Estuarine ecosystems face increasing anthropogenic pressures, necessitating effective monitoring methods to mitigate their impacts on the biodiversity they harbour. The use of environmental DNA (eDNA) based detection methods is increasingly recognized as a promising tool to complement other, potentially invasive monitoring techniques. Integrating such eDNA analyses into monitoring frameworks for large ecosystems is still challenging and requires a deeper understanding of the scale and resolution at which eDNA patterns may offer insights in species presence and community composition space and time. The Scheldt estuary, characterized by its diverse habitats and complex currents, is one of the largest Western European tidal river systems. Until now, it remains challenging to obtain accurate information on fish communities living in and migrating through this ecosystem, consequently confining our knowledge to specific locations. To explore the potential of eDNA based monitoring, we simultaneously combine stow net fishing with eDNA metabarcoding, to assess spatiotemporal shifts in the Scheldt estuary's fish communities. In total, we detected 71 fish species in the estuary using eDNA metabarcoding, partly overlapping with historic fish community data gathered at the different study locations and in contrast to only 42 species using stow net fishing during the same survey period. Community compositions found by both detection methods varied among sampling locations, driven by a clear correlation to the salinity gradient. Limited effects of sampling depth and tide were observed on the eDNA metabarcoding data, allowing a significant reduction of the eDNA sampling effort for future eDNA fish monitoring campaigns in this study system. Our results further demonstrate that seasonal shifts in fish species occurrence can be detected using eDNA metabarcoding. Combining eDNA metabarcoding and stow net fishing further enhances our understanding of this vital waterway's diverse fish populations, allowing a higher resolution and more efficient monitoring strategy.