Regulatory limits on cadmium (Cd) content in food products are tending to become stricter, especially in cereals, which are a major contributor to dietary intake of Cd by humans. This is of particular importance for durum wheat, which accumulates more Cd than bread wheat. The contamination of durum wheat grain by Cd depends not only on the genotype but also to a large extent on soil Cd availability. Assessing the phytoavailability of Cd for durum wheat is thus crucial, and appropriate methods are required. For this purpose, we propose a statistical model to predict Cd accumulation in durum wheat grain based on soil geochemical properties related to Cd availability in French agricultural soils with low Cd contents and neutral to alkaline pH (soils commonly used to grow durum wheat). The best model is based on the concentration of total Cd in the soil solution, the pH of a soil CaCl2 extract, the cation exchange capacity (CEC), and the content of manganese oxides (Tamm's extraction) in the soil. The model variables suggest a major influence of cadmium buffering power of the soil and of Cd speciation in solution. The model successfully explains 88% of Cd variability in grains with, generally, below 0.02 mg Cd kg(-1) prediction error in wheat grain. Monte Carlo cross-validation indicated that model accuracy will suffice for the European Community project to reduce the regulatory limit from 0.2 to 0.15 mg Cd kg(-1) grain, but not for the intermediate step at 0.175 mg Cd kg(-1). The model will help farmers assess the risk that the Cd content of their durum wheat grain will exceed regulatory limits, and help food safety authorities test different regulatory thresholds to find a trade-off between food safety and the negative impact a too strict regulation could have on farmers.

Regulatory limits on cadmium (Cd) content in food products are tending to become stricter, especially in cereals, which are a major contributor to dietary intake of Cd by humans. This is of particular importance for durum wheat, which accumulates more Cd than bread wheat. The contamination of durum wheat grain by Cd depends not only on the genotype but also to a large extent on soil Cd availability. Assessing the phytoavailability of Cd for durum wheat is thus crucial, and appropriate methods are required. For this purpose, we propose a statistical model to predict Cd accumulation in durum wheat grain based on soil geochemical properties related to Cd availability in French agricultural soils with low Cd contents and neutral to alkaline pH (soils commonly used to grow durum wheat). The best model is based on the concentration of total Cd in the soil solution, the pH of a soil CaCl₂ extract, the cation exchange capacity (CEC), and the content of manganese oxides (Tamm’s extraction) in the soil. The model variables suggest a major influence of cadmium buffering power of the soil and of Cd speciation in solution. The model successfully explains 88% of Cd variability in grains with, generally, below 0.02 mg Cd kg⁻¹ prediction error in wheat grain. Monte Carlo cross-validation indicated that model accuracy will suffice for the European Community project to reduce the regulatory limit from 0.2 to 0.15 mg Cd kg⁻¹ grain, but not for the intermediate step at 0.175 mg Cd kg⁻¹. The model will help farmers assess the risk that the Cd content of their durum wheat grain will exceed regulatory limits, and help food safety authorities test different regulatory thresholds to find a trade-off between food safety and the negative impact a too strict regulation could have on farmers.

In situ stabilization of Cd, Pb, and Zn in an Austrian agricultural soil contaminated by atmospheric depositions from a smelter plant was assessed with a pine bark chip-derived biochar, alone and in combination with either compost or iron grit. Biochar amendment was also trialed in an uncontaminated soil to detect any detrimental effect. The pot experiment consisted in ten soil treatments (% w/w): untreated contaminated soil (Unt); Unt soil amended with biochar alone (1%: B1; 2.5%: B2.5) and in combination: B1 and B2.5 + 5% compost (B1C and B2.5C), B1 and B2.5 + 1% iron grit (B1Z and B2.5Z); uncontaminated soil (Ctrl); Ctrl soil amended with 1 or 2.5% biochar (CtrlB1, CtrlB2.5). After a 3-month reaction period, the soil pore water (SPW) was sampled in potted soils and dwarf beans were grown for a 2-week period. The SPW Cd, Pb, and Zn concentrations decreased in all amended-contaminated soils. The biochar effects increased with its addition rate and its combination with either compost or iron grit. Shoot Cd and Zn removals by beans were reduced and shoot Cd, Pb, and Zn concentrations decreased to common values in all amended soils except the B1 soil. Decreases in the SPW Cd/Pb/Zn concentrations did not improve the root and shoot yields of plants as compared to the Ctrl soil.

