Microcomputer Applications in Stochastic Hydrology

by Tiao J. Chang, Ohio Univ, Dep of Civil Engineering, Athens, OH, USA,



Document Type: Proceeding Paper

Part of: Hydraulics and Hydrology in the Small Computer Age

Abstract:

The stochastic precipitation model, namely, Discrete Autoregressive Moving Average (DARMA) process, is used to study daily precipitation time series all over the country. Microsoft Fortran programs are designed to run in an IBM personal computer to compute the autocorrelation function for an initial identification, to estimate the model parameter through nonlinear least squares method, and to select the best model by the minimum variance of the run length distribution. The results show that the seasonal data having strong autocorrelations are inclined to be better fitted by Discrete Autoregressive (DAR) model and those having weak autocorrelations tend to be fitted by Discrete Moving Average (DMA) model.

Subject Headings: Computer models | Hydrologic models | Stochastic processes | Precipitation | Autoregressive moving average models | Hydrology | Autoregressive models

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