Other Perspectives on Research on LID Performance Enhancement

Transcription

1 Other Perspectives on Research on LID Performance Enhancement

2 Welcome to the Webcast To Ask a Question Submit your question in the chat box located to the left of the slides. We will answer as many as possible during Q&A. To Answer a Poll Question Simply select the preferred option. For those viewing this session alongside several colleagues, respond in a manner that represents your organization as a whole. We ARE Recording this Session All comments and questions will be recorded and included in the archives. We will notify you as soon as the recording and related resources are loaded on the web. We Appreciate Your Feedback Fill out our evaluations our funders need to hear it!

3 Chesapeake Bay Stormwater Training Partnership To learn how you can have access to: FREE Webcasts Free 1-day design, inspection & maintenance workshops Intensive master stormwater seminars Direct On-site technical assistance Self guided web-based learning modules Visit:

4 Going on winter break! See you next year! Check back soon for our DRAFT 2017 webcast schedule!

5 2017 To recognize the best BMPs that have been installed in the Chesapeake Bay Watershed Register your project here:

6 Poll Question #1 How many people are watching with you today? Just me 2-5 people 6-10 people > 10 people

7 Poll Question #2 Tell us a little about yourselves who are you representing today? Local government Private sector Regulatory agency Non-profit Academia Other tell us in the chat box

8 Poll Question #3 Did you see the first webcast on PEDs? Yes No

9 Poll Question #4 What is your exposure to this topic? I m just here for the free webcast. I have only seen the first webcast. I have read numerous articles on the subject. I am currently designing/implementing BMPs with PEDs. I am currently doing addition research on PEDs.

10 Speaker Info Allen P. Davis University of Maryland Ryan Winston Ohio State University Bryan Seipp Center for Watershed Protection Tom Schuyler Chesapeake Stormwater Network

11 Project Overview Synthesis of research on performance enhancing devices and/or media (PEDs) for urban stormwater management Evaluate the water quality benefits of PEDs with urban stormwater BMPs Develop design specifications for the addition of PEDs in BMPs Develop guidance for contractors to construct BMPs with PEDs Provide recommendations on nutrient and sediment removal efficiencies and cost-effectiveness of BMPs with PEDs

12 Design Modifications Alternative media layers (e.g., iron filings, activated carbon, wastewater treatment residuals, activated carbon, biochar, wood chips, fly-ash) Internal design configurations that promote denitrification (e.g., upturned elbows, carbon seeding, anaerobic layers, subsurface ponding, biofilms, controlled subsurface releases) LID treatment train combinations (e.g., bioretention to submerged gravel wetlands), and Plant species to maximize nutrient uptake and/or evapotranspiration rates.

13 Removal Efficiency (%) Focus of PEDs Research: Improved Performance for Particulate & Dissolved Forms 150 Bioretention Removal Efficiencies TSS TP Sol P TN NOx Cu Zn Bacteria

14 PEDs for N and P in Stormwater Allen P. Davis Charles A. Irish Sr. Chair in Civil Engineering Department of Civil and Environmental Engineering University of Maryland College Park, MD December 2016

15 Sources of N & P Natural & Anthropogenic

16

17 P fate in Bioretention Runoff (TP) OM (Mulch / Compost / Peat / Plant Residue) Plant Uptake PP Captured PP DOP DP SRP Uncaptured PP Adsorbed DP Precipitated DP Output PED Focus for P Li & Davis, Water Research, 2016

18 P Sorption - Strong on Iron & Aluminum Oxides O Al OH O Al O P R Fe OH + 2 R O P O - O - Fe O O - O P R + 2 OH - Leach O - Organic Matter Top Soil Sandy Soil Site Soil Compost Mulch Peat Sand

19 The P* Model P P P P P Clays Oxides P P P P* Leaf Litter PP Compost Mulch

20 Field Studies Li & Davis, Water Research, 2016

21 WTR Bioretention Retrofit Mulch 15 tons WTR (wet weight) are mixed with top 40 cm depth of the soil Bioretention Soil Medium Underdrain Pipe Liu and Davis, Environ. Sci. Technol. 2014

