Forecasting the Cultivated Areas of Qat Crop to 2030 And Its Impact on Food Security in The Republic of Yemen Using ARIMA Model - Alsanoy, Adnan Abdulwali; Alhakimi, Saif Sallam (Journal of agricultural, environmental and veterinary sciences, 2021)
This study aimed to forecast and predict the areas planted with Qat tree until the year 2030 in the Republic of Yemen, using the most prominent Autoregressive Integrated Moving Average (ARIMA) models throughout the whole country. This model was adopted in this study for its high accuracy in analysis. This methodology relies on a combination of autoregressive models and integrated moving averages. The results show that ARIMA (1.0.1) is the most appropriate model for forecasting and predicting Qat areas in Yemen until 2030 according to statistical tests of the accuracy of the predictive models. The results indicate an increase in the cultivated areas expected in 2030, which will be 235826 hectares of Qat areas at an annual growth rate higher than the annual growth rate for the time series while the area’s annual growth rate reached (30%). This increase is at the expense of the shortage of the significance of cash crops such as coffee and grains, based on the results of the proposed model for the next ten years. This expansion represents economic and social risks to the agricultural sector. Accordingly, the study recommends that decision-makers need to reformulate and draw economic and social policies for the coming periods to limit the spread of this crop, which negatively affects groundwater depletion because Yemen is one of the poorest countries in terms of water storage.