Inland Water Carbon Research Articles

Closing the inland water carbon cycle.

Inland water carbon dioxide emissions mirror the ocean's carbon uptake and are driven not only by ecosystem heterotrophy but also by chemical equilibration and calcification.

Inherent carbon burial potential of lakes across China

Eutrophication is one of the most important factors for the increasing production of organic carbon in inland waters. Variations in primary productivity across lakes due to eutrophication complicate predictions regarding future carbon burial and management of carbon sequestration in lakes. Phosphorus, an essential nutrient for plants and notorious for eutrophication, often limits primary productivity in lakes. It is crucial to normalize organic carbon burial to the content of total phosphorus (TP) in the water column to compare the inherent carbon burial capacity across lakes. However, the absence of long-term observational data of TP in lake water columns has hindered the ability to do so. In this study, we first verified that TP in sediments of Chinese lakes could substitute for that in the water column to reflect the annual primary productivity of lakes. Then we defined the inherent carbon burial potential of lakes as the total organic carbon to TP atomic ratio (TOC/TP) in the sediments. We quantified the inherent carbon burial potential of 90 lakes across China, exploring its spatial distribution, temporal trends, and potential controlling factors. The inherent carbon burial potential, based on surface sediments, decreased from western to eastern China, ranging from 466.1 to 24.3 with a mean of 137.0 ± 87.4. Mean annual precipitation was negatively related, while mean lake depth was positively related to the inherent carbon burial potential of the lakes across China. Analysis of sediment cores revealed that the mean inherent carbon burial potential of the lakes across China increased from 75.1 to 122.9 since the 1950s. Inherent carbon burial potential of the lakes in southwestern and eastern China, however, decreased since the 1990s. Changes in the extent of cultivated land in the watersheds were positively related to variations in the inherent carbon burial potential of Chinese lakes in the past few decades.

Modeling dissolved organic carbon in inland waters using an unmanned aerial vehicles-borne hyperspectral camera

Remote sensing can provide an alternative solution to quantify Dissolved Organic Carbon (DOC) in inland waters. Sensors embedded on Unmanned Aerial Vehicles (UAV) and satellites that can capture the DOC have already shown good relationships between DOC and the Colored Dissolved Organic Matter absorption (aCDOM.) coefficients in specific spectral regions. However, since the signal recorded by the sensors is reflectance-based, DOC estimates accuracy decreases when inverting the aCDOM. coefficients to reflectance. Thus, the main objective is to study the potential of a UAV-borne hyperspectral camera to retrieve the DOC in inland waters and to develop reflectance-based models using UAV and satellite (Landsat-8 OLI and Sentinel-2 MSI) data. Ensemble based systems (EBS) were favored in this study. The EBSUAV calibration results showed that six spectral regions (543.5, 564.5, 580.5, 609.5, 660, and 684 nm) are sensitive to DOC in waters. The EBSUAV test results showed a good concordance between measured and estimated DOC with an R2 = Nash-criterion (NASH) = 0.86, and RMSE (Root Mean Squares Error) = 0.68 mg C/L. The EBSSAT test results also showed a strong concordance between measured and estimated DOC with R2 = NASH = 0.92 and RMSE = 0.74 mg C/L. The spatial distribution of DOC estimates showed no dependency to other optically active elements. Nevertheless, estimates were sensitive to haze and sun glint.

Metabolic processes drive spatio-temporal variations of carbon sink/source in a karst river

