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Although terrestrial ecosystems have been widely recognized as an important atmospheric carbon (C) sink, the net C sink capacity may have been overestimated due to C loss through aquatic ecosystems, particularly in catchments with fragile landscapes and intense human disturbances. Here, we integrated the three primary pathways of aquatic C export, including C burial, gaseous C emissions, and downstream C export, into the terrestrial-aquatic C assessment within the Wujiang River basin (WRB) in Southwest China, a typical karst river-reservoir system with cascade reservoirs. The assessment reports a net landscape C sink of 12.0, 13.8, 14.0, and 16.1 Tg C/yr in the WRB in the years 2000, 2006, 2013, and 2017, respectively, with the aquatic C export counteracting 10.6%, 11.9%, 14.6%, and 14.1% of the terrestrial C sink in these years. The aquatic C export exhibited a discernible increasing trend, indicating that dam construction and ecological restoration have profoundly altered the C biogeochemical processes and terrestrial-aquatic C transfer dynamics. Particularly, downstream C export contributed 61.8%-82.1% to the aquatic C export with approximately 72% occurring during the wet season, due largely to enhanced rock weathering and allochthonous C supply under severe soil erosion in this karst region. Organic C burial in reservoirs accounted for 0.7%-2.0% of the terrestrial C sink, which was primarily regulated by autochthonous C biogeochemical processes and terrestrial C input. Simultaneously, CO 2 and CH 4 emissions counteracted 1.2%-3.7% of the terrestrial C sink, and this counteracting effect was intensified if the gaseous emissions from depth-profile waters that are characterized by elevated microbial degradation and anoxic conditions were considered. This study emphasizes the substantial role of terrestrial-aquatic C transfer in offsetting the terrestrial C sink, which underscores the need of integrating aquatic C export for a holistic understanding of the net C sink capacity at the landscape scale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Nitrate dynamics within a catchment are critical to the earth's system process, yet the intricate details of its transport and transformation at high resolutions remain elusive. Hydrological effects on nitrate dynamics in particular have not been thoroughly assessed previously and this knowledge gap hampers our understanding and effective management of nitrogen cycling in watersheds. Here, machine learning (ML) models were employed to reconstruct the annual variation trend in nitrate dynamics and isotopes within a typical karst catchment. Random forest model demonstrates promising potential in predicting nitrate concentration and its isotopes, surpassing other ML models (including Long Short-term Memory, Convolutional Neural Network, and Support Vector Machine) in performance. The ML-modeled NO 3 - -N concentrations, δ 15 N-NO 3 - , and δ 18 O-NO 3 - values were in close agreement with field data (NSE values of 0.95, 0.80, and 0.53, respectively), which are notably challenging to achieve for process models. During the transition from dry to wet period, approximately 23.0 % of the annual precipitation (∼269.1 mm) was identified as the threshold for triggering a rapid response in the wet period. The modeled nitrate isotope values were significantly supported by the field data, suggesting seasonal variations of nitrogen sources, with precipitation as the primary driving force for fertilizer sources. Mixing of multiple sources appeared to be the main control of the transport and transformation of nitrate during the rising limb in the wet period, whereas process control (denitrification) took precedence during the falling limb, and the fate of nitrate was controlled by biogeochemical processes during the dry period., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Dissolved organic carbon (DOC) and discharge are often tightly coupled, though these relationships in karst environments remain poorly constrained. In this study, DOC dynamics over 13 hydrological events, alongside monthly monitoring over an entire hydrological year were monitored in a small karst catchment, SW China. The concurrent analyses of power-law model and hysteresis patterns reveal that DOC behavior is generally transport-limited due to flushing effects of increased discharge but highly variable at both intra- and inter-event scales. The initial discharge at event onset and discharge-weighted mean concentration of DOC ([DOC] DW ) of individual events can explain 37.7 % and 19.9 % of the variance of DOC behavior among events, respectively. The sustained