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.

Global diversity, coexistence and consequences of resistome in inland waters

Human activities have long impacted the health of Earth's rivers and lakes. These inland waters, crucial for our survival and productivity, have suffered from contamination which allows the formation and spread of antibiotic-resistant genes (ARGs) and consequently, ARG-carrying pathogens (APs). Yet, our global understanding of waterborne pathogen antibiotic resistance remains in its infancy. To shed light on this, our study examined 1240 metagenomic samples from both open and closed inland waters. We identified 22 types of ARGs, 19 types of mobile genetic elements (MGEs), and 14 types of virulence factors (VFs). Our findings showed that open waters have a higher average abundance and richness of ARGs, MGEs, and VFs, with more robust co-occurrence network compared to closed waters. Out of the samples studied, 321 APs were detected, representing a 43 % detection rate. Of these, the resistance gene 'bacA' was the most predominant. Notably, AP hotspots were identified in regions including East Asia, India, Western Europe, the eastern United States, and Brazil. Our research underscores how human activities profoundly influence the diversity and spread of resistome. It also emphasizes that both abiotic and biotic factors play pivotal roles in the emergence of ARG-carrying pathogens.

An optical mechanism-based deep learning approach for deriving water trophic state of China's lakes from Landsat images

Widespread eutrophication has been considered as the most serious environment problems in the world. Given the critical roles of lakes in human society and serious negative effects of water eutrophication on lake ecosystems, it is thus fundamentally important to monitor and assess water trophic status of lakes. However, a reliable model for accurately estimating the trophic state index (TSI) of lakes across a large-scale region is still lacking due to their high complexity. Here, we proposed an optical mechanism-based deep learning approach to remotely estimate TSI of lakes based on Landsat images. The approach consists of two steps: (1) determining the optical indicators of TSI and modeling the relationship between them, and (2) developing an approach for remotely deriving the determined optical indicator from Landsat images. With a large number of in situ datasets measured from lakes (2804 samples from 88 lakes) across China with various optical properties, we trained and validated three machine learning methods including deep neural network (DNN), k-nearest neighbors (KNN) and random forest (RF) to model TSI with the optical indicators and TSI and derive the determined optical indicator from Landsat images. The results showed that (1) the total absorption coefficients of optically active constituents at 440 nm (at-w(440)) performs best in characterizing TSI, and (2) DNN outperforms other models in the inversion of both TSI and at-w(440). Overall, our proposed optical mechanism-based deep learning approach demonstrated a robust and satisfactory performance in assessing TSI using Landsat images (root mean squared error (RMSE) = 5.95, mean absolute error (MAE) = 4.81). This highlights its merit as a nationally-adopted method in lake water TSI estimation, enabling the convenience of the acquisition of water eutrophic information in large scale, thereby assisting us in managing lake ecology. Therefore, we assessed water TSI of 961 lakes (>10 km2) across China using the proposed approach. The resulting at-w(440) and TSI ranged from 0.01 m-1 to 31.42 m-1 and from 6 to 96, respectively. Of all these studied lakes, 96 lakes (11.40 %) were oligotrophic, 338 lakes were mesotrophic (40.14 %), 360 lakes were eutrophic (42.76 %), and 48 were hypertrophic (5.70 %) in 2020.

Methane accumulation and its potential precursor compounds in the oxic surface water layer of two contrasting stratified lakes

Methane (CH4) supersaturation in oxygenated waters is a widespread phenomenon despite the traditional perception of strict anoxic methanogenesis. This notion has recently been challenged by successive findings of processes and mechanisms that produce CH4 in oxic environments. While some of the processes contributing to the vertical accumulation of CH4 in the oxygenated upper water layers of freshwater lakes have been identified, temporal variations as well as drivers are still poorly understood. In this study, we investigated the accumulation of CH4 in oxic water layers of two contrasting lakes in Germany: Lake Willersinnweiher (shallow, monomictic, eutrophic) and Lake Stechlin (deep, dimictic, eutrophic) from 2019 to 2020. The dynamics of isotopic values of CH4 and the role of potential precursor compounds of oxic CH4 production were explored. During the study period, persistent strong CH4 supersaturation (relative to air) was observed in the surface waters, mostly concentrated around the thermocline. The magnitude of vertical CH4 accumulation strongly varied over season and was generally more pronounced in shallow Lake Willersinnweiher. In both lakes, increases in CH4 concentrations from the surface to the thermocline mostly coincided with an enrichment in 13C-CH4 and 2H-CH4, indicating a complex interaction of multiple processes such as CH4 oxidation, CH4 transport from littoral sediments and oxic CH4 production, sustaining and controlling this CH4 supersaturation. Furthermore, incubation experiments with 13C- and 2H-labelled methylated P-, N- and C- compounds clearly showed that methylphosphonate, methylamine and methionine acted as potent precursors of accumulating CH4 and at least partly sustained CH4 supersaturation. This highlights the need to better understand the mechanisms underlying CH4 accumulation by focusing on production and transport pathways of CH4 and its precursor compounds, e.g., produced via phytoplankton. Such knowledge forms the foundation to better predict aquatic CH4 dynamics and its subsequent rates of emission to the atmosphere.

Remote estimation of phycocyanin concentration in inland waters based on optical classification

In recent years, under the dual pressure of climate change and human activities, the cyanobacteria blooms in inland waters have become a threat to global aquatic ecosystems and the environment. Phycocyanin (PC), a diagnostic pigment of cyanobacteria, plays an essential role in the detection and early warning of cyanobacterial blooms. In this context, accurate estimation of PC concentration in turbid waters by remote sensing is challenging due to optical complexity and weak optical signal. In this study, we collected a comprehensive dataset of 640 pairs of in situ measured pigment concentration and the Ocean and Land Color Instrument (OLCI) reflectance from 25 lakes and reservoirs in China during 2020-2022. We then developed a framework consisting of the water optical classification algorithm and three candidate algorithms: baseline height, band ratio, and three-band algorithm. The optical classification method used remote sensing reflectance (Rrs) baseline height in three bands: Rrs(560), Rrs(647) and Rrs(709) to classify the samples into five types, each with a specific spectral shape and water quality character. The improvement of PC estimation accuracy for optically classified waters was shown by comparison with unclassified waters with RMSE = 72.6 μg L-1, MAPE = 80.4 %, especially for the samples with low PC concentration. The results show that the band ratio algorithm has a strong universality, which is suitable for medium turbid and clean water. In addition, the three-band algorithm is only suitable for medium turbid water, and the line height algorithm is only suitable for high PC content water. Furthermore, the five distinguished types with significant differences in the value of the PC/Chla ratio well indicated the risk rank assessment of cyanobacteria. In conclusion, the proposed framework in this paper solved the problem of PC estimation accuracy problem in optically complex waters and provided a new strategy for water quality inversion in inland waters.

Microplastics in water from the confluence of tropical rivers: Overall review and a case study in Paraiba do Sul River basin

Rivers are known for carrying out a fundamental role in the transportation of human debris from continental areas to the marine environment and have been identified as hotspots for plastic pollution. We characterized microplastics (MPs) along confluence areas in the Paraíba do Sul River basin, the biggest river in southeastern Brazil. This water body crosses highly industrialized areas, with the highest population density, and the major water demand in South America. Considering the important ecological function of this extensive watershed and the implications of MP pollution, we evaluate the spatial variation of MP concentration in the confluence areas and upstream from the confluence. Samples were taken from the superficial layer of the water column in February and June 2022, using manta net with 300 μm mesh size. A total of 19 categories and 2870 plastic particles were determined. The confluences areas of rivers showed the highest concentration of MPs, highlighting the confluences of the Paraiba do Sul and Muriaé rivers (0.71 ± 0.25 MP/m3), followed by Paraíba do Sul and Dois Rios rivers (0.42 ± 0.23 MP/m3) and Paraíba do Sul and Pomba rivers (0.38 ± 0.14 MP/m3). Black fibers were the main category, followed by blue fibers and blue fragments. The MPs in the surface waters of Paraíba do Sul River is significantly influenced by the sampling points spatiality. This result corroborates other studies around the world and reinforces the argument that affluents are important sources for the introduction of MPs in larger rivers. Nevertheless, our results provide a better understanding of the different contributing factors and occurrence of MPs in river basins.

