Obtaining the Manning roughness with terrestrialremote sensing technique and flood modeling using FLO-2D

Abstract

Determining the Manning roughness coefficients is one of the most important steps in flood modeling. The roughness coefficients cause differences in flood areas, water levels, and velocities in the process of modeling. This study aims to determine both the Manning roughness coefficient in the river sections and outside of the river regions by using the Cowan method and remote sensing technique in the flood modeling. In the flood modeling, FLO-2D Pro program which can simulate flood propagation in two dimensions was utilized. Mert River in Samsun province located in the northern part of Turkey was chosen as the study area. Samples taken from the river were subjected to sieve analysis, the types of constituent material were determined according to the median diameters and the roughness coefficients were obtained using the Cowan method. For regions outside of the river were applied the maximum likelihood method being one of the controlled classification methods. Manning roughness values were assigned the classified image sections. Remote sensing techniques were meticulously employed to achieve time management in areas outside the river and a new approach was proposed in the Manning assessment of flood areas to ensure uniformity in the study area. In the classification made using the maximum likelihood method, the overall classification accuracy was 92.9% and the kappa ratio “κ” was 90.64%. The results were calibrated with the last hazardous flood images in 2012 and HEC-RAS 2D program, another flood modeling program.