Source Apportionment and

APPLICATION OF SWAT MODEL ON THREE WATERSHEDS WITHIN THE VENICE LAGOON WATERSHED (ITALY): SOURCE APPORTIONMENT AND SCENARIO ANALYSIS R. Salvetti*, A. Azzellino*, D. Gardoni*, R. Vismara*, M. Carpani**, C. Giupponi**, M. Acutis**, M. Vale***, P. Parati***

POLITECNICO DI MILANO

UNIVERSITÀ DEGLI STUDI DI MILANO

* DIIAR - Environmental Engineering Department, Technical University of Milan ** Department of Crop Science (Di ProVe), University of Milan *** ARPAV (Regional Agency for Environmental Prevention and Protection in Veneto), Osservatorio Regionale Acque Interne

ARPA VENETO

4th International SWAT Conference July 3rd-5th 2007

Aims of the study APPLICATION OF SWAT MODEL TO THREE BASINS OF THE VENICE LAGOON WATERSHED TO

• Assess the apportionment of point and non point sources • Quantify the non point sources in terms of rain-driven and not-rain-driven diffuse sources POLITECNICO DI MILANO

•Simulate a scenario analysis to assess the effect of a UNIVERSITÀ DEGLI STUDI DI MILANO

ARPA VENETO

reduction of agricultural loads

Study area

Dese Zero Watershed 290 km2

Vela Watershed 101 km2 Naviglio Brenta Bondante Watershed 307 km2

~ 5.000 tN y-1 POLITECNICO DI MILANO

About 35% of the VLW area

3.000 tN y-1

UNIVERSITÀ DEGLI STUDI DI MILANO

ARPA VENETO

Venice Lagoon Watershed

2038 km2

Watershed characteristics NBB

DZ

VL

Urban Area

24%

26%

13%

Agricultural Area

69%

72%

86%

Dominant crops

Corn, soy, wheat, sugar beet

Corn, soy, wheat, sugar beet

Corn, soy, wheat, sugar beet

Groundwater Recharge Area

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Contribution from external basins

UNIVERSITÀ DEGLI STUDI DI MILANO

ARPA VENETO

Very complex network of drainage/irrigation channels

Measures available #S

$T

T$$T WWTP discharge Streamflow data

$T $T $T POLITECNICO DI MILANO

UNIVERSITÀ DEGLI STUDI DI MILANO

ARPA VENETO

Industrial discharge Water quality data

T$$T

T$ T$ T$ $T $T # $T $T S #S$T $T $T T$$T

$T

T$#S $T $T

$T T$$T $T T$$T

T$ $T $T

$T

$T

$T

T$$T$T$T$T$T

$T $T$T #S

$T

T$$T

$T

T$ $T T $ T$$T $T $T $T$T $T$T T $ T$ T$ $T

T$$T $T T $ T$ $T

T$ $T $T T$$T$T

T$#S #S

Sources apportionment WET WEATHER LOADS

DRY WEATHER LOADS

Point loads

POLITECNICO DI MILANO

UNIVERSITÀ DEGLI STUDI DI MILANO

ARPA VENETO

Diffuse loads

• WWTPs discharge

• Groundwater recharge

• Industrial discharge

• Channel network

• Direct sewer discharge Direct discharge/instream measurements BOD/nitrogen mass balance

Diffuse loads

• Surface runoff loads

USEPA QUAL2E BASINS-SWAT loads from WWTPs/Industries and from channel network loads from direct sewer discharge and from groundwater recharge

BASINS-SWAT input 20 soil classes

&

18 Subbasins 105 HRU

10 stations - 13 years daily & meteorological data

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# #

&

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& ## # ## ## ##

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&

UNIVERSITÀ DEGLI STUDI DI MILANO

33 Subbasins 169 HRU

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&

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POLITECNICO DI MILANO

ARPA VENETO

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## ##

## ## ## ## ## ### ##

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42 Subbasins

13 landuse212 classes HRU

& years crop rotations 9 - four ## #

SWAT calibration Groundwater flow (m3/s)

8 7 6

GW from external watersheds

5 4 3 Groundwater estimates

2

Groundwater simulated

1 0 jan

feb

mar

apr

may

jun

jul

aug

sep

oct

nov

dec

Additional inlet contribution Parameter calibration

POLITECNICO DI MILANO

• BLAI (corn, wheat) • HVSTI (corn, wheat) • CN • OV_N

UNIVERSITÀ DEGLI STUDI DI MILANO

ARPA VENETO

• • • • •

USLE_P ERORGN ERORGP NPERCO FRT_LY1

SWAT model: hydrological calibration DDE station 1999 10 Sutcliffe coefficient of efficiency Nash

