Yinxue Liu, Michel Wortmann, Laurence Hawker, Jeffrey Neal, Jiabo Yin, Marcus Suassuna Santos, Bailey Anderson, Richard Boothroyd, Andrew Nicholas, Greg Sambrook Smith, Philp J Ashworth, Hannah Cloke, Solomon Gebrechorkos, Julian Leyland, Boen Zhang, Ellie Vahidi, Helen Griffith, Pauline Delorme, Stuart James McLelland, Daniel R Parsons, Stephen E Darby, Louise Slater
Bankfull discharge, the maximum flow a river can convey before spilling over its banks, is central to modelling flood risk and understanding river-channel evolution. Global flood inundation models assume a 2-year return period for bankfull conditions, but this assumption remains untested globally. Here we use observations and machine learning to estimate bankfull discharge at ~1-km resolution along a recently developed global river network. We show that the widely used 2-year discharge reasonably approximates bankfull-flow magnitude, but bankfull return periods vary substantially within and across climate zones. Bankfull conditions occur more frequently in tropical and temperate regions (median return periods of 1.5 and 1.8 years; interquartile ranges of 2.5 and 3.2 years, respectively) and less frequently in cold and arid regions (2.8 and 4.3 years; interquartile ranges of 4.8 and 6.0 years). This variation across climate zones provides a basis for improving the representation of channel capacity in global flood models.