biological and environmental engineering soil & water research group re-conceptualizing swat for...

Biological and Environmental Engineering

Soil & Water Research Group

Re-conceptualizing SWAT for Variable Source Area Hydrology

Zachary Easton1*, Daniel Fuka1, Todd Walter1, Dillon Cowan2, Elliot Schneiderman3, Tammo Steenhuis1

1Dept. Biological and Environmental Engineering, Cornell University2School of Civil and Environmental Engineering, Cornell University

3New York City Dept. Environmental Protection, Kingston, NY*[email protected]



Re-conceptualizing SWAT

• Variable Source Area (VSA) Hydrology• Curve Number and VSA hydrology• Convincing SWAT it recognizes VSAs



Rain

Infiltration

“Runoff”

Common Perception of Runoff

Infiltration Excessa.k.a. Hortonian Flow (Horton 1933, 1940)



NewNew YorkYork

March

AprilM

ayJu

ne

July

August

September

October

November

1 10 100

20

0

30

50

40

70

60

80

100

90

10

Return Period (yr)

% o

f Are

a G

ener

ating

Hor

toni

an F

low

Is Hortonian Flow Common?

Walter et al. 2003. ASCE J. Hydrol. Eng. 8: 214-218



Rain

Subsurfacewaterrises

Some areas saturate to the surface

Saturation Excess Runoff



Rain

Rain on saturated areas becomes overland flow

Upland interflow may exfiltrate

Dunne and Black. 1970. Water Resour. Res. 6: 478-490Dunne and Black. 1970. Water Resour. Res. 6: 1296-1311

Saturation Excess Runoff



Variable Source Areas

Current Water Quality Models were not Intended to Capture this Complexity•General Watershed Loading Function (GWLF)•Soil Water Assessment Tool (SWAT)•Agricultural Nonpoint Source Pollution Model (AGNPS)

Flow Path



USDA-NRCS Curve Number Model

“Runoff”=Pe2/(Pe+S)

S=25400/CN-254

Tables link CN to land use andsoil infiltration capacity



Curve Numbering VSA hydrologyQ = Pe

2/(Pe+S)Watershed

UnsaturatedSaturated

AfQ

P

Steenhuis et al. 1995. ASCE Div Drain. & Irr. 121:234-238

Q = AfPe

dQ/dPe = Af

Af = f(S,Pe)



We know how much area is contributing…

…but from where in the landscape?

Af = f(S,Pe)



High : 33.103500

Low : 3.520011

Soil Topographic Index

33.10

3.52

Soil Topographic IndexWetness Index Classes

10=f(S)

=f(S)

=f(S)=f(S)

=f(S)

=f(S)

=f(S) =f(S)

f(S)

=f(S)

Easton et al., 2008. J. Hydrol. 348: 279-291.Lyon et al. 2004. Hydrol. Proc. 18(15): 2757-2771.Schneiderman et al. 2007. Hydrol. Proc. 21: 3420-3430.

Wetness IndexClasses

ilocal storage



Soils Landuse

HRUs

Revisit the HRU concept• Define HRUs as the

coincidence of soil type and landuse• Hydrological/chemical

properties are defined at the HRU

• So runoff/P loss is the same here (lowland pasture)

• As here (upland pasture)• Is this a good assumption?



LanduseSTI

HRUs

SSURGO

• VSA concept defines HRUs as the coincidence of soil topographic index and landuse

• So runoff/P loss is now not the same here (lowland pasture)

• As here (upland pasture)• Better Assumption?



Distributing CN-values

0102030405060708090

100

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

CN

or

Sto

rage

Fractional Contributing Area

Local Storage

CN

Wetness IndexClasses

• Average of Standard CNs = 73.1 distributed according to landuse/soils

• Average of VSA CNs = 73.1, distributed according to a wetness index



050

100150200250300350400

Jan-99 Mar-99 May-99 Jul-99 Sep-99 Nov-99

So

il W

ater

(mm

)• High runoff prone area = high moisture content (in general)• We relate local soil water storage, e,i, to AWC with the following:

ρb = soil bulk density (g cm-3) clay = soil clay content (cm3 cm-3).

Modify the Available Water Content

5.24

254

100

4.05.0

65.21

,ie

bb clayAWC

Wetness Class 10

Wetness Class 2

Wetness Class 9

Wetness Class 1



0

2

4

6

8

10

12

14

16

Oct-98 Mar-99 Aug-99 Jan-00 Jun-00 Nov-00 Apr-01 Sep-01 Feb-02 Jul-02 Dec-02 May-03 Oct-03 Mar-04 Aug-04

Str

ea

mfl

ow

(c

m)

Measured

SWAT-VSA

0

2

4

6

8

10

12

14

16

Oct-98 Mar-99 Aug-99 Jan-00 Jun-00 Nov-00 Apr-01 Sep-01 Feb-02 Jul-02 Dec-02 May-03 Oct-03 Mar-04 Aug-04

