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International audience; Agriculture is increasingly relying on groundwater irrigation. In the context of climate change, it is crucial to develop reliable methods for sustainability assessment of current and alternative agricultural systems. Among agricultural-borne non-point source pollutants, nitrogen has been the focus of many studies due to its ubiquitous impact on ecosystems, sometimes referred as the "Nitrogen cascade". Modelling such impacts is of primary importance for understanding current agrosystems and to be able to assess their evolution. In the Berambadi catchment (84km2, Karnataka, Southern India), which is part of BVET/ Kabini Critical Zone Observatory, we monitored the effect of application of fertilizers and over-exploitation of water resources by intensive tube well irrigation on groundwater resource. The monitoring highlighted a huge spatial variability of groundwater composition with Cl and NO3 contents spanning 3 orders of magnitude with the highest concentrations found in the most severely groundwater depleted areas. The high nitrate contents in groundwater (on average 100 mgNO3/L, up to 360 mgNO3/L) induces a "hidden" supply by irrigation of 50 kg/ha/yr on average with extremes up to 200 kg/ha/yr (Buvaneshwari et al., 2017). Irrigation with this highly concentrated groundwater induces an important feedback in the soil-plant system. However, groundwater recycling is rarely taken into account in groundwater resource integrated assessment and modelling. Monitoring of the soil pore-water composition was done for a common cash crop, Turmeric, in order to perform a nitrate balance at soil-plant scale and evaluate the influence of soil (Ferralsol vs Vertisol) properties on the flux of nitrate leached towards groundwater. A clear contrasted behaviour was found between the studied soils: the high permeability of Ferralsol induces a flush down of almost all the nitrogen input but limits the intensity of evapotranspiration and hence the risk of salinization. On the contrary, the low permeability and high holding capacity of Vertisols make water and nitrate consumption by the plants more efficient. Moreover, denitrification in the deep soil horizons may limit even more the nitrate output from Vertisol. However, chlorine (and other major elements such as Na, Ca, Mg) concentrations increased dramatically with soil depth, making Vertisol prone to salinization. The water and nitrogen balances at the soil-plant scale were assessed by combining field data and STICS crop model for the two soils. To account for the significant feedback induced by the nitrate rich groundwater recycling, we further introduced the new nitrogen module in the developed integrated coupled crop and groundwater model (AICHA under the RECORD platform) which is designed to assess agricultural systems and their adaptation to climate change. The model results revealed that the solute recycling by pumping can lead to severe groundwater degradation both in terms of quality and quantity. Different scenarios were furthermore tested to optimize the fertilizer application to reduce nitrate leaching and to mitigate the high nitrate concentrations in groundwater. Keywords: Groundwater quality; soil degradation; agriculture; integrated model

International audience; Agriculture is increasingly relying on groundwater irrigation. In the context of climate change, it is crucial to develop reliable methods for sustainability assessment of current and alternative agricultural systems. Among agricultural-borne non-point source pollutants, nitrogen has been the focus of many studies due to its ubiquitous impact on ecosystems, sometimes referred as the "Nitrogen cascade". Modelling such impacts is of primary importance for understanding current agrosystems and to be able to assess their evolution. In the Berambadi catchment (84km2, Karnataka, Southern India), which is part of BVET/ Kabini Critical Zone Observatory, we monitored the effect of application of fertilizers and over-exploitation of water resources by intensive tube well irrigation on groundwater resource. The monitoring highlighted a huge spatial variability of groundwater composition with Cl and NO3 contents spanning 3 orders of magnitude with the highest concentrations found in the most severely groundwater depleted areas. The high nitrate contents in groundwater (on average 100 mgNO3/L, up to 360 mgNO3/L) induces a "hidden" supply by irrigation of 50 kg/ha/yr on average with extremes up to 200 kg/ha/yr (Buvaneshwari et al., 2017). Irrigation with this highly concentrated groundwater induces an important feedback in the soil-plant system. However, groundwater recycling is rarely taken into account in groundwater resource integrated assessment and modelling. Monitoring of the soil pore-water composition was done for a common cash crop, Turmeric, in order to perform a nitrate balance at soil-plant scale and evaluate the influence of soil (Ferralsol vs Vertisol) properties on the flux of nitrate leached towards groundwater. A clear contrasted behaviour was found between the studied soils: the high permeability of Ferralsol induces a flush down of almost all the nitrogen input but limits the intensity of evapotranspiration and hence the risk of salinization. On the contrary, the low permeability and high holding capacity of Vertisols make water and nitrate consumption by the plants more efficient. Moreover, denitrification in the deep soil horizons may limit even more the nitrate output from Vertisol. However, chlorine (and other major elements such as Na, Ca, Mg) concentrations increased dramatically with soil depth, making Vertisol prone to salinization. The water and nitrogen balances at the soil-plant scale were assessed by combining field data and STICS crop model for the two soils. To account for the significant feedback induced by the nitrate rich groundwater recycling, we further introduced the new nitrogen module in the developed integrated coupled crop and groundwater model (AICHA under the RECORD platform) which is designed to assess agricultural systems and their adaptation to climate change. The model results revealed that the solute recycling by pumping can lead to severe groundwater degradation both in terms of quality and quantity. Different scenarios were furthermore tested to optimize the fertilizer application to reduce nitrate leaching and to mitigate the high nitrate concentrations in groundwater. Keywords: Groundwater quality; soil degradation; agriculture; integrated model

