Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 Mainstreaming Green Infrastructure Proceedings of the International Low Impact Development Conference 2016 Portland, Maine August 29–31, 2016 Edited by Robert Roseen, Ph.D., P.E., D.WRE Virginia Roach, P.E James Houle, Ph.D Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved INTERNATIONAL LOW IMPACT DEVELOPMENT CONFERENCE 2016 MAINSTREAMING GREEN INFRASTRUCTURE PROCEEDINGS OF THE INTERNATIONAL LOW IMPACT DEVELOPMENT CONFERENCE 2016 August 29–31, 2016 Portland, Maine SPONSORED BY New England Water Environment Association Environmental and Water Resources Institute of the American Society of Civil Engineers EDITED BY Robert Roseen, Ph.D., P.E., D.WRE Virginia Roach, P.E James Houle, Ph.D Published by the American Society of Civil Engineers Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved Published by American Society of Civil Engineers 1801 Alexander Bell Drive Reston, Virginia, 20191-4382 www.asce.org/publications | ascelibrary.org Any statements expressed in these materials are those of the individual authors and not necessarily represent the views of ASCE, which takes no responsibility for any statement made herein No reference made in this publication to any specific method, product, process, or service constitutes or implies an endorsement, recommendation, or warranty thereof by ASCE The materials are for general information only and not represent a standard of ASCE, nor are they intended as a reference in purchase specifications, contracts, regulations, statutes, or any other legal document ASCE makes no representation or warranty of any kind, whether express or implied, concerning the accuracy, completeness, suitability, or utility of any information, apparatus, product, or process discussed in this publication, and assumes no liability therefor The information contained in these materials should not be used without first securing competent advice with respect to its suitability for any general or specific application Anyone utilizing such information assumes all liability arising from such use, including but not limited to infringement of any patent or patents ASCE and American Society of Civil Engineers—Registered in U.S Patent and Trademark Office Photocopies and permissions Permission to photocopy or reproduce material from ASCE publications can be requested by sending an e-mail to permissions@asce.org or by locating a title in ASCE's Civil Engineering Database (http://cedb.asce.org) or ASCE Library (http://ascelibrary.org) and using the “Permissions” link Errata: Errata, if any, can be found at https://doi.org/10.1061/9780784480540 Copyright © 2017 by the American Society of Civil Engineers All Rights Reserved ISBN 978-0-7844-8054-0 (PDF) Manufactured in the United States of America International Low Impact Development Conference 2016 Preface Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved The International Low Impact Development Conference was held in Portland, Maine in August of 2016 The Proceedings presented here represent a slice of the interesting and timely content that was presented at the conference The conference this past year highlighted the mainstreaming of Green Infrastructure and Low Impact Development in municipal programming as well as new and existing work and research in the United States and internationally We are excited to announce that the 2016 LID conference led to a spin-off conference entitled Operations and Maintenance of Stormwater Control Measures that will be coming to Denver, Colorado in November 2016 We hope that these proceedings provide the in-depth information that you are looking for and we look forward to seeing you at the next LID conference in 2018! Acknowledgments Preparation and planning are the key to a successfully executed conference so we would like to recognize the hard work of the Conference Steering Committee and also others that are not mentioned here Conference Chair Rob Roseen, PH.D., P.E., D.WRE Waterstone Engineering Conference Co-Chairs Virginia Roach CDM Smith James Houle UNH Stormwater Center Technical Program Chair James Houle UNH Stormwater Center Technical Program Vice Chairs Bethany Eisenberg Vanasse Hangen Brustlin Inc William Arcieri Vanasse Hangen Brustlin Inc © ASCE iii International Low Impact Development Conference 2016 Local Host Chair Curtis Bohlen Casco Bay Estuary Program Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved Rachel Rouillard Piscataqua Regions Estuary Partnership Workshop and Field Trip Coordinator Chair James Houle UNH Stormwater Center Workshop and Field Trip Coordinator Vice-Chair Jami Fitch Cumberland County Soil & Water Conservation District Past LID conference Member Scott Struck Geosyntec Finally, we acknowledge and thank the staff of the EWRI of ASCE, who, in the end, make it all happen Director, EWRI Brian K Parsons, M.ASCE Technical Manager, EWRI Barbara Whitten Senior