The likelihood of a flood of a given size occurring can be estimated from historical records such as river heights, rainfall data, and stream flow where these have been recorded over a long time.  Alternatively, design rainfall events which have been developed based on the statistical analysis of a large amount of historical rainfall data from numerous rainfall gauges can be used in catchment models to estimate floods of different likelihoods.     

The likelihood (or probability) of a flood of a given size occurring is often expressed using the terms Average Recurrence Interval (ARI) or Annual Exceedance Probability (AEP).  The term ARI is the most commonly used, but Annual Exceedance Probability is now the preferred term.  On this website, the term ‘chance’ has been used to describe flood likelihood using a concept the community is familiar with.

Some common terms

What is ARI?

Average Recurrence Interval (ARI) is one of the terms used to express the likelihood of a flood of a given size or larger occurring in a given year. ARI is expressed in terms of the long-term average number of years between flood events as large as or larger than the flood of interest. For example, a 100 year ARI flood occurs, on average, once every 100 years.

However, because flooding is a natural phenomenon it does not follow a predictable pattern. A 100 year ARI flood may happen more or less frequently than once every hundred years. Floods with a 100 year ARI have occurred close together, even in consecutive years within the same catchment in Australia’s history. To help combat the misconception that 100 year ARI flood will only occur every hundred years and that a community that has just experienced a 100 year ARI flood won’t flood again for another 99 years, the term Annual Exceedance Probability (AEP) is now the preferred method for describing the likelihood of a flood of a given size occurring.

What is AEP?

Annual Exceedance Probability (AEP) is another term which expresses the likelihood of a flood of a given size or larger occurring in a given year. AEP is expressed as a percentage (%). If a flood has an AEP of 1%, it has a one in 100 likelihood of occurring in any given year, the same as a flood with a 100 year ARI. This relationship is shown in the table below for some flood scenarios that are commonly used in flood mapping.

AEP is the preferred method for describing the likelihood of a flood occurring. This is because it better explains that the chance of a flood of a given magnitude occurring remains constant , that is for any given year there is a 1% chance of a one-in-100-year flood occurring.

What is PMF?

PMF stands for Probable Maximum Flood. This is the estimated largest flood that could possibly occur in an area and is a very rare and unlikely event. The extent of the PMF is generally the extent of the whole floodplain.

The PMF is sometimes modelled in flood studies so that emergency managers can understand the maximum possible extent of flooding that could ever occur in a location and plan accordingly.  However, it is unusual for flood mitigation works to be designed for the PMF.  If your property is shown as inundated in a PMF scenario there is a risk that you could be flooded, although this risk could be very low. 

“Why do one-in-100-year floods (1% AEP) seem to occur so often?”

The phrase, “one-in-100-year flood” can be confusing and can lead to the misconception that if a one-in-100-year flood has occurred recently then it will not occur again for some time. These events can and have occurred in close succession in the past in Australia, including twice in 12 months in Queensland in 2010 and 2011.

One in 100-year-floods can seem to be occurring more often than their likelihood suggests. This can be due to a number of factors:

• Perception: When big floods happen, they often get a lot of media attention, cause big impacts and are very memorable. With news easily available from across Australia and the world, it can seem that floods of this magnitude are happening more often.
• Lack of data: Estimating the likelihood of a flood of a given magnitude occurring is an inexact science based on historical records about rainfall and stream flow at a location over time. In Australia, these records have only been kept over a fairly recent time period. Data for bigger events at some locations, for instance 1% AEP, 0.5% AEP or 0.2% AEP floods may not exist, which makes it more difficult to accurately estimate the magnitude of these events. These floods may actually occur more often statistically than this, but more data needs to be collected over time to reflect this. In other words, we need more big floods to adjust the estimated likelihood for bigger floods.
• Climate Change: Climate change may increase the frequency and severity of storm events and alter rainfall patterns. As a result, flooding patterns may change, with large floods occurring more often than in the past.
  

Why does everyone talk about one-in-100-year (1% AEP) floods?

Because flood mitigation is complex and very costly, a trade-off must be made between the level of protection provided against the flood, the likelihood of the flood event occurring and the cost of flood protection.   Providing complete protection against a PMF would result in very restrictive building regulations, lots of flood mitigation infrastructure and great public expense.

In Australia, a 1% AEP flood is commonly used for land use planning purposes and buildings and flood mitigation strategies are often designed to provide protection against a 1% AEP flood. These floods are large enough to cause a range of impacts and happen frequently enough to warrant mitigation strategies being put in place. This is why these floods are well represented in studies and commonly discussed by the public.  However, a range of other flood events are often considered by floodplain managers.  For example, councils use a smaller design flood such as the 20% AEP (1 in 5) or 10% AEP (1 in 10) to design stormwater pipes to minimise nuisance flooding of roads.  Emergency managers are often interested in flood events larger than the 1% AEP flood to plan evacuation routes and show when critical facilities such as hospitals could be impacted.

 
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