Str

ea

mfl

ow

(c

m)

Measured

SWAT

r2 = 0.76

E = 0.82

r2 = 0.74E = 0.83

0

15

0 15Measured

SW

AT

0

15

0 15Measured

SW

AT

Test Results: Streamflow

-Standard



0

500

1000

1500

2000

2500

3000

3500

1996 1998 2000 2002 2004

Cu

mu

lati

ve

Ru

no

ff (

mm

)

10

1

WetnessIndex

6

0

500

1000

1500

2000

2500

1996 1998 2000 2002 2004C

um

ula

tiv

e R

un

off

(m

m)

a b

SWAT-VSA SWAT-Standard

Test Results: Runoff from Pastures

Easton et al., 2008. J. Hydrol. 348: 279-291



swat_hrus

SURQ [mm]

1.978 - 4.014

4.014 - 4.440

4.440 - 4.783

4.783 - 5.214

5.214 - 5.75

swat_vsa_hrus

SURQ [mm]

0 - 0.939

0.939 - 2.201

2.201 - 4.532

4.532- 8.868

8.868- 10.213

SWAT-VSA Runoff (mm)

SWAT Runoff (mm)

0-0.93 0.93-2.20 2.20-4.53 4.53-8.86 8.86-10.21

0.66-0.93 0.93-2.20 2.20-4.53 4.53-8.86 8.86-10.21

a b

Test Results: Runoff





SW_END [mm]

93 - 163

163 - 242

242 - 277

277 - 298

298 - 317

SW_END [mm]

65 - 99

99 -139

139 - 196

196 - 245

245 - 304

SWAT Soil Water (mm)

SWAT-VSA Soil Water (mm)

93-163 163-242 242-277 277-298 298-317

93-163 163-242 242-277 277-298 298-317

a b

Test Results: Soil water





1m Cont.

585 m

600 m

WaterLevelLoggers

0 100 mNTest Results: Soil Water

Data curtsey of :Lyon et al. 2006. Adv. Water Resour. 29(2): 181-193.

Lyon et al. 2006. HESS. 10: 113-125.Wetness Index Classes

10

1



SWAT-VSA

Movie courtesy of Dr. Steve Lyon



R2 = 0.57

500

700

900

1100

1300

1500

500 700 900 1100 1300 1500Measured Water Table (mm)

SW

AT

Wat

er T

able

(m

m)

Mixed ForestPastureShrub

R2 = 0.79

700

900

1100

1300

1500

700 900 1100 1300 1500Measured Water Table (mm)

SW

AT

-VS

A W

ate

r T

ab

le (

mm

)

1098765

a b

Index

Test Results: Soil water




0

50

100

150

200

250

300

Oct-98 Apr-99 Oct-99 Apr-00 Oct-00 Apr-01 Oct-01 Apr-02 Oct-02 Apr-03 Oct-03 Apr-04

Dis

solv

ed

P (

kg)

Measured

SWAT-VSA

0

50

100

150

200

250

Oct-98 Apr-99 Oct-99 Apr-00 Oct-00 Apr-01 Oct-01 Apr-02 Oct-02 Apr-03 Oct-03 Apr-04

Dis

solv

ed P

(kg)

Measured

SWAT

r2 = 0.76E = 0.71

r2 = 0.68E = 0.47

a

b

0

300

0 300Measured

SW

AT0

300

0 300MeasuredS

WA

T

Test Results: Phosphorus

-Standard



swat_hrus

ORGP KG/HA

0 - 0.076

0.076 - 0.154

0.154 - 0.189

0.189 - 0.225

0.225 - 0.287

swat_vsa_hrus

ORGP KG/HA

0 - 0.044

0.044 - 0.088

0.088 - 0.223

0.223 - 0.694

0.694 - 0.99

SWAT-VSA Dissolved P (kg ha-1)

SWAT Dissolved P (kg ha-1)

0-0.04 0.04-0.09 0.09-0.22 0.22-0.69 0.69-0.99

0-0.04 0.04-0.09 0.09-0.22 0.22-0.69 0.69-0.99

a b

Test Results: PhosphorusSWAT-VSA SWAT-Standard



Take-home Messages• Storm runoff is generated from small parts of the

landscape• Areas prone to saturate – e.g., toe slopes, shallow soils,

topographically converging areas• Variable Source Areas – they expand and contract

• We can predict where and when storm runoff will be generated

• We can improve integrated and distributed predictions by considering VSAs• Implications for watershed management



Curve Numbering VSA hydrologyQ = Pe

2/(Pe+S)Watershed

UnsaturatedSaturated

AfQ

P

Steenhuis et al. 1995. ASCE Div Drain. & Irr. 121:234-238

Af = f(S,Pe)

Af = dQ/dPe

Af = 1-(S2/(Pe+S)2

As = 1-(S2/(σe+S)2

σe=S(√(1/(1-As))-1

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