Preprints
https://doi.org/10.5194/gmd-2022-234
https://doi.org/10.5194/gmd-2022-234
Submitted as: development and technical paper
10 Oct 2022
Submitted as: development and technical paper | 10 Oct 2022
Status: this preprint is currently under review for the journal GMD.

An improved subgrid channel model with upwind form artificial diffusion for river hydrodynamics and floodplain inundation simulation

Youtong Rong, Paul Bates, and Jeffrey Neal Youtong Rong et al.
  • School of Geographical Sciences, University of Bristol, Bristol, BS8 1QU, UK

Abstract. An accurate estimation of river channel conveyance capacity and the water exchange at the river-floodplain interfaces is pivotal for flood modelling. However, in large-scale models limited grid resolution often means that small-scale river channel features cannot be well represented in traditional 1D/2D schemes. As a result instability over river and floodplain boundaries can occur, and flow connectivity, which has a strong control on the floodplain hydraulics, is not well-approximated. A subgrid channel model (SGC) based on the local inertial form of the shallow water equations, which allows utilization of approximated sub-grid scale bathymetric information while performing very efficient computations has been proposed as a solution, and it has been widely applied to calculate the wetting and drying dynamics in river-floodplain systems at regional scales. Unfortunately, SGC approaches to date have not included latest developments in numerical solutions of the local inertial equations, and the original solution scheme was reported to suffer from numerical instability in low friction regions such as urban areas. In this paper, for the first time, we implement a newly developed diffusion and explicit adaptive weighting factor in the SGC model. An adaptive artificial diffusion is explicitly included in the form of an upwind solution scheme based on the local flow status to improve the numerical flux estimation. A structured sequence of numerical experiments is performed, and the results confirm that the new SGC model improved the model performance in terms of water level and inundation extent, especially in urban areas where the Manning parameter is less than 0.03 m−1/3 s. By not compromising computational efficiency, this improved SGC model is a compelling alternative for river-floodplain modelling, particularly in large-scale applications.

Youtong Rong et al.

Status: open (until 03 Jan 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Youtong Rong et al.

Youtong Rong et al.

Viewed

Total article views: 337 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
287 45 5 337 3 3
  • HTML: 287
  • PDF: 45
  • XML: 5
  • Total: 337
  • BibTeX: 3
  • EndNote: 3
Views and downloads (calculated since 10 Oct 2022)
Cumulative views and downloads (calculated since 10 Oct 2022)

Viewed (geographical distribution)

Total article views: 326 (including HTML, PDF, and XML) Thereof 326 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Dec 2022
Download
Short summary
A novel subgrid channel model (SGC) is developed for river-floodplain modelling, allowing utilization of sub-grid scale bathymetric information while performing computations on relatively coarse grids. By including an adaptive artificial diffusion, potential numerical instability, which the original SGC solver had, in low friction regions such as the urban areas is addressed. Evaluation of the new SGC model through a structured tests confirmed that the accuracy and stability has been improved.