Riverine carbon dioxide (CO2) exchange is a crucial component of the global carbon cycle. However, the changes in the CO2 sink/source in karst rivers caused by differences in lithological features and climate, hindered the resolution of the spatio-temporal heterogeneity of global inland water carbon emissions. Here, we use hydrochemical data and CO2 gas isotopic data to reveal the spatio-temporal variations of CO2 sink/source in karst rivers and their controlling mechanisms. Fifty-two monitoring transects were set up in the subtropical Lijiang River in southwest China in June and December 2019. Our results indicated that the CO2 flux across the water-air interface (FCO2) in the Lijiang River basin ranged from −43.77 to 519.67 mmol/(m2·d). In June, the Lijiang River acted as an atmospheric carbon source due to higher water temperatures (Twater). However, driven by hydrodynamic conditions and the metabolism of aquatic photosynthesis, the river shifts from being an atmospheric carbon source in June to an atmospheric carbon sink in December. The stable isotopes of CO2 (δ13C-CO2) show significant differences in the spatio-temporal variations of CO2 sink/source. In December, the transects of the Lijiang River basin with a negative CO2 flux are significantly negatively correlated with dissolved oxygen (DO) and chlorophyll-a (Chl-a) concentration (p < 0.05). This confirms that the enhancement of aquatic photosynthesis efficiency increased water DO concentrations, which resulted in the positive movement of water δ13C-CO2 and a decrease in the partial pressure of CO2 (pCO2) and FCO2. Comparative analysis with global river FCO2 indicates that under the combined driving forces of metabolic processes of aquatic photosynthetic organisms and hydrodynamic conditions, rivers tend to act more frequently as CO2 sinks, particularly in subtropical and temperate rivers. In conclusion, this study represents a new example focusing on CO2 dynamics to address the spatio-temporal heterogeneity of carbon emissions in inland waters on a global scale.

Environmental factors controlling seasonal and spatial variability of zooplankton in thermokarst lakes along a permafrost gradient of Western Siberia

Humic thermokarst lakes of permafrost peatlands in Western Siberia Lowland (WSL) are major environmental controllers of carbon and nutrient storage in inland waters and greenhouse gases emissions to the atmosphere in the subarctic. In contrast to sizable former research devoted to hydrochemical and hydrobiological (phytoplankton) composition, zooplankton communities of these thermokarst lakes and thaw ponds remain poorly understood, especially along the latitudinal gradient, which is a perfect predictor of permafrost zones. To fill this gap, 69 thermokarst lakes of the WSL were sampled using unprecedented spatial coverage, from continuous to sporadic permafrost zone, in order to assess zooplankton (Cladocera, Copepoda, Rotifera) diversity and abundance across three main open water physiological seasons (spring, summer and autumn). We aimed at assessing the relationship of environmental factors (water column hydrochemistry, nutrients, and phytoplankton parameters) with the abundance and diversity of zooplankton. A total of 74 zooplankton species and taxa were detected, with an average eight taxa per lake/pond. Species richness increased towards the north and reached the maximum in the continuous permafrost zone with 13 species found in this zone only. In contrast, the number of species per waterbody decreased towards the north, which was mainly associated with a decrease in the number of cladocerans. Abundance and diversity of specific zooplankton groups strongly varied across the seasons and permafrost zones. Among the main environmental controllers, Redundancy Analysis revealed that water temperature, lake area, depth, pH, Dissolved Inorganic and Organic Carbon and CO2 concentrations were closely related to zooplankton abundance. Cladocerans were positively related to water temperature during all seasons. Copepods were positively related to depth and lake water pH in all seasons. Rotifers were related to different factors in each season, but were most strongly associated with DOC, depth, CH4, phytoplankton and cladoceran abundance. Under climate warming scenario, considering water temperature increase and permafrost boundary shift northward, one can expect an increase in the diversity and abundance of cladocerans towards the north which can lead to partial disappearance of copepods, especially rare calanoid species.

Carbon Emissions From Chinese Inland Waters: Current Progress and Future Challenges

