Hydrological processes are known as major driving forces in structuring wetland plant communities, but the specific relationships are not always well understood. The recent dry conditions of Poyang Lake (i.e., the largest freshwater lake in China) are having a profound impact on its wetland vegetation, leading to the degradation of the entire wetland ecosystem. We developed an integrated framework to quantitatively investigate the relationship between the spatial distribution of major wetland herbaceous communities and the hydrological regimes of Poyang Lake. First, the wetland herbaceous community classification was built using a support-vector machine and simultaneous parameter optimization, achieving an overall accuracy of over 98%. Secondly, based on the inundation conditions since 2000, four hydrological drivers of the spatial distribution of these communities were evaluated by canonical correspondence analysis. Finally, the hydrological niches of the communities were quantified by Gaussian regression and quantile methods. The results show that there were significant interspecific differences in terms of the hydrological niche. For example, Carex cinerascens Ass was the most adaptable to inundation, while Triarrhena lutarioriparia + Phragmites australis Ass was the least. Our integrated analytical framework can contribute to hydrological management to better maintain the wetland plant community structure in the Poyang Lake area.

In recent years, the altered hydrological regimes and frequent extreme hydrological events in its watershed have significantly affected the stability and biodiversity of the dish-shaped lakes (DSLs) ecosystem in Poyang Lake. This study uses long-term water level records from the Xingzi hydrological station, multi-source remote sensing imagery, and field surveys to assess how altered hydrological regimes and frequent extreme hydrological events influence the coupled hydro-ecological evolution of DSLs under different gate-controlled conditions. The results reveal the following: (1) After 2003, average monthly water levels declined by 0.84 m, shifting prolonged inundation depths from the 10.0 to 14.0 m range into the 5.5 to 9.5 m range. Extreme hydrological events disrupted the hydrological regimes, triggering a clear “collapse–recovery” succession in submerged plants and major shifts in shoal wetland vegetation. (2) Gate-controlled DSLs (GC DSLs) mitigated many of these impacts by reducing the autumnal drawdown in the water area change rate to 0.324 km²/d, curbing the upward expansion of emergent and hygrophytic vegetation during high-water-level years, and stabilizing habitats during low-water-level years, although different management strategies and substrate characteristics may still lead to divergent habitat trajectories. (3) The habitat heterogeneity exhibited by the DSLs’ vegetation communities along the elevation gradient had differential effects on migratory birds, and GC DSLs can offer migratory birds relatively stable resting habitats and food resources during extreme hydrological events. The study recommends that DSL management should adopt a hierarchical dynamic regulation strategy to balance natural hydrological fluctuations with human interventions, thereby strengthening the resilience of DSL wetland habitats to extreme hydrological events.

Data-driven models are widely used in the field of water level prediction due to their generalizability and predictive abilities. In long-series prediction, however, data-driven models degrade rapidly due to the uncertainty and constraints of model data and parameters. To address the problem of inaccurate continuous water level prediction, this study introduced a data assimilation technique, the unscented Kalman filter (UKF), and embedded support vector regression (SVR) into the framework and applied it to Dongting Lake, the second largest freshwater lake in China. The results demonstrated that the assimilation model is significantly better than the non-assimilation model in predicting water levels and is not affected by the characteristics of lake level changes, with the R² increasing from 0.975–0.982 to 0.998–0.999 and the RMSE decreasing from 0.436–0.159 m to 0.105–0.042 m. The prediction lead time also increased with the increase of continuous assimilation data. Further analysis of the assimilation model showed that when there was an assimilation cycle, the prediction remained stable for successive sets of two or more assimilated data, and the prediction lead time increased with successive assimilated data, from 4–8 days (one successive assimilation data) to 9–12 days (five successive assimilation data). Overall, this study found that the data assimilation framework can improve the prediction ability of data-driven models, with assimilated models having a smaller fluctuation range and higher degree of concentration than non-assimilated models. The increase in assimilated data will improve model accuracy as well as the number of days of prediction lead time when an assimilation cycle exists.

