Indices for monitoring climate variability and the impacts of drought have long been used as the basis for planning and assessing the need for domestic and international aid to affected populations. Associated with this has been ongoing debate as to which indices are the most reliable and appropriate to aid decisions by government and private agencies on when and where to provide financial assistance.

The simplest indices measure meteorological drought, the effects of which are measured in terms of agricultural, hydrological, and socioeconomic drought. Even though lack of rain is the primary cause of agricultural drought, rainfall data alone are frequently insufficient to assess the effect of drought on agricultural productivity.

In this study we consider a range of seasonal indices in terms of how they relate to the impact of drought on rural Australia. This includes reviewing available and prospective indices that could aid government decision makers, in terms of when and where to intervene, in developing and implementing their policies. Clear and consistent policy helps agricultural managers to determine their production and financial targets and strategies, how much physical and financial risk they and their farms will be exposed to, and even whether they should continue to remain in farming. The significance of policy in considering triggers for government intervention is that it alters the level of risk that farmers are exposed to, which in turn influences the management strategies and tactics that farmers are likely to adopt. Minimising the risk to the biophysical resource base of every farm is also of paramount importance.

We conclude that indices may provide effective summaries of droughts provided the purpose is clearly and precisely defined: in terms of activity, location and timing. However, given the important role of context in evidence-based decision-making, which in this case covers a range of industries, management systems, types of droughts, and seasons across Australia, it is likely that no single index could be effective for widespread, general usage in monitoring climate variability.