urban forestry and the clean water act

23
Urban Forestry and the Clean Water Act David J. Nowak USDA Forest Service, Northern Research Station Syracuse, NY

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Urban Forestry and the Clean Water Act. David J. Nowak USDA Forest Service, Northern Research Station Syracuse, NY. Outline. I-Tree Hydro Chesapeake analyses. i-Tree - Hydro. Management model designed to be relatively easy to use - PowerPoint PPT Presentation

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Page 1: Urban Forestry  and the Clean Water Act

Urban Forestry and the Clean Water Act

David J. Nowak

USDA Forest Service, Northern Research Station

Syracuse, NY

Page 2: Urban Forestry  and the Clean Water Act

Outline

• I-Tree Hydro• Chesapeake analyses

Page 3: Urban Forestry  and the Clean Water Act

i-Tree - Hydro• Management model designed to be

relatively easy to use• Object-oriented, physical based, semi-

distributed, topographic model• TOPMODEL theory is used to simulate

saturation excess overland flow (for forest area), base flow and ET process

• Warm weather, semi-distributed urban soil-vegetation-atmosphere transfer scheme (SVATS)

• C++ code with GIS inputs

Page 4: Urban Forestry  and the Clean Water Act

i-Tree Hydro Strengths

• Specifically designed to incorporate urban tree and impervious surface effects on stream flow and water quality

• Built to simulate the dynamic forest interception, infiltration and ET processes as well as urban impervious effect on runoff generation.

• Calibrated against measure stream flow data

• Relatively easy to use

Page 5: Urban Forestry  and the Clean Water Act

i-Tree Hydro Weaknesses

• Lacks capabilities of fully-distributed model

• Currently does not allow for specific locational designs of tree cover, impervious cover, or retention/detention ponds (operates on general cover types)

• Works on watershed basis (with gauging station)

Page 6: Urban Forestry  and the Clean Water Act

Model Inputs• Hourly discharge data (USGS)• Digital elevation map (USGS)• Hourly weather and evaporation data

• Evaporation data calculated from weather data

• Structural information on watershed (NCLD and i-Tree Eco (UFORE) data) e.g.,• Tree cover• Impervious cover• Shrub and grass cover• LAI

Page 7: Urban Forestry  and the Clean Water Act

Model Calculations• Topographic index with tree and impervious

cover• Interception routine• Canopy parameters (throughfall, storage

capacity, daily leaf and trunk area)• Depression storage (impervious)• Evaporation and transpiration from vegetation,

soil and water surfaces• Infiltration into soils• Subsurface, overland and impervious runoff

Page 8: Urban Forestry  and the Clean Water Act

Model Outputs

• For each time step (1 hour for these simulations):• Canopy interception• Depression storage• Infiltration• Evapotranspiration• Surface and subsurface (base flow)

runoff• Channel discharge (total runoff)

Page 9: Urban Forestry  and the Clean Water Act

Water Quality• Separate program with inputs from i-Tree

Hydro files• Multiple options that incorporate

universal soil loss equation; buildup wash off routines

• Currently only using EMC• Many other options need more input data

• Dissolved sediment / solid pollutant load• Septic load• Dissolved pollutant concentration

Page 10: Urban Forestry  and the Clean Water Act

Preliminary Model Results• Watersheds

• Accotink (Washington, DC)• Baisman Run (Baltimore, MD)• Gwynns Falls (Baltimore, MD)• Mill Creek (Lancaster, PA)• Rock Creek (Washington, DC)

Page 11: Urban Forestry  and the Clean Water Act
Page 12: Urban Forestry  and the Clean Water Act

Baisman Run

Watershed Area (m2) 3,844,800

Percent Impervious cover 0.2

Percent Tree Cover 68.7

Percent of Tree Cover over Impervious Area 5

Percent Water Cover 0

Average Tree Leaf Area Index (LAI) 3.5

Percent Shrub Cover 7.8

Percent Grass Cover 20

Percent Evergreen Trees 4.2

Percent Evergreen Shrubs 21

Shrub LAI 3.9

Leaf on Day 80

Leaf off Day 294

Page 13: Urban Forestry  and the Clean Water Act

Baisman Run

CRF1 = 0.56 CRF2 = 0.63CRF3 = 0.70

Red – Observed; Black - Modeled

Page 14: Urban Forestry  and the Clean Water Act

020

4060

8095

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

1,000,000

Runoff(m3/yr)

Tree Cover (%)

Impervious Cover (%)

Baisman Run

Page 15: Urban Forestry  and the Clean Water Act

Baisman Run

0.0

10.0

20.0

30.0

40.0

50.0

60.0

0 10 20 30 40 50 60 70 80 90 100

Percent Impervious Cover

Per

cent

Cha

nge

in A

nnua

l Str

eam

Flo

w

.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

0 10 20 30 40 50 60 70 80 90 100

Percent Tree Cover

Per

cent

Cha

nge

in A

nnua

l Str

eam

Flo

w

.

