Forecasting Solid Waste Trends in Gujarat Using SPSS-ARIMA MODEL

Abstract

This study presents an analysis and forecast of Solid Waste Generation (SWG) trends in the state of Gujarat, India. Utilizing ten years of historical SWG data sourced from annual reports of Gujarat's environmental and urban authorities, the research employs the Autoregressive Integrated Moving Average (ARIMA) time series model via SPSS software. The primary objective is to accurately forecast the SWG for the next ten years to support proactive urban planning and resource allocation for waste management infrastructure. Following the Box- Jenkins methodology, the optimal model identified and validated was ARIMA (1, 1, 1). The key finding indicates a projected increase in daily SWG, reaching approximately 15,401.80 TPD by 2034. The resulting forecasts provide crucial, reliable guidelines for policymakers in Gujarat on capacity planning, landfill management, and achieving sustainable waste management targets.