Assessing the impacts of environmental change and anthropogenic activities on the historical and current total suspended matter (TSM) pattern in Dongting Lake, China, is a large challenge. We addressed this challenge by using more than three decades of Landsat data. Based on in situ measurements, we developed an algorithm based on the near-infrared (NIR) band to estimate TSM in Dongting Lake. The algorithm was applied to Landsat images to derive TSM distribution maps from 1978 to 2013 in the wet season, revealing significant inter-annual and spatial variability. The relationship of TSM to water level, precipitation, and wind speed was analyzed, and we found that: (1) sand mining areas usually coincide with regions that have high TSM levels in Dongting Lake; (2) water level and seven-day precipitation were both important to TSM variation, but no significant relationship was found between TSM and wind speed or other meteorological data; (3) the increased level of sand mining in response to rapid economic growth has deeply influenced the TSM pattern since 2000 due to the resuspension of sediment; and (4) TSM variation might be associated with policy changes regarding the management of sand mining; it might also be affected by lower water levels caused by the impoundment of the Three Gorges Dam since 2000.

The Tiaoxi River is the main source of water for Lake Taihu and can result in plumes in the lake after heavy precipitation events. These plumes have played a crucial role in the water quality changes within the lake. High temporal resolution GOCI (Geostationary Ocean Color Imager) data were used to study the spatial distribution of the total suspended matter concentration in Lake Taihu after heavy precipitation events in the Tiaoxi River Basin via an empirical model. The plumes were analyzed after two heavy precipitation events in 2011 and 2013 using 16 GOCI images, which indicated that the Tiaoxi River had a great influence on the spatial distributions of total suspended matter and algal blooms. It was concluded that the main factors affecting the plumes in the Tiaoxi River were precipitation intensity, runoff, and total suspended matter concentration. Human activity, such as sand excavation also played a crucial role in sediment discharge. The results of this study demonstrate that the visualization of GOCI data makes it possible to use remote sensing technology to continuously monitor an inland water environment on an hourly scale, which is of great significance for studying the diffusion and evolution of river plumes.

The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to urgent demand and rapid development in high-resolution earth observation systems, it has become crucial to assess hyperspectral satellite imagery capabilities on inland water monitoring. The Orbita hyperspectral (OHS) satellite is the latest hyperspectral sensor with both high spectral and spatial resolution (2.5 nm and 10 m, respectively), which could provide great potential for remotely estimating the concentration of Chl-a for inland waters. However, there are still some deficiencies that are mainly manifested in the Chl-a concentration remote sensing retrieval model assessment and accuracy validation, as well as signal-to-noise ratio (SNR) estimation of OHS imagery for inland waters. Therefore, the radiometric performance of OHS imagery for water quality monitoring is evaluated in this study by comparing different atmospheric correction models and the SNR with several remote sensing images. Several crucial findings can be drawn: (1) the three-band model ((1/B15-1/B17)B19) developed by OHS imagery is most suitable for estimating the Chl-a concentration in Dianchi Lake, with the root-mean-square error (RMSE) and the mean absolute percentage error (MAPE) of 15.55 µg/L and 16.31%, respectively; (2) the applicability of the FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes) atmospheric correction model for OHS imagery in a eutrophic plateau lake (Dianchi Lake) was better than the 6S (Second Simulation of Satellite Signal in the Solar Spectrum) model, and QUAC (Quick Atmospheric Correction) model, as well as the dark pixel method; (3) the SNR of the OHS imagery was similar to that of Hyperion imagery and was significantly higher than SNR of the HSI imagery; (4) the spatial resolution showed slight influence on the SNR of the OHS imagery. The results show that OHS imagery could be applied to remote sensing retrieval of Chl-a in eutrophic plateau lakes and presents a new tool for dynamic hyperspectral monitoring of water quality.

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.

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.

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.