EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Morphodynamics of Lowland River Networks Modeled as Simple Binary Trees

Gary Parker1 and Li Zhang2
Gary Parker and Li Zhang
  • 1University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign, Dept. of Civil & Environmental Engineering and Dept. of Geology, Urbana, United States of America (
  • 2School of Civil and Hydraulic Enginering, Huazhong University of Science and Technology, Wuhan, China

River networks are ubiquitous in nature. The example of the Amazon River, South America, is shown below.

Typically, channel branches farther upstream tend to be steeper than branches farther downstream. Here we explain this tendency via a simple model of lowland sand-bed stream networks. Any given downstream branch bifurcates into two branches upstream, here each assumed to have discharges equal to half of the downstream branch. . Each branch satisfies (at bankfull flow) a relation each for flow resistance, sand transport and sediment mobility Shields number. We show that if the transport rate of sand increases downstream in proportion to the water discharge, the river slope must be the same everywhere, so that the long profile following any path shows no upward concavity. When the sand load increases downstream at a lower rate than the water discharge, on the other hand, upward concavity is manifested. The bifurcations are allowed to continue upstream until a specified drainage density is reached. The inverse of drainage density scales the distance from any channel to the nearest ridge; at an appropriately low value, it is assumed that sediment can be delivered to the nearest stream solely through overland processes. We use the above conditions to determine the extent of the spatial network, and also the spatial variation of network denudation rate.


How to cite: Parker, G. and Zhang, L.: Morphodynamics of Lowland River Networks Modeled as Simple Binary Trees, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6773,, 2022.