Boithias et al. – 2012 Int. SWAT Conference 1

Improving modelling of dissolved and particulate pesticides transport in rivers using the SWAT model in an agricultural catchment

2012 Int. SWAT Conference, Delhi, India

L. Boithias*, S. Sauvage, R. Srinivasan, J. Arnold, G. Merlina, S. Jean, JL. Probst, JM. Sánchez-Pérez

*l.boithias@gmail.com

Boithias et al. – 2012 Int. SWAT Conference 2

Introduction

• Relationship pesticides vs. TSM, DOC, POC (e.g. Gao et al., 1997; Wu et al.,

2004; Thevenot et al., 2009; Taghavi et al., 2010)

– Koc : organic carbon normalised partition coefficient – Kow : octanol/water distribution coefficient -> measure of hydrophobicity

– Kd : partition coefficient

• In SWAT:– SWAT simulates suspender matter– Partition is based on constants (Koc in soil and Kd in rivers)

– It is suggested to use a combined equation from Karickhoff et al. (1979)and Chapra (1997)

owd KK ⋅⋅= −810085.3

)()( owd KfMESfK ⋅=

Fixed POC For Kow є [2.1; 6.3]

TSMC

C

C

CCK

leso

sorbed

FW

FWRWd

1

lub

⋅=−= (m3.g-1)

Kd variable in space and time :

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The Save catchment

Larra gauging station

Meteorological stations

Catchment area : 1117km²

Rainfall : 600-800mm

ET : 500-600mm

Neste canal: 1 m3.s-1

(irrigation)

Save River: 6 m3.s-1

60% of calcicsoil with up to

50% clay

Agriculture = 90%

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Water quality monitoring

• Hourly discharge• Particulate organic carbon• Total suspended matter (TSM)• Pesticides (diss. and part.)

SeuilSonde

∆x = 20-30 cm

AutomaticManual

Height (cm)

Time (days)

Sampler

Sampling period = f(water height)

Aguaflash : 242 samples

Laboratory analysis: 46 soughtmolecules

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0

10

20

30

40

j-09 a-09 s-09 o-09 n-09 d-09 j-10 f-10 m-10 a-10 m-10 j-10

Dai

ly ra

infa

ll (m

m)

0.0

1.0

2.0

3.0

j-09 a-09 s-09 o-09 n-09 d-09 j-10 f-10 m-10 a-10 m-10 j-10

Time (days)

Met

olac

hlor

(µg.

L-1)

Observed (dissolved)Observed (sorbed)EU 0.1 µg.L-1

Measured pesticides concentrations

0.0

0.1

0.2

0.3

0.4

j-09 a-09 s-09 o-09 n-09 d-09 j-10 f-10 m-10 a-10 m-10 j-10

Time (days)

Acl

onife

n (µ

g.L-

1)

Example of metolachlor and aclonifen: moleculesshow a complex signal

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Pesticide fate modeling in SWAT

sedocd concCK

F⋅+

=1

1d

sedoc

sedocp F

concCK

concCKF −=

⋅+⋅

= 11

Phase distribution in rivers

Root zone

Saturated zone

Deep aquifer

SOILDegradation

Infiltration (d)

TRANSFERSSurface runoff (d,p)

Sub-surface runoff (d)Groundwater recharge RIVER

DegradationVolatilization (d)

Settling (p)

SEDIMENTS BEDDegradation

Resuspension (d,p)Diffusion (d)Burying (p)

AIR / PLANTSVolatilizationDegradation

Leaching

APPLICATION

Vadose zone

Biological and chemical

processesPhysical

processes

solution

solidphasep C

CK =

100

orgCSKK ocp ⋅=

Phase distribution in soil

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Kd sensitivity in SWAT

River

Soil

-0,95-1,17CKoc

-0,30-0,44SKoc

AclonifenMetolachlorSi mean

)(IP

I

I

PS i ⋅

∂∂=Sentivity analysis :

3x more sensitive

How can we better implement CKoc ? ocd KCOPK ⋅= %From Karickhoff et al. (1979) :

)()( owd KfMESfK ⋅=

From Boithias (2012)

> In SWAT we have TSM > Kow is a laboratory value

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Relationship between %POC and TSM

02.05

09.0% +

−=

TSMPOC

Min. TSM atgauging station

%OM in top soil

horizons

R² = 0.6

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Relationship between Koc and Kow

16 hydrological events : 11 high flow periods + 5 low flow periods

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Relationship between Koc and Kow

36.031055.7 owoc KK ⋅⋅= −

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Conclusion

• The methodology may be applied to a wide range of catchment and organic contaminants

• This equation can be implemented in any model describing the fate of pesticides in both dissolved and sorbed phases

36.031055.702.05

09.0owd K

TSMK ⋅⋅⋅

+−

= −

(m3.g-1)

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For further questions :

l.boithias@gmail.com

http://www.aguaflash-sudoe.eu/

Thanks for your attention !