Abstract
The Dynamic Regression model (DR) was used for forecasting the discharge of Adhaim and Greater Zab rivers with considering the effect of rainfall on the discharges. The auto correlation function (ACF) was used to determine the stationary level of the time series, also the partial auto correlation function (PACF) was used to identify a suitable Auto Regression Integrated Moving Average (ARIMA) model for time series of rainfall and discharges for both rivers and the factors of the transfer function models (TF) were determined. The model passed the tests successfully and the dynamic regression model for both rivers became suitable for forecasting the discharges depending upon the historical data of the rainfall and the discharges. Key words : Rainfall , Adhaim river , Greater Zab river
Highlights
The Dynamic Regression model (DR) was used for forecasting the discharge of Adhaim and Greater Zab rivers with considering the effect of rainfall on the discharges
The model passed the tests successfully and the dynamic regression model for both rivers became suitable for forecasting the discharges depending upon the historical data of the rainfall and the discharges
نموذج الانحدار الحركي ،حیث أن ھذه السلسلة تمثل تلك العوامل التي تؤثر على الجریان.
Summary
The Dynamic Regression model (DR) was used for forecasting the discharge of Adhaim and Greater Zab rivers with considering the effect of rainfall on the discharges. : Ntسلسلة الاضطراب : pرتبة معامل الانحدار الذاتي غیر الموسمي : Pرتبة معامل الانحدار الذاتي الموسمي : qرتبة معامل الوسط المتحرك غیر الموسمي : Фkkمعامل الارتباط الذاتي الجزئي : Θ8معامل الوسط المتحرك الموسمي نموذج) (Auto Regression) (ARأو) (Moving average)(MAلأغراض النمذجة. ان نموذج )( ARIMA سلاسل الامطار والتصاریف الى التوزیع الطبیعي وتتمثل ھذه الطریقة بالمعادلة التالیة ]: [٦
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