Human activities changed organic carbon transport in Chinese rivers during 2004-2018

Landsat monitoring reveals the history of river organic pollution across China during 1984-2023

River organic pollution exhibits pronounced spatiotemporal dynamics in response to environmental changes. However, the traditional method of tracking chemical oxygen demand (COD) and/or other organic pollution indicators at fixed locations over expansive regions is labor-intensive, time-consuming, and inadequate for achieving full spatial coverage. To address this limitation, here we developed a Random Forest algorithm using Landsat satellite data in conjunction with sub-daily (every 4 h) COD data at 1,997 sites across China. The proposed model achieved high accuracy, with a root mean square error of 0.52 mg/L and a mean absolute percent difference of 13.01 %. Additionally, the model was robust across clear, algae-laden, turbid, and black-smelling waters. Then, the algorithm was applied to investigate the spatiotemporal variations of COD concentration in Chinese rivers during 1984-2023. Across China, high river COD concentrations were observed in the eastern Songliao (3.56 ± 1.11 mg/L), Haihe (3.00 ± 0.89 mg/L), and Huaihe (3.57 ± 0.67 mg/L) basins. Anthropogenic activities could explain 79.39 % of the spatial variability in COD concentrations, and the cropland distribution had a significant impact. During 1984-2023, 73.58 % of China's rivers exhibited significant changes in COD concentrations (p < 0.05). With respect to the 800 mm isoprecipitation line, 56.62 % of the southeastern rivers showed decreasing trends; in contrast, 84.25 % of the northwestern rivers displayed increasing trends in COD concentrations. The temporal variations in COD concentrations were driven by the combined effects of factors including rainfall, vegetation coverage, and human activities; their relative contributions were 0.02 - 42.45 %, 0.07 - 68.76 %, and 0.06 - 90.31 % for COD changes in different provinces. This study underscores the feasibilities of using long-term Landsat data to efficiently and dynamically monitor organic pollution in rivers on a large scale, providing crucial implications for spatiotemporal monitoring of other water quality indicators.

Enhancing machine learning models for total organic carbon prediction by integrating geospatial parameters in river watersheds

This study utilizes machine learning (ML) algorithms to develop a robust total organic carbon (TOC) prediction model for river waters in the Geumho River sub-basins, South Korea, considering both non-rain and rain events. The model incorporates geospatial parameters such as land use, slope, flow rate, and basic water quality metrics including biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and suspended solids (SS). A key aspect of this research is examining how land use information enhances the model's predictive accuracy. We compared two ML algorithms-extreme gradient boosting (XGBoost) and deep neural networks (DNN)-with a traditional multiple linear regression (MLR) approach. XGBoost outperformed the others, achieving an R2 value between 0.61 and 0.68 in the test dataset and demonstrating significant improvement during rain events with an R2 of 0.77 when including land use data. In contrast, this enhancement was not observed with the MLR model. Feature importance analysis using Shapley values highlighted COD as the primary predictor for non-rain events, while during rain events, COD, TP, TN, SS and agricultural land collectively influenced TOC levels. This study significantly advances understanding of TOC variability across different land use scenarios in river systems and underscores the importance of integrating geospatial and water quality parameters to enhance TOC prediction, particularly during rain events. This methodology provides a valuable framework for developing river management strategies and monitoring long-term TOC trends, especially in scenarios with gaps in essential monitoring data.

High-Resolution Estimates of N2O Emissions from Inland Waters and Wetlands in China

Inland waters (rivers, lakes, and reservoirs) and wetlands (marshes and coastal wetlands) represent large and continuous sources of nitrous oxide (N2O) emissions, in view of adequate biomass and anaerobic conditions. Considerable uncertainties remain in quantifying spatially explicit N2O emissions from aquatic systems, attributable to the limitations of models and a lack of comprehensive data sets. Herein, we conducted a synthesis of 1659 observations of N2O emission rates to determine the major environmental drivers across five aquatic systems. A framework for spatially explicit estimates of N2O emissions in China was established, employing a data-driven approach that upscaled from site-specific N2O fluxes to robust multiple-regression models. Results revealed the effectiveness of models incorporating soil organic carbon and water content for marshes and coastal wetlands, as well as water nitrate concentration and dissolved organic carbon for lakes, rivers, and reservoirs for predicting emissions. Total national N2O emissions from inland waters and wetlands were 1.02 × 105 t N2O yr-1, with contributions from marshes (36.33%), rivers (27.77%), lakes (25.27%), reservoirs (6.47%), and coastal wetlands (4.16%). Spatially, larger emissions occurred in the Songliao River Basin and Continental River Basin, primarily due to their substantial terrestrial biomass. This study offers a vital national inventory of N2O emissions from inland waters and wetlands in China, providing paradigms for the inventorying work in other countries and insights to formulate effective mitigation strategies for climate change.

