The importance of hydrology in routing terrestrial carbon to the atmosphere via global streams and rivers.

SignificanceStream/river carbon dioxide (CO2) emission has significant spatial and seasonal variations critical for understanding its macroecosystem controls and plumbing of the terrestrial carbon budget. We relied on direct fluvial CO2 partial pressure measurements and seasonally varying gas transfer velocity and river network surface area estimates to resolve reach-level seasonal variations of the flux at the global scale. The percentage of terrestrial primary production (GPP) shunted into rivers that ultimately contributes to CO2 evasion increases with discharge across regions, due to a stronger response in fluvial CO2 evasion to discharge than GPP. This highlights the importance of hydrology, in particular water throughput, in terrestrial-fluvial carbon transfers and the need to account for this effect in plumbing the terrestrial carbon budget.

Characterizing the Impact of Cyanobacterial Blooms on the Photoreactivity of Surface Waters from New York Lakes: A Combined Statewide Survey and Laboratory Investigation.

Cyanobacterial blooms introduce autochthonous dissolved organic matter (DOM) into aquatic environments, but their impact on surface water photoreactivity has not been investigated through collaborative field sampling with comparative laboratory assessments. In this work, we quantified the apparent quantum yields (Φapp,RI) of reactive intermediates (RIs), including excited triplet states of dissolved organic matter (3DOM*), singlet oxygen (1O2), and hydroxyl radicals (•OH), for whole water samples collected by citizen volunteers from more than 100 New York lakes. Multiple comparisons tests and orthogonal partial least-squares analysis identified the level of cyanobacterial chlorophyll a as a key factor in explaining the enhanced photoreactivity of whole water samples sourced from bloom-impacted lakes. Laboratory recultivation of bloom samples in bloom-free lake water demonstrated that apparent increases in Φapp,RI during cyanobacterial growth were likely driven by the production of photoreactive moieties through the heterotrophic transformation of freshly produced labile bloom exudates. Cyanobacterial proliferation also altered the energy distribution of 3DOM* and contributed to the accelerated transformation of protriptyline, a model organic micropollutant susceptible to photosensitized reactions, under simulated sunlight conditions. Overall, our study provides insights into the relationship between the photoreactivity of surface waters and the limnological characteristics and trophic state of lakes and highlights the relevance of cyanobacterial abundance in predicting the photoreactivity of bloom-impacted surface waters.

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.

Geographic distribution of bacterial communities of inland waters in China.

Microorganisms are integral to freshwater ecological functions and, reciprocally, their activity and diversity are shaped by the ecosystem state. Yet, the diversity of bacterial community and its driving factors at a large scale remain elusive. To bridge this knowledge gap, we delved into an analysis of 16S RNA gene sequences extracted from 929 water samples across China. Our analyses revealed that inland water bacterial communities showed a weak latitudinal diversity gradient. We found 530 bacterial genera with high relative abundance of hgcI clade. Among them, 29 core bacterial genera were identified, that is strongly linked to mean annual temperature and nutrient loadings. We also detected a non-linear response of bacterial network complexity to the increasing of human pressure. Mantel analysis suggested that MAT, HPI and P loading were the major factors driving bacterial communities in inland waters. The map of taxa abundance showed that the abundant CL500-29 marine group in eastern and southern China indicated high eutrophication risk. Our findings enhance our understanding of the diversity and large-scale biogeographic pattern of bacterial communities of inland waters and have important implications for microbial ecology.

Elevated nitrogen loadings facilitate carbon dioxide emissions from urban inland waters.

Carbon dioxide (CO2) production and emissions from inland waters play considerable roles in global atmospheric CO2 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 CO2 emissions. Here, we investigated the spatiotemporal patterns of partial pressure of CO2 (pCO2) and CO2 fluxes (FCO2) in typical urban inland waters in Tianjin, China. Our observation indicated that pCO2 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 pCO2 and FCO2 emphasized that the water environmental conditions and anthropogenic activities jointly adjusted primary productivity and biological respiration of inland waters. Meanwhile, statistically positive correlations between pCO2/FCO2 and NH4+-N/NO3--N (p < 0.05) suggested that nitrogen biogeochemical processes, especially the nitrification, played a dominant role in CO2 emissions attributing to the water acidification that stimulated CO2 production and emissions. Except for slight CO2 sinks in waters with low organic contents, the total CO2 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 CO2 emissions from urban inland waters.

