Lake topography and wind waves determining seasonal-spatial dynamics of total suspended matter in turbid Lake Taihu, China: assessment using long-term high-resolution MERIS data

Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies

A consistent dataset of lake surface water temperature, ice cover, water-leaving reflectance, water level and extent is presented. The collection constitutes the Lakes Essential Climate Variable (ECV) for inland waters. The data span combined satellite observations from 1992 to 2020 inclusive and quantifies over 2000 relatively large lakes, which represent a small fraction of the number of lakes worldwide but a significant fraction of global freshwater surface. Visible and near-infrared optical imagery, thermal imagery and microwave radar data from satellites have been exploited. All observations are provided in a common grid at 1/120° latitude-longitude resolution, jointly in daily files. The data/algorithms have been validated against in situ measurements where possible. Consistency analysis between the variables has guided the development of the joint dataset. It is the most complete collection of consistent satellite observations of the Lakes ECV currently available. Lakes are of significant interest to scientific disciplines such as hydrology, limnology, climatology, biogeochemistry and geodesy. They are a vital resource for freshwater supply, and key sentinels for global environmental change.

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.

Decline of suspended particulate matter concentrations in Lake Taihu from 1984 to 2020: observations from Landsat TM and OLI

Suspended particulate matter (SPM) affects the optical properties of water, which can be used as a marker of water quality. The water quality of Lake Taihu has changed immensely since the 1980's. However, despite the link between water quality and SPM, long-term systematic studies on SPM have not been conducted in this lake. Here, we used Landsat-5 TM and Landsat-8 OLI data to model changes in the SPM concentration of Lake Taihu from 1984 to 2020. Various models were generated, calibrated, and finally validated using in situ SPM, remote sensing reflectance (R_rs) data, and synchronous satellite data. After comparing various commonly used models, it was found that the exponential model based on band combination [R_rs(red) + R_rs(NIR)/R_rs(green)] had the highest accuracy, with an average unbiased relative error greater than 35%. Subsequently, the SPM products of Lake Taihu during 1984-2020 were generated. Overall, the SPM concentration showed a downward trend over the study period, which might be primarily attributable to a decline in wind speed. These findings may assist in the conservation of Lake Taihu and its associated water resources.

Temporal dependence of chlorophyll a-nutrient relationships in Lake Taihu: Drivers and management implications

Eutrophication and its associated algal blooms are principal environmental challenges confronting lakes worldwide. The empirical relationships between nutrient (total nitrogen, TN; total phosphorus, TP) and chlorophyll a (Chla) level are widely used as a theoretical basis for lake eutrophication management. Here, seasonal environmental variables and Chla from 2005 to 2020 in Chinese shallow eutrophic Lake Taihu were examined and Chla-nutrient equations in the entire period and annually from 2005 to 2020 were explored using 95% quantile regression model. The results showed robust linear relationships of logChla-logTN and logChla-logTP in the vast majority of cases. Based on Chla-nutrient equations in the entire study period, 0.69 mg/L TN and 52 μg/L TP are recommended as nutrient threshold in Lake Taihu. Furthermore, the results revealed increasing Chla sensitivity to nutrient for each study month (i.e. February, May, August, and November) from 2005 to 2020, whose drivers included increase in water temperature and water level, decrease in wind speed, mass ratio of nitrogen to phosphorus, and grazing effect. It is noteworthy that atmospheric stilling is likely to be the key climatic factor promoting annual peak Chla in Lake Taihu. For one, the deviations of the sub-index of Trophic State Index indicated that light is a critical limiting factor of summer Chla in Lake Taihu. For another, calmer water mainly due to atmospheric stilling decreased near 40% non-algal turbidity and a substantially increased buoyant cyanobacteria during the study period, improving phytoplankton "light niche". Thus, increasing algal sensitivity to nutrient occurred until the additional algal-turbidity induce further light limitations or the exhaustion of TN (or TP) cause nutrient limitation. Given atmospheric stilling is a global phenomenon, this study would affect future algal bloom mitigation efforts in shallow lakes as temperature is always the focus in the recent literatures on global climate change.

