Volume 1, Number 1 (2-2013)                   DEEJ 2013, 1(1): 51-58 | Back to browse issues page

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Different types of time series analysis models are commonly used for predicting hydrological
factors. In this study, the situation of Soleimanieh spring discharge in Kashan was
investigated using various time series models and mean monthly flow during 11 year period.
Then, spring discharge predicted using the best modals for future 9 years. In this research, the
data were analyzed using 12 time series models including Autoregressive, Moving average,
Autoregressive-composite moving average, seasonal and non-seasonal models such as Box
and Jenkins. Finally, the results showed that the value of AIC is the lowest and model
parameters don,t exceed of one in SARIMA (1, 1, 0) (1, 1, 1) [12] model. So, this model was
selected to predict discharge data. Then, Komogorov-Smirnov test was used to investigate the
normality situation of the predicted data. The obtained results showed that predicted data are
normal. Therefore, according to the results, it can be conducted as the type of selected model
is very important and it affects the accuracy of output response. Also, according to the
uncertain nature of hydrological issues, time series models are one of the best methods in
hydrological prediction.

Type of Study: Research | Subject: Special
Received: 2012/07/5 | Accepted: 2012/08/26 | Published: 2013/02/3

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