Remote sensing of fluorescent humification levels and its potential environmental linkages in lakes across China.

The pollution or eutrophication affected by dissolved organic matter (DOM) composition and sources of inland waters had attracted concerns from the public and government in China. Combined with remote sensing techniques, the fluorescent DOM (FDOM) parameters accounted for the important part of optical constituent as chromophoric dissolved organic matter (CDOM) was a useful tool to trace relative DOM sources and assess the trophic states for large-scale regions comprehensively and timely. Here, the objective of this research is to calibrate and validate a general model based on Landsat 8 OLI product embedded in Google Earth Engine (GEE) for deriving humification index (HIX) based on EEMs in lakes across China. The Landsat surface reflectance was matched with 1150 pairs fieldtrip samples and the nine sensitive spectral variables with good correlation with HIX were selected as the inputs in machine learning methods. The calibration of XGBoost model (R2 = 0.86, RMSE = 0.29) outperformed other models. Our results indicated that the entire dataset of HIX has a strong association with Landsat reflectance, yielding low root mean square error between measured and predicted HIX (R2 = 0.81, RMSE = 0.42) for lakes in China. Finally, the optimal XGBoost model was used to calculate the spatial distribution of HIX of 2015 and 2020 in typical lakes selected from the Report on the State of the Ecology and Environment in China. The significant decreasing of HIX from 2015 to 2020 with trophic states showed positive control of humification level of lakes based on the published document of Action plan for prevention and control of water pollution in 2015 of China. The calibrated model would greatly facilitate FDOM monitoring in lakes, and provide indicators for relative DOM sources to evaluate the impact of water protection measures or human disturbance effect from Covid-19 lockdown, and offer the government supervision to improve the water quality management for lake ecosystems.

Natural versus anthropogenic controls on the dissolved organic matter chemistry in lakes across China: Insights from optical and molecular level analyses.

Dissolved organic matter (DOM) plays an essential role in the global carbon biogeochemical cycle for aquatic ecosystems. The complexity of DOM compounds contributes to the accurate monitoring of its sources and compositions from large-scale patterns to microscopic molecular groups. Here, this study demonstrates the diverse sources and compositions for humic-rich lakes and protein-rich lakes for large-scale regions across China with the linkage to optical components and molecular high-resolution mass spectrometry properties. The total fluorescence intensity of colored DOM (CDOM) for humic-rich lake regions (0.176 Raman unit; R.U.) is significantly (p<0.05) higher than that of the protein-rich lake region (0.084 R.U.). The combined percentages of CDOM absorption variance explained by the anthropogenic and climatic variables across the five lake regions of Northeastern lake region (NLR), Yungui Plateau lake region (YGR), Inner Mongolia-Xinjiang lake region (MXR), Eastern lake region (ELR), and Tibetan-Qinghai Plateau lake region (TQR) were 86.25%, 82.57%, 80.23%, 88.55%, and 87.72% respectively. The averaged relative intensity percentages of CHOS and CHONS formulas from humic-rich lakes (90.831‰, 10.561‰) were significantly higher than that from the protein-like lakes (47.484‰, 5.638‰), respectively. The more complex molecular composition with higher aromaticity occurred in the humic-rich lakes than in the protein-rich lakes. The increasing anthropogenic effects would significantly enhance the sources, transformation, and biodegradation of terrestrial DOM and link to the greenhouse gas emission and the carbon cycle in inland waters.