Ecological traits do not predict the uptake of microplastics by fishes in a Neotropical River

Pollution by synthetic polymers is even more problematic to the environment when this material is fragmented into small portions, forming microplastics (MPs). We analyzed the contamination of ichthyofauna by MPs in an important river of the Atlantic Rainforest in regard to abundance, diversity of morphotypes, polymers, colors, and sizes of the synthetic particles in 20 species of fish. Fish were collected in November 2019 and in March 2020 in five sites along the Pomba River. Of the 101 fish analyzed, 49 (49%) presented MPs in at least one organ. Of the 20 species of fish collected 13 included individuals with at least one MP in their analyzed organs. The organs, trophic categories and feeding areas did not affect the general abundance of MPs types. Blue MPs were predominant, followed by the colors black, red, and white. MP fibers represented 91% of total MPs. Most MPs were between 2 and 3 mm in size. Polyethylene terephthalate (PET), polypropylene (PP), polyamide (PA), polyvinylidene chloride "Nylon" (PVDC), and high-density polyethylene (HDPE) were detected in the fishes. The exposure of the fish species to MPs was associated mainly with individual size and species-specific aspects, regardless of ecological traits. Considering that 55% of the fish species studied are consumed by humans, it is necessary to study the potential impact of MP ingestion on human health and to understand to what extent we may be consuming both plastic particles and contaminants that are adsorbed to MPs.

Sources and fates of particulate organic matter in inland waters with complex land use patterns

Elucidating the sources of particulate organic matter (POM) is the foundation for understanding their fates and the seasonal variation of their movement from the land-to-ocean aquatic continuum (LOAC). The POM from different sources has different reactivity, which determines their fates. However, the key link between the sources and fates of POM, especially in the complex land use watersheds in bays is still unclear. Stable isotopes and contents of organic carbon and nitrogen were applied to reveal them in a complex land use watershed with different gross domestic production (GDP) in a typical Bay, China. Our results showed that the POMs preserved in suspended particulate organic matter (SPM) were weakly controlled by assimilation and decomposition in the main channels. Source apportionments of SPM in the rural area were controlled by soil (46 % ~ 80 %), especially inert soils eroded from land to water due to precipitation. The contribution of phytoplankton resulted from slower water velocity and longer residence time in the rural area. The soil (47 % ~ 78 %) and manure and sewage (10 % ~ 34 %) were the two major contributors to SOMs in the developed and developing urban areas. The manure and sewage were important sources of active POM in the urbanization of different LUI, which showed discrepancies in the three urban areas (10 % ~ 34 %). Due to soil erosion and the most intensive industry supported by GDP, the soil (45 % ~ 47 %) and industrial wastewater (24 % ~ 43 %) were the two major contributors to SOMs in the industrial urban area. This study demonstrated the close relationship between the sources and fates of POM with complex land use patterns, which could reduce uncertainties in future estimates of the LOAC fluxes and secure ecological and environmental barriers in a bay area.

Meta-analysis reveals cyanotoxins risk across African inland waters

Global eutrophication and climate warming exacerbate production of cyanotoxins such as microcystins (MCs), presenting risks to human and animal health. Africa is a continent suffering from severe environmental crises, including MC intoxication, but with very limited understanding of the occurrence and extent of MCs. By analysing 90 publications from 1989 to 2019, we found that in various water bodies where MCs have been detected so far, the concentrations were 1.4-2803 times higher than the WHO provisional guideline for human lifetime exposure via drinking water (1 µg/L) in 12 of 15 African countries where data were available. MCs were relatively high in the Republic of South Africa (averaged 2803 μg/L) and Southern Africa as a whole (702 μg/L) when compared to other regions. Values were higher in reservoirs (958 μg/L) and lakes (159 μg/L) than in other water types, and much higher in temperate (1381 μg/L) than in arid (161 μg/L) and tropical (4 μg/L) zones. Highly significant positive relationships were found between MCs and planktonic chlorophyll a. Further assessment revealed high ecological risk for 14 of the 56 water bodies, with half used as human drinking water sources. Recognizing the extremely high MCs and exposure risk in Africa, we recommend routine monitoring and risk assessment of MCs be prioritized to ensure safe water use and sustainability in this region.

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.

Exploring microplastic pollution in a Mediterranean river: The role of introduced species as bioindicators

Studies of plastic contamination in freshwater ecosystems and their biota remain scarce, despite the fact that the vast majority of plastic waste initially passes through lotic ecosystems. Biomonitoring provides valuable information regarding plastic pollution and microplastic threats to biota and human health. The aim of this study was to explore the potential use of a non-indigenous fish species as a bioindicator of microplastic pollution in an Eastern Mediterranean River. Our study area is located in a heavily modified and vastly impacted urban river which flows through the largest part of the Metropolitan area of Athens, Greece. We used an introduced chub species (Squalius vardarensis) to assess microplastic ingestion in the river. The results indicated moderate occurrence and abundance of microplastics in the fish gastrointestinal tracts; one-third of specimens (35%) contained microplastics, although the average number of microplastics per specimen was relatively low (1.7 ± 0.2). Overall, the abundance of microplastics in the water confirmed the moderate level of microplastics contamination in our study area. The major polymer types of microplastics identified by FT-IR analysis were: polyethylene (PE), polyvinyl alcohol (PVA) and polypropylene (PP); reflecting the fragmentation of larger litter from industrial packaging and/or household goods. Surface runoff of the urban environment, via motorways and major road networks, could be the contributing factor to the reported microplastics. Our results suggest that generalist's non-indigenous species such as chubs could be used as bioindicators of microplastics in inland waters. Introduced fishes can be a feasible, nondestructive, and cost-effective option for the assessment of microplastics in freshwater ecosystems, while freshwater chubs' high abundance and omnipresence in European rivers further serve this scope. However, it is worth noting that the suitability of any particular species as a bioindicator of microplastics may depend on a variety of factors, including their feeding behavior, habitat, and exposure to microplastics in their environment.

An improved algorithm for estimating the Secchi disk depth of inland waters across China based on Sentinel-2 MSI data

Accurate remote sensing of the Secchi disk depth (Z_SD) in waters is beneficial for large-scale monitoring of the aquatic ecology of inland lakes. Herein, an improved algorithm (termed as Z_SD20 in this work) for retrieving Z_SD was developed from field measured remote sensing data and is available for various waters including clear waters, slightly turbid waters, and highly turbid waters. The results show that Z_SD20 is robust in estimating Z_SD in various inland waters. After further validation with an independent in situ dataset from 12 inland waters (0.1 m < Z_SD < 18 m), the developed algorithm outperformed the native algorithm, with the mean absolute square percentage error (MAPE) reduced from 32.8 to 19.4%, and root mean square error (RMSE) from 0.87 to 0.67 m. At the same time, the new algorithm demonstrates its generality in various mainstreaming image data, including Ocean and Land Color Instrument (OLCI), Geostationary Ocean Color Imager (GOCI), and Moderate Resolution Imaging Spectroradiometer (MODIS). Finally, the algorithm's application was implemented in 410 waters of China based on Sentinel-2 MSI imagery to elucidate the spatiotemporal variation of water clarity during 2015 and 2021. The new algorithm reveals great potential for estimating water clarity in various inland waters, offering important support for protection and restoration of aquatic environments.

