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Salas, J.D., Saada, N.M., Chung, C.H., Lane, W.L. and Frevert, D.K. (2000) Stochastic Analysis, Modeling and Simulation (SAMS) Version 2000—User’s Manual. Colorado State University, Fort Collins.

has been cited by the following article:

• TITLE: Simulation of Long Term Characteristics of Annual Rainfall in Selected Areas in Saudi Arabia

  AUTHORS: Nidhal Saada

  KEYWORDS: Rainfall Modeling, Hurst Coefficient, ARMA, Trend Analysis

  JOURNAL NAME: Computational Water, Energy, and Environmental Engineering, Vol.4 No.2, April 20, 2015

  ABSTRACT: Simulation experiments with different stochastic models were conducted to investigate the long term characteristics of rainfall in Saudi Arabia using selected Autoregressive Moving Average (ARMA) models. The results of the study indicated that the ARMA models were able to capture the long term statistics for one of the rainfall records investigated (Surat Obeida). However, the other rainfall record investigated in this study (Malaki) was characterized with a slow and long decaying structure and a high Hurst coefficient indicating the possibility of non-stationarity of the data. Trend analysis (Pettitt test) of the data revealed that a break point or a shift in the record happened around 1983 at Malaki. As a result, ARMA models should not be used in modeling the rainfall data at that station.