22 P Concentration (mg P/L) Mass of P (kg/ha year) Pollutant Mass Load Reduction P concentration comparison PP SRP DOP P Mass Load Reduction PP SRP DOP Concentration in (mg P/L) Concentration out (mg P/L) Mass in (kg/ha year) Mass out (kg/ha year) Liu & Davis, Environ. Sci. Technol. 2014

23 Continued Enhancements: Yan, James, Davis, J. Environ. Engg 2016

24 P Sorbed (mg P/kg) Oxalate-Extraction BSM + Alum BSM + WTR + Alum IHP 1500 BSM + WTR R 2 = BSM R 2 =0.84 R 2 =0.99 SRP AMP Oxalate Ratio: (Al + Fe) ox : P ox Yan, James, Davis, J. Environ. Engg 2016

25 Conclusions Media selection is critical for P removal in bioretention systems, compost can leach P; Media with high amorphous Al & Fe content reduces P; WTR- and alum-modified BSM exhibit high sorption capacity for both inorganic and organic P; High flow media (HFM) can be modified with WTR and alum, to provide high runoff infiltration and improved P removal.

26 Nitrogen Nitrogen composition and dynamics in stormwater are complex Putting the Bio in Bioretention

27 Nitrogen Speciation Particulate N PON PIN Total N Dissolved N Organic N Inorganic N NH 3 -N NO x -N Particulate Organic Nitrogen 0.93 mg N/L (57%) Dissolved Organic Nitrogen NO mg N/L (15%) 0.28 mg N/L (17%) NO 2 - NH mg N/L (9%) 0.02 mg N/L (1%) Li & Davis, Environ. Sci. Technol. 2014

28 N behavior and fate in Bioretention Changes in N Species, but not significant removal (only by volume reduction N to groundwater ) Li & Davis, Environ. Sci. Technol. 2014

29 Standard Bioretention PON DON NO3 NH4 DENITRIFICATION PB DON MINERALIZATION N2 AMMONIFICATION NITRIFICATION NO3 NO3 No Mechanism for N removal in Standard Bioretention Design

30 Creating a Comprehensive N Removal Treatment Total Runoff N EASY Particulate N Step 1 Organic N NH 3 -N NO 3 -N Filter Particulate Nitrogen. Over time it will decompose to Organic N HARD MODERATE Organic N NH 3 -N NO 3 -N Step 2 Step 3 Adsorb Organic N and Bioconversion to Ammonia-N Ammonia-N NO 3 -N Adsorb Ammonia-N and Nitrification to Nitrate-N HARD Step 4 NO 3 -N Denitrification to Remove all N All N Removed

31 1. Adsorption of Organic N Mohtadi, James, & Davis, Water Environ. Res. 2016

32 2. Adsorption of Ammonium Clinoptilolite Zeolite Khorsha & Davis, Water Environ. Res. In revision

33 3. Denitrification Wood Chips as C source for Denitrification Peterson, Igielski & Davis, J. Sustainable Water Built Environ. 2016

34 3. Denitrification Igeilski, Kjellerup & Davis, In preparation

35 PON DON N Bioretention NO3 NH4 DON MINERALIZATION DENITRIFICATION N2 NH4 AMMONIFICATION NH4 ACTIVATED CARBON NITRIFICATION NO3 NO3 NO3 ZEOLITE N 2 N2 N2 DENITRIFICATION N2 WOOD CHIPS & PEA GRAVEL

36 N Summary Nitrogen composition and dynamics in stormwater is complex No Mechanism for N removal in Standard Bioretention Design Compost and Bioretention Appear to be a bad mix when discussing Nitrogen Substantial N Removal in Bioretention will require a layered, treatment train approach and may be limited by time/storage volume Subsurface wetlands may be the best BMP for N removal

37 Next Steps 2 NFWF Grants to get these into field Prince George s County & Low Impact Development Center Enhanced P Enhanced N Rigorously monitor Media development for P and N removal beneath Pervious pavement

