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Analysis of the Effect of Uncertainty in Rainfall-Runoff Models on Simulation Results Using a Simple Uncertainty-Screening Method
被引:3
|作者:
Shin, Mun-Ju
[1
]
Kim, Chung-Soo
[2
]
机构:
[1] Jeju Prov Dev Corp, Water Resources Res Team, 1717-35 Namjo Ro, Jeju Si 63345, Jeju Do, South Korea
[2] Korea Inst Civil Engn & Bldg Technol, Dept Land Water & Environm Res, 283 Goyangdae Ro, Goyang Si 10223, Gyeonggi Do, South Korea
来源:
WATER
|
2019年
/
11卷
/
07期
关键词:
uncertainty analysis;
rainfall-runoff model;
DREAM algorithm;
indicators of hydrologic alterations;
equifinality;
SENSITIVITY;
EQUIFINALITY;
CALIBRATION;
EVOLUTION;
D O I:
10.3390/w11071361
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Various uncertainty analysis methods have been used in various studies to analyze the uncertainty of rainfall-runoff models; however, these methods are difficult to apply immediately as they require a long learning time. In this study, we propose a simple uncertainty-screening method that allows modelers to investigate relatively easily the uncertainty of rainfall-runoff models. The 100 best parameter values of three rainfall-runoff models were extracted using the efficient sampler DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, and the distribution of the parameter values was investigated. Additionally, the ranges of the values of a model performance evaluation statistic and indicators of hydrologic alteration corresponding to the 100 parameter values for the calibration and validation periods was analyzed. The results showed that the Sacramento model, which has the largest number of parameters, had uncertainties in parameters, and the uncertainty of one parameter influenced all other parameters. Furthermore, the uncertainty in the prediction results of the Sacramento model was larger than those of other models. The IHACRES model had uncertainty in one parameter related to the slow flow simulation. On the other hand, the GR4J model had the lowest uncertainty compared to the other two models. The uncertainty-screening method presented in this study can be easily used when the modelers select rainfall-runoff models with lower uncertainty.
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页数:24
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