Remote sensing retrieval of inland water quality parameters using Sentinel-2 and multiple machine learning algorithms

Remote sensing has long been an effective method for water quality monitoring because of its advantages such as high coverage and low consumption. For non-optically active parameters, traditional empirical and analytical methods cannot achieve quantitative retrieval. Machine learning has been gradually used for water quality retrieval due to its ability to capture the potential relationship between water quality parameters and satellite images. This study is based on Sentinel-2 images and compared the ability of four machine learning algorithms (eXtreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), Random Forest (RF), and Artificial Neural Network (ANN)) to retrieve chlorophyll-a (Chl-a), dissolved oxygen (DO), and ammonia-nitrogen (NH³-N) for inland reservoirs. The results indicated that XGBoost outperformed the other three algorithms. We used XGBoost to reconstruct the spatial-temporal patterns of Chl-a, DO, and NH³-N for the period of 2018-2020 and further analyzed the interannual, seasonal, and spatial variation characteristics. This study provides an efficient and practical way for optically and non-optically active parameters monitoring and management at the regional scale.

A ground-based remote sensing system for high-frequency and real-time monitoring of phytoplankton blooms

The worldwide expansion of phytoplankton blooms has severely threatened water quality, food webs, habitat stability and human health. Due to the rapidity of phytoplankton migration and reproduction, high-frequency information on phytoplankton bloom dynamics is crucial for their forecasting, treatment, and management. While several approaches involving satellites, in situ observations and automated underwater monitoring stations have been widely used in the past several decades, they cannot fully provide high-frequency and continuous observations of phytoplankton blooms at low cost and with high accuracy. Thus, we propose a novel ground-based remote sensing system (GRSS) that can monitor real-time chlorophyll a concentrations (Chla) in inland waters with a high frequency. The GRSS mainly consists of three platforms: the spectral measurement platform, the data-processing platform, and the remote access control, display and storage platform. The GRSS is capable of obtaining a remote sensing irradiance ratio (R(λ)) of 400-1000 nm at a high frequency of 20 s. Eight different Chla retrieval algorithms were calibrated and validated using a dataset of 481 pairs of GRSS R(λ) and in situ Chla measurements collected from four inland waters. The results showed that random forest regression achieved the best performance in deriving Chla (R² = 0.95, root mean square error = 13.40 μg/L, and mean relative error = 25.7%). The GRSS successfully captured two typical phytoplankton bloom events in August 2021 with rapid changes in Chla from 20 μg/L to 325 μg/L at the minute level, highlighting the critical role that this GRSS can play in the high-frequency monitoring of phytoplankton blooms. Although the algorithm embedded into the GRSS may be limited by the size of the training dataset, the high-frequency, continuous and real-time data acquisition capabilities of the GRSS can effectively compensate for the limitations of traditional observations. The initial application demonstrated that the GRSS can capture rapid changes of phytoplankton blooms in a short time and thus will play a critical role in phytoplankton bloom management. From a broader perspective, this approach can be extended to other carriers, such as aircraft, ships and unmanned aerial vehicles, to achieve the networked monitoring of phytoplankton blooms.

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.

Microplastics contamination in sediments from Portuguese inland waters: Physical-chemical characterisation and distribution

Plastics are the major constituent of waste accumulated in inland waters and subsequently transferred to the ocean. The smaller plastic particles, typically obtained from the fragmentation of larger pieces, are vehicles for food chain accumulation of plastic components and contaminants sorbed to these particles through their ingestion by small organisms. The monitoring of the level and trends of the contamination by microplastics is essential to determine the relevance and potential sources of this contamination necessary to define strategies to reduce this threat. This work presents microplastic contamination levels and trends of sediments of four Portuguese inland waters, namely Ria de Aveiro, Ria Formosa, Mira river, and Mondego river, between 02/2019 and 09/2020. The contamination is classified considering the type of polymer and size, shape, and colour of particles. Polymers are identified by micro-ATR-FTIR with true and false identification rates larger and lower than 95% and 5%, respectively. Duplicate analysis results are used to quantify contamination heterogeneity subsequently applied to assess if a specific contamination trend is not meaningful for a 99% confidence level. The analytical procedure is described in detail to clarify the scope of the analysis. Tests' quality is controlled by following strict quality control measures. Results from sixty-three sediment samples proved the ubiquitous presence of microplastic (MP) in these inland waters with contamination levels ranging between 20 MP kg^-1 and 1090 MP kg^-1, excluding six samples not contaminated with these particles. Overall, more than 86% of the microplastics were fragments lower than 1000 μm, and 33% were identified as polyethylene or polypropylene. A large diversity of microplastic colours was observed. For the Mondego River and Ria de Aveiro locations monitored for consecutive years, no significant variations of microplastic contamination were observed for a 99% confidence level.

Using CDOM spectral shape information to improve the estimation of DOC concentration in inland waters: A case study of Andean Patagonian Lakes

For the last two decades different scientific disciplines have focused on lacustrine dissolved organic matter (DOM) given its importance in the biogeochemistry of carbon and in ecosystem functioning. New satellites supply the appropriate resolutions to evaluate chromophoric dissolved organic matter (CDOM) in inland waters, opening the possibility to estimate DOM at appropriate spatiotemporal scales. This requires, however, a robust relationship between CDOM and dissolved organic carbon (DOC). In this work, we evaluated the use of CDOM as a proxy of DOC in 7 Andean Patagonian lakes. Considering the entire data set, CDOM absorption coefficients (a₃₅₅ and a₄₄₀) were linearly related with DOC. Shallow lakes, however, drove this relationship showing a moderate relationship, whereas, deep lakes with lower colour presented a weaker relationship. Therefore, we assessed the use of CDOM spectral shape information to improve DOC estimates regardless of observed DOM differences due to climatic seasonality and lakes' morphometry. The use of well-known CDOM spectral shape metrics (i.e., S_275-295 and a₂₅₀:a₃₆₅ ratio) significantly improved DOC estimation. Particularly, using a Gaussian decomposition approach we found that much of the variation in the spectral shape, associated with the variability of CDOM:DOC ratio, was explained by differences in two dynamic regions centred at 270 and 320 nm. A strong nonlinear relationship was found between the a₂₇₀:a₃₂₀ ratio and the DOC-specific absorption coefficients a*₃₅₅ and a*₄₄₀. This was translated into a further improvement in DOC estimation yielding the higher R² and lower mean absolute differences (MAPD < 16%), either considering the entire data set or shallow and deep lakes separately. Our results highlight that incorporating the CDOM spectral shape information improves the characterization of the DOC pool of inland waters, which is particularly relevant for remote and/or inaccessible sites and has significant implications for the environmental management, biogeochemical studies and future remote sensing applications.

Evaluation of trophic state for inland waters through combining Forel-Ule Index and inherent optical properties

Eutrophication is a severe environmental pollution problem for inland waters and poses significant threats to the water safety. Monitoring trophic state of inland waters using optical remote sensing generally requires the inversion of water quality parameters, such as chlorophyll-a, secchi depth, etc. However, the accurate inversion of these individual indicators remains challenging, while the associated retrieval errors can propagate and degrade the evaluation of trophic state. Hence, we proposed a novel monitoring method by developing a Trophic State Index (TSI) based on optical remote-sensing parameters, i.e., Forel-Ule index (FUI) and non-water absorption coefficient at 674 nm (referred to as a_t-w(674)) retrieved from Sentinel-3 Ocean and Land Color Instrument (OLCI) imagery. The estimated TSI showed favorable correspondence with observed water quality data, including coefficient of determination (r² = 0.91), root mean squared error (RMSE = 5.54), and mean absolute percentage error (MAPE = 10.69%). Using the Sentinel-3 OLCI data, the proposed method also had very good performance in the field spectrum (MAPE = 5.25 % , RMSE = 3.36). The monthly trophic state evaluation also showed congruence (MAPE = 12.51 % , RMSE = 6.41) with surface water quality monthly report (SWQMR) from the Ministry of Environment and Ecology of the People's Republic of China. The monthly TSI showed favorable agreement for 23 ungauged lakes (RMSE = 7.26, MAPE = 12.78%), indicating potential utility for regional lake water quality monitoring. The proposed method was then applied to 47 other large (>50 km²) water bodies in the Middle-and-Lower watershed of Yangtze River and the Huaihe watershed to evaluate the spatial and temporal variation of trophic state from 2016 to 2020. The TSI results revealed several lakes, such as Lake Honghu and Lake Luoma, with rapidly deteriorating water quality during the study period, while other lakes show relative improvement (e.g., Xiashan Reservoir), indicating unbalanced environmental pressure over the region. Overall, this study showed promising performance and potential for satellite-based monitoring of regional aquatic environments.

