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 varying 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
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 varying 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
Original language | English |
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Pages (from-to) | 955-972 |
Number of pages | 18 |
Journal | Earth Surface Dynamics |
Volume | 8 |
DOIs | |
Publication status | Published - 16 Nov 2020 |
Keywords
- landscape scale experiments
- hydrodynamic model
- estuary
- meandering river
- braided river