38 PEDs for Stormwater Control Measures: Nitrogen & Phosphorus Ryan Winston, PhD, P.E. Research Scientist Department of Food, Agricultural, and Biological Engineering Chesapeake Bay Webinar 8 December 2016

39 Food, Agricultural, and Biological Engineering Effects of Urban Development on Pollutant Loading (Line and White, 2007) Pollutant Export Rate (kg/ha/yr) TN TP TSS Undeveloped Developed

40 Sediment Loading Increased Pollutant Load: Impacts use of surface waters and aquatic biota

41 Food, Agricultural, and Biological Engineering Excess Nutrients Cause algal blooms and eutrophication Photo Credit: ESA Closed Toledo s water supply for 3 days in 2014

42 Food, Agricultural, and Biological Engineering How Can We Control Nutrients? Two methods to control: Reduce nutrient sources or transport Reduce runoff volume

43 Food, Agricultural, and Biological Engineering Bioretention Typical Cross-Section Standard design in NC and OH

44 Water Quality Food, Agricultural, and Biological Engineering

45 Food, Agricultural, and Biological Engineering DOT Bioretention Cells Contributing drainage area: Large Cell SA: 2020 ft 2 Captured 1 in rain event Small Cell SA: 1090 ft 2 Captured 0.3 in rain event 0.98 ac 100% impervious roadway Centipede grass sod Media 87% sand, 8% silt, 3% clay, 2% OM by volume

46 Concentration (mg/l) Food, Agricultural, and Biological Engineering Bioretention Cells EMC Reductions Average influent and effluent nutrient concentrations Significant nitrate reduction Bioretention Inlet Small Cell Outlet Large Cell Outlet Target TN Conc. Target TP Conc * * * * * * * TKN NO2,3-N TN NH4-N TP Luell et al. (2011). Water Science and Technology Irreducible Concentrations?

47 Food, Agricultural, and Biological Engineering Bioretention with IWS zones North Cell: 18 IWS South Cell: 30 IWS Low OM media 3-5% by volume Pine bark fines Pollutant In N S TN NO TP OP Denitrification? Passeport et al. (2009). J. Irrig. Drain. Eng.

48 Food, Agricultural, and Biological Engineering Ursuline College Bioretention Cell Characteristics UC Catchment area 0.89 acres Imperviousness 77% Bioretention surface area 1960 ft 2 Media characteristics Vegetation 87% sand, 4% silt, 9% clay Forbs & perennial grasses 77% Impervious 5% of watershed area Implemented 24 inches of IWS

49 Food, Agricultural, and Biological Engineering Water Quality Performance 1.01 mg/l 1.88 mg/l 0.04 mg/l 0.07 mg/l 49 mg/l 16 mg/l -85% reduction -50% reduction 68% reduction 20-40% reduction 40-60% reduction 60-90% reduction

50 Tea.co.uk Food, Agricultural, and Biological Engineering What is the Culprit? Soil media mix controls performance Organic Matter: 8-20% by volume (compost) OH 3-5% by volume (pine bark) - NC 10% by volume (compost) - MN Mehlich III P content: mg/kg - OH mg/kg - NC mg/kg MN Ursuline P content 97 mg/kg NC Mix OH Mix

51 Runoff Reduction Food, Agricultural, and Biological Engineering

52 HA North HA South Food, Agricultural, and Biological Engineering Holden Arboretum (HA) cells Characteristics HA South HA North Catchment area 0.48 acres 0.67 acres Imperviousness 58% Bioretention surface area 610 ft ft 2 Media characteristics 88% sand, 2% silt, 10% clay Vegetation Forbs and perennial grasses Shrubs/trees

53 Food, Agricultural, and Biological Engineering Ursuline College Bioretention Cell Characteristics UC Catchment area 0.89 acres Imperviousness 77% Bioretention surface area 1960 ft 2 Media characteristics Vegetation 87% sand, 4% silt, 9% clay Forbs & perennial grasses 77% Impervious 5% of watershed area Implemented 24 inches of IWS

