Abstract
Water scarcity is a pressing global challenge, and arid regions like Saudi Arabia face the urgent need for effective water stress management. The current study proposes an innovative method to tackle this issue by utilizing a hybrid time series analysis model, comprising of Autoregressive Integrated Moving Average (ARIMA) and Generalized Least Squares (GLS) techniques to estimate groundwater depletion trends in Saudi Arabia. The research employs historical groundwater data, climatic variables, and socioeconomic indicators to formulate comprehensive insight of the factors influencing groundwater depletion. The ARIMA component of the hybrid model captures the temporal dynamics of groundwater levels, while GLS considers the spatial and cross-correlation dependencies among observation points, enhancing the accuracy of depletion estimates. The study also demonstrates the significance of climatic variability and socioeconomic factors in exacerbating water stress in the region. Furthermore, the hybrid ARIMA-GLS model offers a robust tool for forecasting future groundwater depletion trends, aiding proactive decision-making in mitigating water stress. The numerical results for different wells proved to be essential in assessing the Mean Absolute Percent Error (MAPE). For instance, the MAPE values were found to be as (i) hybrid ARIMA-CLS (MAPE = 0.1507), (ii) ARIMA-CLS (MAPE = 0.429834), (iii) ARIMA-CLS (MAPE = 0.109115) for 4-H-84-N, 4-H-86-U, 4-S-316-U, respectively with the expectation of (iv) ARI (MAPE = 6.0285) for DA-45-U well. It is therefore believed that this research contributes to the broader discussion on managing the water resource in arid regions and highlights the significance of integrated approaches that consider both temporal and spatial dimensions. Further, it offers valuable insights and a practical framework for addressing water stress challenges in Saudi Arabia and serves as a model for water management in other arid regions grappling with similar issues.