Optimization and Evaluation of Widely-Used Total Suspended Matter Concentration Retrieval Methods for ZY1-02D’s AHSI Imagery

Total suspended matter concentration (CTSM) is an important parameter in aquatic ecosystem studies. Compared with multispectral satellite images, the Advanced Hyperspectral Imager (AHSI) carried by the ZY1-02D satellite can capture finer spectral features, and the potential for CTSM retrieval is enormous. In this study, we selected seven typical Chinese inland water bodies as the study areas, and recalibrated and validated 11 empirical models and two semi-analytical models for CTSM retrieval using the AHSI data. The results showed that the semi-analytical algorithm based on the 697 nm AHSI-band achieved the highest retrieval accuracy (R2 = 0.88, average unbiased relative error = 34.43%). This is because the remote sensing reflectance at 697 nm was strongly influenced by CTSM, and the AHSI image spectra were in good agreement with the in-situ spectra. Although further validation is still needed in highly turbid waters, this study shows that AHSI images from the ZY1-02D satellite are well suited for CTSM retrieval in inland waters.

Occurrence and ecological risk assessment of PPCPs in typical inflow rivers of Taihu lake, China

The occurrence and ecological risks of ten typical pharmaceutical and personal care products (PPCPs) at 12 typical inflow rivers of Taihu lake was investigated in this study. Seven out of the ten typical PPCPs targeted were detected in all the water samples and sediment samples tested. The PPCPs concentration detected were 0-94.91 ng/L for water samples and 0-18.27 ng/g for sediment samples. Sulfamethoxazole (SMZ) and erythromycin (ERY) has relatively higher concentration than other PPCPs in surface water samples, ciprofloxacin (CIP) and ofloxacin (OFX) has relatively higher concentration in the sediment samples. Inflow river-Caoqiao river has a relatively highest contamination of TN and TP, the PPCPs concentration in the river channel, estuary, lake-body also shows high value. This occurs in both the surface water and sediment sample, implied a relatively high pollution input from Caoqiao river. SMZ holds high long-term ecological risks in both surface water and sediment of almost all the tested inflow rivers of Taihu lake. Only ERY has medium short-term risks in surface water, other analyzed PPCPs hold low or insignificant short-terms risks for both surface water and sediments. This study fills the gap of PPCPs ecological risk of surface water and sediment of 12 typical inflow rivers of Taihu Lake, and revealed the importance of control sulfanilamide of the economic belt around Taihu Lake. The results of the present study are useful in providing information for PPCPs control and sustainable water management in freshwater lakes.

Response of community composition and biomass of submerged macrophytes to variation in underwater light, wind and trophic status in a large eutrophic shallow lake

Light climate is of key importance for the growth, community composition of submerged macrophytes in lakes and, they, in turn, are affected by lake depth and the degree of eutrophication. To test the relationships between submerged macrophyte presence and the ratio of Secchi disk depth (SDD) to water depth, i.e. SDD/depth, nutrients and wind, we conducted an extensive sampling campaign in a macrophyte-dominated area of the eastern region (n = 36) in 2016 in Lake Taihu, China, and combined the data gathered with results from extensive physico-chemical monitoring data from the entire lake. We confirmed that SDD/Depth is the primary factor controlling the community composition of macrophytes and showed that plant abundance increased with increasing SDD/Depth ratio (p < 0.01), but that only SDD/Depth > 0.4 ensured growth of submerged macrophytes. Total phosphorus and total nitrogen also influenced the growth and community composition of macrophytes (p < 0.01), while Chla was an indirectly affecting factor by reducing underwater light penetration. Wave height significantly influenced plant abundance (p < 0.01), whereas it had little effect on the biomass (p > 0.05). The key to restore the macrophyte beds in the lake is to reduce the nutrient loading. A decrease of the water level may contribute as well in the shallow bays but will not bring plants back in the main part of the lake. As the tolerance of shade and nutrients varied among the species studied, this should be taken into account in the restoration of lakes by addition of plants.

Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors

Research on the consistency of suspended particulate matter (SPM) concentration retrieved from multisource satellite sensors can serve as long-time monitoring of water quality. To explore the influence of the atmospheric correction (AC) algorithm and the retrieval model on the consistency of the SPM concentration values, Landsat 8 Operational Land Imager (OLI) and Sentinel 2 MultiSpectral Imager (MSI) images acquired on the same day are used to compare the remote sensing reflectance (Rrs) SPM retrieval values in two high-turbidity lakes. An SPM retrieval model for Shengjin Lake is established based on field measurements and applied to OLI and MSI images: two SPM concentration products are highly consistent (R2 = 0.93, Root Mean Squared Error (RMSE) = 20.67 mg/L, Mean Absolute Percentage Error (MAPE) = 6.59%), and the desired results are also obtained in Chaohu Lake. Among the four AC algorithms (Management Unit of the North Seas Mathematical Models (MUMM), Atmospheric Correction for OLI'lite'(ACOLITE), Second Simulation of Satellite Signal in the Solar Spectrum (6S), Landsat 8 Surface Reflectance Code & Sen2cor (LaSRC & Sen2cor)), the two Rrs products, as well as the final SPM concentration products retrieved from OLI and MSI images, have the best consistency when using the MUMM algorithm in SeaWIFS Data Analyst System (SeaDAS) software. The consistency of SPM concentration values retrieved from OLI and MSI images using the same model or same form of models is significantly better than that retrieved by applying the optimal models with different forms.

Emerging role of dissolved organic nitrogen in supporting algal bloom persistence in Lake Taihu, China: Emphasis on internal transformations

Dissolved organic nitrogen (DON) accounts for a significant fraction of the dissolved nitrogen (N) pool in eutrophic lakes, and substantial components of DON are available for phytoplankton. However, long-term changes in DON concentrations in eutrophic lakes have been poorly documented, and the particulate-related internal cycling of DON at the molecular level remains unclear. In this study, changes in the concentration of DON during the past 14 years of Lake Taihu, China were analyzed. Algae and sediment suspensions were incubated under summer sunlight to examine transformations of DON (e.g., photodissolution) at the bulk concentration and molecular level. Concentrations of DON in Lake Taihu ranged from 0 to 4.59 mg L^-1, with a mean of 0.82 ± 0.60 mg L^-1 (n = 3360). Although annual averages of the concentration of DON (n = 240) showed no significant linear variation from 2005 to 2018, the percentage of DON in total dissolved nitrogen (TDN) increased linearly (p < .05) and was maintained at >50% after 2015. Seasonally, DON concentrations were highest in spring (1.10 ± 0.56 mg L^-1), followed by winter (0.87 ± 0.58 mg L^-1) and summer (0.54 ± 0.37 mg L^-1) concentrations, and lowest in autumn (0.44 ± 0.38 mg L^-1). Outdoor incubation experiments suggest that both algae and sediment suspensions contribute to significant increases of DON concentrations but contribute to decreases of inorganic N concentrations at the end of incubations. Moreover, the production of DON by algae suspensions differed from that of sediment suspensions, with more labile components released from algae (e.g., proteins and amino acids), while more refractory components were released from sediment suspensions (e.g., lignin with low H/C and O/C). Taken together, these results emphasize the increasing percentage of DON in TDN during 2009-2018 and the different patterns of algae- and sediment-dominated internal DON transformations in Lake Taihu.

