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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/esurf-2020-14
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-2020-14
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Mar 2020

17 Mar 2020

Review status
A revised version of this preprint is currently under review for the journal ESurf.

Implementing a hydrodynamic model to complement water depth and flow velocity data for physical scale experiments of rivers and estuaries

Steven A. H. Weisscher1, Marcio Boechat-Albernaz1, Jasper R. F. W. Leuven1, Wout M. Van Dijk1, Yasuyuki Shimizu2, and Maarten G. Kleinhans1 Steven A. H. Weisscher et al.
  • 1Faculty of Geosciences, Utrecht University, Princetonlaan 8A, 3584 CB, Utrecht, the Netherlands
  • 2Faculty of Engineering, Hokkaido University, North 13, West 8, Kitaku, Sapporo, Hokkaido, 080-8628, Japan

Abstract. Physical scale experiments enhance our understanding of fluvial, tidal and coastal processes. However, it has proven challenging to acquire accurate and continuous data on water depth and flow velocity due to limitations of the measuring equipment and necessary simplifications during post-processing. A novel means to augment measurements is to numerically model flow over the experimental digital elevation models. We investigated to what extent the numerical hydrodynamic model Nays2D can reproduce unsteady, nonuniform shallow flow in scale experiments and under which conditions a model is preferred to measurements. To this end, we tested Nays2D for one tidal and two fluvial scale experiments and extended Nays2D to allow for flume tilting which is necessary to steer tidal flow. The modelled water depth and flow velocity closely resembled the measured data for locations where the quality of the measured data was most reliable, and model results may be improved by applying a spatially variable roughness. The implication of the experimental data-model integration is that conducting experiments requires fewer measurements and less post-processing in a simple, affordable and labour-inexpensive manner that results in continuous spatio-temporal data of better overall quality. Also, this integration will aid experimental design.

Steven A. H. Weisscher et al.

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Steven A. H. Weisscher et al.

Steven A. H. Weisscher et al.

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Latest update: 03 Aug 2020
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Short summary
Accurate and continuous data collection is challenging in physical scale experiments. A novel means to augment measurements is to numerically model flow over the experimental digital elevation maps. We tested this modelling approach for one tidal and two river scale experiments and showed that modelled water depth and flow velocity closely resemble the measurements. The implication is that conducting experiments requires fewer measurements and results in flow data of better overall quality.
Accurate and continuous data collection is challenging in physical scale experiments. A novel...
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