 24
Exceedences (%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mean Exc. (ug/L) N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
su
mm
er No. of Samples 68 57 57 53 62 55 48 55 48 32 25 50 66
Exceedences (%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mean Exc. (ug/L) N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
fall
No. of Samples 31 26 27 25 21 20 24 24 17 14 10 21 24
Exceedences (%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mean Exc. (ug/L) N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
50 CRWD Stormwater Monitoring Data Analysis Report
Table 3.4 (con’t). Seasonality of metals toxicity exceedences in stormflow of CRWD sub-watersheds.
Season Parameter Kittson-
dale 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
Copper
sp
ring
No. of Samples 26 21 16 24 22 27 12 17 24 11 13 23 24
Exceedences (%) 100.0 95.2 87.5 79.2 81.8 66.7 91.7 0.0 100.0 63.6 100.0 100.0 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
su
mm
er No. of Samples 68 57 57 53 62 55 48 55 48 32 25 50 66
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
fall
No. of Samples 31 26 27 25 21 20 24 24 17 14 10 21 24
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
Lead
sp
ring
No. of Samples 26 21 16 24 22 27 12 17 24 11 13 23 24
Exceedences (%) 100.0 100.0 93.8 83.3 90.9 77.8 100.0 0.0 100.0 90.9 100.0 100.0 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
su
mm
er No. of Samples 68 57 57 53 62 55 48 55 48 32 25 50 66
Exceedences (%) 97.1 96.5 80.7 92.5 98.4 90.9 95.8 9.1 100.0 93.8 100.0 100.0 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
fall
No. of Samples 31 26 27 25 21 20 24 24 17 14 10 21 24
Exceedences (%) 100.0 92.3 77.8 72.0 95.2 90.0 100.0 16.7 100.0 92.9 100.0 100.0 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
CRWD Stormwater Monitoring Data Analysis Report 51
Table 3.4 (con’t). Seasonality of metals toxicity exceedences in stormflow of CRWD sub-watersheds.
Season Parameter Kittson-
dale 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
Nickel
sp
ring
No. of Samples 26 21 16 24 22 27 12 17 24 11 13 23 24
Exceedences (%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mean Exc. (ug/L) N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
su
mm
er No. of Samples 68 57 57 53 62 55 48 55 48 32 25 50 66
Exceedences (%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mean Exc. (ug/L) N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
fall
No. of Samples 31 26 27 25 21 20 24 24 17 14 10 21 24
Exceedences (%) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Mean Exc. (ug/L) N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
Zinc
sp
ring
No. of Samples 26 21 16 24 22 27 12 17 24 11 13 23 24
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
su
mm
er No. of Samples 68 57 57 53 62 55 48 55 48 32 25 50 66
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
fall
No. of Samples 31 26 27 25 21 20 24 24 17 14 10 21 24
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
52 CRWD Stormwater Monitoring Data Analysis Report
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
Kittson-dale
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 NA NA NA 1.0E+00 NA 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 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 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 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
spring-fall N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
summer-fall N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 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 9.5E-02 6.1E-01 N/A
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 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
spring-fall N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A
summer-fall N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 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 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 53
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.
54 CRWD Stormwater Monitoring Data Analysis Report
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 non-
BMP 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 55
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 – 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 sub-
watersheds. This logically suggests that the larger, less common rainfall events are
56 CRWD Stormwater Monitoring Data Analysis Report
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 0.5-
inch 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
CRWD Stormwater Monitoring Data Analysis Report 57
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-
58 CRWD Stormwater Monitoring Data Analysis Report
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 59
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-And-
Resources/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.
60 CRWD Stormwater Monitoring Data Analysis Report
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.
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District.
DATE: October 31, 2013 TO: CRWD Board of Managers FROM: Anna Eleria, Water Resource Project Manager RE: 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 Board’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 11-06-13.docx
November 6, 2013 Board Meeting
IV. Special Report - B) CRWD Lakes Statistical Analysis
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 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.
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 Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013
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Table 1. Available data for the lake statistical analyses.
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.
