"Simple models use simple assumptions to translate rainfall risk into flood risk. But if these assumptions are incorrect, our estimates of flood risk (that is, the probability of a given flood magnitude occurring in any particular year) could be wrong. Flood risk is used to guide infrastructure assessment through cost-benefit ratios, so getting it right is important."

The reported costs of flooding in Australia have been increasing. Yet our knowledge regarding flood prediction still has many gaps. Overlay this with climate change and the level of uncertainty multiplies.

There are calls for improving our modelling and prediction of flooding and its effects. This is sensible. However, there will always be uncertainty. We therefore also need to improve the way we make decisions given uncertain futures.

This means getting more sophisticated with our economic modelling and cost-benefit analysis. Selecting a few flooding scenarios, developing an infrastructure option to suit the scenario, and then weighing up the costs and benefits is unlikely to lead to a robust solution.

Instead, we need to start embracing uncertainty in our economic modelling, working with a wide range of future scenarios and a suite of interventions to best meet those futures.

Good economic modelling draws on well-established approaches to decision making under uncertainty, which helps to develop adaptive pathways comprised of suites of measures that can be tweaked over time to respond to conditions as they evolve. This will often lead to better outcomes than prescriptive solutions that are limited to a single measure.


This insight was written in response to the article ‘Planning for a rainy day: there’s still lots to learn about Australia’s flood patterns‘ by Fiona Johnson, Christopher J White and Seth Westra, which first appeared on theconversation.com on 8 November 2016.