Landsat 8-observed water quality and its coupled environmental factors for urban scenery lakes: A case study of West Lake

Urban scenery lakes are not only popular sites for recreation, water sport, and visit of citizens and tourists, but also function for urban water drainage and storage, and hence, their water quality is a sensitive indicator of urban aquatic environment. This study focused on two important water quality parameters, TSM (total suspended matter) and CDOM (colored dissolved organic matter) in West Lake, a world famous urban scenery lake in Hangzhou, China. Based on Landsat 8 images, remote sensing inversion models for TSM and CDOM in West Lake were compared and the best ones were determined using exponential functions and green/red band ratios. Results show that the accuracy of TSM models is relatively better while CDOM models performed relatively poor, indicating that empirical estimation of CDOM for inland complex waters remains a challenge. The Landsat 8-derived results in West Lake from 2013 to 2017 show that TSM presented diverse distributions in different sections and months/seasons-the relatively high-concentration TSM was usually found in the north section and during spring festivals, holidays and summer vacations. These spatiotemporal patterns demonstrate the evidence that TSM in West Lake was highly linked to anthropogenic impacts, such as tourist visits, commercial activities, and urban drainage projects in Hangzhou. The relations between TSM and precipitation were also examined, but no significant correlations were found, showing that the impacts of rainfall on water quality of urban lakes are complicated, and using remote sensing for such studies is still with limitations. PRACTITIONER POINTS: Water quality (TSM and CDOM) of urban scenery lakes is highly influenced by urban tourist activities. Precipitation and TSM have not found significant relations in urban scenery lakes. An exponential model based on Landsat 8's bands 3 and 4 is good for TSM estimation. CDOM estimation remains a challenge for water color remote sensing in urban scenery lakes.

Spatiotemporal Variations in Seston C:N:P Stoichiometry in a Large Eutrophic Floodplain Lake (Lake Taihu): Do the Sources of Seston Explain Stoichiometric Flexibility?

Although sources of seston are much more complicated in lakes compared to oceans, the influences of different sources on the spatiotemporal variations in seston stoichiometry are still underexplored, especially in large eutrophic floodplain lakes. Here, we investigated seston stoichiometric ratios across a typical large eutrophic floodplain lake (Lake Taihu, East China) over one year. In addition, we used the n-alkane proxies to examine the influence of the seston source on seston stoichiometry variation. Throughout the study, the average value of the C:N:P ratio of 143:19:1 across Lake Taihu was close to the canonical lake’s ratios (166:20:1). Similar to other eutrophic lakes, seston C:N ratios varied the least across all environments, but C:P and N:P ratios varied widely and showed a strong decreasing trend in ratios of N:P and C:P from growing season to senescence season. This seasonal change was mainly associated with the decreasing contribution from algal-derived materials in seston pools because the non-algal dominated seston exhibited significantly lower ratios than algal-dominated seston. Furthermore, the spatial heterogeneity of stoichiometric ratios was also related to the seston source. During the senescence season, the terrestrial-dominated seston from agricultural watershed exhibited the lowest ratios in estuary sites compared with other areas. Statistically, the predictive power of environmental variables on stoichiometric ratios was strongly improved by adding n-alkanes proxies. Apart from source indicators, particulate phosphorus (PP) contents also partly explained the spatiotemporal variations in stoichiometric ratios. This study, thus, highlights the utility of multiple-combined n-alkane proxies in addition to simple C:N ratios to get more robust source information, which is essential for interpreting the spatiotemporal variations in seston stoichiometric ratios among eutrophic floodplain lakes and other freshwater ecosystems.

Remote Sensing of Secchi Depth in Highly Turbid Lake Waters and Its Application with MERIS Data

The Secchi disk depth (ZSD, m) has been used globally for many decades to represent water clarity and an index of water quality and eutrophication. In recent studies, a new theory and model were developed for ZSD, which enabled its semi-analytical remote sensing from the measurement of water color. Although excellent performance was reported for measurements in both oceanic and coastal waters, its reliability for highly turbid inland waters is still unknown. In this study, we extend this model and its evaluation to such environments. In particular, because the accuracy of the inherent optical properties (IOPs) derived from remote sensing reflectance (Rrs, sr−1) plays a key role in determining the reliability of estimated ZSD, we first evaluated a few quasi-analytical algorithms (QAA) specifically tuned for turbid inland waters and determined the one (QAATI) that performed the best in such environments. For the absorption coefficient at 443 nm (a(443), m−1) ranging from ~0.2 to 12.5 m−1, it is found that the QAATI-derived absorption coefficients agree well with field measurements (r2 > 0.85, and mean absolute percentage difference (MAPD) smaller than ~39%). Furthermore, with QAATI-derived IOPs, the MAPD was less than 25% between the estimated and field-measured ZSD (r2 > 0.67, ZSD in a range of 0.1–1.7 m). Furthermore, using matchup data between Rrs from the Medium Resolution Imaging Spectrometer (MERIS) and in-situ ZSD, a similar performance in the estimation of ZSD from remote sensing was obtained (r2 = 0.73, MAPD = 37%, ZSD in a range of 0.1–0.9 m). Based on such performances, we are confident to apply the ZSD remote sensing scheme to MERIS measurements to characterize the spatial and temporal variations of ZSD in Lake Taihu during the period of 2003–2011.

