Hydrodynamic modeling as a tool for analyzing the hydrological effects of river maintenance activities

Climate change exacerbates water scarcity globally, impacting vital wetland ecosystems that provide crucial ecological services. As a result, peatland areas experience a gradual decrease in water table levels, leading to their degradation and emphasizing the need for effective water level management strategies. This study examines the hydrological and ecological consequences of riverbed maintenance—specifically vegetation mowing—on the Upper Biebrza Valley. Using a coupled hydrodynamic-groundwater flow model supported by an Artificial Neural Network (ANN), we simulated the impacts of different mowing scenarios on groundwater levels, water balance, and vegetation response. The results show that mowing vegetation from the riverbed temporarily lowers river water levels, which increases the hydraulic gradient and accelerates water outflow from adjacent peatlands. In the most intensive scenario, riverbed mowing led to a short-term increase of up to 24 % in groundwater discharge to the river compared to the reference (non-mowed) condition. However, this effect is temporally limited and site-specific. The impact on groundwater levels and wetland habitats varied significantly between plant communities, with species located closest to the river showing the highest sensitivity to water table decline. These findings demonstrate that routine riverbed maintenance can negatively affect peatland hydrology and ecosystem resilience, even when applied partially. The study emphasizes the need to reassess standard maintenance practices, particularly in protected and climate-sensitive landscapes.