Exploratory study of the Sentinel-3 level 2 product for monitoring chlorophyll-a and assessing ecological status in Danish seas.

In situ Chl-a data were used to perform empirical calibration and validation of Sentinel-3 level 2 product in Danish marine waters. Comparing in situ data with both same-day and ±5 days moving averaged Sentiel-3 Chl-a values yielded two similar positive correlations (p > 0.05) with rpearson values of 0.56 and 0.53, respectively. However, as the moving averaged values resulted in significantly more available data than daily matchups (N = 392 vs. N = 1292) at a similar quality of correlation with similar model parameters (slope (1.53 and 1.7) and intercept (-0.28 and -0.33) respectively), which were not significantly different (p > 0.05), the further analyses were focused on ±5 days moving averaged values. A thorough comparison of seasonal and growing season averages (GSA) also showed a very good agreement, except for a few stations characterized by very shallow depth. Overestimation by the Sentinel-3 occurred in shallow coastal areas and was attributed to the interferences from benthic vegetation and high levels of Colored Dissolved Organic matter (CDOM) interfering with the Chl-a signals. Underestimation observed in the inner estuaries with shallow Chl-a rich waters, however, seen as a result of self-shading at high Chl-a concentrations, reducing effective absorption by phytoplankton. Besides the observed minor disagreements, there was no significant difference when the GSA values from in situ and Sentinel-3 were compared for all three water types (p > 0.05, N = 110). Analyzing Chl-a estimates along a depth gradient showed significant (p < 0.001) non-linear trends of declining concentrations from shallow to deeper waters for both in situ (explaining 15.2 % of the variance (N = 109)) and Sentinel-3 data (explaining 36.3 % of the variance (N = 110)), with higher variability in shallow waters. Furthermore, Sentinel-3 enabled full spatial coverage of all 102 monitored water bodies providing GSA data at much higher spatial and temporal resolutions for good ecological status (GES) assessment compared to only 61 through in situ sampling. This underlines the potential of Sentinel-3 for substantially extending the geographical coverage of monitoring and assessment. However, the systematic over- and underestimation of Chl-a in shallow nutrient rich inner estuaries through Sentinel-3 requires further attention to enable routine application of the Sentinel-3 level 2 standard product in the operational Chl-a monitoring in Danish coastal waters. We provide methodological recommendations on how to improve the Sentinel-3 products' representation of in situ Chl-a conditions. Continued frequent in situ sampling remains important for monitoring as these measurements provide essential data for empirical calibration and validation of satellite based estimates to reduce possible systematic bias.

Simulating chlorophyll-a fluorescence changing rate and phycocyanin fluorescence by using a multi-sensor system in Lake Taihu, China.

Algal pollution in water sources has posed a serious problem. Estimating algal concentration in advance saves time for drinking water plants to take measures and helps us to understand causal chains of algal dynamics. This paper explores the possibility of building a short-term algal early warning model with online monitoring systems. In this study, we collected high-frequency data for water quality and weather conditions in shallow and eutrophic Lake Taihu by an in situ multi-sensor system (BIOLIFT) combined with a weather station. Extracted chlorophyll-a from water samples and chlorophyll-a fluorescence differentiated according to different algal classeses verified that chlorophyll-a fluorescence continuously measured by BIOLIFT only represent chlorophyll-a of green algae and diatoms. Stepwise linear regression was used to simulate the chlorophyll-a fluorescence changing rate of green algae and diatoms together (ΔChla-f%) and phycocyanin fluorescence concentration (blue-green algae) on the water surface layer (CyanoS). The results show that nutrients (total N, NO3-N, NH4-N, total P) were not necessary parameters for short-term algal models. ΔChla-f % is greatly influenced by the seasons, so seasonal partition of data before modeling is highly recommended. CyanoSmax and ΔChla-f% were simulated by only using multi-sensor and meteorological data (R2 = 0.73; 0.75). All the independent variables (wave, water temperature, relative humidity, depth, cloud cover) used in the model were measured online and predictable. Wave height is the most important independent variable in the shallow lake. This paper offers a new approach to simulate and predict the algal dynamics, which also can be applied in other surface water.