AbstractInland waters are significant emitters of greenhouse gases for the atmosphere and play an important role in the global carbon cycle. With a vast land area in East Asia spanning a broad range of climatic conditions, China has a large number of natural and human‐made water bodies. These inland water systems are of global importance because of their high carbon emission fluxes. Over the past decades, China has experienced unprecedented environmental changes driven by rapid economic development, which have profoundly modified its inland water carbon biogeochemistry and associated emissions. This review focuses on carbon dioxide (CO2) and methane (CH4) emission dynamics from China's inland waters in response to global change. Major drivers of CO2 and CH4 emissions, including aquatic metabolism, hydrological and climatic factors, and prevailing human impacts, are examined. To advance our understanding of carbon emissions from China's inland waters, we further identify several critical knowledge gaps, such as inadequate research in headwater streams and the climate‐sensitive Tibetan Plateau aquatic ecosystems. Furthermore, insufficient understanding of carbon emissions from inland waters undergoing extensive human interventions (e.g., damming, flow regulation, pollution, and farming practices in aquaculture ponds) is highlighted. We suggest that future efforts should be made to better capture the spatiotemporal heterogeneity in dissolved CO2 and CH4 concentrations and fluxes across China as well as their long‐term trends. To overcome uncertainties in carbon sources and current flux estimates, future research to mechanistically understand carbon transport and transformation in Chinese inland waters and their underlying processes is particularly needed.

New insight into and characterization of DOC, DON and CDOM for urban waters in the lower reaches of the Yellow River, China

Dissolved organic matter (DOM), usually measured as concentrations of dissolved organic carbon (DOC) and nitrogen (DON) and chromophoric dissolved organic matter (CDOM), plays a crucial role in the global carbon and nitrogen cycles in inland waters. The aim of this study is to characterize spatial variations of DOC, DON, and C:N molar ratios and CDOM using absorption spectroscopy and further determine their relationships using pearson correlations (r) for urban waters along trophic gradients in the lower reaches of the Yellow River (YR) of China. A dataset of 122 urban water samples were collected from four typical cities during 2021–2022. Principal component analysis (PCA) was performed to assess the relative distribution of these urban water samples. These urban waters can be grouped into two categories: mesotrophic waters (n = 57) and eutrophic waters (n = 65) based on trophic state index (TSI) threshold value of 50. Results revealed that there were significantly higher DOC, CDOM absorption and SUVA254 along with lower S275–295 and M (t-test, p < 0.01) in eutrophic waters compared with mesotrophic waters. DOC was significantly higher than DON (p < 0.01). DOC was highly related to DON (R2 = 0.649) and COD (R2 = 0.840) suggesting they were derived from a common source. CDOM absorption a(254) was strongly correlated with DOC (R2 = 0.770) and COD (R2 = 0.800). DON can be calculated based on the strong correlations between DOC and DON and then C:N molar ratios can be further obtained for these urban waters. These results implied that CDOM optical absorption a(254) can be viewed as the best indicators of DOC and associated with water quality parameters. These findings can help us to better understand DOC, DON and CDOM of DOM coupled cycling processes for urban waters with similar climatic and hydrologic conditions on basin scale in China.

Development of subsurface chlorophyll maximum layer and its contribution to the primary productivity of water column in a large subtropical reservoir

The phenomenon of subsurface chlorophyll maximum (SCM) layer emerging at a certain water depth is commonly found in stratified water bodies. Also, it is a crucial contributing region to the primary productivity of the water column. Currently, there is a lack of concern about the occurrence of SCM phenomena in studies targeting inland water bodies such as natural lakes and artificial reservoirs. This led to a significant underestimation of the level of primary productivity in these water bodies and their trophic state. In this study, a subtropical reservoir (the Xinanjiang Reservoir, XAJR) was investigated, to understand the characteristics of SCM layer in deep-large reservoir and its contribution to the primary productivity of the water column. Water sampling were conducted from September 2020 to August 2021, and in September 2022. Buoy station data for this reservoir between 2019 and 2021 were also collected. Based on the detailed observations of the water column profile in riverine area (X1), transitional area (X2), and central area (X3 and X4) of this reservoir, it was found that there was an obvious SCM phenomenon, which was closely related to the characteristics of seasonal thermal stratification. The SCM layer of XAJR appeared at depth around 3–5 m underwater from May to August, and as the thermal stratification strength increased, so did the depth and thickness of the SCM layer. It was estimated that gross primary productivity of euphotic layer of XAJR ranged from 347.9 to 4508.6 mgC·m−2·d−1. The average primary productivity level of the SCM layer reached 1411.7mgC·m−2·d−1, accounting for about 40–90% of the gross primary productivity of euphotic layer. This study contributes to a better understanding of the factors influencing changes in the development of the SCM layer in large reservoirs, as well as its critical role in the inland water carbon cycle.