Data Description Como Crosby Loeb McCarrons Little Crosby
Aquatic vegetation and species survey 2012 2012 2012 2012
Como Lake Turtle Study 2011
Crosby Lake Sediment Data 2010
Daphnia Size 1984‐2007 1999‐2007 2003‐2007 1988‐2007
DNR Fisheries‐Lake Management Plan 2005 2010
Lake Elevations 1978‐2012 2003‐2004, 2006‐2012 1924‐2012
Lake Sampling Data 1982, 1984‐2012 1999‐2012 2003‐2012 1988‐2012 2011‐2012
Macrophyte Surveys 2005, 2010 2009 2005 2005
Phytoplankton Data 1984‐2011 1999‐2011 2003‐2011 1988‐1998, 2000‐2011
Zooplankton Data 1984‐2011 1999‐2011 2003‐2011 1988‐1998, 2000‐2011
Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013
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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
Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013
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evaluate potential causes. For this analysis, the grouping was completed; however a detailed review of other factors was outside the scope of this assessment. Multivariate Assessment using the Lake Trophic Status Index The interrelationship between simultaneously collected variables can be used to identify conditions in a lake that affect those measured variables. One way this can be done is by evaluating the differences among TSI values for each of the three collected variables (Carlson 1992). Theoretically, the empirical relationships between TP, chlorophyll‐a, and Secchi should result in the same TSI value. Because these empirical relationships are derived from regressions that have error terms, some variability can be expected. However, in some situations the differences are not random and can be used to identify factors interfering with the relationship. The figure below represents a plot of the TSI differences with 4 primary zones for interpretation. Table 2 provides some interpretation of the data in each zone. If points fall below the x axis, chlorophyll‐a is under predicted suggesting that P is not limiting algal growth, rather algal growth is limited by light availability, nitrogen limitation or zooplankton grazing. Points lying to the right of the y axis indicate better clarity than expected which may be a result of larger algae such as aphanizomenon, a colony forming blue‐green algae. Points to the left of the y‐axis suggest smaller particles dominate suggesting water color or turbidity is a critical factor. Points lying along the diagonal and to the left of the axis suggest that P and clarity are correlated, but the expected chlorophyll response is not demonstrated. This suggest non‐algal turbidity such as clay is controlling water clarity and keeping the P unavailable for algal production.
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Carlson and Simpson, 1996. Following is a discussion of the results of the statistical analysis for each lake. LAKE MCCARRON Descriptive Statistics Total phosphorus, chlorophyll‐a and Secchi depth were assessed for basic statistical assumptions such as normality, equal variance, and central tendencies (Table 2). None of the data sets as a whole are normal or lognormal, although Secchi depth demonstrates a lognormal distribution in all but one year.
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Table 2. General statistical description of Lake McCarrons water quality data.
Statistic TP (mg/L) Chl‐a (µg/L) Secchi (m)
No. of observations 177 177 177Minimum 0.009 0.317 0.700Maximum 0.175 74.800 8.4001st Quartile 0.016 2.780 1.700Median 0.026 6.500 2.7503rd Quartile 0.039 13.370 4.000Mean 0.031 9.760 2.952Variance (n‐1) 0.001 107.056 2.199Standard deviation (n‐1) 0.025 10.347 1.483Skewness (Pearson) 3.258 2.856 0.697Kurtosis (Pearson) 14.539 12.298 0.206Standard error of the mean 0.002 0.787 0.114Geometric mean 0.026 6.197 2.580Geometric 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.
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Table 3. Evaluation results for tests of normality and equal variance among groups.
1Levene’s test 2Shapiro‐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.
Parameter Data Logs of Data Residuals1 Residuals of Logs1
Equal Variance?1
Normally Distributed?2
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Total Phosphorus
No No Yes No No No Yes No
Chlorophyll‐a
No No Yes No No No Yes No
Secchi Depth
Yes No No Yes Yes No No Yes
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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.
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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.
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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 307Minimum 0.031 0.1 0.20Maximum 0.970 223.3 4.201st Quartile 0.089 6.8 0.70Median 0.129 20.1 1.203rd Quartile 0.228 49.4 2.20Mean 0.182 32.8 1.58Variance (n‐1) 0.023 1261.7 1.09Standard deviation (n‐1) 0.150 35.5 1.05Skewness (Pearson) 2.358 1.9 0.86Kurtosis (Pearson) 6.879 4.8 ‐0.31Standard error of the mean 0.009 2.1 0.06Geometric mean 0.142 16.5 1.26Geometric 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
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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.