A spatial model for nutrient mitigation potential of blue mussel farms in the western Baltic Sea.

Worldwide, coastal and marine policies are increasingly aiming for environmental protection, and eutrophication is a global challenge, particularly impairing near-coastal marine water bodies. In this context, mussel mitigation aquaculture is currently considered an effective tool to extract nutrients from such water bodies. Mussel mitigation farming using longline systems with loops of collector material is a well-developed technology and considered promising in the western Baltic Sea. Besides several spatially limited field studies, a suitable spatial model for site-specific implementation is still lacking. In this study, we present a modular spatial model, consisting of a spatial and temporal habitat factor model (Module 1), blue mussel growth model (Module 2), mussel farm model (Module 3), and an avoidance of food limitation model (Module 4). The modules integrate data from in situ monitoring, mussel growth experiments, and eco-physiological modelling for the western Baltic Sea, to estimate spatially explicit nutrient reduction potentials. The model is flexible with respect to farm setups and harvest times and considers natural variability, model uncertainty, and required hydrodynamics. Modelling results proved valid at all scales and modules, and point out key areas for efficient mussel mitigation farms in Danish, German and Swedish areas. Modelled long-term mean mitigation potentials for harvest in November reach up to 0.88 tN/ha and 0.05 tP/ha for a farm setup using 2 m depth-range of the water column and 3.0 tN/ha and 0.17 tP/ha using up to 8 m, respectively. For Danish water bodies, we demonstrate that in efficient areas, mitigation farms (18.8 ha, 90 km collector substrate in loops with 2 m depth-range) required <3.6% of the space to extract the target nitrogen loads for good ecological status. The developed approach could prove valuable for implementing environmental policies in aquatic systems, e.g. in situ nutrient mitigation, aquaculture spatial planning, and habitat suitability mapping.

Identifying spatio-temporal dynamics of trace metals in shallow eutrophic lakes on the basis of a case study in Lake Taihu, China.

In shallow eutrophic lakes, metal remobilization is closely related to the resuspension and eutrophication. An improved understanding of metal dynamics by biogeochemical processes is essential for effective management strategies. We measured concentrations of nine metals (Cr, Cu, Zn, Ni, Pb, Fe, Al, Mg, and Mn) in water and sediments during seven periods from 2014 to 2018 in northern Lake Taihu, to investigate the metal pollution status, spatial distributions, mineral constituents, and their interactions with P. Moreover, an automatic weather station and online multi-sensor systems were used to measure meteorological and physicochemical parameters. Combining these measurements, we analyzed the controlling factors of metal dynamics. Shallow and eutrophic northern Lake Taihu presents more serious metal pollution in sediments than the average of lakes in Jiangsu Province. We found chronic and acute toxicity levels of dissolved Pb and Zn (respectively), compared with US-EPA "National Recommended Water Quality Criteria". Suspended particles and sediment have been polluted in different degrees from uncontaminated to extremely contaminated according to German pollution grade by LAWA (Bund/Länder-Arbeitsgemeinschaft Wasser). Polluted particles might pose a risk due to high resuspension rate and intense algal activity in shallow eutrophic lakes. Suspended particles have similar mineral constituents to sediments and increased with increasing wind velocity. Al, Fe, Mg, and Mn in the sediment were rarely affected by anthropogenic pollution according to the geoaccumulation index. Among them, Mn dynamics is very likely associated with algae. Micronutrient uptake by algal will affect the migration of metals and intensifies their remobilization. Intensive pollution of most particulate metals were in the industrialized and down-wind area, where algae form mats and decompose. Moreover, algal decomposition induced low-oxygen might stimulate the release of metals from sediment. Improving the eutrophication status, dredging sediment, and salvaging cyanobacteria biomass are possible ways to remove or reduce metal contaminations.

Highly time-resolved analysis of seasonal water dynamics and algal kinetics based on in-situ multi-sensor-system monitoring data in Lake Taihu, China.