Colloids in Thermokarst Lakes along a Permafrost and Climate Gradient of Permafrost Peatlands in Western Siberia Using In Situ Dialysis Procedure

Thermokarst lakes in the Western Siberian Lowland (WSL) are major environmental factors controlling organic carbon and trace metal storage in inland waters and greenhouse gas emissions to the atmosphere. In contrast to previously published research devoted to lake hydrochemistry, hydrobiology, sedimentary carbon, and processes controlling the lake total dissolved (&lt;0.45 μm) solute composition, the colloidal forms of organic carbon (ОC), and related elements remain poorly known, especially across the permafrost gradient in this environmentally important region. Here we sampled 38 thermokarst lakes in the WSL, from the continuous to the permafrost-free zone, and we assessed both the total (&lt;0.45 μm) and low-molecular-weight (&lt;1 kDa) concentrations of 50 major and trace elements using conventional filtration and in situ dialysis. We aimed at quantifying the relationships between the colloidal content of an element and the lake surface area, permafrost coverage (absent, sporadic, isolated, discontinuous, and continuous), pH, and the concentrations of the main colloidal constituents, such as OC, Fe, and Al. There was a positive correlation between the lake area and the contents of the colloidal fractions of DOC, Ni, rare earth elements (REE), and Hf, which could be due to the enhanced mobilization of OC, trace metals, and lithogenic elements from silicate minerals in the soil porewater within the lake watershed and peat abrasion at the lake border. In all permafrost zones, the colloidal fractions of alkalis and alkaline-earth metals decreased with an increase in lake size, probably due to a decrease in the DOC concentration in large lakes. There was an increase in the colloidal fractions of DOC, Fe, Al, trivalent and tetravalent trace cations, Mn, Co, Ni, As, V, and U from the southern, permafrost-free zone to the northern, permafrost-bearing zones. This observation could be explained by an enhanced feeding of thermokarst lakes by suprapermafrost flow and the thawing of dispersed peat ice in the northern regions. Considering the large permafrost gradient of thermokarst lakes sampled in the present study, and applying a space-for-time substitution approach, we do not anticipate sizable changes in the colloidal status of DOC or major or trace elements upon climate warming and the permafrost boundary shifting northwards. For incorporating the obtained results into global biogeochemical models of OC, metal micronutrients, and toxicant migration in the permafrost regions, one has to consider the connectivity among lakes, soil waters, and rivers. For this, measurements of lake colloids across the main hydrological seasons, notably the winter period, are necessary.

Dissolved Organic Carbon Dynamics Variability from Ponds Draining Different Landscapes in a Typical Agricultural Watershed

Dissolved organic carbon (DOC) in inland waters (rivers, reservoirs, lakes, and small ponds) plays a significant role in the global carbon cycle and affects global climate change. In addition, DOC is also a vital indicator of the water environment due to its multiple physical, chemical, and ecological roles. Lakes and ponds of small sizes are abundant on a global and regional scale, and a large increase in ponds is expected with global agricultural land expansion. However, the DOC characteristics of ponds in agricultural watersheds are still unclear, posing a challenge to better understanding the carbon cycle of inland waters. In this study, we explored the DOC variability and their influencing factors in ponds draining different landscapes in a typical agricultural watershed to address the issue. The field measurements over a year showed the DOC concentration varied among ponds draining different landscapes. Specifically, the mean DOC concentrations in the natural pond, sewage pond, aquaculture pond, and irrigation pond were (6.17 ± 1.49) mg/L, (12.08 ± 2.92) mg/L, (9.36 ± 2.92) mg/L, and (8.91 ± 2.71) mg/L, respectively. Meanwhile, monthly measurements found the DOC varied across sampling dates. The DOC variability was positively correlated with nutrients, primary production, and precipitation, suggesting anthropogenic loadings, an internal production rate, and hydrological regime that regulated the substantial variability of DOC in these ponds at the watershed scale. Further, large pollutant discharge and high primary production led to peak DOC occurring in the sewage pond. Our results implied that more attention should be paid to ponds in agricultural watersheds to better understand the roles of inland waters in the global carbon cycle.