dry-cold antecedent conditions make DOC hysteresis behavior during the earliest event complex and different from subsequent events. At event scale, the variability in DOC export is primarily controlled by [DOC] DW (explaining 64.3 %) and the yield of total dissolved solutes (Y TDS , explaining 30.4 %), reflecting the impacts of variable hydrological connectivity and intense soil-water-rock interactions in this karst catchment. On an annual scale, DOC yield (Y DOC , 222.86 kg C km -2 ) was mostly derived during the wet season (98.19 %) under the hydrological driving force. The difference in annual Y DOC between this karst catchment and other regions can be well explained by annual water yield (Y water , explaining 24.2 %) and [DOC] (explaining 35.4 %), whereas the variance in DOC export efficiency among catchments is almost exclusively controlled by [DOC] alone, independent of drainage area and annual Y water . This study highlights the necessity of high-frequency sampling for modeling carbon biogeochemical processes and the particularity of the earliest hydrological events occurred after a long cold-dry period in karst catchments. Under the changing climate, whether DOC dynamics in karst catchments will present source-limited patterns during more extreme hydrological events merits further study., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The exchange and transformation of dissolved organic matter (DOM) at the sediment-water interface are crucial factors in regulating watershed biogeochemistry, with the molecular composition of DOM serving as a pivotal determinant in elucidating this process. High-resolution mass spectrometry (HRMS) is an effective tool for resolving the composition of DOM. By analyzing the compositional characteristics of DOM at the sediment-water interface under three different salinities at the same latitude region in northern China, the findings indicate certain variations in component characteristics of DOM between low-salinity inland waters and high-salinity seawaters, with the former exhibiting greater molecular diversity and higher molecular weights, whereas the latter displayed a higher saturation and bioavailability. Notably, the presence of more CHOS substances in the low-salinity inland waters underscores the transformation of the DOM influenced by terrestrial inputs and anthropogenic activities. Conversely, the presence of more CHO and CHNO substances in high-salinity seawater underscores the microbial effects. The chemical transformation process from overlying water to pore water to sediments was characterized by methylation, hydrogenation, decarboxylation, and reduction, as determined by calculating the relations between the H/C and O/C ratios of different compound types. These findings indicate that HRMS can yield more refined results in revealing the process of DOM at the sediment-water interface under different environments, which provides a more reliable basis for a deeper understanding of the source-sink mechanism of sediment organic matter.

The water quality in the drinking water reservoir directly affects people's quality of life and health. When external pollution input is effectively controlled, endogenous release is considered the main cause of water quality deterioration. As the major nitrogen (N) and phosphorus (P) sources in reservoirs, sediment plays a vital role in affecting the water quality. To understand the spatial and temporal variation of N and P in the sediment, this study analyzed the current characteristics and cumulative effects of a semi-humid reservoir, Yuqiao Reservoir, in North China. The N and P concentrations in the reservoir sediment were decreased along the flow direction, while the minimum values were recorded at the central sediment profile. External input and algal deposition were the main factors leading to higher sediment concentrations in the east (Re-E) and west (Re-W) areas of reservoir sediment profiles. According to the long-term datasets, the peaks of both sediment total nitrogen content and deposition rate were observed in the 2010s, which has increased about three times and six times than in the1990s, respectively. Therefore, the increase in phosphorus concentration may be the main reason for eutrophication in water in recent years. The mineralization of organic matter has a significant promoting effect on releasing N and P from sediments, which will intensify eutrophication in water dominated by P and bring huge challenges to water environment management. This study highlights that the current imbalance in N and P inputs into reservoirs and the endogenous P release from sediment will have a significant impact on water quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Carbon dioxide (CO 2 ) production and emissions from inland waters play considerable roles in global atmospheric CO 2 sources, while there are still uncertainties regarding notable nutrient inputs and anthropogenic activities. Urban inland waters, with frequently anthropogenic modifications and severely nitrogen loadings, were hotspots for CO 2 emissions. Here, we investigated the spatiotemporal patterns of partial pressure of CO 2 (pCO 2 ) and CO 2 fluxes (FCO 2 ) in typical urban inland waters in Tianjin, China. Our observation indicated that pCO 2 values were oversaturated in highly polluted waters, particularly in sewage rivers and urban rivers, exhibiting approximately 9 times higher than the atmosphere equilibrium concentration during sampling campaigns. Obviously, the spatiotemporal distributions of pCO 2 and FCO 2 emphasized that the water environmental conditions and anthropogenic activities jointly adjusted primary productivity and biological respiration of inland waters. Meanwhile, statistically positive correlations between pCO 2 /FCO 2 and NH 4 + -N/NO 3 - -N (p < 0.05) suggested that nitrogen biogeochemical processes, especially the nitrification, played a dominant role in CO 2 emissions attributing to the water acidification that stimulated CO 2 production and emissions. Except for slight CO 2 sinks in waters with low organic contents, the total CO 2 emissions from the urban surface waters of Tianjin were remarkable (286.8 Gg yr -1 ). The results emphasized that the reductions of nitrogen loadings, sewage draining waters, and agricultural pollution could alleviate CO 2 emissions from urban inland waters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The water-level fluctuations zones (WLFZs) are crucial transitional interfaces within river-reservoir systems, serving as hotspots for N 2 O emission. However, the comprehension of response patterns and mechanisms governing N 2 O emission under hydrological fluctuation remains limited, especially in karstic canyon reservoirs, which introduces significant uncertainty to N 2 O flux assessments. Soil samples were collected from the WLFZs of the Hongjiadu (HJD) Reservoir along the water flow direction from transition zone (T1 and T2) to lacustrine zone (T3, T4 and T5) at three elevations for each site. These soil columns were used to conduct simulation experiments under various water-filled pore space gradients (WFPSs) to investigate the potential N 2 O flux pattern and elucidate the underlying mechanism. Our results showed that nutrient distribution and N 2 O flux pattern differed significantly between two zones, with the highest N 2 O fluxes in the transition zone sites and lacustrine zone sites were found at 75 % and 95 % WFPS, respectively. Soil nutrient loss in lower elevation areas is influenced by prolonged impoundment durations. The higher N 2 O fluxes in the lacustrine zone can be attributed to increased nutrient levels resulting from anthropogenic activities. Furthermore, correlation analysis revealed that soil bulk density significantly impacted N 2 O fluxes across all sites, while NO 3 - and SOC facilitated N 2 O emissions in T1-T2 and T4-T5, respectively. It was evident that N 2 O production primarily contributed to nitrification in the transition zone and was constrained by the mineralization process, whereas denitrification dominated in the lacustrine zone. Notably, the annual N 2 O efflux from WLFZs accounted for 27 % of that from the water-air interface in HJD Reservoir, indicating a considerably lower contribution than anticipated. Nevertheless, this study highlights the significance of WLFZs as a vital potential source of N 2 O emission, particularly under the influence of anthropogenic activities and high WFPS gradient., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Accurate prediction of dissolved oxygen (DO) dynamics is crucial for understanding the influence of environmental factors on the stability of aquatic ecosystem. However, limited research has been conducted to determine the optimal frequency of water quality monitoring that ensures continuous assessment of water health while minimizing costs. To address these challenges, the present study developed a hybrid stochastic hydrological model (i.e., ARIMA-GARCH hybrid model) and machine learning (ML) models. The objective of this study is to identify the best-performing model and establish the optimal monitoring frequency. Results revealed that high-frequency DO monitoring data exhibit greater variability compared to low-frequency data. Moreover, the ARIMA-GARCH model demonstrates promising potential in predicting DO concentrations for low-frequency