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- Title
Uncertainty Analysis of Multiple Hydrologic Models Using the Bayesian Model Averaging Method.
- Authors
Leihua Dong; Lihua Xiong; Kun-xia Yu
- Abstract
Since Bayesian Model Averaging (BMA) method can combine the forecasts of different models together to generate a new one which is expected to be better than any individual model's forecast, it has been widely used in hydrology for ensemble hydrologic prediction. Previous studies of the BMA mostly focused on the comparison of the BMA mean prediction with each individual model's prediction. As BMAhas the ability to provide a statistical distribution of the quantity to be forecasted, the research focus in this study is shifted onto the comparison of the prediction uncertainty interval generated by BMAwith that of each individualmodel under two different BMA combination schemes. In the first BMA scheme, three models under the same Nash-Sutcliffe efficiency objective function are, respectively, calibrated, thus providing three-member predictions ensemble for the BMA combination. In the second BMA scheme, all three models are, respectively, calibrated under three different objective functions other than Nash- Sutcliffe efficiency to obtain nine-member predictions ensemble. Finally, the model efficiency and the uncertainty intervals of each individual model and two BMA combination schemes are assessed and compared.
- Subjects
HYDROLOGIC models; BAYESIAN analysis; HYDROLOGICAL forecasting; UNCERTAINTY; APPLIED mathematics; MATHEMATICAL analysis
- Publication
Journal of Applied Mathematics, 2013, p1
- ISSN
1110-757X
- Publication type
Article
- DOI
10.1155/2013/346045