Nonlinear Prediction of Daily Streamflow Time Series Models in the Hualien Area

應用非線性混沌理論方法預測花蓮地區河川日平均流量

10.6937/TWC.202103/PP_69(1).0001

沈少文(SHAW WEN SHEEN)

chaos theory ； local approximation method ； Nash-Sutcliffe efficiency ； persistence index ； streamflow prediction ； 混沌理論 ； 局部漸進預測法 ； 納許效率係數 ； 持續指數 ； 河川流量預測

台灣水利

69卷1期（2021 / 03 / 01）

1 - 19

英文

The aim of this study was to employ methods from chaos theory, including phase space reconstruction and local approximation methods, to examine the existence of chaos in streamflow dynamics. The major objective was to investigate and compare the prediction accuracy of the daily streamflow time series from the gauging stations in the eastern Taiwan. The gauging stations were at Xiuguluam River. The observed streamflow time series spanned a time period of 30 years from 1990 to 2019. The first 27-year streamflow data were used as the training data set, and the remaining 3-year were used as the testing data set. This study applied efficiency criteria: coefficient of variation, Nash-Sutcliffe efficiency, and persistence index. The results concluded that there was existence of chaos in streamflow dynamics. The prediction accuracy performance was better in the recession period than in the rising period at the gauging stations used in this study. Local approximation method was an effective model to predict daily streamflow time series.

本研究應用混沌理論方法分析臺灣東部花蓮地區河川日流量，本研究分析秀姑巒溪瑞穗大橋測站與玉里大橋測站30年（1990－2019）河川日平均流量資料，使用27年（1990－2016）河川日平均流量資料來預測最後3年（2017－2019）河川日平均流量，本研究使用變異係數、納許效率係數與持續指數來評估預測模型正確有效程度，研究結果指出研究地區流量測站河川日平均流量顯示有混沌現象，預測模型於河川流量退水段預測較河川流量上升段佳，局部漸進預測法能有效預測河川日平均流量。

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