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Re-conceptualizing SWAT for Variable Source Area Hydrology. Zachary Easton 1* , Daniel Fuka 1 , Todd Walter 1 , Dillon Cowan 2 , Elliot Schneiderman 3 , Tammo Steenhuis 1 1 Dept. Biological and Environmental Engineering, Cornell University

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Re conceptualizing swat for variable source area hydrology
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 University

2School of Civil and Environmental Engineering, Cornell University

3New York City Dept. Environmental Protection, Kingston, NY

*zme2@cornell.edu


Re conceptualizing swat
Re-conceptualizing SWAT

  • Variable Source Area (VSA) Hydrology

  • Curve Number and VSA hydrology

  • Convincing SWAT it recognizes VSAs


Common perception of runoff

Infiltration

“Runoff”

Common Perception of Runoff

Rain

Infiltration Excess

a.k.a. Hortonian Flow

(Horton 1933, 1940)


Re conceptualizing swat for variable source area hydrology

NewYork

100

90

80

June

70

60

May

September

July

50

% of Area Generating Hortonian Flow

40

August

30

20

October

April

10

November

0

March

1

10

100

Return Period (yr)

Is Hortonian Flow Common?

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


Saturation excess runoff

Rain

Subsurface

water

rises

Some areas saturate to the surface

Saturation Excess Runoff


Saturation excess runoff1

Rain

Upland interflow may exfiltrate

Saturation Excess Runoff

Rain on saturated areas becomes overland flow

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

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


Variable source areas

Flow Path

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)


Re conceptualizing swat1
Re-conceptualizing SWAT

  • Variable Source Area (VSA) Hydrology

  • Curve Number and VSA hydrology

  • Convincing SWAT it recognizes VSAs


Usda nrcs curve number model
USDA-NRCS Curve Number Model

“Runoff”=Pe2/(Pe+S)

S=25400/CN-254

Tables link CN to land use and

soil infiltration capacity


Curve numbering vsa hydrology
Curve Numbering VSA hydrology

P

Q = Pe2/(Pe+S)

Watershed

Q

Af

DQ = AfDPe

Unsaturated

Saturated

dQ/dPe = Af

Af = f(S,Pe)

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


We know how much area is contributing
We know how much area is contributing…

Af = f(S,Pe)

…but from where in the landscape?


Soil topographic index wetness index classes
Soil Topographic IndexWetness Index Classes

Soil Topographic

Index

Wetness Index

Classes

s8=f(S)

10

s7=f(S)

33.10

3.52

s9=f(S)

s10=f(S)

1

s1=f(S)

si = local storage

s6=f(S)

s2=f(S)

s5=f(S)

s3=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.

s4=f(S)


Re conceptualizing swat2
Re-conceptualizing SWAT

  • Variable Source Area (VSA) Hydrology

  • Curve Number and VSA hydrology

  • Convincing SWAT it recognizes VSAs


Revisit the hru concept
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?

Landuse

Soils

HRUs


Re conceptualizing swat for variable source area hydrology

STI

Landuse

SSURGO

HRUs


Distributing cn values
Distributing CN-values topographic index and landuse

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

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

Wetness Index

Classes

10

1


Modify the available water content
Modify the Available Water Content topographic index and landuse

  • 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).

Wetness Class 10

Wetness Class 9

Wetness Class 2

Wetness Class 1


Test results streamflow
Test Results: topographic index and landuseStreamflow

r2= 0.76

E = 0.82

r2 = 0.74

E = 0.83

-Standard


Re conceptualizing swat for variable source area hydrology

Test Results: Runoff from Pastures topographic index and landuse

SWAT-VSA SWAT-Standard

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


Re conceptualizing swat for variable source area hydrology

Test Results: Runoff topographic index and landuse

SWAT-VSA SWAT-Standard

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


Re conceptualizing swat for variable source area hydrology

Test Results: Soil water topographic index and landuse

SWAT-VSA SWAT-Standard

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


Re conceptualizing swat for variable source area hydrology

N topographic index and landuse

0

100

m

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

Test Results: Soil Water

10

1

585 m

1m

Cont.

Water

Level

Loggers

600 m


Re conceptualizing swat for variable source area hydrology

SWAT-VSA topographic index and landuse

Movie courtesy of Dr. Steve Lyon


Re conceptualizing swat for variable source area hydrology

Test Results: Soil water topographic index and landuse

a

b

Index

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


Test results phosphorus
Test Results: Phosphorus topographic index and landuse

a

r2 = 0.76

E = 0.71

b

-Standard

r2 = 0.68

E = 0.47


Test results phosphorus1
Test Results: Phosphorus topographic index and landuse

SWAT-VSA SWAT-Standard


Take home messages
Take-home Messages topographic index and landuse

  • 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 hydrology1
Curve Numbering VSA hydrology topographic index and landuse

Q = Pe2/(Pe+S)

P

Af = dQ/dPe

Watershed

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

Q

Af

As= 1-(S2/(σe+S)2

Unsaturated

Saturated

σe=S(√(1/(1-As))-1

Af = f(S,Pe)

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