When One Becomes Many: Including Complex Channel Systems in Large Scale Flood Models

Over 70% of flood events recorded in the past two decades in the Global Flood Database and WorldFloods dataset have occurred in locations where complex channel systems occur. Here we define complex channel systems as parts of the river network that diverge, such as bifurcations, multi-threaded channels, canals and deltas. Yet, large scale flood models have, until now, used only single-threaded networks due to the lack of a river network that reflects complex channel systems . Therefore, these large-scale models fundamentally misrepresent the physical processes in these often highly populated areas, leading to sub-optimal estimates of flood risk.Using the new Global River Topology (GRIT) dataset, a global bifurcation and multi-directional river network (Wortmann et al. 2023), we extend the river channel bathymetry estimation routine of Neal et al. (2021) to model multi-channels with LISFLOOD-FP. We compare the multi-thread model results to observations and to previous versions of LISFLOOD-FP using a single-threaded river network in the Indus, Mekong and Niger rivers at 1 arc second (~30m). By using GRIT, we find marked improvements in model results, observing better connectivity to areas of the floodplain that are far from the main channel and more channel floodplain interactions in wetlands. This work paves the way to further our understanding of global flood risk and to finally consider the diverse, evolving nature of geomorphologically active river networks. As this work progresses, we will continue to model a typology of bifurcations and multi-directional rivers to help further our understanding of the significance of complex river systems.Neal, J., Hawker, L., Savage, J., Durand, M., Bates, P., & Sampson, C. (2021). Estimating river channel bathymetry in large scale flood inundation models. Water Resources Research, 57(5), e2020WR028301.Wortmann, M., Slater, L., Hawker, L., Liu, Y., & Neal, J. (2023). Global River Topology (GRIT) (0.4) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7629908