Flood forecasting for heteroscedastic streamflow processes
نویسندگان
چکیده
The paper presents a nonlinear heteroscedastic model for flow forecasting. The model is composed of two submodels: the former provides the expected value of the flow, conditional on available information, e.g. past flow and precipitation records; the latter provides the variance of the prediction error as a function of past values of the prediction error itself and precipitation measures. The proposed model is tested on a real world case study, the inflow to Lake Verbano, Italy, where the inflow forecast is used for optimizing release decisions from the lake. Results are discussed and compared with those obtained with conventional modelling approach, where the flow is estimated based on a linear model of the flow logarithm, and the variance is not given a dynamical description but is assumed to be a time-varying parameter.
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تاریخ انتشار 2008