E ~ 0.4 6

80 70 4 60

2

50

December

October

12/08/00

August13/07/00

13/06/00

July14/05/00

14/04/00

June15/03/00

14/02/00

May15/01/00

16/12/99

16/11/99

April

17/10/99

March

17/09/99

18/08/99

19/07/99

February

19/06/99

0

Predicted Measured 20/05/99

20/04/99

2

November

4

September

August

July

May

June

-1

21/03/99

19/02/99

20/01/99

0 21/12/98

6

3

20

m sMarch

30

April

8

40 0

January

ARPA VENETO

2000

Predicted Predicted 10 Measured

10 UNIVERSITÀ DEGLI STUDI DI MILANO

E = 0.65

Measured

February

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Nash Sutcliffe coefficient of efficiency

Daily flowrate - DDE station

January

3 -1

Flowrate (m s )

m3 s-1

8

19/05/96

17/05/96

0 15/05/96

3

Oct(Rain_Event)

15Oct07

14Oct06

13Oct05

12Oct04

11Oct03

8000

13/05/96

-1

10Oct02

June(Rain_Event)

07June06

06June05

May(Rain_Event)

06May05

Predicted Observed

11/05/96

6

09/05/96

07/05/96

05/05/96

ARPA VENETO

15

Flowrate (m s )

UNIVERSITÀ DEGLI STUDI DI MILANO

18

3

POLITECNICO DI MILANO

05May04

10000

04May03

03May02

kg N

SWAT model: RESULTS 12000

kg N during rainstorm events

Error rainstorm event ± 15%

6000

4000

2000

0

21

12

9

Daily event Rainstorm event

SWAT model: RESULTS – mean of 10 years simulation

SWAT output

Total N annual load ~ 2200 t N y-1 Total P annual load ~ 140 t P y-1 Present State - Ntot

WWTP and industrial discharge Tributary channels or irrigation systems Atmospheric deposition runoff Urban runoff 3%

13%

Direct sewer discharge Groundwater recharge Agricultural runoff

6%

8%

20% runoff loads 15% point loads

5%

65% dry weather diffuse loads 31% 34%

Present State - Ptot POLITECNICO DI MILANO

WWTP and industrial discharge Tributary channels or irrigation systems Atmospheric deposition runoff Urban runoff

9%

UNIVERSITÀ DEGLI STUDI DI MILANO

Direct sewer discharge Groundwater recharge Agricultural runoff

13%

24%

19%

ARPA VENETO

35%

Implementation of an agricultural scenario kg N ha-1 y-1

kg P ha-1 y-1

Corn

- 37%

-17%

Corn + manure

-53%

-27%

Agricultural nitrogen runoff load 300 250

Present state Agricultural scenario

tN/y

200 150 100 50 POLITECNICO DI MILANO

0 DZ

NBB

VL

Sum

UNIVERSITÀ DEGLI STUDI DI MILANO

∆N = 139 tN y-1 (~ 50% agricultural nitrogen runoff load) ARPA VENETO

∆N = 7 tP y-1 (~ 15% phopshorus runoff load)

Loads at the basin closure

∆N = 139 tN y-1

Nitrogen load at the basin closure

(- 6 %)

2400 2000

Present state Agricultural scenario

tN/y

1600 1200 800 400 0 DZ

NBB

VL

Sum

∆P = 7 tP y-1

Phosphorus load at the basin closure 160 140 120

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Agricultural scenario

100 tP/y

UNIVERSITÀ DEGLI STUDI DI MILANO

(- 5 %)

Present state

80 60 40 20

ARPA VENETO

0 DZ

NBB

VL

Sum

Conclusions •

The application of SWAT model allowed to quantify the total annual

nutrient load and to assess the source apportionment

• The dry weather diffuse sources (i.e. groundwater/spring recharge and tributary/irrigation channels coming from bordering watersheds) constitute the most important source (65% N and 35% P);

•

Runoff loads cover about 20% of the total N load and about 30% of

the total P load. Agricultural runoff constitute about 2/3 of the runoff load;

• POLITECNICO DI MILANO

Better-business agricultural scenario: reduction in agricultural runoff

loads of about 50% for N and of about 15% for P Æ decrease in the total annual load of about 5-6%.

UNIVERSITÀ DEGLI STUDI DI MILANO

•

Most significant model outputs Æ implemented in a decision support

system software (mDSS) ARPA VENETO