National audience

National audience; With the increasing scarcity of natural resources, the unsustainability of the conventional and intensive agriculture and the need of food security, agronomy engineering is facing a serious challenge. In this context, different projects aim to design and evaluate innovative cropping systems in order to increase the productivity of agro-ecosystems while preserving the diverse ecosystem services they provide or support. Simulation can help agronomists to test the robustness of field experiments results by testing various soil and climate conditions. While there are already crop models that simulate correctly crop development, there are few models that simulate the way farmer conduct their cropping systems. Yet, it is a key challenge because innovative cropping systems are often based on new farming practices, which take more into account the state of the crop and of the environment than conventional cropping systems. In addition, the use of “fixed dates” in simulations for farming practices is not adapted because it is important to take into account weather variations, which have a strong effect on the dates of farming operations. Therefore, the evaluation of innovative cropping systems by simulation requires building decision model that mimic farmers’ decision-making, and help in analyzing impacts of farmers’ practices on the sustainability of the cropping system. The modelling and simulation platform dedicated to the study of agro-ecosystems RECORD (J-E. Bergez et al., 2013) has been developed at INRA (French national institute for agricultural research). One of the objectives of the RECORD project was to help modelers in developing decision models and in coupling them to crop models. A generic conceptual decision-modelling framework (Bergez et al., 2016) has been proposed. It allows to design flexible management plan of activities using the concepts of a directed multigraph without loops and of a knowledge base. In the context of cropping system modelling, the graph of activities represents the farmer’s work plan and relies on the knowledge base to activate or disable technical operations. The knowledge base evolves all along the simulation collecting information provided by the biophysical model, as the farmer does when monitoring and observing the environment. Based on this conceptual decision-modelling framework an original graphical plugin “Decision” (Bergez et al., 2016) has been developed. It helps agronomist modelers in sketching and implementing their decision models and in linking them with biophysical models. The plugin allows defining activities (tasks), relation between activities and decision rules to trigger the different tasks. As the RECORD platform is based on DEVS (Discrete Event System Specification) formalism (Zeigler et al., 2000), the software implementation of the plugin is expressed in this formalism. We have applied this decision-modelling framework to the context of an ongoing project whose issue is bio economic evaluation of innovative cropping systems compared to conventional ones. To produce simulation results required by this project, a coupled model has been designed following the conceptual approach that an agricultural system can be divided into three sub-systems: Agent, Operating, and Biophysical (Le Gal et al. 2009; Martin-Clouaire and Rellier 2009). The model couples the crop model STICS (Brisson et al., 1998, J-E. Bergez et al., 2014), to a decision model using the Decision plugin and to a climate series reader. The model is generic because STICS can simulate the behavior of soil–crop systems for a large range of crops, and because the decision model is parametrable. It is used for different species commonly cultivated in south west of France (maize, sunflower, wheat, sorghum …), for different years (1982-2012), for two ways of farming practices: conventional (what do farmers commonly use) and innovative which are currently tested in experimental fields.

National audience

International audience; Modelling the water and nitrogen balance in Intercropping vineyards with cover crop is a key issue for a better prediction of the competition for water and nitrogen between the two species in a variety of climate, soils and vineyards management. APES (Agricultural Production and Externalities Simulator) is a field-scale modular simulation platform for cropping systems, developed within the Seamless project. The simulation of cover cropped vineyards requires the use of Crop, Vineyard, climate, soil and resource arbitration components. This new tool was developed and evaluated on field experiments in southern France and showed promising results to simulate a large range of crop management strategy combining type of intercrop and nitrogen management, under soil-rainfall combinations, on water and nitrogen budget and yield. In the present study, we use both water stress and nitrogen stress indexes to assess competition for water and nitrogen in a vineyard cover cropped with barley under Mediterranean soil and climate.

International audience

International audience; Crop growth simulation models are powerful tools for assessing the effects of management practices or policy changes on the environment and agricultural production (Van Ittersum & Donatelli, 2003). Assessments can be made at a very fine scale, e.g., for one farm, or at a much coarser scale, e.g. assessing the impacts of the implementation of the Water Framework Directive on European agricultural systems. These models simulate the behaviour of crops or cropping systems taking into account soil, climate, agro-management and crop characteristics. An example of such a model is the Agricultural Production and Externalities Simulator (APES; Donatelli et al., 2009), which allows entire crop rotations to be simulated taking into account the specific characteristics of such systems. Whatever the scale of the assessment, the usually large data demands of these cropping systems models have to be met. Obtaining the required input data becomes a challenge when cropping systems models are applied to assessments for large and heterogeneous areas such as Europe. Soil and daily climate data are available from the European databases assembled by the Joint Research Centre of the European Union. However, little detailed data is available on the management of crops, i.e. the timing, amount and type of input used and the application method. This agro-management information refers to all operations relevant for crop production, for example tillage, sowing, fertilization and irrigation (crop protection is not taken into account). Surveys aimed at collecting detailed management information are cumbersome as they require the involvement of many experts and they only provide average information on agro-management that is in fact flexible and variable in practice as it depends on factors associated with soil, climate and crop conditions. In this paper, we describe an approach that has been applied to generate agro-management information for 21 crops and 19 regions in the EU on the basis of ‘easily-obtainable’ survey data and generic expert rules. We compare this agro-management information with detailed agromanagement information from a survey carried out in four EU regions. This research has been conducted within the SEAMLESS project (Van Ittersum et al., 2008).