Inland Waters Increasingly Produce and Emit Nitrous Oxide.

Nitrous oxide (N2O) is a long-lived greenhouse gas and currently contributes ∼10% to global greenhouse warming. Studies have suggested that inland waters are a large and growing global N2O source, but whether, how, where, when, and why inland-water N2O emissions changed in the Anthropocene remains unclear. Here, we quantify global N2O formation, transport, and emission along the aquatic continuum and their changes using a spatially explicit, mechanistic, coupled biogeochemistry-hydrology model. The global inland-water N2O emission increased from 0.4 to 1.3 Tg N yr-1 during 1900-2010 due to (1) growing N2O inputs mainly from groundwater and (2) increased inland-water N2O production, largely in reservoirs. Inland waters currently contribute 7 (5-10)% to global total N2O emissions. The highest inland-water N2O emissions are typically in and downstream of reservoirs and areas with high population density and intensive agricultural activities in eastern and southern Asia, southeastern North America, and Europe. The expected continuing excessive use of nutrients, dam construction, and development of suboxic conditions in aging reservoirs imply persisting high inland-water N2O emissions.

A satellite-based hybrid model for trophic state evaluation in inland waters across China.

Eutrophication is one of the major threats to the inland water ecosystem. Satellite remote sensing provides a promising way to monitor trophic state at large spatial scale in an efficient manner. Currently, most satellite-based trophic state evaluation approaches have focused on water quality parameters retrieval (e.g., transparency, chlorophyll-a), based on which trophic state was evaluated. However, the retrieval accuracies of individual parameter do not meet the demand for accurate trophic state evaluation, especially for the turbid inland waters. In this study, we proposed a novel hybrid model to estimate trophic state index (TSI) by integrating multiple spectral indices associated with different eutrophication level based on Sentinel-2 imagery. The TSI estimated by the proposed method agreed well with the in-situ TSI observations, with root mean square error (RMSE) of 6.93 and mean absolute percentage error (MAPE) of 13.77%. Compared with the independent observations from Ministry of Ecology and Environment, the estimated monthly TSI also showed good consistency (RMSE=5.91,MAPE=10.66%). Furthermore, the congruent performance of the proposed method in the 11 sample lakes (RMSE=5.91,MAPE=10.66%) and the 51 ungauged lakes (RMSE=7.16,MAPE=11.56%) indicated the favorable model generalization. The proposed method was then applied to assess the trophic state of 352 permanent lakes and reservoirs across China during the summers of 2016-2021. It showed that 10%, 60%, 28%, and 2% of the lakes/reservoirs are in oligotrophic, mesotrophic, light eutrophic, and middle eutrophic states respectively. Eutrophic waters are concentrated in the Middle-and-Lower Yangtze Plain, the Northeast Plain, and the Yunnan-Guizhou Plateau. Overall, this study improved the trophic state representativeness and revealed trophic state spatial distribution of Chinese inland waters, which has the significant meanings for aquatic environment protection and water resource management.

Unexpected low CO2 emission from highly disturbed urban inland waters.

Constituents and functionality of urban inland waters are significantly perturbed by municipal sewage inputs and tailwater discharge from wastewater treatment plants. However, large knowledge gaps persist in understanding greenhouse gas dynamics in urban inland waters due to a lack of in situ measurements. Herein, via a 3-year field campaign (2018-2020), we report river and lake CO2 emission and related aquatic factors regulating the emission in the municipality of Beijing. Mean pCO2 (546 ± 481 µatm) in the two urban lakes was lower than global non-tropical freshwater lakes and CO2 flux in 47% of the lake observations was negative. Though average pCO2 in urban rivers (3124 ± 3846 µatm) was among the higher range of global rivers (1300-4300 µatm), average CO2 flux was much lower than the global river average (99.7 ± 147.5 versus 358.4 mmol m-2 d-1). The high pCO2 cannot release to the atmosphere due to the low gas exchange rate in urban rivers (average k600 of 1.3 ± 1.3 m d-1), resulting in low CO2 flux in urban rivers. Additionally, eutrophication promotes photosynthetic uptake and aquatic organic substrate production, leading to no clear relationships observed between pCO2 and phytoplankton photosynthesis or dissolved organic carbon. In consistence with the findings, CO2 emission accounted for only 32% of the total greenhouse gas (GHG) emission equivalence (CO2, CH4 and N2O) in Beijing waters, in contrast to a major role of anthropogenic CO2 to anthropogenic GHG in the atmosphere in terms of radiative forcing (66%). These results pointed to unique GHG emission profiles and the need for a special account of urban inland waters in terms of aquatic GHG emissions.