Inland water metabolic carbon processes and associated biological mechanisms that drive carbon source-sink instability

&lt;p&gt;Due to their complexity, inland water carbon (C) cycling processes significantly impact the C source-sink stability status of terrestrial ecosystems over short-term, long-term, and geological timescales. Stable C source-sink processes primarily include terrestrial biospheric production, lithospheric organic carbon (OC) oxidization, rock weathering, and riverine C transport. Conversely, the effect of metabolic C processes on the C source-sink status of inland waterbodies is not stable. Therefore, inland water metabolic C processes may cause significant C sink underestimations, which relevant studies have largely ignored. A new way to account for this missing inland water C sink is an in-depth understanding of the metabolic C processes and associated driving effects of biological regulation mechanisms on the C source-sink status. This new approach can help to more accurately quantify the global ecosystem C budget. The purpose of this review is threefold: (i) to clarify metabolic C processes and associated biological regulation mechanisms of inland waterbodies; (ii) to systematically analyze C cycling processes and associated C source-sink statuses of inland waterbodies at different timescales; (iii) to reveal driving mechanisms of metabolic C processes on C source-sink stability in inland waterbodies. Doing so will help us better understand how to more accurately calibrate C source-sink functions globally while also garnering an in-depth understanding of the role that terrestrial ecosystems play in C neutralization under global climate change.&lt;/p&gt;

Estimation of dissolved organic carbon from inland waters at a large scale using satellite data and machine learning methods

Dissolved Organic Carbon (DOC) in inland waters plays an essential role in the global carbon cycle and has significant public health effects. Machine learning (ML) together with remote sensing has emerged as a powerful and promising combination to quantify water quality parameters from space. However, inland water sample data for DOC is limited. Hence, little is known about the potential to quantify DOC content in inland waters, especially over large-scale areas. This study presents the first attempt to estimate DOC in inland waters over a large-scale area using satellite data and ML methods with the newly published open-source dataset AquaSat. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were trained using more than 16 thousand samples across the continental United States matched with satellite data from Landsat 5, 7 and 8 missions. Satellite data from the Landsat missions were further extended with environmental data from the ERA5-Land product and used as input to train the ML algorithms. Our results show that including environmental data as inputs considerably improved the prediction of DOC for all ML algorithms, with GPR showing the most promising performance results with moderate estimation errors (RMSE: 4.08 mg/L). Permutation feature importance analysis showed that the wavelength range in the visible Green band (from Landsat) and the monthly average air temperature (from ERA5-Land) were the most important variables for the ML approaches. The results demonstrate the predictive strength of GPR and its useful feature to derive per pixel standard deviations for detailed analysis. Our results further highlight the important role of considering environmental processes to explain DOC variations over large scales. The application and performance of the GPR in mapping spatiotemporal variations of DOC in an entire water body were discussed by taking Lake Okeechobee (the 8th largest freshwater lake in the U.S.) as an illustrative example. While performance evaluation showed that DOC concentrations can be retrieved with adequate accuracy, algorithm development was challenged by the heterogenous nature of large-scale open source in situ data, issues related to atmospheric correction, and the low spatial and temporal resolution of the environmental predictors. This research demonstrates how open source, large-scale datasets like AquaSat in combination with ML and satellite remote sensing can make research toward large-scale estimation of inland water DOC more realistic while highlighting its remaining limitations and challenges.