In situ stabilization of Cd, Pb, and Zn in an Austrian agricultural soil contaminated by atmospheric depositions from a smelter plant was assessed with a pine bark chip-derived biochar, alone and in combination with either compost or iron grit. Biochar amendment was also trialed in an uncontaminated soil to detect any detrimental effect. The pot experiment consisted in ten soil treatments (% w/w): untreated contaminated soil (Unt); Unt soil amended with biochar alone (1%: B1; 2.5%: B2.5) and in combination: B1 and B2.5 + 5% compost (B1C and B2.5C), B1 and B2.5 + 1% iron grit (B1Z and B2.5Z); uncontaminated soil (Ctrl); Ctrl soil amended with 1 or 2.5% biochar (CtrlB1, CtrlB2.5). After a 3-month reaction period, the soil pore water (SPW) was sampled in potted soils and dwarf beans were grown for a 2-week period. The SPW Cd, Pb, and Zn concentrations decreased in all amended-contaminated soils. The biochar effects increased with its addition rate and its combination with either compost or iron grit. Shoot Cd and Zn removals by beans were reduced and shoot Cd, Pb, and Zn concentrations decreased to common values in all amended soils except the B1 soil. Decreases in the SPW Cd/Pb/Zn concentrations did not improve the root and shoot yields of plants as compared to the Ctrl soil.

International audience | The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO). STICS-MACRO has the advantage of being able to simulate pesticides fate in complex cropping systems and to consider some agricultural practices such as fertilization, mulch, or crop residues management, which cannot be accounted for with MACRO. The performance of STICS-MACRO was tested, without calibration, from measurements done in two French experimental sites with contrasted soil and climate properties. The prediction of water percolation and pesticides concentrations with STICS-MACRO was satisfactory, but it varied with the pedoclimatic context. The performance of STICS-MACRO was shown to be similar or better than that of MACRO. The improvement of the simulation of crop growth allowed better estimate of crop transpiration therefore of water balance. It also allowed better estimate of pesticide interception by the crop which was found to be crucial for the prediction of pesticides concentrations in water. STICS-MACRO is a new promising tool to improve the assessment of the environmental risks of pesticides used in cropping systems.

Overreliance on the same herbicide mode of action leads to the spread of resistant weeds, which cancels the advantages of herbicide-tolerant (HT) crops. Here, the objective was to quantify, with simulations, the impact of glyphosate-resistant (GR) weeds on crop production and weed-related wild biodiversity in HT maize-based cropping systems differing in terms of management practices. We (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, with the weed dynamics model FlorSys; (2) quantified how much the presence of GR weeds contributed to weed impacts on crop production and biodiversity; (3) determined the effect of cultural practices on the impact of GR weeds and (4) identified which species traits most influence weed-impact indicators. The simulation study showed that during the analysed 28 years, the advent of glyphosate resistance had little effect on plant biodiversity. Glyphosate-susceptible populations and species were replaced by GR ones. Including GR weeds only affected functional biodiversity (food offer for birds, bees and carabids) and weed harmfulness when weed effect was initially low; when weed effect was initially high, including GR weeds had little effect. The GR effect also depended on cultural practices, e.g. GR weeds were most detrimental for species equitability when maize was sown late. Species traits most harmful for crop production and most beneficial for biodiversity were identified, using RLQ analyses. None of the species presenting these traits belonged to a family for which glyphosate resistance was reported. An advice table was built; the effects of cultural practices on crop production and biodiversity were synthesized, explained, quantified and ranked, and the optimal choices for each management technique were identified.

Overreliance on the same herbicide mode of action leads to the spread of resistant weeds, which cancels the advantages of herbicide-tolerant (HT) crops. Here, the objective was to quantify, with simulations, the impact of glyphosate-resistant (GR) weeds on crop production and weed-related wild biodiversity in HT maize-based cropping systems differing in terms of management practices. We (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, with the weed dynamics model FLORSYS; (2) quantified how much the presence of GR weeds contributed to weed impacts on crop production and biodiversity; (3) determined the effect of cultural practices on the impact of GR weeds and (4) identified which species traits most influence weed-impact indicators. The simulation study showed that during the analysed 28 years, the advent of glyphosate resistance had little effect on plant biodiversity. Glyphosate-susceptible populations and species were replaced by GR ones. Including GR weeds only affected functional biodiversity (food offer for birds, bees and carabids) and weed harmfulness when weed effect was initially low; when weed effect was initially high, including GR weeds had little effect. The GR effect also depended on cultural practices, e.g. GR weeds were most detrimental for species equitability when maize was sown late. Species traits most harmful for crop production and most beneficial for biodiversity were identified, using RLQ analyses. None of the species presenting these traits belonged to a family for which glyphosate resistance was reported. An advice table was built; the effects of cultural practices on crop production and biodiversity were synthesized, explained, quantified and ranked, and the optimal choices for each management technique were identified.