Spatiotemporal changes of eutrophication and heavy metal pollution in the inflow river system of Baiyangdian after the establishment of Xiongan New Area

Pollution in inflow rivers seriously endangers the water environment in downstream lakes. In this study, an inflow river system of the Baiyangdian-Fuhe river system (FRS) was investigated to display timely pollution patterns of eutrophication and heavy metals after the establishment of Xiongan New Area, aiming to reveal the weak parts in current pollution treatments and guide the further water quality management. The results showed that the pollution of eutrophication was worse than the heavy metals in FRS, with serious eutrophic parameters of ammonia nitrogen (NH₄ ⁺-N) and chemical oxygen demand (COD). There were greatly spatiotemporal variations of the pollution in FRS. (1) Concentrations of NH₄ ⁺-N and total phosphorus were all higher in summer and autumn, whereas, COD contents were higher in spring; the water quality index (WQI) of eutrophication linearly increased along FRS in summer and autumn, with pollution hotspots around the estuary area. (2) The pollution levels of plumbum exceeded cadmium (Cd) and chromium (Cr) but without strongly spatiotemporal changes; however, Cd and Cr in the town area and Cd in spring showed higher concentrations; the WQI of heavy metals showed single peak curves along FRS, with significantly higher values around the town area. Additionally, the four potential pollution sources: domestic sewage, traffic pollution, agricultural wastewater and polluted sediments were identified based on the pollution patterns and pollutant associations. These findings demonstrated current treatments failed to eliminate the pollution in some hotspots and periods, and the in-depth understanding of the pollution spatiotemporal patterns in this study, especially the pollution hotspots, serious periods and potential sources, are crucial to furtherly develop spatiotemporally flexible pollution treatment strategies.

Environmental drivers of nitrous oxide emission factor for a coastal reservoir and its catchment areas in southeastern China

While Asia is projected to be one of the major nitrous oxide (N₂O) sources in the coming decades, a more accurate assessment of N₂O budget has been hampered by low data resolution and poorly constrained emission factor (EF). Since urbanized coastal reservoirs receive high nitrogen loads from diverse sources across a heterogeneous landscape, the use of a single fixed EF may lead to large errors in N₂O assessment. In this study, we conducted high spatial resolution sampling of dissolved N₂O, nitrate-nitrogen (NO₃^--N) and other physico-chemical properties of surface water in Wenwusha Reservoir and other types of water bodies (river, drainage channels, and aquaculture ponds) in its catchment areas in southeastern China between November 2018 and June 2019. The empirically derived EF (calculated as N₂O-N:NO₃^--N) for the reservoir showed considerable spatial variations, with a 10-fold difference ranging from 0.8 × 10^-3 to 8.8 × 10^-3. The average EF varied significantly among the four types of water bodies in the following descending order: aquaculture ponds > river > drainage channels > reservoir. Across all the water bodies, the mean EF in summer was 1.8-3.5 and 1.7-2.8 fold higher than that in autumn and spring, respectively, owing to the elevated water temperature. Overall, our derived EF deviated considerably from the IPCC default value, which implied that the use of default EF could result in over- or under-estimation of N₂O emissions by up to 42%. We developed a multiple regression model that could explain 82% of the variance in EF based on water temperature and the ratio between dissolved organic carbon and nitrate-nitrogen (p < 0.001), which could be used to improve the estimate of EF for assessing N₂O emission from coastal reservoirs and other similar environments.

Classification method for quantification of waterbird nutrient cycling guilds

This classification method for quantification of waterbird nutrient cycling guilds focuses on the location of feeding habitats and the quantitative role of waterbirds in the nutrient and energy flow for inland aquatic ecosystems. The classification is a complex integration of the taxonomic, trophic, feeding and daily habitat use patterns based on most relevant previous studies and reference data in relation with the ecology and nutrient cycling of waterbirds: A) Net-importer guild: includes species which feed mostly outside inland waters in the terrestrial ecosystems and wetlands, but use water bodies as gathering and roosting sites (geese, cranes). B) Importer-exporter guild: includes species which feed both outside and in of inland waters and wetlands (dabbling ducks and gulls). C) Net-exporter guild: includes species which feed mostly on inland waters and wetlands (diving ducks, grebes, cormorants, small herons, most shorebirds). Conclusion of main findings that method can significantly contribute to the better understanding how waterbirds can effect the environment and the guilds as ecological indicators quantify their ecosystem functions, services.•

Net-importer guild includes species which feed mostly outside the inland waters

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Importer-exporter guild includes species which feed both in- and outside inland waters

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Net-exporter guild includes species which feed mostly inside the inland waters

Freshwater systems and ecosystem services: Challenges and chances for cross-fertilization of disciplines

Freshwater ecosystems are among the most threatened in the world, while providing numerous essential ecosystem services (ES) to humans. Despite their importance, research on freshwater ecosystem services is limited. Here, we examine how freshwater studies could help to advance ES research and vice versa. We summarize major knowledge gaps and suggest solutions focusing on science and policy in Europe. We found several features that are unique to freshwater ecosystems, but often disregarded in ES assessments. Insufficient transfer of knowledge towards stakeholders is also problematic. Knowledge transfer and implementation seems to be less effective towards South-east Europe. Focusing on the strengths of freshwater research regarding connectivity, across borders, involving multiple actors can help to improve ES research towards a more dynamic, landscape-level approach, which we believe can boost the implementation of the ES concept in freshwater policies. Bridging these gaps can contribute to achieve the ambitious targets of the EU's Green Deal.

Organophosphate esters in inland and coastal waters in northern Greece

The occurrence and distribution of organophosphate esters (OPEs) in inland and coastal waters in Thessaloniki, Greece, were studied during the period 2019-2020. Samples from rivers and streams as well as coastal waters, were analyzed for the presence of 11 OPEs in dissolved and particulate fraction. OPEs were ubiquitous pollutants in the aquatic environment. Concentrations of dissolved fraction of ΣOPEs concentrations ranged from 400 to 2158 ng L^-1 in rivers, 400-1270 in coastal sites and 377-30,560 ng L^-1 in streams. TBOEP showed the highest concentrations followed by TPHP, TNBP and TClPP. Significant particulate fractions were determined for TNBP, TClPP TPHP and TCP. Field partition coefficients in inland waters were dependent on the concentration of total suspended solids. Risk assessment did not show potential threat due to OPEs in rivers and coastal sites, however, potential adverse effects were found in streams.

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, Chl_BS, 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.

Environmental controls of harmful cyanobacterial blooms in Chinese inland waters

Harmful cyanobacterial blooms (CyanoHABs) are expanding world-wide, adversely affecting aquatic food production, recreational and tourism activities and safe drinking water supplies. China's inland waters have been increasingly threatened by CyanoHABs during the past several decades. The environmental factors controlling CyanoHABs are highly variable in space and time in China due to significant variations in climate, geography, geological and geochemical conditions among its many regions. Here, we synthesize diverse examples among Chinese water bodies regarding interactive effects of anthropogenic, climatic and geographic drivers influencing CyanoHAB potentials and dynamics in lakes and reservoirs; in order to provide a perspective and integrative approach to mitigating CyanoHABs. In China's many shallow water bodies, water quality is highly susceptible to human activity and to changing climatic and hydrological conditions, when compared to deeper lakes. Rapid increases in population, economic activity, and wastewater have accelerated CyanoHABs in China since 1980s, especially in the heavily urbanized, agricultural and industrial regions in the middle and lower Yangtze River basins. Climatic changes have provided an additional catalyst for expansion of CyanoHABs. In particular, rising spring temperatures have accelerated the onset and proliferation of Microcystis spp, blooms in the middle and lower reaches of Yangtze River basin. Large hydroelectric and water supply projects, like the Three Gorges Reservoir (TGR), have altered hydrological regimes, and have led to an increase of CyanoHABs in reservoirs and tributaries due to increases in water residence times. Manipulating water level fluctuations in the TGR may prove useful for controlling CyanoHAB in its tributary bays. Overall,CyanoHAB mitigation strategies will have to incorporate both N and P input reductions in these shallow systems. Furthermore, nutrient reduction strategies must consider climate change-induced increases in extreme weather events, including more intense rainfall and protracted heat waves and droughts, which can extend the magnitudes and duration of CyanoHABs. Ensuring the maintenance of natural hydrologic connectivity between lakes and rivers is of utmost importance in mitigating CyanoHABs throughout China.

