Rectilinear Inverse Distance Weighting Methodology for Bathymetric Cross-Section Interpolation along the Mississippi River

Abstract

In frequently monitored fluvial systems, such as the middle Mississippi River, large databases of hundreds of cross-section surveys are often needed for assessment of long-term morphologic change and contributing hydraulic parameters. Developing customized interpolation schemes with optimized coefficients for each survey in such large databases is impractical. Using a database of 158 cross-section bathymetric surveys of the middle Mississippi River, automated surface generation of commonly available interpolation algorithms, [i.e., triangulated irregular networks (TIN), inverse distance weighting (IDW), spline with tension, and ordinary kriging] were evaluated and compared with an interpolation algorithm developed for this database, termed rectilinear IDW (RIDW). TIN and RIDW interpolation algorithms had the lowest root-mean square error (RMSE) among all methods evaluated, with the largest difference between them occurring along the perimeter of the interpolated surfaces. TIN interpolation resulted in sharp, geometric edges along the boundaries of the interpolated surfaces requiring postprocessing, whereas RIDW interpolation produced smoother edges that sometimes elongated scour holes.