Impervious held at 10%Canopy held at 70%

Page 16: Urban Forestry  and the Clean Water Act

Watershed Area (m2) 61,910,100

Percent Impervious cover 21.3

Percent Tree Cover 31.9

Percent of Tree Cover over Impervious Area 10

Percent Water Cover 0.3

Average Tree Leaf Area Index (LAI) 3.5

Percent Shrub Cover 7.8

Percent Grass Cover 33.8

Percent Evergreen Trees 4.2

Percent Evergreen Shrubs 21

Shrub LAI 3.9

Leaf on Day 80

Leaf off Day 294

Accotink

Page 17: Urban Forestry  and the Clean Water Act

Accotink

CRF1 = 0.67 CRF2 = 0.56CRF3 = 0.74

Red – Observed; Black - Modeled

Page 18: Urban Forestry  and the Clean Water Act

100

80

60

40

200

020

4060

8095

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

30,000,000

35,000,000

40,000,000

45,000,000

50,000,000

Runoff

(m3/yr)

Tree Cover (%)

Impervious Cover (%)

Accotink

Page 19: Urban Forestry  and the Clean Water Act

Accotink – Storm Simulations2 year storm

10 year storm

50 year storm

Early In-Leaf Season

-50000

0

50000

100000

150000

Hour

m3/

hr

Trees

No Trees

Difference

Mid In-Leaf Season

-20000

0

20000

40000

60000

Hour

m3/

hr

Trees

No Trees

Difference

Late In-Leaf Season

-50000

0

50000

100000

150000

Hour

m3/

hr

Trees

No Trees

Difference

Early In-Leaf Season

-100000

0

100000

200000

300000

Hour

m3/

hr

Trees

No Trees

Difference

Mid In-Leaf Season

-50000

0

50000100000

150000

200000

Hour

m3/

hr

Trees

No Trees

Difference

Late In-Leaf Season

-100000

0

100000

200000

300000

Hour

m3/

hr

Trees

No Trees

Difference

Early In-Leaf Season

-100000

0100000

200000300000

400000

Hour

m3/

hr

Trees

No Trees

Difference

Mid In-Leaf Season

-100000

0

100000200000

300000

400000

Hour

m3/

hr

Trees

No Trees

Difference

Late In-Leaf Season

-100000

0

100000200000

300000

400000

Hourm

3/h

r

Trees

No Trees

Difference

Page 20: Urban Forestry  and the Clean Water Act

Water Quality Results (median national pooled EMC)

  Reduction (t/total hours)

WatershedTree

CanopyTotal %

reduction% per

% canopy TSS BOD COD TPSol P TKN

NO2NO3 Cu Pb Zn

Total hours

Accotink 31.9 3.7 0.1 40.3 8.5 33.0 0.19 0.08 1.1 0.39 8.2 37.5 95.4 8760

Baisman Run 68.7 12.1 0.2 4.5 1.0 3.7 0.02 0.01 0.1 0.04 0.9 4.2 10.7 6600

Gwynns Falls 27.0 3.3 0.1 44.9 9.5 36.8 0.21 0.08 1.2 0.44 9.1 41.7 106.2 8760

Mill Creek 7.1 1.6 0.2 12.3 2.6 10.1 0.06 0.02 0.3 0.12 2.5 11.4 29.1 4008

Rock Creek 27.0 5.2 0.2 136.8 28.9 112.2 0.65 0.26 3.7 1.34 27.9 127.3 323.9 8760

Page 21: Urban Forestry  and the Clean Water Act

Water Policies – Total Maximum Daily Load (TMDL)• over 40% of our assessed waters still do not meet the

water quality standards of the Clean Water Act• TMDL specifies the maximum amount of a pollutant

that a waterbody can receive and still meet water quality standards

• urban vegetation may help keeping urban waterways below TMDL limits

Page 22: Urban Forestry  and the Clean Water Act

On-Going Work

• Cross comparisons with Larry Band• 2005 and 2007 Pond Branch

• Other watersheds across US

Page 23: Urban Forestry  and the Clean Water Act

Questions?