Application of the SWAT Hydrologic Model for Urban Stormwater Management

Jaehak Jeong, PhD, PE Assistant Professor

Texas A&M AgriLife Research Texas A&M University

UT Arlington, June 5th, 2015

Roger Glick, PhD Manager

Watershed Protection Department City of Austin

Urbanization and Hydrology

Increase in impervious cover promotes higher runoff and lower infiltration

Stream flow gets flashy Urban Non-Point Sources

(Roesner et al., 2001)

Why SWAT for Urban Modeling?

Fully supported open source 30+ years expertise in hydrologic and water

quality modeling (>1,600 journal papers) Widely used for TMDLs, water rights, climate

change, etc. Simulates landscape managements Works for small scale (~50acres) as well as large

scale (>300,000ac) GIS Interface

Urban Stormwater Simulation

Urban BMPs

Green Infrastructure

Subdaily model

SWAT modules for sub-hourly simulation

Overland flow, stream flow, ponds, reservoirs, and point sources

Soil erosion and sediment transport

Sedimentation-Filtration basin

Retention-Irrigation basin

Detention pond

Wet pond

Green roof

Rain garden

Cistern

Porous pavement

Case study: Jollyville Sand Filter

Jollyville Sand filter in Austin, TX USA

Drainage area = 2.8ha 100% urban, 90%

impervious cover Roads: 84% Commercial: 11% Offices: 5%

High res. DEM (1ft x 1ft) Sandfilter is located at the

outlet of the catchment

Sand filter

Flow direction

Flow direction

Jollyville Sand Filter Outlet weir

Forebay/Filter area divider

Inlet weir

Rainfall (1997-1999) on IDF Curve

0

50

100

150

200

250

300

350

10 100 1000 10000

Rain

fall

dept

h, m

m

Rainfall duration, min

100-year 50-year

25-year 10-year

5-year 2-year

JV1997 JV1998

JV1999

1997 - 1,100mm 1998 - 950mm 1999 - 401mm

(Jeong et al., 2013)

Long-term Performance Analysis 15min flow & TSS

calibrated for 3 years (1997-1999)

Inflow: R2=0.83 Outflow: R2=0.84 TSS: R2=0.21

(Jeong et al., 2013)

Short-term Performance

Two storm events in April 1999

Only 40% of the runoff was treated and 60% bypassed the sand filter

No significant First-Flush effect found on this particular storm event.

R2=0.93 NSE=0.9

R2=0.21 NSE=0.03

LID Simulation Strategies

Impervious Cover

Rain Garden HRU Water Yield

Cistern Green Roof

Porous Pavement

Pervious Cover

% runoff to treat No treatment + RG bypass

Urban HRU

LID Discharge Estimation

Green Roof: excess rainfall + seepage Rain Garden: bypass flow + orifice discharge Cistern: bypass flow Porous Pavement: bypass flow + lateral drainage

Brentwood Watershed

Brentwood WS Austin, TX 149.8 ha Highly urbanized

(~99%) SWAT City of Austin Great details 137 subbasins (1.1

ha/sub) 1212 HRUs (0.12

ha/hru)

Runoff Calibration

Period NSE R2

15-min Daily Monthly 15-min Daily Monthly

Calibration 0.88 0.91 0.91 0.89 0.91 0.94

Validation 0.71 0.84 0.73 0.71 0.86 0.89

0

50

100

150

Mar

-12

May

-12

Jul-1

2

Sep-

12

Nov

-12

Jan-

13

Mar

-13

May

-13

Jul-1

3

Sep-

13

Nov

-13

Jan-

14

Mar

-14

May

-14

Jul-1

4

Sep-

14

Nov

-14

Mon

thly

Run

off

(m3 /

s)

ObservedSimulated

‘Good’ performance Calibrated at various temporal scales

Scenario Analysis

As LID adoption rate increases: Surface runoff decreases ET increases

GR

10 15 25 50 5% 100

RG CS PP

Scenario Analysis Flow at the outlet

GR RG

CS PP

Field Scale Validation Green Roof

Porous Pavement Multi-year field data collected at Urban Solutions Center,

Dallas, TX (Dr. Jaber)

Lady Bird Johnson Wildflower Center (U of Texas, Austin) & City of Austin

Utilize New SWAT BMP Capabilities to Assess Flows and Impacts on Aquatic Life

Determine methods for areas with primarily confined flow

Infrastructure in Urban Areas

Related Articles

J. Jeong, N. Kannan, J. Arnold, R. Glick, L. Gosselink, R. Srinivasan, and M. E. Barrett (2013) “Modeling Sedimentation-Filtration Basins for Urban Watersheds in SWAT.” ASCE J. Environ. Eng. 139(6): 838-848

J. Jeong, N. Kannan, J. G. Arnold (2014) “Effects of Urbanization and Climate Change on Stream Health in North-Central Texas” J. Environ. Qual., 43:100-109, doi: 10.2134/jeq2011.0345

C. Furl, H. Sharif, J. Jeong (2015) “Analysis and Simulation of Large Erosion Events at Central Texas Unit Source Watersheds” Journal of Hydrology, 527: 494-504

J. Jeong, J. Williams, W. Merkel, J. Arnold, X. Wang, C. G. Rossi (2014) “Flood Routing for watershed simulations models considering the effect of water surface gradient”, Trans. ASABE, 57(3): 791-801

N. Kannan, J. Jeong, J.G. Arnold, L. Gosselink, R. Glick, and R. Srinivasan, (2014). "Hydrologic Modeling of Retention Irrigation System." J. Hydrol. Eng., 19(5), 1036–1041.

J. Jeong, N. Kannan, J. Arnold, R. Glick, L. Gosselink, R. Srinivasan, and D. Harmel (2011) “Development of Subdaily Erosion and Sediment Transport Models in SWAT” Trans. ASABE 54(5): 1685-1691

J. Jeong, N. Kannan, J. Arnold, R. Glick, L. Gosselink, R. Srinivasan (2010). “Development and integration of sub-hourly rainfall-runoff modeling capability in a watershed model” Water Resources Management, 24(15): 4505-4527

W. F. Hunt, N. Kannan, J. Jeong, and P. W. Gassman (2009). “Stormwater Best Management Practices: Review of Current Practices and Potential Incorporation in SWAT”, International Agricultural Engineering Journal, 18(1-2): 73-89.