Dynamics and controls of inland water CH4 emissions across the Conterminous United States: 1860-2019

Inland waters (rivers, lakes, and reservoirs) have been recognized as hotspots of methane (CH4) emissions. However, the magnitude and spatiotemporal pattern of CH4 emissions and their underlying mechanisms remain largely unknown due to a lack of process-based quantification of CH4 production, consumption, and evasion within the aquatic ecosystem. Here we developed a process-based aquatic CH4 module within the framework of the Dynamic Land Ecosystem Model (DLEM) to explicitly simulate inland water carbon fluxes and the associated CH4 processes. We further applied this model to assess the inland-water CH4 emissions across the conterminous United States (CONUS) as affected by the climate variability, land use, fertilizer nitrogen (N) application, atmospheric N deposition, and rising atmospheric CO2 concentration during 1860-2019. The inland water CH4 emissions across the CONUS had doubled from the 1860s (1.65±0.18 Tg CH4-C∙yr−1) to the 2010s (3.73±0.36 Tg CH4-C∙yr−1). In the 2000s, inland water accounts for 8% of the regional CH4 budget that offsets 11∼14% of the terrestrial C uptake across the CONUS. Our study showed that the small headwater streams (1st –3rd order) account for 49% of the diffusive CH4, and reservoirs constitute 50% of the ebullitive CH4 emissions during the 2010s. Climate change and variability played a dominant role in the increased CH4 emissions from rivers and lakes. This study implies that effective mitigation strategies to reduce CH4 emissions should pay much attention to global climate change and headwater stream management.

A novel semianalytical remote sensing retrieval strategy and algorithm for particulate organic carbon in inland waters based on biogeochemical-optical mechanisms

The estimation of particulate organic carbon (POC) concentrations from satellite images can provide crucial spatiotemporal continuous observation data for the carbon cycle and ecological environmental governance. Here, we developed a novel inversion algorithm for deriving POC in inland water based on remote sensing and geochemical isotopes, which is summarized as follows. First, we developed empirical relationships between the phytoplankton absorption coefficient and endogenous POC concentration (CendPOC) and between the nonalgal particulate absorption coefficient and terrestrial POC concentration (CterPOC). Second, based on the valid relationships, semianalytical retrieval models were established to estimate CendPOC and CterPOC. Third, the proportions of endogenous POC (RendPOC) and terrestrial POC (RterPOC) to the total POC concentration (CPOC) were derived using a three-band empirical model. Finally, CPOC was obtained by dividing CendPOC by RendPOC (RendPOC ≥ 0.5) or dividing CterPOC by RterPOC (RendPOC < 0.5). Validation with field data shows that our proposed algorithm can accurately derive CPOC (0–20 mg/L), with a root mean square deviation (RMSD), median bias (MB), median absolute percent difference (MAPD), and median ratio (MR) of 1.15 mg/L, −0.05 mg/L, 24%, and 0.98, respectively. Synchronous validation based on Sentinel-3/OLCI images confirmed the accuracy, with RMSD, MB, MAPD, and MR values of 0.41 mg/L, −0.16 mg/L, 28%, and 0.91, respectively. The algorithm was applied to ocean and land color sensor (OLCI) images to reveal the temporal and spatial variations in POC in Lake Taihu.

Anthropogenically driven climate and landscape change effects on inland water carbon dynamics: What have we learned and where are we going?

Inland waters serve as important hydrological connections between the terrestrial landscape and oceans but are often overlooked in global carbon (C) budgets and Earth System Models. Terrestrially derived C entering inland waters from the watershed can be transported to oceans but over 83% is either buried in sediments or emitted to the atmosphere before reaching oceans. Anthropogenic pressures such as climate and landscape changes are altering the magnitude of these C fluxes in inland waters. Here, we synthesize the most recent estimates of C fluxes and the differential contributions across inland waterbody types (rivers, streams, lakes, reservoirs, and ponds), including recent measurements that incorporate improved sampling methods, small waterbodies, and dried areas. Across all inland waters, we report a global C emission estimate of 4.40 Pg C/year (95% confidence interval: 3.95-4.85 Pg C/year), representing a 13% increase from the most recent estimate. We also review the mechanisms by which the most globally widespread anthropogenically driven climate and landscape changes influence inland water C fluxes. The majority of these drivers are expected to influence terrestrial C inputs to inland waters due to alterations in terrestrial C quality and quantity, hydrological pathways, and biogeochemical processing. We recommend four research priorities for the future study of anthropogenic alterations to inland water C fluxes: (1) before-and-after measurements of C fluxes associated with climate change events and landscape changes, (2) better quantification of C input from land, (3) improved assessment of spatial coverage and contributions of small inland waterbodies to C fluxes, and (4) integration of dried and drawdown areas to global C flux estimates. Improved measurements of inland water C fluxes and quantification of uncertainty in these estimates will be vital to understanding both terrestrial C losses and the "moving target" of inland water C emissions in response to rapid and complex anthropogenic pressures.