Predicting algal blooms is challenging due to rapid growth rates under suitable conditions and the complex physical, chemical, and biological processes involved. Physico-chemical parameters, monitored in this study by a high-resolution in-situ multi-sensor system and derived from lab-based water sample analyses, show the seasonal variation and have different degrees of vertical gradients across the water column. Through analyzing the changes and relations between multi-factors, we reveal pictures of water quality dynamics and algal kinetics. Nitrate has regular seasonal changes different to the seasonal patterns of total dissolved Phosphorus. Positive correlations are found between Chlorophyll a fluorescence and temperature, wind-induced resuspension and mixing promote the augment of Cyanobacteria fluorescence (Phycocyanin) signal. While the resuspension can also result in the increase of turbidity and affect the light environment for hydrophytes, the algal scums are the main reason for the high turbidity on the surface, which lower the illumination radiation in the water body. Those parameters are the primary dominants responsible for the change of algae from our monitoring data, which could be used as indicators for the dynamic changes of algae in the future.

Hyperspectral Data and Machine Learning for Estimating CDOM, Chlorophyll a, Diatoms, Green Algae and Turbidity.

Inland waters are of great importance for scientists as well as authorities since they are essential ecosystems and well known for their biodiversity. When monitoring their respective water quality, in situ measurements of water quality parameters are spatially limited, costly and time-consuming. In this paper, we propose a combination of hyperspectral data and machine learning methods to estimate and therefore to monitor different parameters for water quality. In contrast to commonly-applied techniques such as band ratios, this approach is data-driven and does not rely on any domain knowledge. We focus on CDOM, chlorophyll a and turbidity as well as the concentrations of the two algae types, diatoms and green algae. In order to investigate the potential of our proposal, we rely on measured data, which we sampled with three different sensors on the river Elbe in Germany from 24 June⁻12 July 2017. The measurement setup with two probe sensors and a hyperspectral sensor is described in detail. To estimate the five mentioned variables, we present an appropriate regression framework involving ten machine learning models and two preprocessing methods. This allows the regression performance of each model and variable to be evaluated. The best performing model for each variable results in a coefficient of determination R 2 in the range of 89.9% to 94.6%. That clearly reveals the potential of the machine learning approaches with hyperspectral data. In further investigations, we focus on the generalization of the regression framework to prepare its application to different types of inland waters.

Simulation-based assessment of the impact of fertiliser and herbicide application on freshwater ecosystems at the Three Gorges Reservoir in China.

Dams have profound impacts on river ecosystems, amongst them inundation of land, altered dynamics of the water body or uprising reservoir backwaters influencing tributary or upstream river sections. Along the outstandingly ecologically important Yangtze River in China, the Three Gorges Reservoir (TGR) is the largest project, covering an area of 1080 km2. From the beginning, the dam-project came in for criticism on increasing environmental risks due to sub-merging former industrial and urban areas. We simulated dynamics of biotic and abiotic components of the TGR ecosystem (trophic guilds of aquatic organisms, hydrodynamics, nutrients), as well as the behaviour of the herbicidal substance propanil and its metabolites 3,4-Dichloroaniline (DCA) and 3,3',4,4'-tetrachloroazoxybenzene (TCAB). A modelling environment, provided by the AQUATOX software, was adapted to the specific situation at a tributary reach to the Yangtze river 'Daning River'. As the simulated food web contained several interconnected trophic levels, a significant biomagnification of metabolites was demonstrated by our simulation studies. In particular, newly emerging stagnant downstream sections of tributaries exhibited high probabilities due to accumulating pesticides from upstream sources. The common problem of algal blooms in the TGR-region was addressed by dose-response simulation experiments with essential nutrients. Impacts on structure and abundance of populations of aquatic organisms were shown. However, even high nutrient loads resulted in only slight changes of densities of organisms of all trophic levels. Nevertheless, the probabilities for large-scale algal blooms affecting drinking water quality were considered low because of high flow velocities and discharge rates towards the Yangtze River. We see high potential of simulation-based assessments that provide information for risk managers dealing with whole catchment areas. They are put in the position to differentiate the magnitude of impacts of various factors and decide about the most effective remediation measures.

Since 2015 the SinoGerman research project SIGN supports water quality improvement in the Taihu region, China.

