A simple innovative method for calibration of Manning’s roughness coefficient in rivers using a similarity concept

Abstract

Geometric characteristics and Manning’s roughness coefficient (n) are needed in steady and unsteady flow analysis in open channels and rivers. Various methods are used to estimate n of a river reach while there is always some uncertainty in its estimation. One of the methods for estimating n is its calibration using observed inflow and outflow hydrographs in a river reach. This calibration procedure is conducted by adjusting n such that the outflow hydrograph calculated by an adopted flow routing model matches the observed outflow hydrograph. The available calibration methods usually consider a uniform roughness along the reach of a river. In this study, a new method for calibration of n is presented that can recognize different regions with different n in a river reach even when only one recorded inflow and corresponding outflow hydrographs are available. In the proposed method, at first different cases are generated where, in each case, the river reach is divided into several sub-reaches in a systematic procedure. Then for each case, the n of all sub-reaches are optimized by using the Monte Carlo method and random search optimization. In the next step, the best case among all cases is identified by applying similarity criteria defined in this study. Finally, a clustering method is employed to identify different regions with different n values for the selected best case. The method was applied to some synthetic data and also Tiber river data and showed promising results.