Application of tank, NAM, ARMA and neural network models to flood forecasting

✍ Scribed by Tawatchai Tingsanchali; Mahesh Raj Gautam

• Publisher: John Wiley and Sons
• Year: 2000
• Tongue: English
• Weight: 166 KB
• Volume: 14
• Category: Article
• ISSN: 0885-6087
• DOI: 10.1002/1099-1085(20001015)14:14<2473::aid-hyp109>3.0.co;2-j

✦ Synopsis

Two lumped conceptual hydrological models\ namely tank and NAM and a neural network model are applied to ~ood forecasting in two river basins in Thailand\ the Wichianburi on the Pasak River and the Tha Wang Pha on the Nan River using the ~ood forecasting procedure developed in this study[ The tank and NAM models were calibrated and veri_ed and found to give similar results[ The results were found to improve signi_cantly by coupling stochastic and deterministic models "tank and NAM# for updating forecast output[ The neural network "NN# model was compared with the tank and NAM models[ The NN model does not require knowledge of catchment characteristics and internal hydrological processes[ The training process or calibration is relatively simple and less time consuming compared with the extensive calibration e}ort required by the tank and NAM models[ The NN model gives good forecasts based on available rainfall\ evaporation and runo} data[ The black!box nature of the NN model and the need for selecting parameters based on trial and error or rule!of!thumb\ however\ characterizes its inherent weakness[ The performance of the three models was evaluated statistically[ Copyright Þ 1999