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.