Simulation Models of Sequences of Dry and Wet Daysby J. W. Delleur, Purdue Univ, West Lafayette, IN, USA,
T. J. Chang, Purdue Univ, West Lafayette, IN, USA,
M. L. Kavvas, Purdue Univ, West Lafayette, IN, USA,
Abstract: A new statistical model has been developed for the simulation of sequences of dry and wet days. The model is based on the discrete autoregressive-moving average (DARMA) family of stochastic processes. The model building is based on a three-step procedure consisting of identification, estimation and model selection. The model identification and parameter estimation are based on the best fit of the autocorrelation function, while the selection of the optimum model is based on the reproduction of the probability distribution function of the lengths of the runs of dry days and wet days. The model has thus the property of reproducing the persistence of dry spells and wet spells which are important in the evaluation and forecast of droughts and floods. Refs.
Subject Headings: Simulation models | Stochastic processes | Precipitation | Autoregressive models | Forecasting | Parameters (statistics)
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