Diferencia entre fórmulas empíricas para la predicción del coeficiente de Manning físico y efectivo

Abstract

In this research, a comparison between effective and physical roughness parameters is carried out, together with an analysis of the performance of empirical equations for the prediction of the roughness coefficient. For this reason, three most common morphologies present in mountain rivers are used: Cascade, Plane-bed and Steep-pool. The physical roughness parameters were previously obtained from studies carried out by Cedillo et al., (2021a) in a study that includes multiple field measurements of various hydraulic variables. On the other hand, the effective roughness parameters were estimated from an analysis of the GLUE methodology implemented in the 1D hydrodynamic model in HECRAS. The estimation of these effective parameters was achieved from the analysis of the degree of adjustment of the model in relation to the field data called likelihood. The difference between the effective and physical coefficients depends on the magnitude of the flow and the morphology. In addition, a predictability analysis is performed through the use of various empirical equations to find the roughness coefficient: Bathurst, (1985) and Bathurst's semi-logarithmic equations, (2002), Nondimensional Hydraulic Geometry Equations (NDHG) established by Ferguson, (2007), Rickenmann & Recking, (2011), Cedillo et al., (2021a) and Cedillo et al., (2021b). Thus, the comparisons are made with both effective and physical parameters and the results are analyzed using the metrics: Absolute Error (MAE), Root Mean Square Error (RMSE) and Efficiency (Ef). The results show that the Nondimensional Hydraulic Geometry Equations (NDHG) present better predictability compared to the exponential and semilogarithmic equations. The equation established of Cedillo et al., (2021b) that was calibrated with the physical roughness data has a better predictability than those obtained by (Ferguson, 2007) and (Rickenmann & Recking, 2011). For the case of effective roughness, the equation established of Cedillo et al., (2021b) for Plane-bed and Step-pool has better performance than those proposed by (Ferguson, 2007) and (Rickenmann & Recking, 2011). On the other hand, regarding a comparison of likelihood curves with the results of Pappenberger, Beven, Horritt, & Blazkova, (2005), the curves obtained in this research have similarity in a type of curve analyzed by Pappenberger, Beven, Horritt, & Blazkova, (2005) where a well-defined maximum value is used as the effective roughness coefficient