Use of terrestrial photosieving and airborne topographic LiDAR to assess bed grain size in large rivers: a study on the Rhine River. Issue 10 (10th June 2020) - Chardon, Valentin; Schmitt, Laurent; Piégay, Hervé; Lague, Dimitri
Abstract: Most grain size monitoring is still being conducted by manual sampling in the field, which is time consuming and has low spatial representation. Due to new remote sensing methods, some limitations have been partly overcome, but methodological progress is still needed for large rivers as well as in underwater conditions. In this article, we tested the reliability of two methods along the Old Rhine River (France/Germany) to estimate the grain size distribution (GSD) in above‐water conditions: (i) a low‐cost terrestrial photosieving method based on an automatic procedure using Digital Grain Size (DGS) software and (ii) an airborne LiDAR topo‐bathymetric survey. We also tested the ability of terrestrial photosieving to estimate the GSD in underwater conditions. Field pebble counts were performed to compare and calibrate both methods. The results showed that the automatic procedure of terrestrial photosieving is a reliable method to estimate the GSD of sediment patches in both above‐water and underwater conditions with clean substrates. Sensitivity analyses showed that environmental conditions, including solar lighting conditions and petrographic variability, significantly influence the GSD from the automatic procedure in above‐water conditions. The presence of biofilm in underwater conditions significantly altered the GSD estimation using the automatic procedure, but the proposed manual procedure overcame this problem. The airborne LiDAR topographic survey is an accurate method to estimate the GSD of above‐water bedforms and is able to generate grain size maps. The combination of terrestrial photosieving and airborne topographic LiDAR methods is adapted to assess the GSD over several kilometers long reaches of large rivers. © 2020 John Wiley & Sons, Ltd. Abstract : Spatial representation of the airborne terrestrial LiDAR and photo‐sieving sampling.