1Levene’s test 2Shapiro‐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.
Parameter Data Logs of Data Residuals1 Residuals of Logs1
Equal Variance?1
Normally Distributed?2
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Total Phosphorus
No No No No No No No No
Chlorophyll‐a
No No No No No No No No
Secchi Depth
No No No No No No No No
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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.
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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.
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Table 6. General statistical description of Lake McCarrons water quality data.
Statistic TP (mg/L) Chl‐a (µg/L) Secchi (m)
No. of observations 87 87 87Minimum 0.010 0.2 0.50Maximum 0.330 47.0 4.90Range 0.320 46.8 4.401st Quartile 0.032 2.8 1.63Median 0.051 4.7 2.003rd Quartile 0.091 8.8 2.88Mean 0.066 8.0 2.26Variance (n‐1) 0.002 75.6 0.85Standard deviation (n‐1) 0.050 8.7 0.92Skewness (Pearson) 2.415 2.2 0.55Kurtosis (Pearson) 8.414 5.0 ‐0.23Standard error of the mean 0.005 0.9 0.10Geometric mean 0.053 5.1 2.07Geometric 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.
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Table 7. Evaluation results for tests of normality and equal variance among groups.
1Levene’s test 2Shapiro‐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.
Parameter Data Logs of Data Residuals1 Residuals of Logs1
Equal Variance?1
Normally Distributed?2
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Total Phosphorus
No No No No No No No No
Chlorophyll‐a
No No No No No No No No
Secchi Depth
No No No No No No No No
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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
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water column is available for algal production and may be adhered to small particles such as clay or other TSS components. TP may be increasing in the lake, but it does not appear to all be readily available for algal production. Because there is a P surplus, other factors need to be considered in managing Crosby Lake including fisheries and submerged aquatic vegetation abundance. Potential Divers of Water Quality Crosby Lake Conclusions
1. Water quality in Crosby Lake’s three most recent years demonstrates an increase in total
phosphorus and a decrease in water clarity. Algal abundance is high in 2010 and 2011, although
water quality in 2012 was typical of previous years even though TP was higher. This suggests
that water quality in Crosby Lake is degrading but that algal abundance is not necessarily
controlled directly by TP (some fraction of phosphorus may be unavailable or zooplankton
grazing may play a role).
2. Water clarity appears to be primarily driven by algal abundance.
3. Statistical trend testing verifies that water quality in Crosby Lake is trending poorer with
increases in total phosphorus and chlorophyll‐a and decreases in water clarity. However, this
may be a function of inundation by the Mississippi River which occurred for 164 days over the
past 4 years.
Loeb Lake Total phosphorus, chlorophyll‐a and Secchi depth were assessed for basic statistical assumptions such as normality, equal variance, and central tendencies (Table 9). Secchi depth is normally distributed for Loeb Lake. TP and chlorophyll‐a were not normally or log‐normally distributed. Variance for all three parameters was low.
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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.
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Table 8. Evaluation results for tests of normality and equal variance among groups.
1Levene’s test 2Shapiro‐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.
Parameter Data Logs of Data Residuals1 Residuals of Logs1
Equal Variance?1
Normally Distributed?2
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Equal Variance?
Normally Distributed?
Total Phosphorus
Yes No Yes No Yes Yes Yes No
Chlorophyll‐a
Yes No Yes Yes Yes No Yes Yes
Secchi Depth
Yes Yes Yes Yes Yes Yes Yes Yes
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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
Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013
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
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.
Technical Memo Statistical Analysis of Lake Data in the Capitol Region Watershed District Capitol Region Watershed District September 18, 2013
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
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.
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District
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 – 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
B) 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 – 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. Receipt of $4,650 surety and maintenance agreement.
2. Provide a copy of the NPDES permit.
November 6, 2013 Board Meeting
V. Action Item A) Approve Minutes
of October 16, 2013
DRAFT Regular Board Meeting
(Sylvander)
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District
3. 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.
