glue method

The aim of this study is the calibration and validation of the physical-empirical SLSM model for simulation of the snow depth in the Saghez synoptic station. For this purpose, essential daily meteorological data of the model for the time period of 1992-2014 were prepared from the Iranian Meteorological Organization and by applying the Generalized Likelihood Uncertainty Estimation (GLUE) method, that performed by considering 15 parameters and performing 15000 simulations and using both Coefficient of Determination and Nash-Sutcliffe Efficiency indices for evaluating the accuracy of the model, Calibration and validation of the model were performed for the 1992-2009 and 2010-2014 time periods, respectively. Calibration process of the model was led to extracting 108 behavioral simulations and for performing validation of the model, the median of the 108 behavioral simulations was considered as the final output of the model and compared with the measured snow depth data. The results of the model validation showed that in most of the cases, the calibrated SLSM model has an acceptable efficiency to following the fluctuations of the measured snow depth data but it partly underestimates high values of the snow depth.

The aim of this research was the evaluation of COUP Model for simulation of soil frost depth at Bijar synoptic station. The simulations were first carried out based on the default parameter values. Afterwards, 30 parameters that had a close relationship with soil frost depth were selected and calibration of the model was performed with adopting Generalized Likelihood Uncertainty Estimation (GLUE) method and simulations of the model for before and after calibration cases were compared. The periods of 1992-2006 and 2007-2009 were selected for model calibration and validation, respectively. On the basis of comparisons between model simulations and observations for soil temperatures at 20 and 50 cm depths and soil frost depth for before and after calibration, the results showed dramatically better performance after calibration compared with before that. The results of model validation showed a good correspondence between simulations and observations at more cases and the model simulations were able to follow observation fluctuations. However, some differences were available between simulations and observations. Some parts of differences are attributed to non-contribution of soil moisture data at calibration procedure and the other parts were attributed to uncertainties in model structure and its governing equations.