The Best-Fitted Model for Analyzing Climatic Impact on Crop Production: A Comparative Study of ARIMA and ARIMAX Models
DOI:
https://doi.org/10.32350/sir.103.04Keywords:
ARIMAX, climate change, cotton, mean maximum temperature, sugarcaneAbstract
The agriculture sector is highly vulnerable to weather variations. Agricultural output is influenced by several climate-related phenomena, including changes in temperature and rainfall patterns. The main objective of this study was to investigate the impact of climatic parameters on cotton and sugarcane production using Autoregressive Integrated Moving Average (ARIMA) and ARIMAX models. Annual data on mean maximum temperature (YMMTX), mean minimum temperature (YMMTN), and total rainfall for 1981–2021 at the Bahawalnagar and Bahawalpur stations was obtained from the Pakistan Meteorological Department (PMD), Karachi. Time-series data on crop production and cultivated area was obtained from the Pakistan Bureau of Statistics. Stationarity of data was assessed using the Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) tests. Based on the minimum values of the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Root Mean Square Error (RMSE), the best-fitted ARIMAX models for cotton and sugarcane production in Bahawalnagar and Bahawalpur were ARIMAX (1,1,0), (1,0,0), (1,1,0), and (3,1,0), respectively. The results indicated that climatic factors significantly affect cotton and sugarcane production. These findings may be useful for planning and development departments, farmers, and other stakeholders.
Highlights
- Climatic impact on agricultural production in Bahawalpur and Bahawalnagar.
- ARIMA and ARIMAX models were compared using historical data for the time period (1981-2021).
- ARIMAX demonstrated better forecasting performance than ARIMA based on AIC, BIC, and RMSE.
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Copyright (c) 2026 Sajid Ali Khan, Muhammad Ali, Bulbul Jan, Azhar Iqbal
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