EASPEGESTADSUPDATINRACT1EJ2 INRA | Herbicide-tolerant (HT) crops such as those tolerant to glyphosate simplify weed management and make it more efficient, at least at short-term. Overreliance on the same herbicide though leads to the spread of resistant weeds. Here, the objective was to evaluate, with simulations, the impact on the advent of glyphosate resistance in weeds of modifications in agricultural practises resulting from introducing HT maize into cropping systems. First, we included a single-gene herbicide resistance submodel in the existing multispecific FLORSYS model. Then, we (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, (2) compared these systems in terms of glyphosate resistance, (3) identified pertinent cultural practises influencing glyphosate resistance, and (4) investigated correlations between cultural practises and species traits, using RLQ analyses. The simulation study showed that, during the analysed 28years, (1) glyphosate spraying only results in glyphosate resistance in weeds when combined with other cultural factors favouring weed infestation, particularly no till; (2) pre-sowing glyphosate applications select more for herbicide resistance than post-sowing applications on HT crops; and (3) glyphosate spraying selects more for species traits avoiding exposure to the herbicide (e.g. delayed early growth, small leaf area) or compensating for fitness costs (e.g. high harvest index) than for actual resistance to glyphosate, (4) actual resistance is most frequent in species that do not avoid glyphosate, either via plant size or timing, and/or in less competitive species, (5) in case of efficient weed control measures, actual resistance proliferates best in outcrossing species. An advice table was built, with the quantitative, synthetic ranking of the crop management effects in terms of glyphosate-resistance management, identifying the optimal choices for each management technique.

Herbicide-tolerant (HT) crops such as those tolerant to glyphosate simplify weed management and make it more efficient, at least at short-term. Overreliance on the same herbicide though leads to the spread of resistant weeds. Here, the objective was to evaluate, with simulations, the impact on the advent of glyphosate resistance in weeds of modifications in agricultural practises resulting from introducing HT maize into cropping systems. First, we included a single-gene herbicide resistance submodel in the existing multispecific FLORSYS model. Then, we (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, (2) compared these systems in terms of glyphosate resistance, (3) identified pertinent cultural practises influencing glyphosate resistance, and (4) investigated correlations between cultural practises and species traits, using RLQ analyses. The simulation study showed that, during the analysed 28 years, (1) glyphosate spraying only results in glyphosate resistance in weeds when combined with other cultural factors favouring weed infestation, particularly no till; (2) pre-sowing glyphosate applications select more for herbicide resistance than post-sowing applications on HT crops; and (3) glyphosate spraying selects more for species traits avoiding exposure to the herbicide (e.g. delayed early growth, small leaf area) or compensating for fitness costs (e.g. high harvest index) than for actual resistance to glyphosate, (4) actual resistance is most frequent in species that do not avoid glyphosate, either via plant size or timing, and/or in less competitive species, (5) in case of efficient weed control measures, actual resistance proliferates best in outcrossing species. An advice table was built, with the quantitative, synthetic ranking of the crop management effects in terms of glyphosate-resistance management, identifying the optimal choices for each management technique.

Volatilization may represent a major dissipation pathway for pesticides applied to soils or crops, and these losses may be modified by soil surface conditions or in the presence of plant residues. This paper investigates the effect of surface conditions on volatilization through experimental results. The two experiments consisted of volatilization flux measurements for 3 days after an application of S-metolachlor together with benoxacor: one with two wind tunnels to compare the effect of the presence of crop residues on the soil on volatilization losses and another one at the field scale from bare soil without crop residues. Volatilization fluxes were large immediately after application (between 77 and 223 ng m−2 s−1 for S-metolachlor depending on experimental conditions), decreasing down to a few nanograms per square meter per second on the last day. Volatilization fluxes followed a diurnal cycle driven by environmental conditions. The losses found for both compounds were in accordance with their physicochemical properties. The crop residue on the soil surface modified soil surface conditions—primarily the soil water content essentially, the degradation of S-metolachlor, and the dynamics of volatilization loss.

