Improving salinity hazard predictions by factoring in a range of human impacts in the context of climate change

Abstract

Predictions of climate change in Australia point to a significant warming, a decrease in precipitation and an increase in evaporation in many areas of S, SW and SE Australia over the next century and beyond, unless greenhouse gas emissions are significantly reduced. Precipitation amount and intensity are predicted to increase in regions of summer rainfall, mostly the tropical northern third of the continent. Recent climate change is already affecting many physical and biological systems, especially in the SW, and this 'hot and dry' event in the winter rainfall regions is likely to have further significant impacts on human and natural systems. The predicted change will result in a climate different from that generally reconstructed for the Holocene and Late Pleistocene in Australia, where increases in salinity levels in our SE Australian riverine systems appear to correlate with cold dry events rather than a hot dry climate. It is therefore likely that the impacts of salinity in our natural systems over the next century and beyond in SE Australia may be quite different to those events recorded in the Late Quaternary geological record. The rates of change and the ability of our natural systems to respond to these changes remain problematic. Local climate variability and future and past climate changes have not yet been factored into salinity hazard and risk mapping, yet these may prove vital in predicting and assessing the extent of the salinity problem and the scale of and location of investment required to manage the problem. This issue compounds the problems created by a paucity of other temporal and spatial data that has severely restricted the reliability of salinity hazard predictions, particularly at sub-catchment scales. Disentangling the relative contributions and effects of human impacts on salinity and groundwater changes is a difficult exercise. To date most salinity hazard mapping and predictions have not considered some of the variables that might significantly affect the reliability of these constructs and predictions due to data limitations. This paper examines these issues, discusses ways in which improvements to predictions may be made through a combination of maximizing the use of existing data, the use of other proxies and new data acquisition. We argue that some attempt must be made to account for these issues in salinity hazard/risk predictions, and/or the uncertainties that arise from these data gaps must be made more explicit to help data acquisition strategies, and policy, management and investment planning.