Hydrological processes are known as driving forces in structuring wetland plant communities, but still specific relationships are not always well understood. The dynamic, seasonally inundated wetland at Poyang Lake (less than 1000  km2 in the dry season and more than 3000 km2 in the wet season), the largest freshwater lake in China, underpinnes critical regional ecosystem services (e.g. flood water retention, water supply and biodiversity conservation). However, recent drier conditions of Poyang Lake are having a profound impact on its wetland vegetation leading to degradation of the entire wetland ecosystem, thereby also threatening the winter habitat of migratory birds. We aim to develop an integrated framework to quantitatively investigate the spatial distribution of major herbaceous communities that provide habitat for the migratory birds in response to Poyang Lake flood inundation. First, ground references are obtained from a combination of drone imagery and field surveys as an input for the wetland herbaceous community classification model. Our classification model is based on a machine learning technique applied to Sentinel-2 satellite data. This new search strategy provides an accurate classification based on the more optimal input variables and model parameters gained simultaneously. Secondly, based on the dynamic changes in water levels since 2000, we statistically evaluate the key environmental drivers of the hydrological regime on the spatial distribution of the wetland vegetation communities. This showed that: 1) different plant communities exhibited varying tolerance to flood inundation and 2) two key factors, i.e., average water depth and average duration of the inundation events, were found to be able to characterize the communities’ tolerance independently. For example, Carex cinerascens Ass. which had the widest inundation stress tolerance, being adapted to an inundation duration of 120~230 d and depth of 1.5~1.7 m, accounted for the largest herbaceous community (>27% cover) within the entire study area. Different survival strategies to inundation stress, such as dormancy and morphological restructuring, can explain the varying tolerance of plant species/communities. Our work elucidated the linkages between hydrological processes and herbaceous plants’ distribution in wetlands, and the approach can be readily applied at small to large catchment scales and provides a straightforward practical tool to predict the possible responses of the lake wetland vegetations to potential hydrological changes.

As typical river-connected wetland lakes in the middle and lower Yangtze River basin, the dish-shaped lakes (DSLs) of Poyang Lake have experienced significant impacts on ecosystem stability and regional biodiversity due to the increasing frequency of extreme hydrological events and altered hydrological regimes in recent decades. This study systematically analyzed the effects of new hydrological regimes and extreme hydrological events on the coupled hydro-ecological evolution of DSLs under different sluice-controlled conditions, utilizing long-term water level data from the Xingzi Station, multi-source remote sensing images, and field survey data. The results revealed that: (1) Post-2003, regional water levels exhibited a significant decline (monthly decrease of 0.84 m), with prolonged water level duration shifting from the 10.0–14.0 m range to lower intervals (6.0–10.0 m). Extreme hydrological events triggered notable succession of beach wetland vegetation and a "collapse-recovery" dynamic in submerged vegetation by altering water levels, inundation extent, and duration. (2) Compared to non-Gate Controlled DSLs (non-GC DSLs), Gate control DSLs (GC DSLs) effectively mitigated ecological impacts from extreme events through water level regulation, prolonging the autumn retreat phase (water area change rate: -0.312 km²/d), suppressing downward expansion of emergent/hygrophytic vegetation along elevation gradients during high-water level years, and stabilizing vegetation habitats in low-water level years. However, regulatory strategies and underlying surface characteristics could drive divergent habitat evolution. (3) Habitat heterogeneity induced by vegetation community reorganization along elevation gradients differentially influenced wintering waterbirds: foraging patterns of wading birds (e.g., Siberian Crane) shifted due to reduced Vallisneria spp. coverage, while goose and duck species feeding on Carex spp. were less affected. GC DSLs provided relatively stable habitats and food resources during extreme hydrological events. The study proposes a tiered dynamic regulation strategy to balance natural hydrological fluctuations with artificial interventions, enhancing the resilience of DSL wetlands against extreme hydrological disturbances.

Since large-flow water diversion began in the middle route of the South-to-North Water Diversion Project, inverted siphons have experienced varying degrees of local flow pattern disorder at their inlets and outlets, resulting in a significant decline in hydraulic performance. Taking the Kuhe inverted siphon as a case study, a combination of numerical simulation and on-site testing was used to explore the causes of flow pattern disorder at the outlet of the inverted siphon. Meanwhile, based on the actual engineering situation, the influence of the flow pattern optimization measure of installing a 5D (five times the diameter of the pier) diversion pier at the outlet of the inverted siphon on its hydraulic characteristics was studied. Research findings indicated that before the implementation of flow pattern optimization measures, the Karman vortex street phenomenon was found to occur when water flowed through the piers; the interaction of the vortex streets behind each pier led to flow pattern disorder and affected the flow capacity. After implementation of the flow pattern optimization measures, the diversion piers had a significant inhibitory effect on the formation and development of the Karman vortex street behind the piers under the dispatching and design flow conditions. The flow velocities in each vertical layer were adjusted, with a significant improvement in the flow pattern. The hydraulic loss of the Kuhe inverted siphon was reduced by 11.5 mm, or approximately 7.8%. Under the dispatching flow condition, the water diversion flow of the Kuhe inverted siphon increased by approximately 4.11%. The water diversion capacity of the structure could be effectively enhanced by adding diversion piers to the tails of the piers. This method can be widely applied in similar open-channel long-distance water diversion projects.