International Journal of Agricultural Engineering

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Multiplicative Seasonal ARIMA Modelling of Monthly Stream Flows of Choriti River


Affiliations
1 AICRP on Water Management, C.E.S. Wakawali, Dr. Balasaheb Sawant Konkan Krishi Vidyapeeth, Dapoli, Ratnagiri (M.S.), India
2 Bindan Chandra Krishi Vishwavidyalaya, Mohanpur (W.B.), India
     

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The multiplicative seasonal ARIMA (p,d,q) × (P,D,Q)s models of different orders were tried for modelling of monthly inflow of Choriti river of Konkan region of Maharashtra, based on 20 years data. The parameters of seasonal ARIMA models were estimated by fitting ARIMA models to differenced series (d=0 and D=1) at different lags. The goodness of fit of models was tested by Box-Pierce Portmanteau lack of fit test and comparison of historical and forecasted monthly inflows. The forecasted performance of the model was evaluated by using goodness of fit tests. Lower values of ischolar_main mean squared error; mean relative error and integral square error for multiplicative seasonal ARIMA (0,0,1) × (0,1,1)12 model indicated closer agreement between forested and historical monthly inflow series.

Keywords

Autoregressive Integrated Moving Average Model, Forecasting, White Noise, Akaike Information Criteria.
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  • Multiplicative Seasonal ARIMA Modelling of Monthly Stream Flows of Choriti River

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Authors

B. L. Ayare
AICRP on Water Management, C.E.S. Wakawali, Dr. Balasaheb Sawant Konkan Krishi Vidyapeeth, Dapoli, Ratnagiri (M.S.), India
B. S. Dhekale
Bindan Chandra Krishi Vishwavidyalaya, Mohanpur (W.B.), India

Abstract


The multiplicative seasonal ARIMA (p,d,q) × (P,D,Q)s models of different orders were tried for modelling of monthly inflow of Choriti river of Konkan region of Maharashtra, based on 20 years data. The parameters of seasonal ARIMA models were estimated by fitting ARIMA models to differenced series (d=0 and D=1) at different lags. The goodness of fit of models was tested by Box-Pierce Portmanteau lack of fit test and comparison of historical and forecasted monthly inflows. The forecasted performance of the model was evaluated by using goodness of fit tests. Lower values of ischolar_main mean squared error; mean relative error and integral square error for multiplicative seasonal ARIMA (0,0,1) × (0,1,1)12 model indicated closer agreement between forested and historical monthly inflow series.

Keywords


Autoregressive Integrated Moving Average Model, Forecasting, White Noise, Akaike Information Criteria.