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This study aims to investigate the effects of climate change on harvestability for sugarcane-growing regions situated between mountain ranges and the narrow east Australian coastline.

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 low (B1) and high (A2) emissions scenarios for the period of 2046-2065. The 25th, 50th and 75th percentiles of paired model differences were assessed using 95 per cent bootstrapped confidence intervals.

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. Spatial plots identified variability within regions. Northern and southern regions were more variable than central regions.

Changes to the frequency of unharvestable days may require a range of management adaptations such as modifying the harvest period and upgrading harvesting technologies.

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.

The purpose of this paper is to develop a geographic information system (GIS)‐based risk assessment tool for visualising climate change impacts in agricultural industries and evaluating eventual adaptation strategies.

A climate change adaptation strategy tool (CCAST) with built‐in GIS capability has been developed for agricultural industries. Development of the GIS functionality within CCAST includes the implementation of map projection, boundary allocation, interpolation and a graphical display of spatial data. In total, 20 climatic and crop indices are computed alongside basic climate variables (rainfall and temperature) from downscaled global climate models at 1,062 sites across the state of New South Wales (NSW) located in eastern Australia.

A case study in Australia is used to demonstrate use of this tool. This shows selecting suitable genotypes of wheat is a key adaptation strategy to mitigate the impacts of climate change on wheat cropping. It shows that spring wheat genotypes will become predominate, while the winter genotypes will only be viable in clearly defined areas where sufficient days of cool temperature exist for completion of vernalisation in a future warmer climate.

CCAST integrates knowledge relevant to climate impact management in a stand‐alone environment. It benefits from statistical analysis and GIS functionalities and provides many user‐friendly GIS features to make it suitable for practitioners on the ground.