Global methane and nitrous oxide emissions from inland waters and estuaries.

Inland waters (rivers, reservoirs, lakes, ponds, streams) and estuaries are significant emitters of methane (CH4 ) and nitrous oxide (N2 O) to the atmosphere, while global estimates of these emissions have been hampered due to the lack of a worldwide comprehensive data set of CH4 and N2 O flux components. Here, we synthesize 2997 in-situ flux or concentration measurements of CH4 and N2 O from 277 peer-reviewed publications to estimate global CH4 and N2 O emissions from inland waters and estuaries. Inland waters including rivers, reservoirs, lakes, and streams together release 95.18 Tg CH4  year-1 (ebullition plus diffusion) and 1.48 Tg N2 O year-1 (diffusion) to the atmosphere, yielding an overall CO2 -equivalent emission total of 3.06 Pg CO2  year-1 . The estimate of CH4 and N2 O emissions represents roughly 60% of CO2 emissions (5.13 Pg CO2  year-1 ) from these four inland aquatic systems, among which lakes act as the largest emitter for both CH4 and N2 O. Ebullition showed as a dominant flux component of CH4 , contributing up to 62%-84% of total CH4 fluxes across all inland waters. Chamber-derived CH4 emission rates are significantly greater than those determined by diffusion model-based methods for commonly capturing of both diffusive and ebullitive fluxes. Water dissolved oxygen (DO) showed as a dominant factor among all variables to influence both CH4 (diffusive and ebullitive) and N2 O fluxes from inland waters. Our study reveals a major oversight in regional and global CH4 budgets from inland waters, caused by neglecting the dominant role of ebullition pathways in those emissions. The estimated indirect N2 O EF5 values suggest that a downward refinement is required in current IPCC default EF5 values for inland waters and estuaries. Our findings further indicate that a comprehensive understanding of the magnitude and patterns of CH4 and N2 O emissions from inland waters and estuaries is essential in defining the way of how these aquatic systems will shape our climate.

Contrasting Impacts of Photochemical and Microbial Processing on the Photoreactivity of Dissolved Organic Matter in an Adirondack Lake Watershed.

Photochemical and microbial processing are the prevailing mechanisms that shape the composition and reactivity of dissolved organic matter (DOM); however, prior research has not comparatively evaluated the impacts of these processes on the photoproduction of reactive intermediates (RIs) from freshly sourced terrestrial DOM. We performed controlled irradiation and incubation experiments with leaf and soil samples collected from an acid-impacted lake watershed in the Adirondack Mountain region of New York to examine the effects of DOM processing on the apparent quantum yields of RIs (Φapp,RI), including excited triplet states of DOM (3DOM*), singlet oxygen (1O2), and hydroxyl radicals (•OH). Photodegradation led to net reductions in Φapp,1O2, Φapp,3DOM*, and Φapp,•OH, whereas (photo-)biodegradation resulted in increases in Φapp,1O2 and Φapp,3DOM*. Photodegradation and (photo-)biodegradation also shifted the energy distribution of 3DOM* in different directions. Multivariate statistical analyses revealed the potential relevance of photo-biodegradation in driving changes in Φapp,1O2 and Φapp,3DOM* and prioritized five bulk DOM optical and redox properties that best explained the variations in Φapp,1O2 and Φapp,3DOM* along the watershed terrestrial-aquatic continuum. Our findings highlight the contrasting impacts of photochemical and microbial processes on the photoreactivity of freshly sourced terrestrial DOM and invite further studies to develop a more holistic understanding of their implications for aquatic photochemistry.