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.

Plastic pollution: A focus on freshwater biodiversity

Plastics are dominant pollutants in freshwater ecosystems worldwide. Scientific studies that investigated the interaction between plastics and freshwater biodiversity are incipient, especially if compared to the marine realm. In this review, we provide a brief overview of plastic pollution in freshwater ecosystems around the world. We found evidence of plastic ingestion by 206 freshwater species, from invertebrates to mammals, in natural or semi-natural ecosystems. In addition, we reported other consequences of synthetic polymers in freshwater ecosystems-including, for instance, the entanglement of animals of different groups (e.g., birds). The problem of plastic pollution is complex and will need coordinated actions, such as recycling programs, correct disposal, stringent legislation, regular inspection, replacement of synthetic polymers with other materials, and ecological restoration. Current information indicates that the situation in freshwater ecosystems may be as detrimental as the pollution found in the ocean, although highly underappreciated.

Chromophoric dissolved organic matter in inland waters: Present knowledge and future challenges

Chromophoric dissolved organic matter (CDOM) plays an important role in the biogeochemical cycle and energy flow of aquatic ecosystems. Thus, systematic and comprehensive understanding of CDOM dynamics is critically important for aquatic ecosystem management. CDOM spans multiple study fields, including analytical chemistry, biogeochemistry, water color remote sensing, and global environmental change. Here, we thoroughly summarize the progresses of recent studies focusing on the characterization, distribution, sources, composition, and fate of CDOM in inland waters. Characterization methods, remote sensing estimation, and biogeochemistry cycle processes were the hotspots of CDOM studies. Specifically, optical, isotope, and mass spectrometric techniques have been widely used to characterize CDOM abundance, composition, and sources. Remote sensing is an effective tool to map CDOM distribution with high temporal and spatial resolutions. CDOM dynamics are mainly determined by watershed-related processes, including rainfall discharge, groundwater, wastewater discharges/effluents, and biogeochemical cycling occurring in soil and water bodies. We highlight the underlying mechanisms of the photochemical degradation and microbial decomposition of CDOM, and emphasize that photochemical and microbial processes of CDOM in inland waters accelerate nutrient cycling and regeneration in the water column and also exacerbate global warming by releasing greenhouse gases. Future study directions to improve the understanding of CDOM dynamics in inland waters are proposed. This review provides an interdisciplinary view and new insights on CDOM dynamics in inland waters.

Effects of dry-wet cycles on nitrous oxide emissions in freshwater sediments: a synthesis

Background

Sediments frequently exposed to dry-wet cycles are potential biogeochemical hotspots for greenhouse gas (GHG) emissions during dry, wet and transitional phases. While the effects of drying and rewetting on carbon fluxes have been studied extensively in terrestrial and aquatic systems, less is known about the effects of dry-wet cycles on N₂O emissions from aquatic systems. As a notable part of lotic systems are temporary, and small lentic systems can substantially contribute to GHG emissions, dry-wet cycles in these ecosystems can play a major role on N₂O emissions.

Methodology

This study compiles literature focusing on the effects of drying, rewetting, flooding, and water level fluctuations on N₂O emissions and related biogeochemical processes in sediments of lentic and lotic ecosystems.

Results

N₂O pulses were observed following sediment drying and rewetting events. Moreover, exposed sediments during dry phases can be active spots for N₂O emissions. The general mechanisms behind N₂O emissions during dry-wet cycles are comparable to those of soils and are mainly related to physical mechanisms and enhanced microbial processing in lotic and lentic systems. Physical processes driving N₂O emissions are mainly regulated by water fluctuations in the sediment. The period of enhanced microbial activity is driven by increased nutrient availability. Higher processing rates and N₂O fluxes have been mainly observed when nitrification and denitrification are coupled, under conditions largely determined by O₂ availability.

Conclusions

The studies evidence the driving role of dry-wet cycles leading to temporarily high N₂O emissions in sediments from a wide array of aquatic habitats. Peak fluxes appear to be of short duration, however, their relevance for global emission estimates as well as N₂O emissions from dry inland waters has not been quantified. Future research should address the temporal development during drying-rewetting phases in more detail, capturing rapid flux changes at early stages, and further explore the functional impacts of the frequency and intensity of dry-wet cycles.

A risk assessment method for remote sensing of cyanobacterial blooms in inland waters

The widespread occurrence of Cyanobacterial blooms (CABs) in inland waters is a typical and severe challenge for water resources management and environment protection. An accurate and spatially continuous risk assessment of CABs is critical for prediction and preparedness in advance. In this study, a multivariate integrated risk assessment (MIRA) method of CABs in inland waters was proposed. MIRA was simplified with the trophic levels, cyanobacterial and other aquatic plant condition using remote sensing indexes, including the Trophic State Index (TSI), Floating Algae Index (FAI) and Cyanobacteria and Macrophytes Index (CMI). First, the dates of risk assessment were carefully selected based on TSI. Then, we obtained the trophic levels, cyanobacterial, and other aquatic plant condition of water using TSI, CMI and FAI on the selected date, and further scored them pixel by pixel to quantify the risk value. Finally, the risk of CABs in water was accurately assessed based on the pixel risk value. Based on Landsat 8 OLI dataset, MIRA was executed and validated in three different lakes of Wuhan urban agglomeration (WUA) with different trophic states. The results demonstrated that the risk of CABs in Lake LongGan was overall higher than that in Lake LiangZi and Lake FuTou. And the risk of CABs in the east part of Lake LongGan was higher than the other parts. Seasonally, the risk level ranking in Lake LiangZi was the highest in summer, while lowest in winter. However, the seasonal risk ranking was spring, summer, autumn, and winter in Lake LongGan. Based on the comparisons with monthly water quality classification data and results of the existing study, including trophic level, ecology risk, and algal extent, the MIRA method was valuable for accurate and spatially continuous identifying the risk of CABs in inland waters with potential eutrophication trends.

Seasonal variation and the distribution of endocrine-disrupting chemicals in various matrices affected by algae in the eutrophic water environment of the pearl river delta, China

The seasonal variation and distribution among different matrices of endocrine-disrupting chemicals (EDCs) were investigated in the eutrophic water ecosystem of the Pearl River Delta, Guangdong, China. The chlorophyll a (Chl a) levels were generally higher in summer than in spring; however, the concentrations of 4-tert-octylphenol (OP), 4-nonylphenol (NP), and bisphenol A (BPA) in surface water were generally higher in spring (oligotrophic) than in summer (eutrophic). The levels of EDCs in SPM were lower in spring than in summer, a pattern seen in the seasonal variation of Chl a and particulate organic carbon (POC). The seasonal variations of EDCs in water bodies with different levels of eutrophication were analyzed in several dimensions including sediment, POC, algae and fish bile. The log K_oc for SPM/water was higher in summer than in spring. The log K_oc values for NP, OP, and BPA exhibited the following trends between matrices: colloid/water > sediment/water > SPM/water > algae/water, colloid/water > sediment/water > algae/water > SPM/water, and colloid/water > algae/water > sediment/water > SPM/water. The EDCs levels were different in fish tissues with the order bile > liver > muscle, with the concentrations being an order of magnitude higher in bile than in liver and an order of magnitude higher in liver than in muscle. The sequence of the bioconcentration factor (log BCF) for bile/water and liver/water was NP < OP < BPA in eutrophic conditions, but NP > OP > BPA in oligotrophic conditions. The order in eutrophic conditions was the same as the log BCF and log K_oc for algae/water, indicating that the accumulation of EDCs in water bodies could be affected by algae, which could be one of the reasons of the seasonal variation of EDCs in water.

