A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models

A typical application of SEAMLESS-IF at meso level : the nitrate directive and the conservation agriculture scenarios in Midi-Pyrenees. D6.3.5.2

International audienceThis deliverable describes a typical meso-level application of SEAMLESS-IF. This application serves two main purposes within the SEAMLESS project. First of all it served as Test Case 2 (TC2) to test the various prototypes delivered by the SEAMLESS project and guide the development of the framework by identifying the requirements for a real-world application of the framework for ex-ante policy and technological innovations analysis. The second purpose of this application and main focus of this deliverable is to illustrate the potential use of SEAMLESS-IF to adress meso-level environmental questions across domains and scales. This deliverable builds on deliverables prepared throughout the SEAMLESS project, compiling and updating the essence of each of these individual deliverables to a final application with SEAMLESS-IF. The deliverable highlights the potential of SEAMLESS-IF to analyse meso-level incitation for better water and nitrogen managements. For this purpose three scenarios have been defined, combing different water and nitrogen managements such as suggest to improve nitrogen management for cereal crop based on simplify N balance. The objective of this scenario is to calculate new amounts of irrigation based on plant available water (PAW) which will be daily estimated by using the APES model. The last scenario is a combination of the previous two scenarios. The CAP2003 applied with 2013 conditions, by including exogenous driving forces, is taken as a reference. After a brief description of the Nitrate Directive and Water Framework Directive and their main measures in order to reduce nitrogen leaching and water consumption, a detailed description of the three modelling phases of SEAMLESS-IF is given. For each part, the main elements and data needed for each scenarios is described

Multi-scale water and land-use modelling for better decision making in agro-eco systems

International audienc

Quantitative approach to assess farming system resilience to climate change uncertainty [Poster]

Poster Diaporama de la présentation orale du poster : 3 diapositives Résumé en page 38 des actesInternational audienceAssessing the resilience of farming system to climate change through their cropping system diversity and socio-economic context is an important challenge for policy makers in the Mediterranean region. In fact, decision-makers are often confronted to contradictory demands when it comes to developing projects to foster suitable strategies of less resilient farms. This paper aims at developing and using a multi-scale quantitative approach for assessing, at short and long-term, the impacts of climate change on farm resilience behavior and various socio-economic and environmental indicators. Two scenarios, the business as usual and climate change, with a time horizon of 2030, have been developed and compared for representative farming system in northern Tunisia. The results of this study indicate that more than 70% are identified as resilient to climate change. Those farms are mostly cultivated with cereal and forage crops, less sensitive to water stress and soil salt accumulation. Inversely, 15% of farms which are dominated by orchards are usually less resilient. Those farms showed an important drop of their farm income (30217 DT), due mainly to their incapacity to adjust their cropping system under water stress condition and soil fertility degradation

An optimal price for sustainable irrigated agriculture in central-eastern Tunisia

International audienceIncreasing pressures on water resources are causing many countries in Mediterranean to (re)consider various mechanisms to improve water use efficiency for agricultural like Tunisia country. The price mechanism remains the most appropriate instrument to allocate this water resource, but the search for the optimal price of water that reconciles different aspects economic and environmental is the most important issue to rise. In this paper, we will show that the search for a compromise between farm income and water consumption is possible through an optimal price applying both the entropy maximization approach and the multiobjective optimization. The results show that the use of Generalised Maximum Entropy (GME) approach is able to calibrate the model. Once the model is calibrated, a Multi-Objective Programming (MOP) was used to determine the optimal price using the compromise method. This optimal price determined has resulted to a slight economic decline in agricultural income against an immediate environmental gain of water saving. This compromise is a way to ensure the sustainability of irrigated agriculture and the preservation of water resources in Tunisia

Preface : Multi-scale water and land-use modelling for better decision making in agro-eco systems

International audienc