Abstract:

Aquatic vegetation, as the primary producer in lakes, provides multiple ecological services such as food sources and habitats. Dynamic monitoring of aquatic vegetation is essential for lake protection. The CART (Classification and Regression Tree) approach was utilized to extract the aquatic vegetation based on the phenological characteristics of different types of vegetation of the multi-temporal MOD09QI NDVI(Normalized Differential Vegetation Index) series. The approach was applied to derive the annual aquatic vegetation maps of the Honghu Lake from 2000 to 2022. The results showed that this approach was effective to distinguish the different types of aquatic vegetation with an overall classification accuracy of 85.6%. The aquatic vegetation generally exhibits a distinct spatial structural characteristic. The emergent vegetation, Zizania latifolia, was concentrated in the southwest lake, while Nelumbo nucifera was scattered in areas around the lakeshore. Submerged vegetation was mainly found from the emergent area towards the lake and the shoreline. In terms of the change trajectory, three main phases were identified. From 2000 to 2004, the aquatic vegetation was relatively scarce, with an average area of 150.56km2. For the second phase of 2005 to 2016, with the implementation of wetland ecological projects to control surrounding pollutions, the aquatic vegetation gradually recovered to an area of 181.85km2. The overall aquatic vegetation area was stable in the normal year without extreme drought and flood in the second phase. After 2017, the average area of aquatic vegetation decreased sharply to 100.35km2. This change might be attributed to the continuously deterioration of water quality, the increase of sediment resuspension that was caused by the dike and debris removal projects, and the flood event in summer 2016. After 2022, the aquatic vegetation area reached the historical lowest, which was below 10% in the last two years. This result provided key information on the potential sites and species that could be used in ecological restoration projects in the future.