Search

To protect and improve water quality in the Great Barrier Reef, the Queensland Government's Reef 2050 Water Quality Improvement Plan targets that 90% of sugarcane, horticulture, cropping and grazing lands in priority areas be managed using best management practices for sediment, nutrient and pesticides by 2025. Progress towards this target is insufficient and variable across catchments and industries. The motivation to adopt improvements in management practices is heavily influenced by social, economic, cultural and institutional dimensions. In this paper we synthesise the literature on how these human dimensions influence decision making for land management practice and highlight where future investment could be focussed. We highlight that focussing on —1) investigating systems to support landholder decision making under climate uncertainty (risk); 2) generating a better understanding of the extent and drivers of landholder transaction cost; 3) understanding if there are competing 'right' ways to farm; and 4) improving understanding of the social processes, trust and power dynamics within GBR industries and what these means for practice change— could improve practice change uptake in the future. • Understanding human factors is essential for land practice change • Human factors include economic, social and cultural and macro institutional elements • These will affect trialling, adoption and dis-adoption of a practice [ABSTRACT FROM AUTHOR]

Australian and Queensland Government's Reef 2050 Water Quality Improvement Plan has set targets for improving the water quality entering the Great Barrier Reef lagoon. Given the large public investment and the deficit of data linking on-farm land management to changes in environmental outcomes, there is a need for a robust and efficient methods of quantifying links between land management and water quality. This paper explores a pragmatic approach to making this link using available data. We demonstrate that a simple parameterisation process is suitable for estimating hydrology and water quality across a wide range of land uses and management practices in agricultural landscapes. However, a manually calibrated model may still require the analysis of parameters to reduce error variances and evaluate uncertainties. Confidence in estimating hydrology and water quality in descending order is: runoff, sediment, nitrogen, phosphorous, and pesticide losses, reflecting the availability of data and inherent error propagation. • A pragmatic modelling by Howleaky is suitable to link management to water quality. • A manually calibrated model may still require a reduction in error variances. • Data availability and inherent error propagation determined confidence in modelling. [ABSTRACT FROM AUTHOR]