Defining the floodplain in hydrologically-variable settings: implications for flood risk management

Flood risk management is an essential responsibility of state governments and local councils to ensure the protection of people residing on floodplains. Globally, floodplains are under increasing pressure from growing populations. Typically, the engineering-type solutions that are used to predict local flood magnitude and frequency based on limited gauging data are inadequate, especially in settings which experience high hydrological variability. This study highlights the importance of incorporating geomorphological understanding into flood risk management in southeast Queensland (SEQ), an area badly affected by extreme flood events in 2011 and 2013. The major aim of this study is to outline the hydrological and sedimentological characteristics of various ‘inundation surfaces’ that are typical of catchments in the sub-tropics. It identifies four major inundation surfaces; within-channel bench [Q ~ 2.33 yr average recurrence interval (ARI)]; genetic floodplain (Q = 20 yr ARI); hydraulic floodplain (20 yr < Q ≤ 200 yr ARI) and terrace (Q > 1000 yr ARI). These surfaces are considered typical of inundation areas within, and adjacent to, the large macrochannels common to this region and others of similar hydrological variability. An additional area within genetic floodplains was identified where flood surfaces coalesce and produce an abrupt reduction in channel capacity. This is referred to here as a Spill-out Zone (SOZ). The associated vulnerability and risk of these surfaces is reviewed and recommendations made based on incorporating this geomorphological understanding into flood risk assessments. These recommendations recognize the importance to manage for risks associated with flow inundation and sediment erosion, delivery and deposition. The increasing availability of high resolution topographic data opens up the possibility of more rapid and spatially extensive assessments of key geomorphic processes which can readily be used to predict flood risk.