2019
DOI: 10.1007/s10652-019-09670-4
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The influence of grid shape and grid size on hydraulic river modelling performance

Abstract: Grid shape (curvilinear/structured versus triangular/unstructured) and grid size affect model output. In this study structured, unstructured and hybrid grids with a high and low resolution were compared. As a case study, we use the Waal River (with main channel and floodplains). We studied simulated water levels using the six grids, considering equal main channel friction, which enabled to study the isolated effects of grid shape and size. The spread in simulated water levels was found to be rather large with … Show more

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Cited by 62 publications
(57 citation statements)
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“…The 2-D cells are a combination of curvilinear (in the main channels) and triangular grid cells. The grid creation was introduced and recommended by Bomers et al (2019) and Kernkamp et al (2011). The grid/element sizes vary from about 0.1 km in rivers to 3 km on the delta shelf.…”
Section: Grid Generation and Improvementmentioning
confidence: 99%
“…The 2-D cells are a combination of curvilinear (in the main channels) and triangular grid cells. The grid creation was introduced and recommended by Bomers et al (2019) and Kernkamp et al (2011). The grid/element sizes vary from about 0.1 km in rivers to 3 km on the delta shelf.…”
Section: Grid Generation and Improvementmentioning
confidence: 99%
“…The model is calibrated such that measured water levels are accurately predicted. Hydraulic model calibration is most commonly done by changing the roughness of the main channel until simulated water levels are close to measured water levels (Bomers et al 2019b). In this study, the same approach was used with the criterion that the calibration must lead to a maximum difference between measured and simulated water levels of 10 cm.…”
Section: Model Environmentmentioning
confidence: 99%
“…This hybrid grid overcomes the shortcomings of a curvilinear grid. It also reduces the computational time while model accuracy stays sufficient (Bomers et al, 2019). (Deltares, 2016).…”
Section: High-fidelity Modelmentioning
confidence: 99%
“…During calibration, this numerical grid generated friction will be compensated such that reliable water levels are predicted. Hydraulic model calibration is most commonly done by changing the roughness of the summer bed until simulated water levels are close to measured water levels (e.g Bomers et al (2019) and Caviedes-Voullième et al (2012)). In this study, the 265 same approach was used.…”
Section: High-fidelity Modelmentioning
confidence: 99%