Optimized methods for diffusive greenhouse gas flux analyses in inland waters

Inland waters are considered hotspots of greenhouse gas (GHG) emissions and have been extensively researched. Static chamber (STAT) and thin boundary layer (BLE) are two commonly used methods for analyzing diffusive GHG emissions from inland waters. However, the STAT method is often disturbed by GHG bubbles; meanwhile, many kinds of headspace gas are used in the BLE method, but the differences between their diffusive GHG emission analysis results are not understood. In this study, the chamber in the STAT method was modified to combat the disturbances from GHG bubbles, and the typically used gases for the BLE method, namely, pure nitrogen, air, and filtered air, were comparatively studied. Results demonstrated that the modified chamber could effectively prevent the invasion of GHG bubbles; it increased the success rate from 67 to 90% in the field test, with no obvious impacts on the results of the GHG emission analyses. The use of air and filtered air in the BLE method yielded the lower values of GHG emissions relative to pure nitrogen, and this finding was potentially attributed to the inhibition effects of the residual GHGs and high humidity in air and filtered air on the extraction of diffusive GHGs from the surface water. This study improved the commonly used methods for diffusive GHG emission analysis, and the current findings are beneficial to the study of GHG emissions from inland waters.

Regional measurements and spatial/temporal analysis of CDOM in 10,000+ optically variable Minnesota lakes using Landsat 8 imagery

Information on colored dissolved organic matter (CDOM) is essential for understanding and managing lakes but is often not available, especially in lake-rich regions where concentrations are often highly variable in time and space. We developed remote sensing methods that can use both Landsat and Sentinel satellite imagery to provide census-level CDOM measurements across the state of Minnesota, USA, a lake-rich landscape with highly varied lake, watershed, and climatic conditions. We evaluated the error of satellite derived CDOM resulting from two atmospheric correction methods with in situ data, and found that both provided substantial improvements over previous methods. We applied CDOM models to 2015 and 2016 Landsat 8 OLI imagery to create 2015 and 2016 Minnesota statewide CDOM maps (reported as absorption coefficients at 440 nm, a₄₄₀) and used those maps to conduct a geospatial analysis at the ecoregion level. Large differences in a₄₄₀ among ecoregions were related to predominant land cover/use; lakes in ecoregions with large areas of wetland and forest had significantly higher CDOM levels than lakes in agricultural ecoregions. We compared regional lake CDOM levels between two years with strongly contrasting precipitation (close-to-normal precipitation year in 2015 and much wetter conditions with large storm events in 2016). CDOM levels of lakes in agricultural ecoregions tended to decrease between 2015 and 2016, probably because of dilution by rainfall, and 7% of lakes in these areas decreased in a₄₄₀ by ≥3 m^-1. In two ecoregions with high forest and wetlands cover, a₄₄₀ increased by >3 m^-1 in 28 and 31% of the lakes, probably due to enhanced transport of CDOM from forested wetlands. With appropriate model tuning and validation, the approach we describe could be extended to other regions, providing a method for frequent and comprehensive measurements of CDOM, a dynamic and important variable in surface waters.

A simplified approach to detect a significant carbon dioxide reduction by phytoplankton in lakes and rivers on a regional and global scale

Carbon dioxide (CO₂) uptake by phytoplankton can significantly reduce the partial pressure of CO₂ (pCO₂) in lakes and rivers, and thereby CO₂ emissions. Presently, it is not known in which inland waters on Earth a significant pCO₂ reduction by phytoplankton is likely. Since detailed, comparable carbon budgets are currently not available for most inland waters, we modified a proxy to assess the pCO₂ reduction by phytoplankton, originally developed for boreal lakes, for application on a global scale. Using data from 61 rivers and 125 lakes distributed over five continents, we show that a significant pCO₂ reduction by phytoplankton is widespread across the temperate and sub-/tropical region, but absent in the cold regions on Earth. More specifically, we found that a significant pCO₂ reduction by phytoplankton might occur in 24% of the lakes in the temperate region, and 39% of the lakes in the sub-/tropical region. We also showed that such a reduction might occur in 21% of the rivers in the temperate region, and 5% of the rivers in the sub-/tropical region. Our results indicate that CO₂ uptake by phytoplankton is a relevant flux in regional and global carbon budgets. This highlights the need for more accurate approaches to quantify CO₂ uptake by primary producers in inland waters, particularly in the temperate and sub-/tropical region.

Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing

Cyanobacterial harmful algal blooms are the most common form of harmful algal blooms in freshwater systems throughout the world. However, in situ sampling of cyanobacteria in inland lakes is limited both spatially and temporally. Satellite data has proven to be an effective tool to monitor cyanobacteria in freshwater lakes across the United States. This study uses data from the European Space Agency Envisat MEdium Resolution Imaging Spectrometer and the Sentinel-3 Ocean and Land Color Instrument to provide a national overview of the percentage of lakes experiencing a cyanobacterial bloom on a weekly basis for 2008-2011, 2017, and 2018. A total of 2321 lakes across the contiguous United States were included in the analysis. We examined four different thresholds to define when a waterbody is classified as experiencing a bloom. Across these four thresholds, we explored variability in bloom percentage with changes in seasonality and lake size. As a validation of algorithm performance, we analyzed the agreement between satellite observations and previously established ecological patterns, although data availability in the wintertime limited these comparisons on a year-round basis. Changes in cyanobacterial bloom percentage at the national scale followed the well-known temporal pattern of freshwater blooms. The percentage of lakes experiencing a bloom increased throughout the year, reached a maximum in fall, and decreased through the winter. Wintertime data, particularly in northern regions, were consistently limited due to snow and ice cover. With the exception of the Southeast and South, regional patterns mimicked patterns found at the national scale. The Southeast and South exhibited an unexpected pattern as cyanobacterial bloom percentage reached a maximum in the winter rather than the summer. Lake Jesup in Florida was used as a case study to validate this observed pattern against field observations of chlorophyll a. Results from this research establish a baseline of annual occurrence of cyanobacterial blooms in inland lakes across the United States. In addition, methods presented in this study can be tailored to fit the specific requirements of an individual system or region.

Nutrient criteria for surface waters under the European Water Framework Directive: Current state-of-the-art, challenges and future outlook

The aim of European water policy is to achieve good ecological status in all rivers, lakes, coastal and transitional waters by 2027. Currently, more than half of water bodies are in a degraded condition and nutrient enrichment is one of the main culprits. Therefore, there is a pressing need to establish reliable and comparable nutrient criteria that are consistent with good ecological status. This paper highlights the wide range of nutrient criteria currently in use by Member States of the European Union to support good ecological status and goes on to suggest that inappropriate criteria may be hindering the achievement of good status. Along with a comprehensive overview of nutrient criteria, we provide a critical analysis of the threshold concentrations and approaches by which these are set. We identify four essential issues: (1) Different nutrients (nitrogen and/or phosphorus) are used for different water categories in different countries. (2) The use of different nutrient fractions (total, dissolved inorganic) and statistical summary metrics (e.g., mean, percentiles, seasonal, annual) currently hampers comparability between countries, particularly for rivers, transitional and coastal waters. (3) Wide ranges in nutrient threshold values within shared water body types, in some cases showing more than a 10-fold difference in concentrations. (4) Different approaches used to set threshold nutrient concentrations to define the boundary between "good" and "moderate" ecological status. Expert judgement-based methods resulted in significantly higher (less stringent) good-moderate threshold values compared with data-driven approaches, highlighting the importance of consistent and rigorous approaches to criteria setting. We suggest that further development of nutrient criteria should be based on relationships between ecological status and nutrient concentrations, taking into account the need for comparability between different water categories, water body types within these categories, and countries.

