In the Orgeval basin, within the PIREN-Seine programme, a flow-controlled
refrigerated sampler has been installed since 2008 at the Avenelles station (see
Fig. 1). Since then, samples have been collected once a week and then gathered
monthly for pesticide analyses. A survey of the crop management techniques of the
main farms was also carried out [12]. Pesticides were then extracted with an offline
solid-phase extraction (SPE) technique with the Oasis hydrophilic lipophilic balance
® (HLB, Waters) cartridge and analysed by liquid chromatography with tandem
mass spectrometry (LC/MS/MS) [13, 14]. Detection limits are 1 ng L
À1 for both
atrazine and DEA.
In the Vesle basin, atrazine and DEA concentrations were extracted for 39 piezometers from the ADES database [15]. Additional specific sampling campaigns
were carried out monthly from November 2003 to February 2005 on 11 piezometers
by the Agence de l’Eau Seine-Normandie (Direction Territoriale des Vallées d’Oise,
DTVO). This covered a larger geographic area and included more specific
hydrogeological contexts.
3 Quantification of Past Pesticide Use
AIs provided at the watershed scale depend on phytosanitary practices (or treatment
programmes) prescribed at the field scale by technical advisors. However, these uses
vary greatly depending on pedoclimatic conditions acting on parasitism, types of
crops and cultivated areas, farmers’ phytosanitary strategies and regulations on
pesticide use.
Most of the AI uses are registered for specific crops and often in a particular case
(type of pest and/or disease). Crop rotations and their diversity (short rotations from
3 to 4 years to rotations of more than 10 years including alfalfa) ensure some
diversity, except in the case of perennial crops such as vineyards. Each farmer has
his/her own strategies in terms of phytosanitary practices based on the advice of
technicians (cooperatives, technical institutes, etc.) and his/her personal choices
(sowing date, crop variety, tillage practices, etc.) [16–18]. Then, for the same crop,
pesticide use may differ from one farm to another or even from one field to another.
This diversity could explain 40–60% of pesticide use [16]. Moreover, pesticide use
evolves rapidly over time, depending on the regulations (banned or new AI), climate
conditions (which cause diseases and pests to vary) and rotation crops [17].
The main source of information on crop rotation in the two study areas is the
French Agricultural Census, which has been available at the municipal level since
1970. It is updated only every 10 years, but annual data were estimated by interpolation using annual data available at the regional scale between these dates [19–21].
With regard to pesticide use, there are few generic databases that can be used over
a long time period and on large study sites. The E-Phy database [22] lists the plant
protection products authorised in France, as well as their composition, homologation
dates and actual registered uses and doses. However, these data cannot be directly
How Should Agricultural Practices Be Integrated to Understand and. . .
145
refrigerated sampler has been installed since 2008 at the Avenelles station (see
Fig. 1). Since then, samples have been collected once a week and then gathered
monthly for pesticide analyses. A survey of the crop management techniques of the
main farms was also carried out [12]. Pesticides were then extracted with an offline
solid-phase extraction (SPE) technique with the Oasis hydrophilic lipophilic balance
® (HLB, Waters) cartridge and analysed by liquid chromatography with tandem
mass spectrometry (LC/MS/MS) [13, 14]. Detection limits are 1 ng L
À1 for both
atrazine and DEA.
In the Vesle basin, atrazine and DEA concentrations were extracted for 39 piezometers from the ADES database [15]. Additional specific sampling campaigns
were carried out monthly from November 2003 to February 2005 on 11 piezometers
by the Agence de l’Eau Seine-Normandie (Direction Territoriale des Vallées d’Oise,
DTVO). This covered a larger geographic area and included more specific
hydrogeological contexts.
3 Quantification of Past Pesticide Use
AIs provided at the watershed scale depend on phytosanitary practices (or treatment
programmes) prescribed at the field scale by technical advisors. However, these uses
vary greatly depending on pedoclimatic conditions acting on parasitism, types of
crops and cultivated areas, farmers’ phytosanitary strategies and regulations on
pesticide use.
Most of the AI uses are registered for specific crops and often in a particular case
(type of pest and/or disease). Crop rotations and their diversity (short rotations from
3 to 4 years to rotations of more than 10 years including alfalfa) ensure some
diversity, except in the case of perennial crops such as vineyards. Each farmer has
his/her own strategies in terms of phytosanitary practices based on the advice of
technicians (cooperatives, technical institutes, etc.) and his/her personal choices
(sowing date, crop variety, tillage practices, etc.) [16–18]. Then, for the same crop,
pesticide use may differ from one farm to another or even from one field to another.
This diversity could explain 40–60% of pesticide use [16]. Moreover, pesticide use
evolves rapidly over time, depending on the regulations (banned or new AI), climate
conditions (which cause diseases and pests to vary) and rotation crops [17].
The main source of information on crop rotation in the two study areas is the
French Agricultural Census, which has been available at the municipal level since
1970. It is updated only every 10 years, but annual data were estimated by interpolation using annual data available at the regional scale between these dates [19–21].
With regard to pesticide use, there are few generic databases that can be used over
a long time period and on large study sites. The E-Phy database [22] lists the plant
protection products authorised in France, as well as their composition, homologation
dates and actual registered uses and doses. However, these data cannot be directly
How Should Agricultural Practices Be Integrated to Understand and. . .
145