The Taihu (Tai lake) region is one of the most economically prospering areas of China. Due to its location within this district of high anthropogenic activities, Taihu represents a drastic example of water pollution with nutrients (nitrogen, phosphate), organic contaminants and heavy metals. High nutrient levels combined with very shallow water create large eutrophication problems, threatening the drinking water supply of the surrounding cities. Within the international research project SIGN (SinoGerman Water Supply Network, www.water-sign.de), funded by the German Federal Ministry of Education and Research (BMBF), a powerful consortium of fifteen German partners is working on the overall aim of assuring good water quality from the source to the tap by taking the whole water cycle into account: The diverse research topics range from future proof strategies for urban catchment, innovative monitoring and early warning approaches for lake and drinking water, control and use of biological degradation processes, efficient water treatment technologies, adapted water distribution up to promoting sector policy by good governance. The implementation in China is warranted, since the leading Chinese research institutes as well as the most important local stakeholders, e.g. water suppliers, are involved.

Total Nitrogen Sources of the Three Gorges Reservoir--A Spatio-Temporal Approach.

Understanding the spatial and temporal variation of nutrient concentrations, loads, and their distribution from upstream tributaries is important for the management of large lakes and reservoirs. The Three Gorges Dam was built on the Yangtze River in China, the world's third longest river, and impounded the famous Three Gorges Reservoir (TGR). In this study, we analyzed total nitrogen (TN) concentrations and inflow data from 2003 till 2010 for the main upstream tributaries of the TGR that contribute about 82% of the TGR's total inflow. We used time series analysis for seasonal decomposition of TN concentrations and used non-parametric statistical tests (Kruskal-Walli H, Mann-Whitney U) as well as base flow segmentation to analyze significant spatial and temporal patterns of TN pollution input into the TGR. Our results show that TN concentrations had significant spatial heterogeneity across the study area (Tuo River> Yangtze River> Wu River> Min River> Jialing River>Jinsha River). Furthermore, we derived apparent seasonal changes in three out of five upstream tributaries of the TGR rivers (Kruskal-Walli H ρ = 0.009, 0.030 and 0.029 for Tuo River, Jinsha River and Min River in sequence). TN pollution from non-point sources in the upstream tributaries accounted for 68.9% of the total TN input into the TGR. Non-point source pollution of TN revealed increasing trends for 4 out of five upstream tributaries of the TGR. Land use/cover and soil type were identified as the dominant driving factors for the spatial distribution of TN. Intensifying agriculture and increasing urbanization in the upstream catchments of the TGR were the main driving factors for non-point source pollution of TN increase from 2003 till 2010. Land use and land cover management as well as chemical fertilizer use restriction were needed to overcome the threats of increasing TN pollution.

Three Gorges Reservoir: density pump amplification of pollutant transport into tributaries.

The impoundment of the Three Gorges Reservoir (TGR) on the Yangtze River in China burdened its tributary backwaters with severe environmental problems.1 Confluence zones of reservoir tributaries with the Yangtze River main channel are main drivers of pollutant dynamics in the TGR2 and are thus keys to develop mitigation measures. Here, we show a novel experimental approach of spatiotemporal water quality analysis to trace water mass movements and identify pollutant transport pathways in reservoir water bodies. Our results show the movements of density currents in a major tributary backwater of the TGR. A huge interflow density current from the Yangtze River main channel transported its heavy metal carriage to the upstream reaches of the tributary backwater. Water from the upstream backwater moved counterwise and carried less but pollutant-enriched suspended sediments. This scenario illustrates the importance of confluence zone hydrodynamics for fates and pathways of pollutants through the widely unknown hydrodynamics of new reservoirs.

An integrated approach to model the biomagnification of organic pollutants in aquatic food webs of the Yangtze Three Gorges Reservoir ecosystem using adapted pollution scenarios.