Remote sensing of cyanobacterial blooms in inland waters: present knowledge and future challenges

Timely monitoring, detection and quantification of cyanobacterial blooms are especially important for controlling public health risks and understanding aquatic ecosystem dynamics. Due to the advantages of simultaneous data acquisition over large geographical areas and high temporal coverage, remote sensing strongly facilitates cyanobacterial bloom monitoring in inland waters. We provide a comprehensive review regarding cyanobacterial bloom remote sensing in inland waters including cyanobacterial optical characteristics, operational remote sensing algorithms of chlorophyll, phycocyanin and cyanobacterial bloom areas, and satellite imaging applications. We conclude that there have many significant progresses in the remote sensing algorithm of cyanobacterial pigments over the past 30 years. The band ratio algorithms in the red and near-infrared (NIR) spectral regions have great potential for the remote estimation of chlorophyll a in eutrophic and hypereutrophic inland waters, and the floating algae index (FAI) is the most widely used spectral index for detecting dense cyanobacterial blooms. Landsat, MODIS (Moderate Resolution Imaging Spectroradiometer) and MERIS (MEdium Resolution Imaging Spectrometer) are the most widely used products for monitoring the spatial and temporal dynamics of cyanobacteria in inland waters due to the appropriate temporal, spatial and spectral resolutions. Future work should primarily focus on the development of universal algorithms, remote retrievals of cyanobacterial blooms in oligotrophic waters, and the algorithm applicability to mapping phycocyanin at a large spatial-temporal scale. The applications of satellite images will greatly improve our understanding of the driving mechanism of cyanobacterial blooms by combining numerical and ecosystem dynamics models.

Estimation of Kd(PAR) in inland waters across China in relation to the light absorption of optically active components

The comprehensive analysis of the relationships between the attenuation of photosynthetic active radiation (K_d(PAR)) and light absorption is an imperative requirement to retrieve K_d(PAR) from remote sensing data for aquatic environments. The spatial distributions of the K_d(PAR) and light absorption of optically active components (a_OACs) were routinely estimated in China lakes and reservoirs. Spatial K_d(PAR) was relatively dependent on the inorganic particles (average relative contribution of 57.95%). The a_OACs could explain 70-87% of K_d(PAR) variations. A linear model is used to predict K_d(PAR), as a function of light absorption coefficient of phytoplankton (a_phy), colored dissolved organic matter (a_CDOM), and inorganic particles (a_NAP): K_d(PAR) = 0.41 + 0.57 × a_CDOM + 0.96 × a_NAP + 0.57 × a_phy (R² = 0.87, n = 741, p < 0.001). In the lakes with low TSM concentration and non-eutrophic lakes with high TSM, a_CDOM was the most powerful predicting factor on K_d(PAR). In eutrophic lakes with high TSM, a_NAP had the most significant impact on K_d(PAR). This study allowed K_d(PAR) to be predicted from a_OACs values in the inland waters.

Non-native freshwater fauna in Portugal: A review

We present the most updated list of non-native freshwater fauna established in Portugal, including the Azores and Madeira archipelagos. This list includes 67 species at national level but corresponds to 84 species records, of which 53 are in the mainland, 23 in the Azores and 8 in Madeira archipelagos. We also discuss the progression of the cumulative number of introductions since 1800 and identify the most probable vectors of introduction, main taxonomic groups and their regions of origin. Furthermore, we review the existing knowledge about ecological and economic impacts, invasion risk and potential distribution of invaders, under present and future climatic conditions, and the applied management actions, including the production of legislation. Along the 20th century the number of successful introductions increased at an approximate rate of two new species per decade until the beginning of 1970s. Since then, this rate increased to about 14 new species per decade. These introductions were mainly a result of fisheries, as contaminants or for ornamental purposes. Fish and mollusks are the taxonomic groups with more established species, representing more than half of the total. Most species (>70%) are native from other regions of Europe and North America. Studies about ecological or socioeconomic impacts are more common for fish, crustaceans and mollusks. Impacts for most amphibians, reptiles and mammals are not thoroughly studied. A few studies on the impacts and management actions of health-threatening mosquitoes are also available. The potential distribution in the Portuguese territory was modelled for 26 species. Only a minority of these models provides projections of distributions under scenarios of future climate change. A comparison of the Portuguese and EU legislation shows large discrepancies in the invasive species lists. Using the EU list and a ranking procedure for the national context, we identify freshwater species of high national concern for which actions are urgently needed.

Temperature sensitivity of biodegradable dissolved organic carbon increases with elevating humification degree in subtropical rivers

Biodegradable dissolved organic carbon (BDOC) plays a key role in C cycle in inland waters. However, the magnitude of temperature sensitivity (Q₁₀ value) of BDOC is still unclear, and the effect of DOC quality on Q₁₀ value of BDOC is not well verified in these aquatic systems. Here, we used a laboratory incubation experiment to determine the Q₁₀ value of BDOC in 57 rivers in the Three Gorges Reservoir area, China, and then tested whether C quality-temperature hypothesis could be applied to BDOC in inland waters. We observed approximately twofold variations in Q₁₀ values of BDOC (1.42-2.67) in these rivers. Moreover, the tight positive relationship between the Q₁₀ values of BDOC and DOC humification index indicated the applicability of C quality-temperature hypothesis in subtropical rivers. In addition, the Q₁₀ values of BDOC exhibited a negative relationship with pH. These findings suggest that DOC quality and pH are powerful predictors of temperature sensitivity of BDOC in subtropical rivers. In conclusion, our results would help to improve the C models and predict the feedback between climate warming and C dynamics in inland waters.

Run to the hills: exotic fish invasions and water quality degradation drive native fish to higher altitudes

While the significance of anthropogenic pressures in shaping species distributions and abundances is undeniable, some ambiguity still remains on their relative magnitude and interplay with natural environmental factors. In our study, we examined 91 late-invasion-stage river locations in Northern Italy using ordination methods and variance partitioning (partial-CCA), as well as an assessment of environmental thresholds (TITAN), to attempt to disentangle the effects of eutrophication and exotic species on native species. We found that exotic species, jointly with water quality (primarily eutrophication) and geomorphology, are the main drivers of the distribution of native species and that native species suffer more joint effects than exotic species. We also found that water temperature clearly separates species distributions and that some native species, like Italian bleak (Alburnus alborella) and Italian rudd (Scardinius hesperidicus), seem to be the most resilient to exotic fish species. We also analyzed the dataset for nestedness (BINMATNEST) to identify priority targets of conservation. As a result, we confirmed that altitude correlated negatively with eutrophication and nestedness of exotic species and positively with native species. Overall, our analysis was able to detect the effects of species invasions even at a late invasion stage, although reciprocal effects seemed comparable at this stage. Exotic species have pushed most native species on the edge of local extinction in several sites and displaced most of them on the rim of their natural distribution. Any potential site- and species-specific conservation action aimed at improving this situation could benefit from a carefully considered prioritization to yield the highest results-per-effort and success rate. However, we encourage future research to update the information available before singling out specific sites for conservation or outlining conservation actions.

