A novel image analysis technique for measuring river surface flow is proposed. When we assume that the brightness distribution of river surface image is convected with the surface velocity, a space-time image for a searching line set parallel to the main flow would indicate velocity information as its image orientation. The new technique, the space-time image velocimetry (STIV), is capable to measure the orientation angle of the pattern using the eigenvalue analysis of the local space-time image. The performance of STIV is compared with the other image analysis technique, the large-scale particle image velocimetry (LSPIV), previously proposed by the authors and it is shown that STIV is an alternative image analysis method for measuring streamwise velocity distributions efficiently.

In this paper, the results of a benchmark test launched within the framework of the NSF–PIRE project “Modelling of Flood Hazards and Geomorphic\ud Impacts of Levee Breach and Dam Failure” are presented. Experiments of two-dimensional dam-break flows over a sand bed were conducted at\ud Université catholique de Louvain, Belgium. The water level evolution at eight gauging points was measured as well as the final bed topography.\ud Intense scour occurred close to the failed dam, while significant deposition was observed further downstream. From these experiments, a benchmark\ud was proposed to the scientific community, consisting of blind test simulations, that is, without any prior knowledge of the measurements. Twelve\ud different teams of modellers from eight countries participated in the study. Here, the numerical models used in this test are briefly presented. The results\ud are commented upon, in view of evaluating the modelling capabilities and identifying the challenges that may open pathways for further research

In this study, a closed-circuit television (CCTV) system, installed for surveillance purposes, is utilized to measure the flow rate during a flood. The procedure to determine both the angle and scale-factor of the camera is described. Then, image analysis techniques, namely the direct visual measurement method, Large-Scale PIV (LSPIV) and Space-Time Image Velocimetry (STIV), are applied to the video images recorded by the CCTV camera. The results of these methods and the conventional float measurement are compared. In addition, the accuracy of the respective methods is discussed. A set of low-quality video images of a flood during a thunderstorm that occurred under the dark ambient conditions (midnight) is analyzed using three image-based methods. The transition of the flow rate during the event is successfully estimated.

Abstract:Inundation disasters, caused by sudden water level rise or rapid flow, occur frequently in various parts of the world. Such catastrophes strike not only in thinly populated flood plains or farmland but also in highly populated villages or urban areas. Inundation of the populated areas causes severe damage to the economy, injury, and loss of life; therefore, a proper management scheme for the disaster has to be developed. To predict and manage such adversity, an understanding of the dynamic processes of inundation flow is necessary because risk estimation is performed based on inundation flow information. In this study, we developed a comprehensive method to conduct detailed inundation flow simulations for a populated area with quite complex topographical features using LiDAR (Light Detection and Ranging) data. Detailed geospatial information including the location and shape of each building was extracted from the LiDAR data and used for the grid generation. The developed approach can distinguish buildings from vegetation and treat them differently in the flow model. With this method, a fine unstructured grid can be generated representing the complicated urban land features precisely without exhausting labour for data preparation. The accuracy of the generated grid with different grid spacing and grid type is discussed and the optimal range of grid spacing for direct representation of urban topography is investigated. The developed method is applied to the estimation of inundation flows, which occurred in the basin of the Shin-minato River. A detailed inundation flow structure is represented by the flow model, and the flow characteristics with respect to topographic features are discussed.

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