Anthropogenic land use substantially increases riverine CO2 emissions.

Carbon dioxide (CO2) emissions from inland waters to the atmosphere are a pivotal component of the global carbon budget. Anthropogenic land use can influence riverine CO2 emissions, but empirical data exploring cause-effect relationships remain limited. Here, we investigated CO2 partial pressures (pCO2) and degassing in a monsoonal river (Yue River) within the Han River draining to the Yangtze in China. Almost 90% of river samples were supersaturated in CO2 with a mean ± standard deviation of 1474 ± 1614 µatm, leading to emissions of 557 - 971 mmol/m2/day from river water to the atmosphere. Annual CO2 emissions were 1.6 - 2.8 times greater than the longitudinal exports of riverine dissolved inorganic and organic carbon. pCO2 was positively correlated to anthropogenic land use (urban and farmland), and negatively correlated to forest cover. pCO2 also had significant and positive relationships with total dissolved nitrogen and total dissolved phosphorus. Stepwise multiple regression models were developed to predict pCO2. Farmland and urban land released nutrients and organic matter to the river system, driving riverine pCO2 enrichment due to enhanced respiration in these heterotrophic rivers. Overall, we show the crucial role of land use driving riverine pCO2, which should be considered in future large-scale estimates of CO2 emissions from streams. Land use change can thus modify the carbon balance of urban-river systems by enhancing river emissions, and reforestation helps carbon neutral in rivers.

Small artificial waterbodies are widespread and persistent emitters of methane and carbon dioxide.

Inland waters play an active role in the global carbon cycle and emit large volumes of the greenhouse gases (GHGs), methane (CH4 ) and carbon dioxide (CO2 ). A considerable body of research has improved emissions estimates from lakes, reservoirs and rivers but recent attention has been drawn to the importance of small, artificial waterbodies as poorly quantified but potentially important emission hotspots. Of particular interest are emissions from drainage ditches and constructed ponds. These waterbody types are prevalent in many landscapes and their cumulative surface areas can be substantial. Furthermore, GHG emissions from constructed waterbodies are anthropogenic in origin and form part of national emissions reporting, whereas emissions from natural waterbodies do not (according to Intergovernmental Panel on Climate Change guidelines). Here, we present GHG data from two complementary studies covering a range of land uses. In the first, we measured emissions from nine ponds and seven ditches over a full year. Annual emissions varied considerably: 0.1-44.3 g CH4  m-2  year-1 and -36-4421 g CO2  m-2  year-1 . In the second, we measured GHG concentrations in 96 ponds and 64 ditches across seven countries, covering subtropical, temperate and sub-arctic biomes. When CH4 emissions were converted to CO2  equivalents, 93% of waterbodies were GHG sources. In both studies, GHGs were positively related to nutrient status (C, N, P), and pond GHG concentrations were highest in smallest waterbodies. Ditch and pond emissions were larger per unit area when compared to equivalent natural systems (streams, natural ponds). We show that GHG emissions from natural systems should not be used as proxies for those from artificial waterbodies, and that artificial waterbodies have the potential to make a substantial but largely unquantified contribution to emissions from the Agriculture, Forestry and Other Land Use sector, and the global carbon cycle.

Integrating carbon emission, accumulation and transport in inland waters to understand their role in the global carbon cycle.