Inter‐laboratory differences in the apparent quantum yield for the photochemical production of dissolved inorganic carbon in inland waters and implications for photochemical rate modeling

AbstractSolar radiation initiates photochemical oxidation of dissolved organic carbon (DOC) to dissolved inorganic carbon (DIC) in inland waters, contributing to their carbon dioxide emissions to the atmosphere. Models can determine photochemical DIC production over large spatiotemporal scales and assess its role in aquatic C cycling. The apparent quantum yield (AQY) spectrum for photochemical DIC production, defined as mol DIC produced per mol chromophoric dissolved organic matter‐absorbed photons, is a critical model parameter. In previous studies, the principle for the determination of AQY spectra is the same but methodological specifics differ, and the extent to which these differences influence AQY spectra and simulated aquatic DIC photoproduction is unclear. Here, four laboratories determined AQY spectra from water samples of eight inland waters that are situated in Alaska, Finland, and Sweden and span a nearly 10‐fold range in DOM absorption coefficients. All AQY values fell within the range previously reported for inland waters. The inter‐laboratory coefficient of variation (CV) for wavelength‐integrated AQY spectra (300–450 nm) averaged 38% ± 3% SE, and the inter‐water CV averaged 63% ± 1%. The inter‐laboratory CV for simulated photochemical DIC production (conducted for the five Swedish lakes) averaged 49% ± 12%, and the inter‐water CV averaged 77% ± 10%. This uncertainty is not surprising given the complexities and methodological choices involved in determining DIC AQY spectra and needs to be considered when applying photochemical rate modeling. Thus, we also highlight current methodological limitations and suggest future improvements for DIC AQY determination to reduce inter‐laboratory uncertainty.

Tracing dissolved organic matter in inflowing rivers of Nansi Lake as a storage reservoir: Implications for water-quality control

Quantitative characterization of dissolved organic matter (DOM) in various aquatic ecosystems has become of increasing importance as its transformation plays a key role in inland water carbon, yet few studies have quantified water DOM inputs to storage lakes for water quality control and safety assurance. This study assessed the quantity and quality of DOM in 21 inflow rivers of Nansi Lake as the important storage lake of large-scale water transfer projects by using excitation-emission matrix spectroscopy coupled with parallel factor analysis (EEM-PARAFAC) and ultraviolet–visible (UV–Vis) spectroscopy. The results showed that DOM contents varied significantly with an average value of 5.8 mg L−1 in different inflow rivers, and three fluorescence substances (including UVC humic-like, UVA humic-like and tyrosine-like components) were identified by EEM-PARAFAC. The distribution of the DOM components was distinctively different among sampling sites, and UVA humic-like component mainly dominated in Nansi Lake. Meanwhile, DOM components with higher aromaticity and molecular weight were found in the west side of lake. Fluorescence spectral indexes manifested that the source of DOM was mainly from allochthonous or terrestrial input. Moreover, significant correlations between water quality and DOM characteristics were observed in Nansi Lake. These findings would be beneficial to understand the biogeochemical role and impact of DOM in inflowing rivers in the water-quality monitoring and control of storage lakes.

Linking the Dissolved and Particulate Domain of Organic Carbon in Inland Waters

AbstractOrganic carbon (OC) in inland waters is found in either dissolved or particulate states, each contributing differently to carbon cycling through state‐specific forms of transport, processing, and mineralization. Degradation of macroscopic organic material into solutes is the most common transition between these states, yet there is also the potential for dissolved organic carbon to aggregate and form particles. This latter process at the soil‐stream interface is subject of a new study by Einarsdóttir et al. (2020, https://doi.org/10.1029/2020JG005654) published in this issue. Their findings advance the understanding of the links between the dissolved and the particulate domain of OC with possible implication for long‐term OC burial and ecosystem functioning of inland waters.