Driving mechanism of different nutrient conditions on microbial mediated nitrate reduction in magnetite-present river infiltration zone

Significant research is focused on the ability of riparian zones to reduce groundwater nitrate contamination. Owing to the extremely high redox activity of nitrate, naturally existing electron donors, such as organic matter and iron minerals, are crucial in facilitating nitrate reduction in the riparian zone. Here, we examined the coexistence of magnetite, an iron mineral, and nitrate, a frequently observed coexisting system in sediments, to investigate nitrate reduction features at various C/N ratios and evaluate the response of microbial communities to these settings. Additionally, we aimed to use this information as a foundation for examining the effect of nutritional conditions on the nitrate reduction process in magnetite-present environments. These results emphasise the significance of organic matter in enabling dissimilatory nitrate reduction to ammonium (DNRA) and enhancing the connection between nitrate reduction and iron in sedimentary environments. In the later phases of nitrate reduction, nitrogen fixation was the prevailing process in low-carbon environments, whereas high-carbon environments tended to facilitate the breakdown of organic nitrogen. High-throughput sequencing analysis revealed a robust association between C/N ratios and alterations in microbial community composition, providing insights into notable modifications in essential functioning microorganisms. The nitrogen-fixing bacterium Ralstonia is more abundant in ecosystems with scarce organic matter. In contrast, in settings rich in organic matter, microorganisms, such as Acinetobacter and Clostridia, which may produce ammonia, play crucial roles. Moreover, the population of iron bacteria grows in such an environment. Hence, this study proposes that C/N ratios can influence Fe(II)/Fe(III) conversions and simultaneously affect the process of nitrate reduction by shaping the composition of specific microbial communities.

Dissolved organic carbon spurs bacterial-algal competition and phosphorus-paucity adaptation: Boosting Microcystis' phosphorus uptake capacity

Dissolved organic carbon (DOC) can alter the availability of background nutrients by affecting the proliferation of heterotrophic bacteria, which exerts a notable influence on algal growth and metabolism. However, the mechanism of how allochthonous DOC (aDOC) precipitates shifts in bacterial-algal interactions and modulates the occurrence of cyanobacteria blooms remains inadequately elucidated. Therefore, this study investigated the relationship between bacteria and algae under aDOC stimulation. We found that excess aDOC triggered the breakdown and reestablishment of the equilibrium between Microcystis and heterotrophic bacteria. The rapid proliferation of heterotrophic bacteria led to a dramatic decrease in soluble phosphorus and thereby resulted in the inhibition of the Microcystis growth. When the available DOC was depleted, the rapid death of heterotrophic bacteria released large amounts of dissolved phosphorus, which provided sufficient nutrients for the recovery of Microcystis. Notably, Microcystis rejuvenated and showed higher cell density compared to the carbon-absent group. This phenomenon can be ascribed that Microcystis regulated the compositions of extracellular polymeric substances (EPS) and the expression of relevant proteins to adapt to a nutrient-limited environment. Using time of flight secondary ion mass spectrometry (TOF-SIM) and proteomic analysis, we observed an enhancement of the signal of organic matter and metal ions associated with P complexation in EPS. Moreover, Microcystis upregulated proteins related to organic phosphorus transformation to increase the availability of phosphorus in various forms. In summary, this study emphasized the role of DOC in algal blooms, revealing the underestimated enhancement of Microcystis nutrient utilization through DOC-induced heterotrophic competition and providing valuable insights into eutrophication management and control.

The impacts of water-sediment regulation on organic carbon in the Yellow River

The Yellow River water-sediment regulation (WSR) is a unique hydraulic engineering project that involves the resuspension and rapid discharge of sediment downstream under the influence of density currents. This process leads to short-term high-intensity sediment scouring, which in turn increases the output of organic carbon. The impact of WSR on the biogeochemical cycling of organic carbon in rivers has not been adequately explored. In this study, we applied stable isotope and 3-D fluorescence analyses to investigate the impact of WSR at the Xiaolangdi (XLD) Reservoir on the sources and fluxes of dissolved organic carbon (DOC) and particulate organic carbon (POC) in the Yellow River. The POC and DOC fluxes during WSR (∼51 days) accounted for 95.5 % and 28.3 % of the annual fluxes. According to the Bayesian model used in the study, the fluxes of POC from sediment, terrestrial plants, and sewage increased by 23.2, 13.36, and 56.55 times, respectively, during the WSR period. On the other hand, the flux from various sources of DOC decreased by ∼0.7 times during the WSR process. The three-dimensional fluorescence index (specific UV absorbance [SUVA254], humification index [HIX], biological index [BIX], and fluorescence index [FI]) further reveals that in the WSR process, more DOC comes from sediment and upstream water. This study provides quantitative insights into the effects of WSR on river organic carbon export dynamics and the driving mechanisms behind them. It also has important implications for understanding the impact of anthropogenic disturbance on the global carbon cycle.

