Harvest disruption projections for the Australian sugar industry

Purpose: To investigate the effects of climate change on harvestability for sugarcane-growing regions situated between mountain ranges and the narrow east Australian coastline.\ud \ud Design/methodology/approach: Daily rainfall simulations from 11 general circulation models (GCMs) were downscaled for seven Australian sugarcane regions (1961:2000). Unharvestable days were calculated from these 11 GCMs and compared to interpolated observed data. The historical downscaled GCM simulations were then compared to simulations under a low (B1) and high (A2) emissions scenario for the period 2046:2065. The 25th, 50th and 75th percentiles of paired model differences were assessed using 95% bootstrapped confidence intervals.\ud \ud Findings: A decrease in the number of unharvestable days for the Burdekin (winter /spring) and Bundaberg (winter) regions and an increase for the Herbert region (spring) were plausible under the A2 scenario. Variability between GCM projections was higher for some regions compared to others and was generally higher in spring than winter. Spatial plots identified variability within regions. Northern and southern regions were more variable than central regions.\ud \ud Practical implications: Recent studies have projected increases in simulated yields under future climate conditions. Changes to the frequency of unharvestable days may require a range of management adaptations to deal with an increased harvest and an effectively shorter harvest window. Regions where an increase in unharvestable days is plausible may consider modifying the harvest period and upgrading harvesting technologies.\ud \ud Originality/value: The application of a targeted industry rainfall parameter (unharvestable days) obtained from downscaled climate models provided a novel approach to investigate the impacts of climate change. This research forms a baseline for industry discussion and adaptation planning towards an environmentally and economically sustainable future. The methodology outlined can easily be extended to other primary industries impacted by wet weather