Enhancing Active Channel Delineation in Alluvial Rivers Using Monthly Aggregation of Sentinel‐2 Imagery

Abstract The active channel of alluvial rivers delineates areas of geomorphic activity over a defined time window. While increasing satellite data availability enables monthly active channel delineations, multi‐year analyses often rely on temporal aggregates (e.g., annual medians) to reduce computational costs and intra‐annual variability. The potential of monthly information to improve active channels delineation and geomorphic interpretation remains largely unexplored. In this work, we delineated active channels for the Po River (Italy) by aggregating monthly Sentinel‐2 classifications of river water and sediment bars into annual frequency maps at 10 m resolution. Annual aggregation mitigated monthly sediment underestimation (12%) but also amplified model overestimation biases (15%). Monthly classification persistence (e.g., classified as active channel for more than N months/year) was then used to reduce these errors and produce active channel areas that closely match those manually delineated from 30 cm orthophotos. The spatiotemporal variability of monthly classifications also show that the active channel area of dynamic reaches can vary ∼50% over the year. These changes revealed areas most prone to water‐stage fluctuations, sediment transport, as well as zones seasonally or progressively colonized by vegetation—patterns hidden in single orthophotos or annual medians. Less dynamic reaches, by contrast, showed minimal differences between annual and monthly‐based delineation methods. These findings emphasize the importance of adapting temporal aggregation to the river type and process analysed, with sub‐annual resolutions better capturing, in dynamic rivers, seasonal and progressive active channel reconfigurations, along with their interaction with sediment and vegetation dynamics.