TY - JOUR
T1 - Effect of the Likelihood Function on the Calibration of the Effective Manning Roughness Factor
AU - Cedillo Galarza, Juan Sebastián
AU - Vázquez Patiño, Ángel Oswaldo
AU - Sánchez-Cordero, Andrés
AU - Duque-Sarango, Paola
AU - Sánchez Cordero, Esteban Remigio
AU - Cedillo Galarza, Juan Sebastian
N1 - Publisher Copyright:
© 2024 by the authors.
PY - 2024/10
Y1 - 2024/10
N2 - Hydrodynamic models (HMs) are tools for simulating flow behavior through the solution of conservation equations. These equations can have different degrees of simplification, which influence the model structure. One-dimensional (1D) HMs are still popular due to their simplicity. A crucial parameter for obtaining accurate 1D HM outputs is the effective Manning roughness factor (EMRF). The EMRF reflects additional numerical and dissipative aspects beyond boundary roughness. Although generalized likelihood uncertainty estimation (GLUE) is an important method for uncertainty analysis, it requires the selection of a likelihood function and a cutoff threshold. The goal of this study was to determine the effect of the likelihood function on the EMRF characteristics for mountain river morphologies, considering a certain cutoff threshold. The results show that the error model and the treatment of the residual in the objective function affect the EMRF range and limits in the studied reaches with a cascade or step pool. Furthermore, the analysis shows that these morphologies deviate from the model structure, which may affect the likelihood curve shape. Notably, the EMRF and measured roughness did not intersect in the studied reach with a plane bed, which is attributed to the presence of vegetation on the banks of that reach.
AB - Hydrodynamic models (HMs) are tools for simulating flow behavior through the solution of conservation equations. These equations can have different degrees of simplification, which influence the model structure. One-dimensional (1D) HMs are still popular due to their simplicity. A crucial parameter for obtaining accurate 1D HM outputs is the effective Manning roughness factor (EMRF). The EMRF reflects additional numerical and dissipative aspects beyond boundary roughness. Although generalized likelihood uncertainty estimation (GLUE) is an important method for uncertainty analysis, it requires the selection of a likelihood function and a cutoff threshold. The goal of this study was to determine the effect of the likelihood function on the EMRF characteristics for mountain river morphologies, considering a certain cutoff threshold. The results show that the error model and the treatment of the residual in the objective function affect the EMRF range and limits in the studied reaches with a cascade or step pool. Furthermore, the analysis shows that these morphologies deviate from the model structure, which may affect the likelihood curve shape. Notably, the EMRF and measured roughness did not intersect in the studied reach with a plane bed, which is attributed to the presence of vegetation on the banks of that reach.
KW - effective roughness
KW - GLUE
KW - mountain rivers
KW - Effective roughness
KW - Mountain rivers
KW - GLUE
UR - https://www.scopus.com/pages/publications/85207486874
UR - https://www.mdpi.com/2073-4441/16/20/2879
U2 - 10.3390/w16202879
DO - 10.3390/w16202879
M3 - Artículo
AN - SCOPUS:85207486874
SN - 2073-4441
VL - 16
SP - 1
EP - 14
JO - Water (Switzerland)
JF - Water (Switzerland)
IS - 20
M1 - 2879
ER -