Exploring accuracy of statistical characterization of gravel beds using Kinect device in the laboratory scale

Mountainous river beds generally consist of gravel particles that the precise description of such bed is not only important hydraulically, but also it has great environmental significance. The accurate estimation of bed roughness gives us valuable information to make reliable hydraulic models of flow in river with rigorous bed form. This study focuses on the accuracy of the Kinect device in determining the digital elevation model (DEM) of the gravel-bed. In this regard, the DEMs of two beds include hemispheres and two beds with artificial gravel beds have been used and their statistical characteristics have been analyzed. The results show that while the error in the area among the particles is quite high, the method can accurately conduct these in general. The comparison of the bed elevation histograms shows that although the artificial gravel beds histograms have higher accuracy compared to the histograms of the beds with hemispheres form, the gravel bed with distance elevations histogram shows the best fit among the four explored beds. Furthermore, exploring the statistical characteristics of these four beds show that the Kinect device is able to obtain reasonable error rate in statistical parameters except the skewness quantity which has the highest rate of relative error. The variogram analysis of artificial gravel beds emphasis that the Kinect and scanner variograms reasonably close to each other and the longitudinal and transversal particles length scales are exactly the same. According to the results of this investigation, application of the Kinect device in statistical analysis of the gravel beds can be suggested.