(identification of substances, annual quantities at the distributor scale), could also
help characterise and spatialise pesticide inputs and these changes at the regional
scale [21]. This new database provides valuable perspectives for the characterisation
of future uses. On the other hand, the characterisation of past practices, in particular
those before the 1990s, remains difficult because of the absence of national databases
and the disappearance of archival documents (re-structuring, destruction of old
archives) and technical knowledge (retirement of advisors) on farms and advisory
bodies.
Besides enlarging the modelling approach to the Seine River basin scale, another
challenge is coupling pesticide transfer from soils and the groundwater model with
the river transport model. Similar developments have been carried out for nitrate
transfer in the PIREN-Seine programme (see [86]). Because specific processes for
pesticide consideration were already integrated into the STICS agronomic model
(especially sorption and degradation), it would also be possible to integrate them into
the biogeochemical module in surface water. In any case, pesticide monitoring in
rivers and groundwater is essential to compare simulated and observed data.
Acknowledgements This work was initiated by the CNRS project EC2CO Phyt’Oracle in 2008
and has since then been extended as part of the PIREN-Seine research programme, a component of
the Zone Atelier Seine within the international Long-Term Socio-Ecological Research (LTSER)
network (www.piren-seine.fr).
References
1. Klein M (1995) PELMO: pesticide leaching model version 2.01. Fraunhofer Institut für
Umweltchemie und Okotoxi-kolgie, Schmallenberg
2. Carsel RF, Imhoff JC, Hummel PR, Cheplick JM, Donigian Jr AS (2003) PRZM-3, a model for
predicting pesticide and nitrogen fate in the crop root and unsaturated soil zones: users manual
for release 3.12. Center for Exposure Assessment Modeling (CEAM). U.S. Environmental
Protection Agency (USEPA), Athens
3. Leistra M, van der Linden AMA, Boesten JJTI, van der Berg F (2001) PEARL model for
pesticide behavior and emissions in soil_plant systems; description of the processes in FOCUS
PEARL v 1.1.1. RIVM report, Alterra report 013 711,401 009. National Institute of Public
Health and the Environment. Wageningen Alterra, Green World Research, Bilthoven
4. Larsbo M, Jarvis N (2003) MACRO5.0. A model of water flow and solute transport in
macroporous soil. Technical description. Emergo 2003:6. Studies in the biogeophysical environment. SLU, Deptartment of Soil Science, Uppsala, p 47
5. Malone R, Ahuja WR, Ma L, Wauchope RD, Ma Q, Rojas KW (2004) Application of the root
zonewater qualitymodel (RZWQM) to pesticide fate and transport: an overview. Pest Manag
Sci 60(3):205–221. https://doi.org/10.1002/ps.789
6. Murgue C, Therond O, Leenhardt D (2016) Hybridizing local and generic information to model
cropping system spatial distribution in an agricultural landscape. Land Use Policy 54:339–354
7. Therond O, Hengsdijk H, Casellas E, Wallach D, Adam M, Belhouchette H et al (2011) Using a
cropping system model at regional scale: low-data approaches for crop management information and model calibration. Agric Ecosyst Environ 142(1–2):85–94
8. Leenhardt D, Angevin F, Biarnès A, Colbach N, Mignolet C (2010) Describing and locating
cropping systems on a regional scale. A review. Agron Sustain Dev 30(1):131–138
158
H. Blanchoud et al.
help characterise and spatialise pesticide inputs and these changes at the regional
scale [21]. This new database provides valuable perspectives for the characterisation
of future uses. On the other hand, the characterisation of past practices, in particular
those before the 1990s, remains difficult because of the absence of national databases
and the disappearance of archival documents (re-structuring, destruction of old
archives) and technical knowledge (retirement of advisors) on farms and advisory
bodies.
Besides enlarging the modelling approach to the Seine River basin scale, another
challenge is coupling pesticide transfer from soils and the groundwater model with
the river transport model. Similar developments have been carried out for nitrate
transfer in the PIREN-Seine programme (see [86]). Because specific processes for
pesticide consideration were already integrated into the STICS agronomic model
(especially sorption and degradation), it would also be possible to integrate them into
the biogeochemical module in surface water. In any case, pesticide monitoring in
rivers and groundwater is essential to compare simulated and observed data.
Acknowledgements This work was initiated by the CNRS project EC2CO Phyt’Oracle in 2008
and has since then been extended as part of the PIREN-Seine research programme, a component of
the Zone Atelier Seine within the international Long-Term Socio-Ecological Research (LTSER)
network (www.piren-seine.fr).
References
1. Klein M (1995) PELMO: pesticide leaching model version 2.01. Fraunhofer Institut für
Umweltchemie und Okotoxi-kolgie, Schmallenberg
2. Carsel RF, Imhoff JC, Hummel PR, Cheplick JM, Donigian Jr AS (2003) PRZM-3, a model for
predicting pesticide and nitrogen fate in the crop root and unsaturated soil zones: users manual
for release 3.12. Center for Exposure Assessment Modeling (CEAM). U.S. Environmental
Protection Agency (USEPA), Athens
3. Leistra M, van der Linden AMA, Boesten JJTI, van der Berg F (2001) PEARL model for
pesticide behavior and emissions in soil_plant systems; description of the processes in FOCUS
PEARL v 1.1.1. RIVM report, Alterra report 013 711,401 009. National Institute of Public
Health and the Environment. Wageningen Alterra, Green World Research, Bilthoven
4. Larsbo M, Jarvis N (2003) MACRO5.0. A model of water flow and solute transport in
macroporous soil. Technical description. Emergo 2003:6. Studies in the biogeophysical environment. SLU, Deptartment of Soil Science, Uppsala, p 47
5. Malone R, Ahuja WR, Ma L, Wauchope RD, Ma Q, Rojas KW (2004) Application of the root
zonewater qualitymodel (RZWQM) to pesticide fate and transport: an overview. Pest Manag
Sci 60(3):205–221. https://doi.org/10.1002/ps.789
6. Murgue C, Therond O, Leenhardt D (2016) Hybridizing local and generic information to model
cropping system spatial distribution in an agricultural landscape. Land Use Policy 54:339–354
7. Therond O, Hengsdijk H, Casellas E, Wallach D, Adam M, Belhouchette H et al (2011) Using a
cropping system model at regional scale: low-data approaches for crop management information and model calibration. Agric Ecosyst Environ 142(1–2):85–94
8. Leenhardt D, Angevin F, Biarnès A, Colbach N, Mignolet C (2010) Describing and locating
cropping systems on a regional scale. A review. Agron Sustain Dev 30(1):131–138
158
H. Blanchoud et al.