Author(s): Angelos Alamanos; Jorge Andres Garcia; Suzanne Linnane; Triona Mcgrath
Linked Author(s): Angelos Alamanos
Keywords: Goal Programming; Agriculture optimization; Ireland; Sustainability; Pollution control
Abstract: Complex agricultural problems with conflicting economic-production and environmental objectives are becoming increasingly topical. Agriculture consumes environmental resources (soil, water, raw materials), emits pollution (fertilizers, pesticides, Greenhouse Gases – GHGs) and has high production expectations (reduce costs, increase yields, production, sales, and thus profits). The optimal way to cover the economic demand and achieve environmental sustainability through the most efficient use of resources and emissions’ control is a challenging multi-objective problem. Integrated approaches are required to balance those, often conflicting, objectives. Ireland seeks such approaches to enhance its capacity and achieve the objectives set by the recent Common Agricultural Policy (CAP), the Nitrates Action Plan (NAP), the 2030 Agri-Food Strategy, and the upcoming River Basin Management Plan (RBMP) (3rd Cycle). Agriculture is based on grassland and cattle, and is the dominant pressure to the quantitative and qualitative status of the Irish water bodies. So, these national and European policies are expected to improve water quantity, quality, enhance sustainable catchment management, reduce GHGs emissions, boost the production and the agro-economy, in efficient and socially acceptable ways. A Goal Programming (GP) model was developed to address the above objectives, for the first time in Ireland, to our knowledge. The targets set are: maximum sales, minimum production or capital costs, maximum exploitation of area for cultivation, minimum emissions of Phosphorus and Carbon, maximum organic fertilizer and minimum use of chemical fertilizer, and maximum expected productions. The model allows for deviations from one or more targets, and the policymakers can penalize those deviations (exceedances or deficits) by weighting them (degree of undesirability of deviations). The model minimizes these deviations from the desirable goals, and also provides the optimal values of different crops and animal types (decision variables), as well as for each goal set. The results prove that the multiple objectives must be planned together as a system in order to provide sustainable solutions. Such solutions are feasible, and the learnings that an integrated model can support policymakers and practitioners to address consider complex systems. Similar approaches are encouraged in terms of building integrated databases that will lead to a holistic monitoring-modelling of the system as a whole, ensuring that no discipline will act in the expense of another.