The impounding of the Three Gorges Reservoir (TGR) at the Yangtze River caused large flooding of urban, industrial, and agricultural areas, and profound land use changes took place. Consequently, substantial amounts of organic and inorganic pollutants were released into the reservoir. Additionally, contaminants and nutrients are entering the reservoir by drift, drainage, and runoff from adjacent agricultural areas as well as from sewage of industry, aquacultures, and households. The main aim of the presented research project is a deeper understanding of the processes that determines the bioaccumulation and biomagnification of organic pollutants, i.e., mainly pesticides, in aquatic food webs under the newly developing conditions of the TGR. The project is part of the Yangtze-Hydro environmental program, financed by the German Ministry of Education and Science. In order to test combinations of environmental factors like nutrients and pollution, we use an integrated modeling approach to study the potential accumulation and biomagnification. We describe the integrative modeling approach and the consecutive adaption of the AQUATOX model, used as modeling framework for ecological risk assessment. As a starting point, pre-calibrated simulations were adapted to Yangtze-specific conditions (regionalization). Two exemplary food webs were developed by a thorough review of the pertinent literature. The first typical for the flowing conditions of the original Yangtze River and the Daning River near the city of Wushan, and the second for the stagnant reservoir characteristics of the aforementioned region that is marked by an intermediate between lake and large river communities of aquatic organisms. In close cooperation with German and Chinese partners of the Yangtze-Hydro Research Association, other site-specific parameters were estimated. The MINIBAT project contributed to the calibration of physicochemical and bathymetric parameters, and the TRANSMIC project delivered hydrodynamic models for water volume and flow velocity conditions. The research questions were firstly focused on the definition of scenarios that could depict representative situations regarding food webs, pollution, and flow conditions in the TGR. The food webs and the abiotic site conditions in the main study area near the city of Wushan that determine the environmental preconditions for the organisms were defined. In our conceptual approach, we used the pesticide propanil as a model substance.

Dechlorination and organohalide-respiring bacteria dynamics in sediment samples of the Yangtze Three Gorges Reservoir.

Several groups of bacteria such as Dehalococcoides spp., Dehalobacter spp., Desulfomonile spp., Desulfuromonas spp., or Desulfitobacterium spp. are able to dehalogenate chlorinated pollutants such as chloroethenes, chlorobenzenes, or polychlorinated biphenyls under anaerobic conditions. In order to assess the dechlorination potential in Yangtze sediment samples, the presence and activity of the reductively dechlorinating bacteria were studied in anaerobic batch tests. Eighteen sediment samples were taken in the Three Gorges Reservoir catchment area of the Yangtze River, including the tributaries Jialing River, Daning River, and Xiangxi River. Polymerase chain reaction analysis indicated the presence of dechlorinating bacteria in most samples, with varying dechlorinating microbial community compositions at different sampling locations. Subsequently, anaerobic reductive dechlorination of tetrachloroethene (PCE) was tested after the addition of electron donors. Most cultures dechlorinated PCE completely to ethene via cis-dichloroethene (cis-DCE) or trans-dichloroethene. Dehalogenating activity corresponded to increasing numbers of Dehalobacter spp., Desulfomonile spp., Desulfitobacterium spp., or Dehalococcoides spp. If no bacteria of the genus Dehalococcoides spp. were present in the sediment, reductive dechlorination stopped at cis-DCE. Our results demonstrate the presence of viable dechlorinating bacteria in Yangtze samples, indicating their relevance for pollutant turnover.

Water mass interaction in the confluence zone of the Daning River and the Yangtze River--a driving force for algal growth in the Three Gorges Reservoir.

Increasing eutrophication and algal bloom events in the Yangtze River Three Gorges Reservoir, China, are widely discussed with regard to changed hydrodynamics and nutrient transport and distribution processes. Insights into water exchange and interaction processes between water masses related to large-scale water level fluctuations in the reservoir are crucial to understand water quality and eutrophication dynamics. Therefore, confluence zones of tributaries with the Yangtze River main stream are dedicated key interfaces. In this study, water quality data were recorded in situ and on-line in varying depths with the MINIBAT towed underwater multi-sensor system in the confluence zone of the Daning River and the Yangtze River close to Wushan City during 1 week in August 2011. Geostatistical evaluation of the water quality data was performed, and results were compared to phosphorus contents of selective water samples. The strongly rising water level throughout the measurement period caused Yangtze River water masses to flow upstream into the tributary and supply their higher nutrient and particulate loads into the tributary water body. Rapid algal growth and sedimentation occurred immediately when hydrodynamic conditions in the confluence zone became more serene again. Consequently, water from the Yangtze River main stream can play a key role in providing nutrients to the algal bloom stricken water bodies of its tributaries.