Coordinator, EWRI Veronique Nguyen Conference Manager Cristina Charron Conference Coordinator Rachel Hobbs Sponsorship and Exhibit Sales Manager Sean Scully Registrar Nives McLarty © ASCE iv International Low Impact Development Conference 2016 Contents Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved Cistern Performance for Stormwater Management in Camden, NJ Farzana Ahmed, Michael Borst, and Thomas O’Connor Low Impact Development for Controlling Highway Stormwater Runoff—Performance Evaluation and Linkage to Cost Analysis Azadeh Akhavan Bloorchian, Jianpeng Zhou, Abdolreza Osouli, Laurent Ahiablame, and Mark Grinter How the Implementation of Green City, Clean Waters in Philadelphia Advances Modeling Capabilities across the Program 16 Eileen Althouse, Edward Lennon Jr., and Julie Midgette Addressing Water Scarcity in South Africa through the Use of LID .20 L N Fisher-Jeffes, N P Armitage, K Carden, K Winter, and J Okedi Development of a Low Impact Development and Urban Water Balance Modeling Tool 29 Steve Auger, Yuestas David, Wilfred Ho, Sakshi Sani, Amanjot Singh, Tim Van Seters, Chris Davidson, Melanie Kennedy, and Kevin MacKenzie Simulation of the Cumulative Hydrological Response to Green Infrastructure 43 Pedro M Avellaneda, Anne J Jefferson, and Jennifer M Grieser Dual Opportunity for Education and Outreach to Evaluate Benefits of GI Implementation 52 Leslie Brunell and Elizabeth Fassman-Beck Examination of Empirical Evidence and Refining Maintenance Techniques for GI 65 Amirhossein Ehsaei and Thomas D Rockaway Comprehensive Benefits Assessment with as a Step toward Economic Valuations of Ancillary Benefits of Green Storm Water Infrastructure and Non-Structural Storm Water Quality Strategies in San Diego, California .78 Clem Brown, Richard Haimann, and Chris Behr A New Method for Sizing Flow-Based Treatment Systems to Meet Volume-Based Standards 89 Kelly L Havens, Zachary J Kent, and Aaron Poresky Evaluating the Real Estate Development and Financial Impacts of the San Diego Region’s Post-Construction Standards and Alternative Compliance Program: A Multi-Disciplinary Effort 98 Juli Beth Hinds © ASCE v International Low Impact Development Conference 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved Estimating Monetized Benefits of Groundwater Recharge from Stormwater Retention Practices 106 John Kosco, Lisa Hair, Jonathan Smith, and Heather Fisher Design Parameters for Manufactured Soils Used in Storm Water Treatment, Wetland Restorations, and LID Projects 114 Geoffrey Kuter, David Harding, and Mike Carignan Performance Optimization of a Green Infrastructure Treatment Train Using Real-Time Controls 123 C Lewellyn, B M Wadzuk, and R G Traver Greening Indiana—One Training at a Time 131 Sheila McKinley Update to Permeable Pavement Research at the Edison Environmental Center 135 Thomas P O’Connor and Michael Borst Full-Scale Structural Testing of Permeable Interlocking Concrete Pavement to Develop Design Guidelines 143 David J Jones, Hui Li, Rongzong Wu, John T Harvey, and David R Smith Developing Low Impact Development (LID)-Based District Planning (DP) Techniques and Simulating Effects of LID-DP .155 C H Son, J I Baek, D H Kim, and Y U Ban Green Infrastructure Performance Model in the Real World: Modeling Natural and Simulated Runoff Events 163 Stephen White, Tyler Krechmer, Taylor Heffernan, Nicholas Manna, Elizabeth Mannarino, Chris Bergerson, Mira Olson, and Jason Cruz Winter Road Salting in Parking Lots: Permeable Pavements vs Conventional Asphalt Pavements .173 H Zhu, J Drake, and K Sehgal © ASCE vi International Low Impact Development Conference 2016 Cistern Performance for Stormwater Management in Camden, NJ Farzana Ahmed1; Michael Borst2; and Thomas O’Connor3 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved Post-Doctoral Research Fellow, Oak Ridge Institute of Science and Education (ORISE), U.S Environmental Protection Agency, 2890 Woodbridge Ave., MS-104, Edison, NJ 08837 E-mail: ahmed.farzana@epa.gov U.S Environmental Protection Agency, 2890 Woodbridge Ave., MS-104, Edison, NJ 08837 Email: borst.mike@epa.gov U.S Environmental Protection Agency, 2890 Woodbridge Ave., MS-104, Edison, NJ 08837 Email: oconnor.thomas@epa.gov ABSTRACT The Camden County Municipal Utilities Authority installed cisterns at locations around the city of Camden, NJ Cisterns provide a cost effective approach to reduce stormwater runoff volume and peak discharge The collected water can be substituted for potable water in some applications reducing the demand This presentation focuses on five cisterns that were monitored as part of a capture-and-use system at community gardens The cisterns capture water from existing rooftops or shade structures installed by CCMUA as part of the project Cistern volumes varied from 305 gallons to 1,100 gallons The design volume was based on the available roof drainage area Water level was monitored at 10-minute intervals using