Title: Sensitivity and uncertainty-based evaluation and simulation of MIKE SHE model in Guishui River Basin, Beijing, China
Authors: Jing Zhang; Zhen Zheng; Binbin Guo
Addresses: The Key Lab of Resource Environment and GIS of Beijing, Capital Normal University, #105 West 3rd Ring Road North, Beijing, 100048, China ' Fuzhou Environmental Science Research Institute, #32 Jinjishan Road Jinan District, Fuzhou, 350011, China ' The Key Lab of Resource Environment and GIS of Beijing, Capital Normal University, #105 West 3rd Ring Road North, Beijing, 100048, China
Abstract: In the process of building a hydrological model, some basin feature parameters are expressed inaccurately. It is an important way to construct models and estimate the uncertainty parameters for evaluating the uncertainty of the overall output. In this paper, an uncertainty-based study was calibrated and evaluated the comprehensive distributed model MIKE SHE to hydrological data in the Guishui River Basin, Beijing of China. The generalised likelihood uncertainty estimation (GLUE) method was used to quantify uncertainties originating from the use of discharge observations and the presence of equifinal solutions. Monte Carlo sampling is randomly generated to 10,000 parameter sets during GLUE calibration. MIKE SHE parameter sets are identified and 5% and 95% uncertainty bounds for monthly streamflow are calculated. The behavioural values of nine individual parameters for MIKE SHE were explored against the likelihood measure values. The results show that more than 50% observations in calibration period fell within the corresponding uncertainty bounds, suggesting a similar level of model performance. The simulation results are corresponded better with the measured flow, but still need to be improved for higher accuracy. There are some relative sensitive and insensitive parameters in the result of uncertainty analysis.
Keywords: MIKE SHE model; semi-arid basin; streamflow simulation; uncertainty; generalised likelihood uncertainty estimation; GLUE; Monte Carlo; China.
International Journal of Water, 2017 Vol.11 No.2, pp.103 - 113
Received: 25 Sep 2014
Accepted: 25 Sep 2015
Published online: 12 Apr 2017 *