54 Food, Agricultural, and Biological Engineering Internal Water Storage (IWS) Zone Ursuline: 24 in Holden N: 18 in Holden S: 15 in

55 Water Balance Summary Food, Agricultural, and Biological Engineering * Source: Brown et al. 2011

56 Food, Agricultural, and Biological Engineering Bioretention Modeling in DRAINMOD Concepts of water movement in BRCs are very similar to Ag. fields with drain tiles Most bioretention design specifications correspond directly to DRAINMOD inputs

57 Volume (in per BRC Area) Ursuline College: Overall Water Balance Measured vs. Modeled Measured Runoff Modeled Runoff Measured Drainage Modeled Drainage Measured Overflow Modeled Overflow Measured Exfiltration+ET Modeled Exfiltration+ET Food, Agricultural, and Biological Engineering

58 Food, Agricultural, and Biological Engineering Underlying Soil K sat Volume Reduction Supports locating most permeable soils on a development site

59 Food, Agricultural, and Biological Engineering Over/Under-Sized Bioretention Ohio design event =0.75 inches Catchment Area : Bioretention Area Ratio 10:1 15:1 Catchment 20:1 (base model) 35:1 50:1

60 Food, Agricultural, and Biological Engineering

61 Food, Agricultural, and Biological Engineering Internal Water Storage Modeled IWS zone depths of: 0 inches (i.e., bottom of practice) 6 inches 12 inches 15 inches 18 inches 24 inches

62 Food, Agricultural, and Biological Engineering

63 Food, Agricultural, and Biological Engineering Lessons Learned 3 biggest factors: underlying soil conductivity, loading ratio, presence of IWS Sensitivity of Model: Moderate: Bowl storage, media depth* mainly affect overflow Least: Rooting Depth *important when IWS depth also increases

64 Food, Agricultural, and Biological Engineering Retrofits to Other SCMs Improvements to other existing stormwater controls can and should be implemented 6 in.

65 Volume Reduction (%) 68% 156% 64% 99% 38% 65% 20% Food, Agricultural, and Biological Engineering 31% Permeable Pavement Modeling with IWS in/hr 0.02 in/hr 0.20 in/hr 0.50 in/hr Depth of Internal Water Storage (in)

66 Food, Agricultural, and Biological Engineering Retrofits to Other SCMs Floating Treatment Wetlands on Wet Ponds 9% coverage 18% coverage No significant benefits Winston et al. (2013). Ecological Engineering

67 Food, Agricultural, and Biological Engineering Retrofits to Other SCMs Upflow filter on drawdown orifice of pond Used Sorbtive Media AI Winston et al. (accepted). Journal of Environmental Engineering

68 Food, Agricultural, and Biological Engineering Crediting Each retrofit needs to be evaluated for effects on as a fxn(sizing): Pollutant concentration Runoff reduction New Curve?

69 Food, Agricultural, and Biological Engineering Food for Thought What if I implement IWS and a soil media enhancement as a retrofit? How do you credit multiple retrofits to one practice? Perhaps multiple RR curves are needed around particular SCM design features/underlying soil type

70 Food, Agricultural, and Biological Engineering Take Homes & Next Steps Employ Internal Water Storage Improves volume reduction ~20% Across all underlying soil types Site SCMs over most permeable soil Higher OM in BR media = nutrient export Looking at 1%, 3%, & 5% OM in field Source of OM also matters! Further modeling needed to quantify runoff reduction for other SCMs across a myriad of designs

71 Discussion and Q&A

72 Webcast Resources Performance Enhancing Devices for Stormwater Best Management Practices draft technical memo Webcast: The Potential to Enhance Nutrient Removal in Bioretention and Sand Filters

73 Evaluation Please take a few moments to answer our 6 question survey to help us better serve your needs in our webcast series. We use this information to report it to assess our work, your needs and to report it to our funders for future webcasts!