Calibration and Uncertainty Analysis of SWAP Model by using GLUE Method

Parameter uncertainty analysis of hydrological models and identifying the statistical characteristics of model output based on the relation between model inputs and parameters is one of the most important issues in hydrological modeling. In this study, the Generalized Likelihood Uncertainty Estimation (GLUE) was used for calibration and uncertainty analysis of soil hydraulic parameters of SWAP (Soil, Water, Atmosphere and Plant) agro-hydrological model based on measured soil moisture in a maize field in Borkhar area, Isfahan province. Results showed that the θr and Ks out of the six Van Genuchten-Mualem parameters, were the most non-identifiable parameters in calibration process and had much contribution into the soil moisture uncertainty in SWAP. Moreover, results confirmed that in Van Genuchten-Mualem equation, the soil hydraulic parameters are fitting parameters and fixing some of them during the calibration process was not realistic. Finally, results indicated that the GLUE method could successfully calibrate the model for soil moisture simulation during the growing season, with most of the measured data (about 75%) falling in the 95% confidence interval.