pressure transducers and rainfall was recorded using tipping bucket rain gauges Cisterns were sampled at to week intervals through the growing season for determination of concentration of microorganisms, nutrients, and metals The analyses detected antimony, arsenic, barium, copper, lead, manganese, nickel, vanadium, and zinc Concentration of all these metals were below recommended water quality criteria for irrigation by EPA guidelines for water reuse The total nitrogen, phosphate, and total organic carbon concentrations varied from 0.23 to 2.26 mg/L, 0.025 to 1.11 mg/L, and 0.55 to 4.06 mg/L, respectively Large total coliform concentrations were observed in some samples The presentation will summarize the data for first growing season giving the results from monitoring the water use and water quality of cisterns INTRODUCTION The Camden County Municipal Utilities Authority (CCMUA) has installed several green infrastructure stormwater control measures (SCMs) throughout the City of Camden to reduce the volume of Combined Sewer Overflows This presentation focuses on five cisterns installed at community gardens The Rutgers Cooperative Extension Water Resources Program developed engineering plans and specifications for each of the sites US EPA is monitoring these five installed cisterns for three consecutive growing seasons This paper summarizes the findings from monitored cisterns for the first year growing season Cisterns collect and store rainwater that can be used for household and other uses A gutter and downspout system directs the collected rainwater to the storage cistern Cisterns can be installed above or below ground Roof harvested rain water has been considered to be one of the most cost effective sources for various non potable uses like irrigation, toilet flushing, and car washing (Ahmed, et al 2011)) Cisterns can reduce stormwater runoff volume and peak discharge rates, and provide an alternative water supply during times of water restriction Factors that influence the quality and quantity of captured rainwater include: roof geometry (size, © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 exposure, and inclination), roof material (chemical characteristics, roughness, surface coating, age, and weatherability), location of the roof (proximity of pollution sources), maintenance history of the roof, rainfall events (wind speed, intensity, and pollutant concentration), other meteorological factors (seasons, weather characteristics, and antecedent dry period), and concentration of substances in the atmosphere (transport, emission, half-life, and phase distribution) (Abbasi and Abbasi 2011) The objectives of this study are to: 1) demonstrate the performance of cisterns, 2) determine how the performance of cistern changes during the first three years of operation, and 3) collect and analyze aqueous samples from cistern for presence of bacteria and other analytes This paper only presents the quantity and quality analysis from the first growing season SITE DESCRIPTION AND INSTRUMENTATION Camden is located in southwestern New Jersey, United States The city is highly urbanized with an aging and overburdened combined sewer system which discharges to the Delaware River As part of the effort to control combined sewer overflows, CCMUA installed the cisterns in 2014 and 2015, with capacities ranging from 300 to 1,100 gallons to provide capture-and-use for irrigating community gardens and existing landscaped areas Since May 2015, US EPA monitored water collection-and-use at five cistern sites: the Vietnamese Community Garden, Kaighns Avenue Neighborhood Community Center, Respond Inc., Cooper Sprouts Community Garden, and St Joan of Arc Church Level loggers (Solinst 3001 LT Levelogger) placed at the bottom of each cistern record water level at 10-minute intervals At five sites, standalone tipping bucket rain gauges (Onset model RGD-04) were installed A layout of the location of the installed sensors are shown in Figure Figure Location of cisterns and rain gauges © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 Figure Cistern at St Joan of Arc Church site These cistern tanks as shown in Figure 2, are made of resins that meet FDA specification to ensure safe water storage The black color limits light penetration to reduce the growth of water borne algae The monitored cisterns are installed near vegetable gardens to provide irrigation water These cisterns capture roof runoff through the downspout from adjacent buildings At some sites no building existed, therefore, a shade structure was constructed to supply roof runoff to the cistern tank If it rains while the cistern is full, the cistern overflows Near the bottom of each tank a spigot and a hose was installed so that the water can be used At two sites, a pump was installed with the spigot that helped to draw the water from the tank Pressure transducer and rain gauge data were used to calculate the