A data-driven method for the determination of water-flow velocity in watershed modelling
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Abstract
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.
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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.27155v1Author comment
This is a conference submission to Geomorphometry 2018, 13-17 August 2018, Boulder, CO, USA
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Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Qiming Zhou conceived and designed the experiments, authored or reviewed drafts of the paper, approved the final draft.
Fangli Zhang conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper.
Liang Cheng contributed reagents/materials/analysis tools.
Data Deposition
The following information was supplied regarding data availability:
The research in this article did not generate any data or code.
Funding
This work was supported by the National Natural Science Foundation of China (41471340 and No. 41301403). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
