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Between 2011 and 2014, the Goyder Institute undertook a major project to develop downscaled climate change projections for South Australia. The resulting ‘SA Climate Ready’ dataset provides the most comprehensive downscaled climate projections data available in South Australia and is intended for the purposes of climate change impact assessment to inform appropriate climate change adaptation planning. Over the same period of time, regional climate change adaptation plans have been developed for many regions of South Australia, according to the SA Government’s ‘Prospering in a Changing Climate’ adaptation planning framework. A number of these adaptation plans have adopted an ‘adaptation pathways’ approach, which identifies a number of pathways for the adaptation of a community, industry or natural resource to climate change. The intention of this type of adaptation plan is that planners, managers and policy makers will switch their planning approach to the most appropriate pathway according to the observed changes in the climate as they develop.
The climate change adaptation planning community within SA does not a have a clear methodology to identify the vulnerability of natural resources and water supply systems in relation to projected changes in rainfall, temperature and other climate variables. An important element of the adaptation pathways approach to climate change adaptation planning is that planners need to know the threshold climate variable values (the ‘trigger’ values) at which an alternative adaptation pathway within the adaptation plan should be adopted. A methodology is required with to guide the identification of threshold values of hydroclimate variables, helping climate change adaptation planners to determine the most appropriate timing of adopting alternative adaptation pathways. The framework to be developed through this research is intended to guide the identification of climate thresholds for climate change adaptation planning.
The project addressed the following priority policy questions identified within the Climate Action program of the Goyder Institute Strategic Research Plan:
The project also considered climate extremes, including high-intensity rainfall events and droughts.
How can climate-affected systems (natural resources, water supply systems) be analysed to identify the elements that most affect their vulnerability to temporal variations in rainfall and other climate variables?
A methodology and framework was developed to assess the vulnerability of industries and natural resources to the impacts of climate change and climate variability, with particular regard to the impacts of extreme rainfall events (high-intensity rainfall and drought periods) and the identification of the trigger points, indicating when a system is likely to be pushed beyond acceptable operating conditions. This was achieved through “stress testing” case study systems or processes to rainfall events of different types, with a particular focus on extreme event types and on a range of time scales, from daily (e.g. events of extreme rainfall intensity) to multiple years (droughts). The developed framework can guide the examination of the operational details of agricultural, industrial or water supply systems, to understand which variables most affect a system’s vulnerability to climatic variations and extreme characteristics of rainfall. The intention of this is to provide information on ways in which the management or operation of systems can be altered to improve their resilience to both climate variability and climate change. Importantly, this will also enable identification of threshold values of climate variables (primarily rainfall patterns) at which the operation of a system requires alteration to function effectively.
A case study of a stormwater capture and Managed Aquifer Recharge scheme was examined to identify the scheme’s vulnerability to rainfall events of different types, such as more intense rainfall or long gaps between rainfall events. In this example, the objective of the analysis was to determine if the vulnerability to those types of rainfall characteristics is due to the size of the stormwater capture basin, or the injection rate of the MAR, or the storage capacity of the aquifer, etc. This enabled recommendations to be made on which of those system variables would have to change to improve the resilience of the scheme to those kinds of rainfall variation.
The primary outcomes of this project:
