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Mathematical Problems in Engineering
Volume 2014, Article ID 985054, 9 pages
http://dx.doi.org/10.1155/2014/985054
Research Article

Effect of Baseflow Separation on Uncertainty of Hydrological Modeling in the Xinanjiang Model

1Department of Water Resources and Environment, Sun Yat-sen University, 135 Xingangxi Road, Guangzhou 510275, China
2Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute, Sun Yat-sen University, 135 Xingangxi Road, Guangzhou 510275, China
3Illinois State Water Survey, The Prairie Research Institute, University of Illinois at Urbana-Champaign, 2204 Griffith Drive, Champaign, IL 61820, USA

Received 14 March 2014; Accepted 18 June 2014; Published 15 July 2014

Academic Editor: Manfred Krafczyk

Copyright © 2014 Kairong Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Based on the idea of inputting more available useful information for evaluation to gain less uncertainty, this study focuses on how well the uncertainty can be reduced by considering the baseflow estimation information obtained from the smoothed minima method (SMM). The Xinanjiang model and the generalized likelihood uncertainty estimation (GLUE) method with the shuffled complex evolution Metropolis (SCEM-UA) sampling algorithm were used for hydrological modeling and uncertainty analysis, respectively. The Jiangkou basin, located in the upper of the Hanjiang River, was selected as case study. It was found that the number and standard deviation of behavioral parameter sets both decreased when the threshold value for the baseflow efficiency index increased, and the high Nash-Sutcliffe efficiency coefficients correspond well with the high baseflow efficiency coefficients. The results also showed that uncertainty interval width decreased significantly, while containing ratio did not decrease by much and the simulated runoff with the behavioral parameter sets can fit better to the observed runoff, when threshold for the baseflow efficiency index was taken into consideration. These implied that using the baseflow estimation information can reduce the uncertainty in hydrological modeling to some degree and gain more reasonable prediction bounds.