Publication Date:
2014-10-19
Description:
With the recent development of distributed hydrological models, the use of multi-site observed data to evaluate model performance is becoming more common. Distributed hydrological model have many advantages, at the same time it also faces the challenge to calibrate over-do parameters. As a typical distributed hydrological model, SWAT parameter calibration also exist problems. In the paper, four different uncertainty approaches Particle Swarm Optimization (PSO) techniques, Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting algorithm (SUFI-2) and Parameter Solution (PARASOL) are taken to comparative study with SWAT model applied in Peace River Basin, central Florida. In our study, the observed river discharge data used in SWAT model calibration were collected from the three gaging stations at the main tributary of the Peace River. Behind these approaches there is a shared philosophy, all methods seek out many parameter set to fit the uncertainties due to the non-uniqueness in model parameter evaluation. Based on the statistical results of four uncertainty methods, difficulty level of each method, the number of runs and theoretical basis, the reasons affected the accuracy of simulation were analyzed and compared. Furthermore, for the four uncertainty method with SWAT model in the study area, the pair-wise correlation between parameters and the distributions of model fit summary statistics computed from the sampling over the behavioral parameter and entire model calibration parameter feasible spaces were identified and examined. It provided additional insight into the relative identifiability of the four uncertainty methods This article is protected by copyright. All rights reserved.
Print ISSN:
0885-6087
Electronic ISSN:
1099-1085
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
