TY - JOUR
T1 - Real-time probabilistic forecasting of flood stages
AU - Chen, Shien Tsung
AU - Yu, Pao Shan
N1 - Funding Information:
The authors would like to thank the National Science Council, Taiwan for financially supporting this research under Contract Nos. NSC 92-2625-Z-006-003, NSC 93-2625-Z-006-001 and NSC 94-2625-Z-006-001.
Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2007/6/30
Y1 - 2007/6/30
N2 - This study is to perform real-time probabilistic flood stage forecasting. The proposed method consists of a deterministic stage forecast derived from the support vector regression, and a probability distribution of forecast error based on the fuzzy inference model. The probabilistic flood stage forecasts can then be obtained by combining the deterministic stage forecasts with the error probability distributions. The proposed approach is applied to the Lang-Yang River in Taiwan pertaining to validation events of six flash floods. The probability distributions of stage forecasts 1-6 h ahead are made, and the predictive uncertainty information is presented and discussed in various aspects. Forecasting results examined by forecast hydrographs with a 95% confidence interval, and the percentages of data included in the confidence region, indicate the effectiveness of the proposed methodology.
AB - This study is to perform real-time probabilistic flood stage forecasting. The proposed method consists of a deterministic stage forecast derived from the support vector regression, and a probability distribution of forecast error based on the fuzzy inference model. The probabilistic flood stage forecasts can then be obtained by combining the deterministic stage forecasts with the error probability distributions. The proposed approach is applied to the Lang-Yang River in Taiwan pertaining to validation events of six flash floods. The probability distributions of stage forecasts 1-6 h ahead are made, and the predictive uncertainty information is presented and discussed in various aspects. Forecasting results examined by forecast hydrographs with a 95% confidence interval, and the percentages of data included in the confidence region, indicate the effectiveness of the proposed methodology.
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U2 - 10.1016/j.jhydrol.2007.04.008
DO - 10.1016/j.jhydrol.2007.04.008
M3 - Article
AN - SCOPUS:34249895257
VL - 340
SP - 63
EP - 77
JO - Journal of Hydrology
JF - Journal of Hydrology
SN - 0022-1694
IS - 1-2
ER -