fraction of available water used from each cistern Water samples were collected every to weeks after the sensor installation The samples were analyzed for microorganisms, metals, and nutrients AVAILABLE WATER USE For each cistern, the relative use of available water was calculated To calculate the relative volume used, the total water use between consecutive rain events is divided by the available water volume in the tank For example, in Figure 3, the green line shows the water level depth inside the cistern tank monitored by pressure transducer at the Kaighns Avenue site The red dots show the cumulative rain depth from 07/31 to 08/12 Precipitation was recorded on 07/30, 08/07, and 08/11 Between 07/30 and 08/07 rain events the available water was 1.04 m and no water was used, so the water use between 07/30 and 08/07 is 0% Between 08/07 and 08/11 rain event water use was 0.12m and available water was 1.04m So L 0.12 100% 11% After calculating the water use between each the water use is 100% L1 1.04 consecutive rain event, the water use was averaged Table shows the water use for each cistern site for first growing season The water use ranged from to 34% At St Joan of Arc Church site, the gardeners did not use any captured water Discussions with one of the gardeners suggested that the reason might be lack of pressure to help to transfer water from the tank to the garden Since no water was used, the roof runoff overflowed from the cistern after it was full and it did not reduce stormwater runoff volume At © ASCE Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 recession rate over the effective infiltration footprint O Ie Aei O = (Outflow) or Recession Rate (CF/hr) I e = “Infiltration rate” estimate (FT/hr) Infiltration rates are expected to be higher initially as the soils have much lower water content conditions prior to application of flow and some volume of water is expected to rapidly leave the system prior to the water reaching the observation well The GIP model uses a form of the The Green-Ampt infiltration equation Green-Ampt infiltration is extensively used in water resources hydrologic modeling applications and has inputs that can easily be estimated from design documents The equations below describe the Green-Ampt infiltration model as applied in GIP F Ks t t1 (C ln F C F1 C ln F1 C F1 = cumulative Infiltration from previous timestep (ft) F = cumulative Infiltration during current timestep (ft) C S h IMD t1 = time at previous time step (min) t = time at current time step (min) h = water level at time t2 (ft) S = soil suction head (ft) IMD = Initial soil moisture deficit (cf/cf) Ks = Saturated Hydraulic conductivity (ft/minute) Parameters “S” and “IMD” were estimated from (Rawls, Brakensiek, & Miller, 1983) The estimate of the initial soil moisture deficit is the difference between the porosity of soil type and field capacity The soil type from the pre-construction geotechnical investigations was used to estimate the parameters Solving fore F1 and F2 iteratively 1000 times the GIP model converges on a solution for infiltration that has occurred for the time step ( Ft ) The model then routes the water through the effective infiltration footprint by multiplying the volume of water infiltrated during the time step by the effective infiltration footprint F1 F Ft Ft Aei Vt This yields an estimate of the volume of water ( Vt ) that infiltrated from the system over the time step GIP proceeds in evaluating infiltration until the metered flow from the SRT application is infiltrated Model runs are manually calibrated by adjusting Ks , IMD , and S to fit model outputs of calculated water level and infiltration rate to observed water level and infiltration rate MODEL RESULTS The GIP model routines were applied to thirteen SCMs These SCMs vary in size and contributing drainage area Example Plots from the GIP model runs are found in Figure and Figure The volume of water used to perform an SRT was translated to an equivalent depth over the drainage area Table Initial application of SRTs was performed at the 1” storm size This was the storm that Philadelphia Water felt would represent the most conservative approach © ASCE 167 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 to testing as it was a storm that occurs frequently enough that it would not overwhelm the systems One inch of stormwater managed over one acre represents one “greened acre”, a water quality based effluent limit for the city of Philadelphia’s Combined Sewer Overflow (CSO) Long-Term Control Plan Update (Philadelphia Water, 2009) After initial SRTs the volume of water applied was changed to at least the designed storm size or a 2” storm depending on physical constrains of the SCM such as available hydrant water pressure and time to perform test Observations showing a water level changes less than expected for a given system storage volume were common after 1” SRTs As the water was shown