Revisiting inland hypoxia: diverse exceedances of dissolved oxygen thresholds for freshwater aquatic life

Water resources in many regions are stressed by impairments resulting from climate change, population growth and urbanization. In the United States (US), water quality criteria (WQC) and standards (WQS) were established to protect surface waters and associated designated uses, including aquatic life. In inland waters of the south central US, for example, depressed dissolved oxygen (DO) consistently results in impaired aquatic systems due to noncompliance with DO WQC and WQS. In the present study, we systematically examined currently available DO threshold data for freshwater fish and invertebrates and performed probabilistic aquatic hazard assessments with low DO toxicity data that were used to derive the US Environmental Protection Agency's (EPA) Ambient Water Quality Criteria (AWQC) for DO and newly published information. Aquatic hazard assessments predicted acute invertebrate DO thresholds for Ephemeroptera, Plecoptera, or Trichoptera (EPT) taxa and species inhabiting lotic systems to be more sensitive than fish. For example, these organisms were predicted to have acute low DO toxicity thresholds exceeding the US EPA guidelines 17, 26, 31 and 38% and 13, 24, 30 and 39% of the time at 8.0, 5.0, 4.0 and 3.0 mg DO/L, respectively. Based on our analysis, it appears possible that low DO effects to freshwater organisms have been underestimated. We also identified influences of temperature on low DO thresholds and pronounced differences in implementation and assessment of the US EPA AWQC among habitats, seasons, and geographic regions. These results suggest some implemented DO guidelines may adversely affect the survival, growth, and reproduction of freshwater aquatic organisms in a region susceptible to climate change and rapid population growth. Given the global decline of species, particularly invertebrates, low DO threshold information, including sublethal (e.g., reproduction, behavior) responses, for additional species (e.g., mollusks, other invertebrates, warm water fish) across seasons, habitats, and life history stages using consistent experimental designs is needed to support more sustainable environmental assessment efforts and management of biodiversity protection goals in inland waters.

Monitoring of inland waters for culturing shrimp Litopenaeus vannamei: application of a method based on survival and chemical composition

This study evaluated the suitability of 21 inland waters (16 well waters and 5 surface waters) from Northwest Mexico via short- (48 h) and medium-term (28 days) tests using postlarvae (PL18) of Litopenaeus vannamei. In the short test, survival was assessed at 48 h after shrimp were placed in groups of 10 postlarvae into 2-L containers of inland water, to which they had been previously acclimated. The second, medium-term test consisted of four replicates with 10 postlarvae, and each group was placed in 15-L containers with the treatment water. Weights (initial and final) and survival were evaluated weekly for 28 days. In those waters for which the short test was positive and the medium-term test was negative and which also had a deficiency of potassium and/or magnesium, a third test was conducted. These last waters were supplemented with salts, and the shrimp survival and weights (initial and final) were recorded for 28 days. The water samples from San Jose, Mochicahui, Sinaloa River, Caimanero inner Lagoon, La Pipima, Campo Santa Fe, Escopama, and Fitmar had >60% survival in the short test. The Caimanero inner Lagoon water had the highest survival (87.5 ± 9.6%) and final mean weight (201.3 ± 86.2 mg). In the third test, it was found that shrimp in the water from La Pipima, Campo Santa Fe, and Fitmar exhibited 100% survival for 2 weeks. Finally, in this work, a decision tree to evaluate the suitability of low-salinity water for shrimp farming was proposed, which can be applied in other regions.

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization's (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.

Ancient dissolved methane in inland waters revealed by a new collection method at low field concentrations for radiocarbon (14C) analysis

Methane (CH₄) is a powerful greenhouse gas that plays a prominent role in the terrestrial carbon (C) cycle, and is released to the atmosphere from freshwater systems in numerous biomes globally. Radiocarbon (¹⁴C) analysis can indicate both the age and source of CH₄ in natural environments. In contrast to CH₄ present in bubbles released from aquatic sediments (ebullition), dissolved CH₄ in lakes and streams can be present in low concentrations compared to carbon dioxide (CO₂), and therefore obtaining sufficient aquatic CH₄ for radiocarbon (¹⁴C) analysis remains a major technical challenge. Previous studies have shown that freshwater CH₄, in both dissolved and ebullitive form, can be significantly older than other forms of aquatic C, and it is therefore important to characterise this part of the terrestrial C balance. This study presents a novel method to capture sufficient amounts of dissolved CH₄ for ¹⁴C analysis in freshwater environments by circulating water across a hydrophobic, gas-permeable membrane and collecting the CH₄ in a large headspace volume. The results of laboratory and field tests show that reliable dissolved δ¹³CH₄ and ¹⁴CH₄ samples can be readily collected over short time periods (∼4-24 h), at relatively low cost and from a variety of surface water types. The initial results further support previous findings that dissolved CH₄ may be significantly older than other forms of aquatic C, and is currently unaccounted for in many terrestrial C balances and models. This method is suitable for use in remote locations, and could potentially be used to detect the leakage of unique ¹⁴CH₄ signatures from point sources into waterways, e.g. coal seam gas and landfill gas.

A Watershed Analysis of Seasonal Concentration- and Loading-based Results for Escherichia coli in Inland Waters

Fecal indicator bacteria, such as Escherichia coli, are frequently monitored in recreational waterbodies as indicators of potential fecal pathogen presence and exposure. The present watershed analysis investigated the influence of season on E. coli concentration (MPN/100 mL) and loading (MPN/day) measurements for inland waters at baseflow conditions. The master dataset collected during 2007-2012 for three watersheds included 896 E. coli (Colilert) samples with simultaneous flow taken for a subset (39 %) of samples. The outcomes for grouped watersheds were reflected in most cases for individual watersheds. Concentration- and loading-based results were highest in summer and spring, and lowest in the winter and fall, respectively. The comparison of these two measurement techniques (concentration and loading) highlight the impact of flow data during baseflow conditions for inland waters and reveal that caution should be used when inferring one method's results from another.

Developments in Earth observation for the assessment and monitoring of inland, transitional, coastal and shelf-sea waters

The Earth's surface waters are a fundamental resource and encompass a broad range of ecosystems that are core to global biogeochemical cycling and food and energy production. Despite this, the Earth's surface waters are impacted by multiple natural and anthropogenic pressures and drivers of environmental change. The complex interaction between physical, chemical and biological processes in surface waters poses significant challenges for in situ monitoring and assessment and often limits our ability to adequately capture the dynamics of aquatic systems and our understanding of their status, functioning and response to pressures. Here we explore the opportunities that Earth observation (EO) has to offer to basin-scale monitoring of water quality over the surface water continuum comprising inland, transition and coastal water bodies, with a particular focus on the Danube and Black Sea region. This review summarises the technological advances in EO and the opportunities that the next generation satellites offer for water quality monitoring. We provide an overview of algorithms for the retrieval of water quality parameters and demonstrate how such models have been used for the assessment and monitoring of inland, transitional, coastal and shelf-sea systems. Further, we argue that very few studies have investigated the connectivity between these systems especially in large river-sea systems such as the Danube-Black Sea. Subsequently, we describe current capability in operational processing of archive and near real-time satellite data. We conclude that while the operational use of satellites for the assessment and monitoring of surface waters is still developing for inland and coastal waters and more work is required on the development and validation of remote sensing algorithms for these optically complex waters, the potential that these data streams offer for developing an improved, potentially paradigm-shifting understanding of physical and biogeochemical processes across large scale river-sea systems including the Danube-Black Sea is considerable.

Biogeochemistry of "pristine" freshwater stream and lake systems in the western Canadian Arctic

Climate change poses a substantial threat to the stability of the Arctic terrestrial carbon (C) pool as warmer air temperatures thaw permafrost and deepen the seasonally-thawed active layer of soils and sediments. Enhanced water flow through this layer may accelerate the transport of C and major cations and anions to streams and lakes. These act as important conduits and reactors for dissolved C within the terrestrial C cycle. It is important for studies to consider these processes in small headwater catchments, which have been identified as hotspots of rapid mineralisation of C sourced from ancient permafrost thaw. In order to better understand the role of inland waters in terrestrial C cycling we characterised the biogeochemistry of the freshwater systems in a c. 14 km² study area in the western Canadian Arctic. Sampling took place during the snow-free seasons of 2013 and 2014 for major inorganic solutes, dissolved organic and inorganic C (DOC and DIC, respectively), carbon dioxide (CO₂) and methane (CH₄) concentrations from three water type groups: lakes, polygonal pools and streams. These groups displayed differing biogeochemical signatures, indicative of contrasting biogeochemical controls. However, none of the groups showed strong signals of enhanced permafrost thaw during the study seasons. The mean annual air temperature in the region has increased by more than 2.5 °C since 1970, and continued warming will likely affect the aquatic biogeochemistry. This study provides important baseline data for comparison with future studies in a warming Arctic.