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Improvement and comparison of likelihood functions for model calibration and parameter uncertainty analysis within a Markov chain Monte Carlo scheme
•The NSE is equivalent to a log-likelihood function with Gaussian I.I.D. residuals.•Minimum variance constraint effectively estimates the parameter of BC transformation.•NSE puts emphasis on high flow owing to the assumption of Gaussian error distribution.•The BC-GED and BC-SGED approaches all put g...
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Published in: | Journal of hydrology (Amsterdam) 2014-11, Vol.519 (Part B), p.2202-2214 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •The NSE is equivalent to a log-likelihood function with Gaussian I.I.D. residuals.•Minimum variance constraint effectively estimates the parameter of BC transformation.•NSE puts emphasis on high flow owing to the assumption of Gaussian error distribution.•The BC-GED and BC-SGED approaches all put greater emphasis on baseflow.•The assumption of skewness of the error distribution may be unnecessary.
In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash–Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box–Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions—NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)—are applied for SWAT-WB-VSA (Soil and Water Assessment Tool – Water Balance – Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach. |
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ISSN: | 0022-1694 1879-2707 1879-2707 |
DOI: | 10.1016/j.jhydrol.2014.10.008 |