to enter the inflow structures efficiently, the lower than expected water level was considered symptomatic of the conservative assumptions in the design process Such assumptions not account for dynamic changes in the water level and infiltration of the system via unsaturated infiltration, heterogeneous soil profile, and ET Applying a larger storm size allowed the flow rate to overwhelm these dynamic processes This change allows a more rigorous assessment of the function of the SCM since it applies a greater stress to the system Figure Front Street Tree Trench GIP Model Plots In all cases of the SRT application hydraulic efficiency of the inflow component (e.g inlet or curb cut) was tested In cases were inefficiencies are discovered minor corrective action is taken to remediate any inefficiency and verified (Heffernan, et al., 2016) prior to application of the SRT Parameters used in model runs are shown in Table Soil type and conductivity are from geotechnical investigation performed during the design phase used to determine the soil conditions present and suitability for use of infiltration based systems The values for Ksat derived from GIP model runs are compared to the pre-construction measurements of Ksat when calibrating the model runs The infiltration rate measurements used in design are the same order of magnitude or higher when compared to the post-construction monitoring results This is a rough comparison as the methods of estimating Ksat from © ASCE 168 International Low Impact Development Conference 2016 169 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved geotechnical investigation can vary from SCM to SCM Figure Morris Leeds Tree Trench GIP Model Plots Table 1: GIP model parameters and post-construction Ksat v pre-construction Ksat Post Construction Monitoring SMP ID 1-1-1 3-2-1 3-6-1 8-1-1 9-2-1 170-1-1 170-2-1 179-5-1 180-1-1 20-8-1 325-1-1 326-1-1 327-1-1 Soil Suction 1.95 6.57 6.3 5.07 2.41 6.5 2.35 5.34 1.9 Soil Initial Moisture Deficit 0.24 0.31 0.35 0.171 0.24 0.18 0.18 0.312 0.32 0.31 0.24 0.18 0.346 Soil Ksat (in/hr) 15 0.2 1.75 1.75 0.75 3.5 0.5 0.73 10 Ksat* 0.5 0.54 0.54 0.29 0.59 1.24 3.3 2.21 0.24 0.14 0.5 0.37 * Ksat from pre-construction investigation performed at system depth Figure shows slight perturbations in the water level data This reflects variations in the inflow performed as a test case to evaluate model response to changes in flow regimes during joint testing procedures performed with research partners at Villanova University This method was applied later in the deployment of the SRT protocol It will be included in future © ASCE International Low Impact Development Conference 2016 applications as a stress test of both the model and the SCM Table 2: SRT application; storm size applied and designed Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved SRT parameters Designed Applied SMP ID Storm size Storm Size 1-1-1 0.86 1.01 3-2-1 1.00 1.00 3-6-1 1.00 2.01 8-1-1 0.66 2.00 9-2-1 1.41 1.00 170-1-1 2.64 1.00 170-2-1 1.99 1.00 179-5-1 1.52 1.73 180-1-1 1.13 1.14 20-8-1 0.99 1.00 325-1-1 1.05 1.24 326-1-1 0.79 1.46 327-1-1 1.03 1.01 Storm size represents depth over the drainage area of the SMP CONCLUSIONS AND FUTURE WORK Oftentimes, physical parameters or environmental conditions of urban GSI differ significantly from those laid out in design documents Monitoring GSI function at the system level allows Philadelphia Water to detect these differences and adjust performance estimates accordingly SRT application and GIP model runs generate quantitative and qualitative data to form a complete estimate of SCM performance Based solely on the volumes of water applied during the SRT procedures the systems tested were shown to fully manage the designed conditions The three SCMs to which a volume lower than the design target was applied (9-2-1, 170-1-1, and 170-2-1) had more than adequate storage volume left at peak storage remaining to take the excess volume Long-term monitoring coupled with parameter estimates from GIP model runs for Ksat is anticipated to provide indicators of loss of performance (primarily as changes in the value of Ksat) Future work will consider these factors as Philadelphia Water scales its green infrastructure program beyond year The GIP model is limited by its assumptions Chief among them is the assumption that Ksat is the same for both vertical and horizontal components of infiltration Future work will isolate the horizontal and vertical components of infiltration Current iterations of the GIP model assume that the initial moisture content of the soil is constant Initially this was done to account for the varying moisture conditions of the SCM in the horizontal surface area Future iterations will implement a form of the Mein-Larson algorithm to account for saturated conditions (Mein & Larson, 1973) © ASCE 170 International Low Impact Development Conference 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved APPENDIX A: EQUIPMENT USED BY PHILADELPHIA WATER'S GSI MONITORING GROUP Figure A 1: Onset HOBO water level logger extracted from observation well Figure A 2: Sensus W-1250 water meter in use during quantitative SRT Figure A 3: Profile View of Typical Stormwater Tree Trench SCM © ASCE 171 International Low Impact Development Conference 2016 Disclaimer: Use of trade names does not imply endorsement of any product or service on behalf of Philadelphia Water or other named parties Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved WORKS CITED City of Portland (2004) Environmental Services, Monitoring Retrieved 05 02, 2016, from The City of Portland Oregon: https://www.portlandoregon.gov/bes/article/63096 Emerson, C (2008, 05) Evaluation of Infiltration Practices as a Means to Control stormwater Runoff PhD Thesis Villanova, PA: Villanova University Heffernan, T., White, S., Krechmer, T., Manna, N., Bergerson, C., Olson, M., et al (2016) Green Stormwater Infrastructure Monitoring of Philadelphia's Green City, Clean Waters Program ASCE EWRI 2016 ASCE Krechmer, T (2015) Modeling the Design and Performance of Stormwater Tree Trenches Master's Thesis, Drexel University, Civil, Architectural, and Environmental Engineering, Philadelphia Mein, R G., & Larson, C (1973) Modeling infiltration during a steady rain Water Resourc Res, 2, 384–394 Onset Computer Corp (2015, 01 23) HOBO U20 Water Level Data Logger 30-Foot Depth U20-001-01 Bourne, MA Retrieved 23 01, 2015, from Onset, HOBO Data Loggers: http://www.onsetcomp.com/files/datasheet/Onset%20HOBO%20U20%20Water%20Level%20Data%20Loggers.pdf Philadelphia Water (2009, 09 01) Green City Clean Waters Retrieved 05 01, 2016, from Phillywatersheds.org: http://www.phillywatersheds.org/ltcpu/LTCPU_Complete.pdf Philadelphia Water (2012) Comprehensive Monitoring Plan Retrieved 05 04, 2016, from phillywatersheds.org: http://phillywatersheds.org/ltcpu/GCCW%20Comprehensive%20Monitoring%20Plan%20Ap pendices.pdf Philadelphia Water (2015, 05 15) Green Stormwater Infrastructure Planning and Design Resources Retrieved 05 02, 2016, from phillywatersheds.org: http://phillywatersheds.org/doc/GSI/GSI_Design_Requirements_&_Guidelines_Packet_515-2015.pdf R Core Team (2015) Vienna, Austria: R Foundation for Statistical Computing Rawls, W J., Brakensiek, D L., & Miller, N (1983) Green-Ampt Infiltration Parameters from Soils Data Journal of Hydraulic Engineering, 109, 62–70 Sensus USA Inc (2016, 05 11) Detector Model W-1250 Raleigh, NC Retrieved 05 11, 2016, from Sensus.com: http://sensus.com/products/portable-test-equipment/ The MathWorks, Inc (2016) Matlab Natick, MA Retrieved from https://www.mathworks.com/products/matlab/?requestedDomain=www.mathworks.com © ASCE 172 International Low Impact Development Conference 2016 Winter Road Salting in Parking Lots: Permeable Pavements vs Conventional Asphalt Pavements H Zhu1; J Drake, Ph.D., M.ASCE2; and K Sehgal3 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved Dept of Civil Engineering, Univ of Toronto, 35 St George St., Toronto, ON, Canada, M5S 1A4 E-mail: huim.zhu@mail.utoronto.ca Dept of Civil Engineering, Univ of Toronto, 35 St George St., Toronto, ON, Canada, M5S 1A4 E-mail: jenn.drake@mail.utoronto.ca Dept of Civil Engineering, Univ of Toronto, 35 St George St., Toronto, ON, Canada, M5S 1A4 E-mail: kirti.sehgal@mail.utoronto.ca ABSTRACT To investigate the possibility of reducing winter road salting using permeable pavement, the University of Toronto, partnering with the Ontario Ministry of Transportation and the City of St Catharines, is currently conducting a winter performance assessment study of a heavily used permeable pavement parking lot located in St Catharines, Ontario The purpose of this two-year study is to evaluate the winter pavement performance and verify the safety and environmental benefits of permeable pavements by comparing them to a conventional asphalt pavement Throughout the 2015/2016 winter, skid resistance measurements were collected following winter maintenance to identify the risk of slips and falls on permeable pavements Conductivity levels in winter outflows have been continuously monitored in order to examine the environmental impacts of the permeable pavement on winter stormwater quality INTRODUCTION Permeable pavements are a commonly used Low Impact Development (LID) practice Permeable pavements allow for the storage of stormwater within an underlying reservoir supporting a more naturalized water balance and flow regime through infiltration and stormwater attenuation (TRCA and CVC, 2010) It has been suggested that snow and ice may melt faster on permeable pavements than traditional pavements, because larger void space and higher moisture level in permeable pavements during winter times (Labens et al., 2012) From the environmental perspective, the opportunity to reduce application rates of road salting for permeable pavements without