Enhanced Role of Streamflow Processes in the Evolutionary Trends of Dissolved Organic Carbon

Investigating dissolved organic carbon (DOC) dynamics and drivers in rivers enhances the understanding of carbon-environment linkages and support sustainability. Previous studies did not fully consider the dynamic nature of key drivers that influence the long-term changing trends in DOC concentration over time (the controlling factors and their roles in DOC trend can undergo alterations over time). We analyzed 42 years (1979-2018) of hydrometeorology, sulfate SO4, and DOC data from a 5.42 km2 watershed in central-southern Ontario, Canada. Our findings reveal a significant (p ≤ 0.01) overall increase in DOC concentrations, mainly due to the coevolution of SO4 and streamflow trends, especially the extreme flows. Over the 42-year period, the changing trend of streamflow (especially the extreme high or low flows) have significantly (p < 0.05) intensified their influence on DOC trends, increasing by an average of 30%. Conversely, the impact of SO4 has weakened, experiencing an average decrease of 32.6%. The upward trend in the annual average DOC concentration is attributed to the increasing number of maximum flow days within a year, while the decreasing trend in the number of minimum flow days has a contrasting effect. In other words, changes in maximum and minimum flow days have a counteracting effect on the DOC concentration trends. These results underscore the importance of considering the effects of altered streamflow processes on carbon cycle changes under evolving environmental conditions.

Source, composition and molecular diversity of dissolved and particulate organic matter varied with riparian land use in tropical coastal headstreams

Source, composition and molecular diversity determine the reactivity and stabilization of organic matter (OM, dissolved [DOM]/particulate [POM]), affecting its behavior and fate. Here, multiple spectral and mass spectrometry techniques were applied to examine how riparian land-use shaped the source, composition and molecular diversity of POM and DOM (HDOM) in adjacent headstreams. Compared to HDOM with abundant lignins, microbially-transformed heteroatoms and carboxyl-rich alicyclic acids (CRAMs), POM exhibited higher allochthonous characteristics and more bioactive components, but lower molecular weight and diversity in different land-use-dominated streams. Compared to wetland-dominated headstreams, both POM and HDOM exhibited more terrestrial origin and condensed aromatics/tannins molecules for agriculture-impacted headstreams and bio-labile lipids, proteins and carbohydrates for forest-impacted headstreams. Structural equation mode (SEM) showed that soil-derived DOM (SDOM) showed the most prominent influence on the source, composition and molecular diversity of POM and the source of HDOM. The molecular composition and diversity of HDOM were mainly influenced by soil properties/SDOM and aquatic microorganisms, respectively. Redundancy analysis (RDA) revealed that autochthonous, bio-labile compositions of POM in forest and wetland streams were positively related to aquatic Bacteroidetes/Cyanobacteria, and carbohydrates/biogenic index of SDOM, while that of HDOM were positively linked with aquatic Bacteroidetes/Cyanobacteria, and SDOM molecular diversity. Terrestrial and aromatic POM in agricultural headstreams were associated with aquatic total nitrogen/Actinobacteria, and humification degree, aromatic/phenolic substances of SDOM, while that of HDOM were mainly regulated by aquatic nitrate/total nitrogen/Actinobacteria, and aromatic/carboxylic-containing moieties of SDOM. Noteworthily, the molecular diversity of agricultural OM increased along the soil-stream continuum due to the input of soil condensed aromatics and tannins. The opposite trend was observed in forest and wetland streams due to the input of bioactive carbohydrates and the microbial-degradation in-stream. These results are helpful to predict the behavior and fate of OM and determine effective management strategies in tropical coastal regions undergoing intense anthropogenic alterations.

Human and natural activities regulate organic matter transport in Chinese rivers

Rivers connect terrestrial and aquatic ecosystems and export approximately 55.47 % of the net terrestrial carbon fixation. However, due to unavailable high-frequency monitoring data, litter is known about diurnal variation in riverine carbon transport on a national scale. Based on daily measurements between March 2021 and February 2022 at 1491 stations across China, this study clarified the spatiotemporal variations in riverine organic matter indicated by chemical oxygen demand (COD). Spatially, COD content showed a spatial pattern with high values in the northwest (p < 0.05), and COD flux was determined by water discharge (84.01 %). Human activities explained 73.20 % of the spatial variations in riverine COD content; in particular, agricultural planting significantly elevated riverine COD (r = 0.73, p < 0.01). Seasonally, 95.53 % of stations showed significant seasonal variations in COD contents (p < 0.05); 69.72 % (25.81 %) were identified as Type II (III) typically had the maximum (minimum) COD in summer (autumn). Moreover, except for human activities (41.08 ± 22.94 %), natural factors also contributed 47.41 ± 24.04 % to the seasonal variations. In summer, high temperatures increased COD by promoting algal proliferation at Type II stations; however, heavy precipitation diluted COD contents at Type III stations. In these cases, seasonal measurements were essential for estimating riverine organic matter transport, especially the values measured in spring and winter. This study has significant implications for managing the aquatic environment, estimating riverine organic matter transport, and balancing the global carbon budget.

Increasing riverine export of dissolved organic carbon from China

River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC ) and DOC concentrations (CDOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2 , p = .01), but little change in CDOC (-0.001 mg/L/year, p > .10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (-0.043 and -0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC , the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.