4. 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. Receipt of $7,000 surety.
2. Provide a copy of the NPDES permit.
3. Revise construction limits, perimeter controls, and revegetation areas to encompass the temporary
parking area..
4. Provide native seed mix appropriate for the river corridor and floodplain such as Mn/DOT 300 series.
5. 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.
6. Identify and provide protection for catch basins on Randolph Avenue.
7. Provide a flood response plan to minimize floodwater contact with demolition materials and exposed
soils.
8. Quantify the net change in floodplain storage and provide compensatory storage for any fill within 100-
yr floodplain.
9. 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
V. 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
C) 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, stacked-
function 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 13th
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 – 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.
DATE: October 31, 2013
TO: CRWD Board of Managers
FROM: Anna Eleria, Water Resource Project Manager
RE: Approve Contract Amendment #4 for Engineer for Highland Ravine Stabilization Project
Background
In early November 2012, CRWD’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
November 6, 2013 Board Meeting
V. Action Item – B) Contract
Amendment for Engineer for
Highland Ravine Project (Eleria)
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
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.
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
Technical Memo Scope of work change #5 Highland Ravine Stabilization Project October 28, 2013
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
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.
Wenck Staff Matthiesen Shoemaker Jonett BoellTitle Sr. Engineer PM/WR Eng LA CAD
Hourly Rate $179 $144 $101 $144 $93TASK 1 Data Collection and Review $
TASK 01 TOTAL: $0.00
TASK 2 Field Work and Site Evaluation $TASK 02 TOTAL: $0.00
TASK 3 Project Design $A Sanitary sewer design and meeting with St. Paul $1,808.00 6 7B Revise plans based on City and CRWD comments $977.00 1 2 2 2 $20C Receive comments from City, DP, and CRWD $288.00 2D Finalize plans based on homeowner, City and CRWD comments $977.00 1 2 2 2 $20
TASK 03 TOTAL: $4,050.00
TASK 4 Construction Bidding $A Revise and resubmit project manual to CRWD for review $490.00 2 2B Finalize project manual $1,048.00 4 4 $100C Pre-bid meeting $462.00 3 $30D Respond to bidder questions $288.00 2E Attend bid opening $462.00 3 $30F Advise CRWD of lowest, qualified bidder and draft memo $432.00 3
TASK 04 TOTAL: $2,000.00
TASK 5 Technical Support for Easement Agreements $A Provide plans and easements to Deer Park (DP) homeowners $144.00 1B Finalize easements with homeowners and agreement with Deer Park $144.00 1C Board approval of homeowner easements and Deer Park agreement $0.00
TASK 05 TOTAL: $288.00
TASK 6 Permitting $A Resubmit plans to City for site plan review $144.00 1
TASK 06 TOTAL: $144.00
TASK 7 Project Coordination and Meetings $A Project coordination $1,152.00 8
TASK 07 TOTAL: $1,152.00
PROJECT TOTALS $7,634.00 2 38 6 13 4 $200
Admin ExpensesTASK ID TASK DESCRIPTION
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District
DATE: October 31, 2013
TO: CRWD Board of Managers
FROM: Mark Doneux, Administrator
SUBJECT: 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
April 3, 2013 Board Meeting
V. Action Item – C) Establish
Monitoring, Research and
Maintenance Division (Doneux)
Citizens
Board of Managers
Administrator
Program ManagerMonitoring, Research
& Maintenance
Water Resource Technician
Water Resource Technician
Water Resoure Technician (Seasonal)
Monitoring Coordinator
Water Resource Technician (.25 FTE)
Maintenance Coordinator
Program ManagerRegulatory Program
Water Resource Technician (.75 FTE)
Technician
Program ManagerCapitol Improvements
and TBI
Water Resource Specialist
Technician
Program ManagerEducation & Outreach
Education Assistant (.50 FTE)
Education Assistant
Program ManagerGrants & BMPs
Technician
Office Manager
Administrative Assistant (.50 FTE)
Engineer Attorney
Ramsey County Commissioners CAC
Technician
CAPITOL REGION WATERSHED DISTRICT
2020 ORGANIZATIONAL CHART
October 31, 2013
Currently same person performing two roles
Future Position
Implement in 2013
Implementation(TBD)
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 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 District’s staff structure to ensure an efficient and effective structure that harnesses staff skills, abilities and professional development goals.