compromising pedestrian safety will have far-reaching implications for the management and protection of our water resources in cold climates Previous studies have observed the influence of permeable pavement on chloride attenuation (Drake et al., 2014, Borst et al., 2014), however, continuous monitoring of the release of chloride from permeable systems has not yet been conducted Researchers Chang (2009) and Abyaneh (2005) have summarized that a linear relationship between conductivity and chloride concentration in stormwater can be developed based on collected stormwater sample on-site Therefore, the chloride concentration in each pavement outflow can be represented by the measured conductivity levels throughout the winter While permeable pavements may require less application of road salting than traditional pavements, property owners must prioritize the risks of slips and falls on the pavement surfaces, and thus, are reluctant to reduce the application rates of road salting Therefore, further investigation is needed to determine if the risk of slips and falls on a permeable surface are equivalent, or less than conventional asphalt pavements under a range of winter conditions Skid resistance describes the impact of roughness of a pavement surface on friction resistance It is © ASCE 173 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 different from the concept of friction, which is influenced by a large amount of factors directly or indirectly relating to road surface Different types of friction testers can measure the coefficient of friction (COF), which is defined as the ratio of the load to the resistance force against the movement in the horizontal direction COF values can be used to represent the skid resistance level on the surface, and relate to risks of slips and falls Usually, a lower COF values indicates lesser resistance to sliding or high slips on the pavement surface Kamal (2014) summarized the relationship between risk of slipping and COF values on winter pavement surfaces: for the group lower slipping risks, the mean COF is 0.57; for the group with higher slipping risks, the mean COF is 0.22 This paper presents the event-based skid resistance measurement results collected throughout 2015/2016 winter to evaluate the safety benefits of permeable pavements, as compared to conventional asphalt Also, continuous conductivity data measured from January 18th to April 26th will be presented to assess the water quality of runoff and permeable pavement outflow METHODOLOGY Site Description: The study site is located at the Lake Street Service Centre (LSSC) in St Catharines, Ontario (Figure 1) The parking lot provides 156 parking spots and is owned by the City of St Catharines The parking lot receives light vehicles and occasionally heavy-duty vehicles Shown in Figure 2, the parking lot consists of four different types of pavements, including conventional asphalt (ASH), Eco-OptilocTM Permeable Interlocking Concrete Pavement (PICP), HydromediaTM Pervious Concrete (PC), and Porous Asphalt (PA) This study focuses exclusively on poured pavement surfaces (ASH, PC and PA) Figure LSSC Parking Lot Overview (Photo Source: Google Map, 2015) © ASCE 174 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 Figure Plan View of LSSC Parking Lot (Crookes, 2015) The cross-sectional structures of three different types of pavements are shown in Figure At the center of each pavement cell, a 100 mm perforated drain pipe is placed at the bottom of clearstone sub-base and leads to a sampling catch basin north-east to the cell An impermeable geotextile liner is placed at the bottom of the clear-stone sub-base to prevent water exfiltration into subgrade soil, and between each pavement cell to prevent water migration between cells The installation of the impermeable liner creates a zero-exfiltration permeable pavement system, where all the water that infiltrates into clear-stone sub-base eventually drains into the sampling catch basins through the perforated pipes Figure Cross-Section View of PA, PC and ASH Cell (From left to right) (Upper Canada Consultants et al., 2011) The winter climate in St Catharines is relatively warm and humid as compared to other Ontario regions The average temperature from January to March is -1.86 °C, with an monthly average snow depth of cm (Environment Canada, 2015) The parking lot receives road salting and plowing as standard winter operating practice A calibrated salt spreader truck operated by city staff applied road salt during maintenance Skid Resistance Measurement: Skid resistance measurements were carried out using an ASFT T2GOTM Friction Tester ASFT T2GOTM is a friction-measuring device that measures the dynamic friction force for a continuous braked wheel The COF, measured at a constant speed of 0.6 ± 0.1 m/s, is equal to the ratio of the horizontal slip resistance force (i.e the dynamic friction force, FD) to the ground reaction