Inland waters receive a significant quantity of carbon (C) from land. The fate of this C during transit, whether it is emitted to the atmosphere, accumulated in sediments or transported to the ocean, can considerably reshape the landscape C balance. However, these different fates of terrestrial C are not independent but are instead linked via several catchment and aquatic processes. Thus, according to mass conservation, any environmental change inducing a shift in a particular C fate should come at the expense of at least one other fate. Nonetheless, studies that have investigated C emission, accumulation and transport concertedly are scarce, resulting in fragmented knowledge of the role of inland waters in the global C cycle. Here, we propose a framework to understand how different C fates in aquatic systems are interlinked and covary under environmental changes. First, to explore how C fates are currently distributed in streams, rivers, reservoirs and lakes, we compiled data from the literature and show that 'C fate allocation' varies widely both within and among inland water systems types. Secondly, we developed a framework that integrates C fates in any inland water system by identifying the key processes underlying their linkages. Our framework places the partitioning between the different C forms, and how this is controlled by export from land, internal transformations and hydrology, as central to understanding C fate allocation. We argue that, by focusing on a single fate, studies could risk drawing misleading conclusions regarding how environmental changes will alter the role of inland waters in the global C cycle. Our framework thus allows us to holistically assess the consequences of such changes on coupled C fluxes, setting a foundation for understanding the contemporary and future fate of land-derived C in inland water systems.

Distinctive Patterns and Controls of Nitrous Oxide Concentrations and Fluxes from Urban Inland Waters.

Inland waters are significant sources of nitrous oxide (N2O), a powerful greenhouse gas. However, considerable uncertainty exists in the estimates of N2O efflux from global inland waters due to a lack of direct measurements in urban inland waters, which are generally characterized by high carbon and nitrogen concentrations and low carbon-to-nitrogen ratios. Herein, we present direct measurements of N2O concentrations and fluxes in lakes and rivers of Beijing, China, during 2018-2020. N2O concentrations and fluxes in the waters of Beijing exceeded previous estimates of global rivers due to the high carbon and nutrient concentrations and high aquatic productivity. In contrast, the N2O emission factor (N2O-N/DIN, median 0.0005) was lower than global medians and the N2O yield (ΔN2O/(ΔN2O + ΔN2), average 1.6%) was higher than those typically observed in rivers and streams. The positive relationship between N2O emissions and denitrifying bacteria as well as the Michaelis-Menten relationship between N2O emissions and NO3--N concentrations suggested that bacteria control the net production of N2O in waters of Beijing with N saturation, leading to a low N2O emission factor. However, low carbon-to-nitrogen ratios are beneficial for N2O accumulation during denitrification, resulting in high N2O yields. This study demonstrates the significant N2O emissions and their distinctive patterns and controls in urban inland waters and suggests that N2O emission estimates based on nitrogen loads and simple emission factor values are not appropriate for urban inland water systems.

Satellites for long-term monitoring of inland U.S. lakes: The MERIS time series and application for chlorophyll-a.

Lakes and other surface fresh waterbodies provide drinking water, recreational and economic opportunities, food, and other critical support for humans, aquatic life, and ecosystem health. Lakes are also productive ecosystems that provide habitats and influence global cycles. Chlorophyll concentration provides a common metric of water quality, and is frequently used as a proxy for lake trophic state. Here, we document the generation and distribution of the complete MEdium Resolution Imaging Spectrometer (MERIS; Appendix A provides a complete list of abbreviations) radiometric time series for over 2300 satellite resolvable inland bodies of water across the contiguous United States (CONUS) and more than 5,000 in Alaska. This contribution greatly increases the ease of use of satellite remote sensing data for inland water quality monitoring, as well as highlights new horizons in inland water remote sensing algorithm development. We evaluate the performance of satellite remote sensing Cyanobacteria Index (CI)-based chlorophyll algorithms, the retrievals for which provide surrogate estimates of phytoplankton concentrations in cyanobacteria dominated lakes. Our analysis quantifies the algorithms' abilities to assess lake trophic state across the CONUS. As a case study, we apply a bootstrapping approach to derive a new CI-to-chlorophyll relationship, ChlBS, which performs relatively well with a multiplicative bias of 1.11 (11%) and mean absolute error of 1.60 (60%). While the primary contribution of this work is the distribution of the MERIS radiometric timeseries, we provide this case study as a roadmap for future stakeholders' algorithm development activities, as well as a tool to assess the strengths and weaknesses of applying a single algorithm across CONUS.

Preliminary Investigation on Phytoplankton Dynamics and Primary Production Models in an Oligotrophic Lake from Remote Sensing Measurements.

