Abstract:GLUE(Generalized Likelihood uncertainty Estimation) is a very wide-used methodology for uncertainty analysis of hydrological model. How to select an appropriate likelihood measure is still an open question so far. Usually the Nash-Sutcliffe coefficient is a traditional likelihood measure

but this measure focuses on the global performance without a special assessment in point condition especially for flood peak. A multi-criteria likelihood measure is presented within GLUE methodology

which consists of peak forecast error

runoff error

peak time error

and Nash-Sutcliffe coefficient. Based on the DHF(Da Huofang)model

it was applied to Biliuhe catchment. Forecasting error analysis was deduced. The results show the multi-criteria likelihood measure has improved compared with the original measure in describing the real uncertainty of model

which is very valuable for model calibration and uncertainty study.