Calibration of the rating curve is a challenge due to uncertainty in the parameters. This problem increases in an area with considerable seasonal vegetation diversity. In this study, the generalized likelihood uncertainty estimation (GLUE) method was combined with the proposed stage-discharge model, introduced by Maghrebi et al., to compute the parameter uncertainty of the rating curve in the Main River in the UK and the Colorado River in Argentina. In GLUE methodology, the sensitivity and uncertainty analysis of each parameter were investigated by comparing the prior and posterior distribution of the effective parameters in the proposed method. It should be noted that all the parameters studied in the proposed model, such as power function parameters (a1, a2, and a3) and Manning’s roughness coefficient can be acquired with an optimal parameter domain using the calibration method. The results demonstrated low sensitivity of roughness parameters and high sensitivity of power function parameter a1 in comparison with other parameters. In order to evaluate the uncertainty results, two average relative interval length (ARILCI) and the percent of observations bracketed by the 95CI (PCI95%) factors at 95% confidence level were used. The results showed that if the observational data were selected from the middle level, a more favorable result would be obtained and demonstrated less uncertainty in the output range of the model.

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