Evaluating an Autoregressive Model for Stream Flow Forecastingby Yuan Cheng, (M.ASCE), Benatec Associates, Inc, Camp Hill, United States,
Abstract: Daily stream discharge generated by an Autoregressive Model is helpful in the design and risk assessment of temporary riverine construction projects. This case study uses actual daily stream records to model and forecast the daily stream discharge at a temporary causeway designed for bridge pier construction. With autocorrelation and spectral density functions, the stream flow trend and deterministic cycles can be identified and separated. With partial autocorrelation function, the persistency of the stream flow can be determined in stochastic terms. Finally, using the autoregressive process, a stream flow forecast model can be established. The use of the model to refine the design of temporary structures and to assess the risk of overtopping will be evaluated and discussed. This case study will conclude with a comparison between actual stream flow data and the model's forecasted discharge.
Subject Headings: Streamflow | Autoregressive models | Forecasting | Water discharge | Risk management | Case studies | Model analysis | Mathematical models
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