*Approval must receive minimum of 3 Yeas
Vote: Approved/Denied W:\04 Board of Managers\Motions\Resolutions 2013\Resolution 13-xx-xx Establishing Monitoring, Research and Maintenance Division 10-29-13.docx
Requested By: Mark Doneux Recommended for Approval: Approved by Attorney: N/A Funding Approved: N/A
Manager Yeas* Nays Absent Abstain Collins Texer Jones Thienes Reider TOTAL
Resolution # 13-194 Date Adopted: November 6, 2013
Resolution Adoption Certified By the Board of Managers: By: ______________________________________ Date: November 6, 2013
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District
DATE: October 31, 2013
TO: CRWD Board of Managers
FROM: Mark Doneux, Administrator
SUBJECT: 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
November 6, 2013 Board Meeting
V. Action Item – D) Approve
Program Manager III Position
(Doneux)
Board Adopted: November 6, 2013
GRADE: 11 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. 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.
2. Effective communication skills, both oral and written. 3. 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.
4. Demonstrated ability in team building and effective coaching. 5. Demonstrated knowledge of budget preparation and contract development. 6. Demonstrated knowledge of procurement, permitting and other processes, and design and
construction contracting. 7. Extensive knowledge of project management techniques. 8. Extensive negotiating skills. 9. Ability to analyze technical reports and construction diagrams. 10. Proven ability to achieve goals, ability to work successfully with considerable independence. 11. Excellent analytical, conflict management, interpersonal, and leadership skills. 12. Ability to write successful grant requests, including knowledge of grant writing requirements. 13. 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.
14. 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.
15. 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.
16. Must have valid Minnesota driver’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: Salaried, exempt from the provisions of the Fair Labor Standards Act. 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
Frequency
Walking/standing: M
Sitting: M
Standing in One Place:
M
Climbing:
O
Pulling/Pushing:
M
Crawling/Kneeling/Squatting:
M
Bending/Stooping:
M
Twisting/Turning:
M
Repetitive movement:
M
Lifting waist to shoulder:
M
Lifting knee to waist:
M
Lifting floor to knee: M
S = Significant M = Moderate O= Occasional
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District.
DATE: October 31, 2014
TO: Board of Managers
FROM: Mark Doneux
RE: 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 2014 Employee 2014 District* Total Cost*
Single Health Insurance $40.00 $299.41 $339.41
Single + 1 Insurance $80.00 $606.11 $686.11
Family Health Insurance** $120.00 $815.71 - $1,314.91 $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.
November 6, 2013
V. Action Items E) Approve 2014
Employee Benefit Program
(Doneux)
2
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 2014 Employee 2014 District Total Cost
Single Dental Insurance $10.00 $30.85 $40.85
Single + 1 Dental Insurance $20.00 $61.29 $81.29
Family Dental Insurance $40.00 $82.55 $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) Effective January 1, 2014, the District move all employee benefit programs from Ramsey County
to those offered through the District’s Insurance Company, the Bearence Management Group.
2) 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.
3) 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.
4) 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.
5) 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
Our Mission is to protect, manage and improve the water resources of Capitol Region Watershed District.
DATE: October 31, 2013
TO: CRWD Board of Managers
FROM: Anna Eleria, Project Manager
Gustavo Castro, Water Resource Specialist
RE: 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
November 6, 2013
VI. Unfinished Business A)
Inspiring Communities
Program Updates (Eleria,
Castro)
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Copyright: ©2013 Esri, DeLorme, NAVTEQ
Capitol Region Watershed DistrictInspiring Communities Program | Project Locations
0 0.6 1.2 1.8 2.40.3Miles I
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.
! 2013 Sites! 2011-2012 Sites
Major HighwaysMajor WaterbodiesParksCRWDSubwatersheds
Falcon Heights
DATE: October 31, 2013
TO: CRWD Board of Managers and Staff
FROM: Mark Doneux, Administrator
RE: November 6, 2013 Administrator’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
1) 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.
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 final site restoration phase.
b) TBI – 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.
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