force (FN) at the point of contact of the test wheel (Figure 4) © ASCE 175 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved International Low Impact Development Conference 2016 Figure Schematic Diagram of ASFT T2GOTM Portable Friction Tester The 2015/2016 winter was exceptionally mild and significant snowfall did not occur until February Skid resistance measurements were collected on six different measuring days under a range of different winter conditions including dry/wet, slushy and heavy snow covered surface During each skid resistance measurement, the following steps were completed: Visual observations and approximate snow depth were recorded T2GO measuring wheel was cleaned with cloth towel before each run For each run, T2GO measurements were collected from one end of the parking lot to the other covering a total testing length of 128 m Testing length for each pavement cell was 32 m A video camera attached on the T2GO handle recorded the COF readings displayed on the computer screen On February 10th, 2016, the total snow depth was observed to be 1-2 cm Road salt was applied as a standard winter maintenance practice, and a series of skid resistance measurements were taken at 20-minute intervals subsequently Another set of skid resistance measurements were also taken hours following maintenance, when substantial amount of snow had melted Data analysis and box plot in this paper are completed using the statistical software R (R Core Team, Version 3.2.3, 2015) Figure Conductivity Level Measuring Equipment in Sampling Catch Basin Conductivity Level Monitoring: The sampling catch basins of the PC and PA cells were equipped with a sharp crested V-notch weir box In the middle of the weir box, a water level logger and conductivity meter (AquiStar® CT2X Conductivity Smart Sensor) measured the water pressure and conductivity level every 15 minute starting from January 18th, 2016 © ASCE 176 International Low Impact Development Conference 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved (Figure 5) The precipitation data was obtained from a weather station located in Brock University, St Catharines, approximately km south to the study site The station provides daily total precipitation data and snow depth data According to the salting protocol of the LSSC maintenance service team, the parking lot surface is plowed and salted when there is snow accumulation of cm or larger RESULT AND ANALYSIS Skid Resistance Measurements: Figure presents the restoration of surface friction following salting summarized with box plots of the pavement COF before and after maintenance on Feb 10th, 2016 Figure Skid Resistance Level Change Before/After Salting (Feb 10th, 2016) Skid resistance levels on PA and PC are significantly lower than ASH surface 20 min, 40 and 60 after salting (p-value < 0.05, Table 1) According to accessibility standards, the required COF value for leveled surfaces designed for pedestrians is 0.5 (Advisory Committee on Accessibility, 2009) The median COF value of ASH surface exceeded required skid resistance level 40 after salting, while the median COF for PC exceeded at 60 after salting PA did not reach this recommended guideline within 60 COF values measured on a winter road condition are affected by two major factors: the thickness of snow layer and the pavement surface roughness (Hall et al., 2009) Thicker snow layer may lead to a greater reduction in the measured COF values if the snow is well compacted (Kamal et al., 2014) On Feb 10th, the snow covered on the parking lot surface were loose and un-bonded, with a depth of only 1~2 cm Therefore, the influence of snow depth is marginal Increasing surface roughness results in a high measured COF values A large presence of salt granules was observed on the ASH surface, which is likely to provide extra roughness on the surface Conversely, on the PA and PC surfaces, some of the salt granules become embedded into near-surface voids providing less additional roughness When salt granules are sitting on top of the surface, the operator of the T2GOTM has to impose an extra force to maintain a constant © ASCE 177 International Low Impact Development Conference 2016 Downloaded from ascelibrary.org by RMIT UNIVERSITY LIBRARY on 01/03/19 Copyright ASCE For personal use only; all rights reserved speed to overcome the gritty surface, and the additional exerted force may be falsely interpreted as an increase in the COF values measured (Bergstrom et al., 2003) As a result, the measured COF values on ASH is higher However, these data may not be a good representation of the real slip and fall risks, as pedestrians are unlikely to add additional forces when walking on such a surface Table Pairwise T-Test Results for Pavement Skid Resistance Comparisons (Feb 10th, 2016) Time Pavement Standard PRange Mean Median Significance Period Type Deviation value ASH 0.15-0.26 0.21 0.21 0.026 Before PC 0.14-0.22 0.17 0.16 0.017