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- Title
A novel method for flood forecasting based on the nonlinear computational units cascaded model.
- Authors
Wang, Chun-Ming; Lin, Gwo-Fong
- Abstract
To facilitate flood forecasting (FF), a novel method based on the nonlinear computational units cascaded (NCUC) model is proposed in this paper. The proposed method is named the NCUC-FF method. The NCUC-FF method overcomes the shortcomings of two types of methods, respectively, based on the artificial neural networks and the conventional rainfall-runoff models. The NCUC-FF method uses only the rainfall records as input to produce accurate forecasts of runoff, and it has an automated calibration method. These are the two distinctive features of the NCUC-FF method. Furthermore, the NCUC-FF method is flexible to meet the modelers' requirements. Modelers can freely choose the pattern of the NCUC model within the NCUC-FF method. Actual applications of the NCUC-FF method for FF are also presented in this paper. The results show that the performance of the NCUC-FF method is outstanding. It is concluded that the NCUC-FF method is useful for FF.
- Subjects
FLOOD forecasting; ARTIFICIAL neural networks; RAINFALL; NONLINEAR systems; CALIBRATION
- Publication
Paddy & Water Environment, 2015, Vol 13, Issue 1, p115
- ISSN
1611-2490
- Publication type
Article
- DOI
10.1007/s10333-013-0413-z