Hydrological Alterations Drive Long‐Term Decline and Resilience Loss of Submerged Aquatic Vegetation in a Large Floodplain Lake

ABSTRACT Submerged aquatic vegetation (SAV) plays a vital role in improving water quality and providing essential habitats for diverse aquatic fauna in floodplain lakes. However, in large floodplain systems, the spatiotemporal dynamics and underlying drivers of SAV remain poorly understood, largely due to monitoring challenges posed by complex topography, highly variable water levels, and diverse vegetation communities. To address this knowledge gap, we developed a novel remote sensing approach that integrates multi‐temporal imagery from the water‐level drawdown period with differential submergence responses of wetland vegetation types. This method effectively overcomes detection difficulties under high water levels and minimises interference from inundated emergent vegetation. Applying this approach, we analysed long‐term changes in SAV extent in Poyang Lake, the largest floodplain lake in China, and used generalised additive models to identify key environmental drivers, with a particular focus on hydrology and water transparency. Our results revealed a substantial and persistent collapse of SAV in Poyang Lake, declining from 655 ± 288 km 2 during 2001–2009 to 44 ± 31 km 2 during 2020–2023, accompanied by reduced variability and slower recovery, indicating a loss of natural dynamic resilience. This collapse was primarily driven by hydrological alterations, including more frequent extreme floods linked to climate change and earlier water‐level recession caused by hydraulic engineering and sand mining. Reduced water transparency further intensified SAV losses. This study enhances understanding of SAV dynamics and their drivers in large, hydrologically complex lakes, while also providing a transferable monitoring framework for other floodplain lakes. These findings offer critical insights for conservation and adaptive management strategies aimed at sustaining these vulnerable ecosystems.