monitoring data, surpassing ML models in performance. Furthermore, increasing the monitoring frequency significantly improves the prediction accuracy of models, regardless of whether point (with lower R 2 values of 0.64 and 0.51 for daily detection than these of every 15 min (0.96 and 0.99) at CHQ and LHT, respectively) or interval predictions (with RIW higher values of 2.00 and 1.55 for daily detection higher than these of 0.02 and 0.16 in every 15 min at CHQ and LHT, respectively) are considered. Additionally, a 4 hourly monitoring frequency was found to be optimal for water quality assessment using each model. These findings identify the superior performing of the ARIMA-GARCH model and highlight the crucial role of monitoring frequency in enhancing DO prediction and improving model performance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Excessive levels of NO 3 - can result in multiple eco-environmental issues due to potential toxicity, especially in coastal areas. Accurate source tracing is crucial for effective pollutant control and policy development. Bayesian models have been widely employed to trace NO 3 - sources, while limited studies have utilized optimized Bayesian models for NO 3 - tracing in the coastal rivers. The Bohai Rim is highly susceptible to ecological disturbances, particularly N pollution, and has emerged as a critical area. Therefore, identification the N fate and understanding their sources contribution is urgent for pollution mitigation efforts. In addition, understanding the influenced key driven factors to source dynamic in the past ten years is also implication to environmental management. In this study, water samples were collected from 36 major river estuaries that drain into the Bohai Sea of North China. The main transformation processes were analyzed and quantified the sources of NO 3 - using a Bayesian stable isotope mixing model (MixSIAR) with isotopic approach (δ 15 N-NO 3 - and δ 18 O-NO 3 - ). The overall isotopic composition of δ 15 N-NO 3 - and δ 18 O-NO 3 - in estuary waters ranged from -0.8-19.3‰ (9.3 ± 4.6‰) and from -7.1-10.5‰ (5.0 ± 4.3‰), respectively. The main sources of nitrate in most river estuaries were manure & sewage, and chemical fertilizer, while weak denitrification and mixed processes were observed in Bohai Rim region. A temporal decrease in the nitrogen load entering the Bohai Sea indicates an improvement in water quality in recent years. By incorporating informative priors and utilizing the calculated coefficients, the accuracy of sourcing results was significantly improved. This study highlighted the optimized MixSIAR model enhanced its accuracy for sourcing analysis and providing valuable insights for policy formulation. Future efforts should focus on improving management strategies to reduce nitrogen into the bay., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Nitrate contamination in aquatic systems is a widespread problem across the world. The isotopic composition (δ 15 N, δ 18 O) of nitrate and their isotope effect ( 15 ε, 18 ε) can facilitate the identification of the source and transformation of nitrate. Although previous researches claimed the isotope fractionations may change the original δ 15 N/δ 18 O values and further bias identification of nitrate sources, isotope effect was often ignored due to its complexity. To fill the gap between the understanding and application, it is crucial to develop a deep understanding of isotopic fractionation based on available evidence. In this regard, this study summarized the available methods to determine isotope effects, thereby systematically comparing the magnitude of isotope effects ( 15 ε and 18 ε) in nitrification, denitrification and anammox. We found that the enzymatic reaction plays the key role in isotope fractionations, which is significantly affected by the difference in the affinity, substrate channel properties and redox potential of active site. Due to the overlapping of microbial processes and accumulation of uncertainties, the significant isotope effects at small scales inevitably decrease in large-scale ecosystems. However, the proportionality of N and O isotope fractionation (δ 18 O/δ 15 N; 18 ε/ 15 ε) associated with nitrate reduction generally follows enzyme-specific proportionalities (i.e., Nar, 0.95; Nap, 0.57; eukNR, 0.98) in aquatic ecosystems, providing enzyme-specific constant factors for the identification of nitrate transformation. With these results, this study finally discussed feasible source portioning methods when considering the isotope effect and aimed to improve the accuracy in nitrate source identification., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)