| Summary: | 碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 105 === Flood forecasting is an essential issue in hydrological studies. In the literature, many flood forecasting models were shown to perform well. However, it has also been recognized that, due to flood flow persistence, even simple models could also achieve good performance. In this study, two model performance criteria, namely the coefficient of efficiency (CE) and coefficient of persistence (CP) were used to evaluate performance of flood forecasting models. Flood flow data at three stations in the Yilan River Basin were represented by autoregressive (AR) models. An asymptotic theoretical relationship between CE and CP, which is dependent on the lag-k autocorrelation coefficient, was derived and used to demonstrate why the simple naïve forecasting model could achieve good performance, in certain cases, even outperform more complicated models.
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