Satellite Estimation of Dissolved Carbon Dioxide Concentrations in China's Lake Taihu.

Lakes play an important role in the global carbon cycle; however, there are still large uncertainties in the estimation of global lake carbon emission due to the limitations in conducting field surveys at large geographic scales. Using long-term Moderate-Resolution Imaging Spectroradiometer (MODIS) imagery and field observation data in eutrophic Lake Taihu, we developed a novel approach to estimate the concentration of dissolved carbon dioxide (cCO2) in lakes. Based on the MODIS-derived chlorophyll-a concentration, lake surface temperature, diffuse attenuation coefficient of photosynthetically active radiation, and photosynthetically active radiation, a spatially explicit cCO2 model was developed using multivariate quadratic polynomial regression (coefficient of determination (R2) = 0.84, root-mean-square error (RMSE) = 11.81 μmol L-1, unbiased percent difference (UPD) = 22.46%). Monte Carlo simulations indicated that the model is stable with relatively small deviations in cCO2 estimates caused by input variables (UPD = 26.14%). MODIS data from 2003 to 2018 showed a significant declining trend (0.42 μmol L-1 yr-1, p < 0.05) in the annual mean cCO2. This was associated with a complex balance between the increasing algae biomass and decreasing external inputs of inorganic carbon, nutrients, and organic matter. The high spatiotemporal variabilities in cCO2 were attributed to river inputs and seasonal changes in temperature and algae biomass. The study shows that satellite remote sensing can play an important role in the field of inland water carbon cycling, providing timely much-needed insights into the drivers of the spatial and temporal changes in dissolved CO2 concentrations in inland waters.

A Novel Algorithm to Estimate Phytoplankton Carbon Concentration in Inland Lakes Using Sentinel-3 OLCI Images

Phytoplankton carbon, an important biogeochemical and ecological parameter, plays a critical role in the carbon cycle and in global warming reduction. Estimation of phytoplankton carbon in inland waters on a large scale using remote sensing is useful for understanding, evaluating, and monitoring the carbon dynamics, and, in particular, for determining the spatial–temporal variation of primary production in inland waters. In a correlation analysis of the phytoplankton carbon concentration and water components, the result revealed no significant correlation between the chlorophyll-a concentration and phytoplankton carbon concentration in inland waters. However, the absorption peak height of particles at 675 nm, which is defined as the absorption at 675 nm subtracted by that at 660 nm, was found to be closely correlated with the phytoplankton carbon concentration. Thus, the absorption peak height of particles at 675 nm could be used as an indicator of the phytoplankton carbon concentration. A semianalytical method based on the remote-sensing reflectance in Sentinel-3 Ocean and Land Color Instrument (OLCI) bands 8, 9, and 17 was developed to derive the absorption peak of particles at a wavelength of 675 nm. Finally, an algorithm for estimating the phytoplankton carbon concentration in inland waters using OLCI bands 8, 9, and 17 was constructed. From 2013 to 2018, eight field campaigns were conducted in inland lakes in different seasons, and the optical properties, optically active water components, and phytoplankton carbon concentrations were obtained. An assessment of its accuracy using an independent data set demonstrated that the algorithm performance is acceptable (mean absolute percentage error, 48.6%, and root mean square error, 0.36 mg/L). As a demonstration, the algorithm was successfully applied to map the phytoplankton carbon concentration in Taihu Lake and Chaohu Lake, China, using OLCI images acquired on December 5, 2017, and August 5, 2018 and December 8, 2017, and August 7, 2017, and the spatial variation of the phytoplankton carbon concentration in Taihu Lake and Chaohu Lake was thoroughly examined. A semianalytical remote-sensing method, instead of a traditional time-consuming approach, was developed in this article, which can be used to estimate phytoplankton carbon concentration quickly, and provides an effective way to map the phytoplankton carbon concentration in inland water on a large scale.