Volatilization may represent a major dissipation pathway for pesticides applied to soils or crops, and these losses may be modified by soil surface conditions or in the presence of plant residues. This paper investigates the effect of surface conditions on volatilization through experimental results. The two experiments consisted of volatilization flux measurements for 3 days after an application of S-metolachlor together with benoxacor: one with two wind tunnels to compare the effect of the presence of crop residues on the soil on volatilization losses and another one at the field scale from bare soil without crop residues. Volatilization fluxes were large immediately after application (between 77 and 223 ng m⁻² s⁻¹ for S-metolachlor depending on experimental conditions), decreasing down to a few nanograms per square meter per second on the last day. Volatilization fluxes followed a diurnal cycle driven by environmental conditions. The losses found for both compounds were in accordance with their physicochemical properties. The crop residue on the soil surface modified soil surface conditions—primarily the soil water content essentially, the degradation of S-metolachlor, and the dynamics of volatilization loss.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]DTAM [Axe_IRSTEA]DTAM-QT2-ADAPTATION [TR2_IRSTEA]SYNERGIE | International audience | Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

[Departement_IRSTEA]Territoires [TR1_IRSTEA]DTAM [Axe_IRSTEA]DTAM-QT2-ADAPTATION [TR2_IRSTEA]SYNERGIE | International audience | Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economic conditions for developing alternative agricultural systems or targeting mitigation measures. Our integrated assessment of these scenarios combines the calculation of spatialized environmental indicators with integrated bio-economic modeling. The latter is achieved by a combined use of Soil and Water Assessment Tool (SWAT) modeling with our own purpose-built land use generator module (Generator of Land Use version 2 (GenLU2)) and an economic model developed using General Algebraic Modeling System (GAMS) for cost-effectiveness assessment. This integrated approach is applied to two embedded catchment areas (total area of 360,000 ha) within the Charente river basin (SW France). Our results show that it is possible to differentiate scenarios based on their effectiveness, represented by either evolution of pressure (agro-environmental indicators) or transport into waters (pesticide concentrations). By analyzing the implementation costs borne by farmers, it is possible to identify the most cost-effective scenarios at sub-basin and other aggregated levels (WFD hydrological entities, sensitive areas). Relevant results and indicators are fed into a specifically designed database. Data warehousing is used to provide analyses and outputs at all thematic, temporal, or spatial aggregated levels, defined by the stakeholders (type of crops, herbicides, WFD areas, years), using Spatial On-Line Analytical Processing (SOLAP) tools. The aim of this approach is to allow public policy makers to make more informed and reasoned decisions when managing sensitive areas and/or implementing mitigation measures.

Non-point source pollution is a cause of major concern within the European Union. This is reflected in increasing public and political focus on a more sustainable use of pesticides, as well as a reduction in diffuse pollution. Climate change will likely to lead to an even more intensive use of pesticides in the future, affecting agriculture in many ways. At the same time, the Water Framework Directive (WFD) and associated EU policies called for a “good” ecological and chemical status to be achieved for water bodies by the end of 2015, currently delayed to 2021–2027 due to a lack of efficiency in policies and timescale of resilience for hydrosystems, especially groundwater systems. Water managers need appropriate and user-friendly tools to design agro-environmental policies. These tools should help them to evaluate the potential impacts of mitigation measures on water resources, more clearly define protected areas, and more efficiently distribute financial incentives to farmers who agree to implement alternative practices. At present, a number of reports point out that water managers do not use appropriate information from monitoring or models to make decisions and set environmental action plans. In this paper, we propose an integrated and collaborative approach to analyzing changes in land use, farming systems, and practices and to assess their effects on agricultural pressure and pesticide transfers to waters. The integrated modeling of agricultural scenario (IMAS) framework draws on a range of data and expert knowledge available within areas where a pesticide action plan can be defined to restore the water quality, French “Grenelle law” catchment areas, French Water Development and Management Plan areas, etc. A so-called “reference scenario” represents the actual soil occupation and pesticide-spraying practices used in both conventional and organic farming. A number of alternative scenarios are then defined in cooperation with stakeholders, including socio-economi