Construction of a Bio-economic Model to Estimate the Feasibility and Cost of Achieving Water Quality Targets in the Burnett-Mary Region, Queensland

Part 4: Modelling and Simulation SystemsInternational audienceThe aim of this study was to develop a bio-economic model to estimate the feasibility and net profit (or net costs)s of achieving set water quality targets (sediment, nitrogen and phosphorus load reductions) in the Burnett Mary region of northern Queensland, Australia to with the aim of protecting the southern portion of the Great Barrier Reef (GBR). Two sets of targets were evaluated – Reef Plan Targets (RPTs) which are the currently formally agreed targets, and more ambitious Ecologically Relevant Targets (ERTs) which current science suggests might be needed to better protect the values of the GBR. This paper describes the construct of a bio-economic optimisation framework which has been used to underpin a Water Quality Improvement Plan (WQIP) for the Burnett Mary region. The bioeconomic model incorporates the available science developed from paddock and catchment scale biophysical model results and farm economic analysis. The model enabled transparent assessment and optimisation of net profits and costs associated with four categories of best management practices (cutting edge unproven technologies called ‘A’ practice, current best-management practices called ‘B’, common industry or ‘C’ practices, and below industry standards or ‘D’ practice) in the grazing and sugar cane industries. The bioeconomic model was able to solve for RPTs or ERTs assigned to either the entire region or within each of five discrete river basins. Key outcomes from the study were that RPTs could be achieved at an annual cost of $3M/year on a whole of region basis. In contrast ERTs could be achieved on a whole of region basis at as net cost of $16M/year. ERTs were not able to be feasibly met on a basin by basin basis. This is the first time such a comprehensive and integrated bio-economic model has been constructed for a region within GBR using environmental software that linked available biophysical and economic modelling