The aim of this study is to test a series of methods relying on hyperspectral measurements to characterize phytoplankton in clear lake waters. The phytoplankton temporal evolutions were analyzed exploiting remote sensed indices and metrics linked to the amount of light reaching the target (EPAR), the chlorophyll-a concentration ([Chl-a]OC4) and the fluorescence emission proxy. The latter one evaluated by an adapted version of the Fluorescence Line Height algorithm (FFLH). A peculiar trend was observed around the solar noon during the clear sky days. It is characterized by a drop of the FFLH metric and the [Chl-a]OC4 index. In addition to remote sensed parameters, water samples were also collected and analyzed to characterize the water body and to evaluate the in-situ fluorescence (FF) and absorbed light (FA). The relations between the remote sensed quantities and the in-situ values were employed to develop and test several phytoplankton primary production (PP) models. Promising results were achieved replacing the FA by the EPAR or FFLH in the equation evaluating a PP proxy (R2 > 0.65). This study represents a preliminary outcome supporting the PP monitoring in inland waters by means of remote sensing-based indices and fluorescence metrics.

One- and Two-Band Sensors and Algorithms to Derive aCDOM(440) from Global Above- and In-Water Optical Observations.

The colored (or chromophoric, depending on the literature) dissolved organic matter (CDOM) spectral absorption coefficient, aCDOM(λ), is a variable of global interest that has broad application in the study of biogeochemical processes. Within the funding for scientific research, there is an overarching trend towards increasing the scale of observations both temporally and spatially, while simultaneously reducing the cost per sample, driving a systemic shift towards autonomous sensors and observations. Legacy aCDOM(λ) measurement techniques can be cost-prohibitive and do not lend themselves toward autonomous systems. Spectrally rich datasets carefully collected with advanced optical systems in diverse locations that span a global range of water bodies, in conjunction with appropriate quality assurance and processing, allow for the analysis of methods and algorithms to estimate aCDOM(440) from spectrally constrained one- and two-band subsets of the data. The resulting algorithms were evaluated with respect to established fit-for-purpose criteria as well as quality assured archival data. Existing and proposed optical sensors capable of exploiting the algorithms and intended for autonomous platforms are identified and discussed. One-band in-water algorithms and two-band above-water algorithms showed the most promise for practical use (accuracy of 3.0% and 6.5%, respectively), with the latter demonstrated for an airborne dataset.

Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine.

Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013-2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2 = 0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.

Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales.

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency's Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.

Net landscape carbon balance of a tropical savanna: Relative importance of fire and aquatic export in offsetting terrestrial production.

The magnitude of the terrestrial carbon (C) sink may be overestimated globally due to the difficulty of accounting for all C losses across heterogeneous landscapes. More complete assessments of net landscape C balances (NLCB) are needed that integrate both emissions by fire and transfer to aquatic systems, two key loss pathways of terrestrial C. These pathways can be particularly significant in the wet-dry tropics, where fire plays a fundamental part in ecosystems and where intense rainfall and seasonal flooding can result in considerable aquatic C export (ΣFaq ). Here, we determined the NLCB of a lowland catchment (~140 km2 ) in tropical Australia over 2 years by evaluating net terrestrial productivity (NEP), fire-related C emissions and ΣFaq (comprising both downstream transport and gaseous evasion) for the two main landscape components, that is, savanna woodland and seasonal wetlands. We found that the catchment was a large C sink (NLCB 334 Mg C km-2  year-1 ), and that savanna and wetland areas contributed 84% and 16% to this sink, respectively. Annually, fire emissions (-56 Mg C km-2  year-1 ) and ΣFaq (-28 Mg C km-2  year-1 ) reduced NEP by 13% and 7%, respectively. Savanna burning shifted the catchment to a net C source for several months during the dry season, while ΣFaq significantly offset NEP during the wet season, with a disproportionate contribution by single major monsoonal events-up to 39% of annual ΣFaq was exported in one event. We hypothesize that wetter and hotter conditions in the wet-dry tropics in the future will increase ΣFaq and fire emissions, potentially further reducing the current C sink in the region. More long-term studies are needed to upscale this first NLCB estimate to less productive, yet hydrologically dynamic regions of the wet-dry tropics where our result indicating a significant C sink may not hold.