A data-driven method for the determination of water-flow velocity in watershed modelling
- Subject Areas
- Computational Science, Spatial and Geographic Information Science
- geomorphometry, digital elevation model, terrain analysis, hydrological modelling, flow velocity, watershed
- © 2018 Zhou et al.
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. A data-driven method for the determination of water-flow velocity in watershed modelling. PeerJ Preprints 6:e27155v1 https://doi.org/10.7287/peerj.preprints.27155v1
Physically-based distributed hydrological models have always played an important role in watershed hydrology. Existing hydrological modeling applications focused more on the estimation of water balance and less on the simulation of water transportation in a catchment. Different from the prediction of flow production, the dynamic simulation of flow concentration depends largely on the field distribution of water-flow velocity. However, it is still difficult to determine the water-flow velocity with terrain analysis techniques, which had always hampered the application of hydrological models in surface water transportation simulation. This study, therefore, proposes a data-driven method for creating a field map of overland flow velocity based on the Manning’s equation. Case study on a gauged watershed is undertaken to validate the spatial distribution of flow velocity. The preliminary results indicate that the proposed empirical method can reasonably determine the spatial distribution of water-flow velocity. Further efforts are still required to support the space-time change of flow velocity under the control of microtopography and instantaneous water depth.
This is a conference submission to Geomorphometry 2018, 13-17 August 2018, Boulder, CO, USA