Decaying algal blooms in eutrophic lakes can introduce organic matter into the water and change nutrient concentrations in the water column. The spatial distribution and composition characteristics, sources, and contribution to eutrophication of dissolved organic matter (DOM) in the overlying water of Lake Taihu, a typical eutrophic lake in China, were analyzed by ultraviolet–visible spectra and three-dimensional fluorescence excitation–emission matrix spectra combined with the statistical decomposition technique, parallel factor analysis. The concentration of DOM was represented by dissolved organic carbon (DOC), and DOC in overlying water of Lake Taihu was 2.86–11.83 mg/L. The colored DOM (CDOM) was characterized by an absorption coefficient at 280 nm (a₂₈₀) and 350 nm (a₃₅₀), which were 6.63–29.87 and 1.84–10.41 m⁻¹, respectively. These values showed an increasing trend from southeast to northwest, and the high values were concentrated in the northwest and northern lake areas. The parallel factor analysis (PARAFAC) identified two protein-like (C1: tyrosine-like and C2: tryptophan-like) and one humic-like (C3: humic acid and fulvic acid) fluorescence components for fluorescent DOM (FDOM). The most dominant components were protein-like components (C1 + C2), whose fluorescence intensity contributed 87.55% ± 3.39% to the total fluorescence intensity (F_t) of FDOM (3.38 R.U.). The mean value of the fluorescence index (FI) and index of recent autochthonous contribution (BIX) of DOM was 1.77 and 0.92, and DOC, a₂₈₀ and fluorescence intensities of FDOM components were all significantly and positively correlated with chl. a, indicating that DOM, CDOM, and FDOM were all mainly derived from algal activities and metabolites. The average humification index of the DOM was 0.66, which indicated a low humification degree. The protein-like DOM was correlated with DON and DOP, and might make great contributions to the continuous occurrence of algal blooms.

Information about the growth, productivity, and distribution of vegetation, which are highly relied on and sensitive to natural and anthropogenic factors, is essential for agricultural production management and eco-environmental sustainability in the Amur River Basin (ARB). In this paper, the spatial–temporal trends of vegetation dynamics were analyzed at the pixel scale in the ARB for the period of 1982–2013 using remotely sensed data of long-term leaf area index (LAI), fractional vegetation cover (FVC), and terrestrial gross primary productivity (GPP). The spatial autocorrelation characteristics of the vegetation indexes were further explored with global and local Moran’s I techniques. The spatial–temporal relationships between vegetation and climatic factors, land use/cover types and hydrological variables in the ARB were determined using a geographical and temporal weighted regression (GTWR) model based on the observed meteorological data, remotely sensed vegetation information, while the simulated hydrological variables were determined with the soil and water assessment tool (SWAT) model. The results suggest that the variation in area-average annual FVC was significant with an increase rate of 0.0004/year, and LAI, FVC, and GPP all exhibited strong spatial heterogeneity trends in the ARB. For LAI and FVC, the most significant changes in local spatial autocorrelation were recognized over the Sanjiang Plain, and the low–low agglomeration in the Sanjiang Plain decreased continuously. The GTWR model results indicate that natural and anthropogenic factors jointly took effect and interacted with each other to affect the vegetated regime of the region. The decrease in the impact of precipitation to vegetation growth over the Songnen Plain was determined as having started around 1991, which was most likely attributed to dramatic changes in water use styles induced by local land use changes, and corresponded to the negative correlation between pasture areas and vegetation indexes during the same period. The analysis results presented in this paper can provide vital information to decision-makers for use in managing vegetation resources.

The Sanjiang Plain (SJP) in Northeast China, a crucial black soil region, serves as a quintessential example of a high-intensity agricultural development zone and stands as China’s largest commercial grain production base. In the context of global climate change, pronounced global warming and increased vegetation greening are expected to significantly impact the agricultural water resource supply and its alignment with crop water requirements in the SJP. This study assesses how climate change and vegetation greening affect the crop water supply–demand relationship in the SJP, addressing the critical question of whether natural precipitation can sustain regional agricultural development. Using the extensively validated ESSI-3 distributed hydrological model, integrated with reanalysis and multi-source satellite data, we analyzed data from 1982 to 2018. The results indicate a statistically significant rise in the regional temperature and leaf area index (p < 0.05), with a notable shift around 2000. Key findings include (1) an increase in crop irrigation water requirements (IWR) post-2000, with significant spatial variation; the central and western regions experienced the highest increases, while the eastern region saw reduced risk to crop water security. Furthermore, (2) climate change accounted for approximately 37.9% of the increased IWR in central and western regions, with vegetation greening contributing about 21.2%. Conversely, in the eastern region, vegetation dynamics had a more pronounced effect (28.6%), while climate change contributed less (12.3%). These results suggest a shift in crop water deficit risk boundaries toward the east and north. To optimize water use, expanding high-water-demand crops in the eastern regions and reducing their cultivation in the west is recommended, enhancing alignment between natural precipitation and crop water needs.

Freshwater quality criteria (FWQC) are essential scientific thresholds established to protect human health and aquatic ecosystems, serving as the foundation for water quality standards, environmental risk management, and pollution control. The latest research advancements were summarized, including the screening of priority pollutants for FWQC and the theory and methodology for environmental criteria in China in the last decade. The potential work has been meticulously analyzed and discussed concerning FWQC to be conducted in the short-term future. The possible prioritized list of pollutants for FWQC should be concerned with including nine categories of heavy metal ions, three categories of non-metal ions, and five categories of organic compounds in the short-term future research. The guidelines for deriving FWQC for the protection of human health for organoleptic effects and for sediment need to be modified and emphasized to ensure the safety of drinking water sources, address issues related to black and odorous surface water, and protect the biodiversity of benthic organisms. Toxicity data, water quality parameters, exposure data, and the geographical distribution of freshwater species should be systematically collected to support the development of FWQC in China. The potential applications of FWQC were also explored in the evaluation and formulation of WQS, ecological risk assessments, and the management of environmental emergencies and damage assessments to support environmental protection and management in China.