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Modeling of pesticide fate in a luxembourgish catchment with the Soil and Water Assessment Tool (SWAT) - combining modeling and monitoring. Stefan Julich 1& ² , Tom Gallé², Marion Frelat², Michael Bayerle², Hassanya El Khabbaz² & Denis Pittois²

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slide1

Modeling of pesticide fate in a luxembourgish catchment with the Soil and Water Assessment Tool (SWAT) - combining modeling and monitoring

Stefan Julich1&² , Tom Gallé², Marion Frelat², Michael Bayerle², Hassanya El Khabbaz² & Denis Pittois²

1 TechnischeUniversitätDresden, Instit. for Soil Science & Site Ecology

² CRTE, CRP Henri Tudor - Luxembourg

m 3 wfd and pocis
M3, WFD and POCIS
  • M3 is a demonstration project for WFD policy implementation of the LIFE+ programme
  • M3 tests state-of-the-art monitoring and modelling tools for programme of measures (POM) evaluation
  • Can passive samplers (POCIS) help to validate and improve simulations of pesticide fate ?
inroduction of study area
Inroduction of study area

elevation

slope

landuse

Land use: ~ 30% managed pasture

~ 30% agriculture (corn, winter cereals, summer cereals)

~ 6% urban area

emission modeling of pesticides
Emission modeling of pesticides

Main challenges in model calibration

  • Monitoring data covering the dynamics of the emissionpathways/sources
  • Pesticide application date, amount, formulation and spatial distribution are unkown
  • Compound fateproperties t1/2 and KOC are spatially variable
  • Calibration atcatchmentoutlet, no distributed calibration possible

t1/2 = 15 d

Log KOC = 1.51

the watershed
The watershed
  • Warkwatershed ca. 82km²
  • First simulationconcentrate on Terbuthylazine
  • Applied on corn (~ 465 ha)
  • Statisticsindicate a applicationof340 g/ha on average
  • Same applicationdatefor all fields
data needs for pesticide fate modelling
Data Needs forpesticidefatemodelling ?
  • Whichcropsaregrown?
  • Whichsubstancesareapplied?
  • Whenarethepesticidesapplied?
  • Whatistheamountoftheapplication?
loads observed vs simulated
Loads – observed vs. simulated

4

6

3

5

2

1

  • Event 1  toolessmobilization (surfacerunoff vs. Parameterization)
  • Event 2  viceversa
slide10

Floodwave

24/5-10/6

4

24/5-10/6

3

2

6

5

1

loads observed vs simulated1
Loads – observed vs. simulated

Mertzig

4

6

3

  • Mertzigforbotheventstolessexport applicationamounts?
  • Niederfeulenfirsteventisunderestimated  toolessmobilizationthroughsurfacerunoff?

5

2

Niederfeulen

1

conclusions outlook
Conclusions & outlook
  • Results indicate  simulations do not match with the measurements
  • under or over estimation of surface runoff
  • POCIS measurement are useful to gain spatially distributed information of pesticide export to rivers
  • Comparison of simulation with POCIS results show the value of adequate Input Data like spatial information of application amounts and application times
conclusions outlook1
Conclusions & outlook
  • Integration of more events in the model validation (measurements are still in progress)
  • Improve hydrological modelling
  • Simulate pesticide with spatially different application dates and amounts
performance of pocis during floodwaves
Performance of POCIS duringfloodwaves
  • Rsdetermined in the fieldwith composite samples over a day
  • Rs on different river sites RSD 20-30 %
  • No explanation for Rsvariability
losses during longer exposure
Lossesduring longer exposure

Memory test

  • Spiked POCIS exposed for differentlength of time in a river
  • Losses for compounds with log KOW <1
  • ke: 0.04-0.1 d-1 (t1/2: 7-17 d)

Exposure time

load calculation bias
Loadcalculationbias
  • Loadcalculation on eventlevelbiasedonly on floodwave close to application
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