Assessing the spatiotemporal shifting of the Arpa river using remote sensing, GIS, and ARIMA for river morphology prediction

River channel migration is a dynamic geomorphological process influenced by hydrological, geographic, and anthropogenic factors. Understanding river shifting patterns is important for sustainable catchment management. This study investigates the spatial and temporal changes of the Arpa River channel over 49 years (1972–2021) using remote sensing and GIS techniques. Landsat images and Data Elevation Models (DEM) were used to measure river morphology and channel migration. The study quantified both spatial and temporal variations by integrating cross-sectional analysis of sinuosity ratio estimation and river channel shifting rate calculations. The Autoregressive Integrated Moving Average (ARIMA) model also predicts future river migration trends. The results show that the Arpa River has undergone significant morphological changes, a reduction in channel width, and lateral migration due to hydrological variations, sediment transport, and anthropogenic pressure. Its findings highlight changes to the river due to urbanization, infrastructure development, and deforestation. Integrating remote sensing and GIS with time-series modeling enhances the predictive capabilities of river migration studies and provides valuable information to policymakers and environmental planners. This study underlines the need for sustainable landscape strategies and sediment management policies to mitigate the adverse impacts of riverbank erosion and shifting.