Effect of transect location, transect spacing and interpolation methods on river bathymetry accuracy

Abstract

Digital elevation models (DEMs) of river channel bathymetries are developed by interpolating elevations between data collected at discrete points or along transects. The accuracy of interpolated bathymetries depends on measurement error, the density and distribution of point data, and the interpolation method. Whereas point measurement errors can be minimized by selecting the most efficient equipment, the effect of data density and interpolation method on river bathymetry is relatively unknown. Thus, this study focuses on transect-based collection methods and investigates the effects of transect location, the spacing between transects, and interpolation methods on the accuracy of interpolated bathymetry. This is accomplished by comparing four control bathymetries generated from accurate and high resolution, sub-meter scale data to bathymetries interpolated from transect data extracted from the control bathymetries using two transect locating methods and four interpolation methods. The transect locating methods are a morphologically-spaced and an equally-spaced model. The four interpolation methods are Ordinary Kriging, Delaunay Triangulation, and Simple Linear, which are applied in curvilinear coordinates (Delaunay Triangulation is also applied in Cartesian coordinates), and Natural Neighbor only in Cartesian Coordinates. The bathymetric data were obtained from morphologically simple and complex reaches of a large (average bankfull width = 90 m) and a small (average bankfull width = 17 m) river. The accuracy of the developed DEMs is assessed using statistical analysis of the differences between the control and interpolated bathymetries and hydraulic parameters assessed from bankfull water surface elevations. Results indicate that DEM accuracy is not influenced by the choice of transect location method (with same averaged cross-section spacing) or a specific interpolation method, but rather by the coordinate system for which the interpolation method is applied and the spacing between transects. They also show negligible differences between the mean depths and surface areas calculated from bathymetries with dense or coarse spacing.

Influence of River Bed Elevation Survey Configurations and Interpolation Methods on the Accuracy of Lidar DTM-Based River Flow Simulations

“…All these results highlight the findings by previous researches, particularly those of Heritage et al (2009) and Glenn et al (2016), that the interpolated river bed accuracy is not influenced by the choice of a specific interpolation method but rather by the survey strategy or configuration. The large RMSEs for the RBCL configuration and the low RMSEs for the XS configuration confirm that as the data points become evenly spaced and covers more portions of the river, the resulting interpolated surfaces become more accurate.…”

“…Studies conducted by Goff and Nordfjord (2004) and Merwade et al (2006) have shown that commonly available interpolation methods such as triangulation, inverse distance weighting (IDW), splines or kriging yield inaccurate river bed topography. Glenn et al (2016) contended that the interpolated river bed accuracy is not influenced by the choice of a specific interpolation method but rather by the coordinate system for which the interpolation method is applied and the spacing between transects. Heritage et al (2009) also concluded that the choice of the interpolation method is less important, but argued that the accuracy of the interpolated surface is dependent on the survey strategy or configuration of data collection (Heritage et al, 2009).…”

Use of Bathymetric and LiDAR Data in Generating Digital Elevation Model over the Lower Athabasca River Watershed in Alberta, Canada

“…Water 2017, 9, 19 13 of 16 Figure 7 shows the DEM of the lower Athabasca River watershed. Note that the water bodies within the flood plain (i.e., data processed from LiDAR) were not included in the final DEM, which was beyond the scope of the current study.…”

“…• Glenn et al [19] investigated the effect of transect location, spacing, and interpolation methods in generating the river bathymetric surfaces in the Snake River and Bear Valley Creak in Idaho. High resolution aerial photographs and multi-beam SONAR survey data were used for the Snake River, and experimental advance airborne research LiDAR (EAARL) data were used for Bear Valley Creek.…”

Multiple Climate Change Scenarios and Runoff Response in Biliu River

“…The regional monthly temperature and precipitation of the study area are derived by linear interpolation of the nearest GCM data. Although it is simple, its precision is acceptable [26][27][28].…”