TY - JOUR
T1 - A statistical model for flood forecasting
AU - Zhao, J. H.
AU - Dong, Z. Y.
AU - Zhao, M. L.
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2009
Y1 - 2009
N2 - A statistical model is proposed in this paper that can be used for river stage forecasting. This model is able to handle the volatilities associated with the data used in flood forecasting. Different from conventional flood forecasting methods, this model works well with fatter-tail distribution and volatility clustering in the flood related data. Observed water stage data from Guangxi, China, are employed to test the proposed method with promising results © Institution of Engineers Australia.
AB - A statistical model is proposed in this paper that can be used for river stage forecasting. This model is able to handle the volatilities associated with the data used in flood forecasting. Different from conventional flood forecasting methods, this model works well with fatter-tail distribution and volatility clustering in the flood related data. Observed water stage data from Guangxi, China, are employed to test the proposed method with promising results © Institution of Engineers Australia.
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U2 - 10.1080/13241583.2009.11465359
DO - 10.1080/13241583.2009.11465359
M3 - RGC 21 - Publication in refereed journal
SN - 1324-1583
VL - 13
SP - 43
EP - 52
JO - Australian Journal of Water Resources
JF - Australian Journal of Water Resources
IS - 1
ER -