Application of a line laser scanner for bed form tracking in a laboratory flume

(a) Picture of the line laser scanner measuring a profile. The red light on the profile is the line emitted by the laser. (b) Overview of the experimental set‐up. Red lines indicate transmitted laser beams and yellow lines indicate reflected laser beams, measured by the camera. (Source: Figure 1; de Ruijsscher et al. 2018;


A new measurement method for continuous detection of bed forms in movable bed laboratory experiments is presented and tested. The device consists of a line laser coupled to a 3‐D camera, which makes use of triangulation. This allows to measure bed forms during morphodynamic experiments, without removing the water from the flume. A correction is applied for the effect of laser refraction at the air‐water interface. We conclude that the absolute measurement error increases with increasing flow velocity, its standard deviation increases with water depth and flow velocity, and the percentage of missing values increases with water depth. Although 71% of the data is lost in a pilot moving bed experiment with sand, still high agreement between flowing water and dry bed measurements is found when a robust LOcally weighted regrESSion (LOESS) procedure is applied. This is promising for bed form tracking applications in laboratory experiments, especially when lightweight sediments like polystyrene are used, which require smaller flow velocities to achieve dynamic similarity to the prototype. This is confirmed in a moving bed experiment with polystyrene.

Distributed under the Creative Commons Attribution License (CC BY).



Journal publication

de Ruijsscher, T. V., Hoitink, A. J. F., Dinnissen, S., Vermeulen, B., & Hazenberg, P. (2018). Application of a Line Laser Scanner for Bed Form Tracking in a Laboratory Flume. Water Resources Research, 54(3), 2078–2094.

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Replication dataset

This replication dataset contains the data of the the flume experiment and the Matlab scripts to process line laser scanner data and to perform statistical analysis.


Modeling tool

The numerical implementation of the LOESS algorithm in Matlab and C++ is open source and can be found on


Search categories

Data-collection methods: Physical and laboratory experiments |

Management goals: Hydrodynamic understanding | Morphological understanding |

Spatial scale: Reach |

Related organisations

Last modified: 01/07/2018


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Timo de Ruijsscher

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