Resumen
Manning?s roughness coefficient (nc" role="presentation">????nc
n
c
) is an important parameter characterizing the flow capacity of water transfer channels, and it is also an important and sensitive parameter in one-dimensional (1D) flow simulation. This study focused on the roughness inversion for datasets with different sequence lengths, time steps and anomalous data points. A case study was performed with the datasets of the Shandong Jiaodong Water Transfer Project under steady-state conditions. For sequence lengths, the datasets of 6, 12, 24, 40, 88, and 142 h were selected, all with a time step of 1 min. Subsequently, the time step was changed to 5, 10, 15, 30, 60, and 120 min for the 40 h dataset mentioned above. Finally, the flow data point under a certain moment was selected and changed by 10%, 20%, 30%, and 40% respectively. The results show that there is a quadratic relationship between the nc" role="presentation">????nc
n
c
value and the objective function value and the optimal nc" role="presentation">????nc
n
c
value is nc=−b/2a" role="presentation">????=-??/2??nc=-b/2a
n
c
=
-
b
/
2
a
. It is recommended that the nc" role="presentation">????nc
n
c
value retains four decimal places and is inverted using high-frequency and cleaned datasets.