High Temporal Resolution Monitoring of Suspended Matter Changes from GOCI Measurements in Lake Taihu

The Tiaoxi River is the main source of water for Lake Taihu and can result in plumes in the lake after heavy precipitation events. These plumes have played a crucial role in the water quality changes within the lake. High temporal resolution GOCI (Geostationary Ocean Color Imager) data were used to study the spatial distribution of the total suspended matter concentration in Lake Taihu after heavy precipitation events in the Tiaoxi River Basin via an empirical model. The plumes were analyzed after two heavy precipitation events in 2011 and 2013 using 16 GOCI images, which indicated that the Tiaoxi River had a great influence on the spatial distributions of total suspended matter and algal blooms. It was concluded that the main factors affecting the plumes in the Tiaoxi River were precipitation intensity, runoff, and total suspended matter concentration. Human activity, such as sand excavation also played a crucial role in sediment discharge. The results of this study demonstrate that the visualization of GOCI data makes it possible to use remote sensing technology to continuously monitor an inland water environment on an hourly scale, which is of great significance for studying the diffusion and evolution of river plumes.

Long-term change of total suspended matter in a deep-valley reservoir with HJ-1A/B: implications for reservoir management

The valley reservoirs service as a critical resource for society by providing drinking water, power generation, recreation, and maintaining biodiversity. Management and assessment of the water environment in valley reservoirs are urgent due to the recent eutrophication and water quality deterioration. As an essential component of the water body, total suspended matter (TSM) hinder the light availability to underwater and then affect the photosynthesis of aquatic ecosystem. We used long-term HJ-1A/B dataset to track TSM variation and elucidating the driving mechanism of valley reservoirs. Taking a typical deep-valley reservoir (Xin'anjing Reservoir) as our case study, we constructed a TSM model with satisfactory performance (R², NRMSE, and MRE values are 0.85, 18.57%, and 20%) and further derived the spatial-temporal variation from 2009 to 2017. On an intra-annual scale, the TSM concentration exhibited a significant increase from 2.13 ± 1.10 mg L^-1 in 2009 to 3.94 ± 0.82 mg L^-1 in 2017. On a seasonal scale, the TSM concentration in the entire reservoir was higher in the summer (3.36 ± 1.54 mg L^-1) and autumn (2.74 ± 0.82 mg L^-1) than in the spring (1.84 ± 1.27 mg L^-1) and winter (1.44 ± 2.12 mg L^-1). On a monthly scale, the highest and lowest mean TSM value occurred in June (4.66 ± 0.45 mg L^-1) and January (0.67 ± 1.50 mg L^-1), and the monthly mean TSM value increased from January to June, then dropped from June to December. Combing HJ-1A/B-derived TSM, climatological data, basin dynamic, and morphology of the reservoir, we elucidated the driving mechanism of TSM variation. The annual increase of TSM from long-term HJ-1A/B data indicated that the water quality of Xin'anjiang Reservoir was decreasing. The annual increase of phytoplankton jointed with an increase of built-up land and decrease of forest land in the basin may partially be responsible for the increasing trend in TSM. This study suggested that combining the long-term remote sensing data and in situ data could provide insight into the driving mechanism of water quality dynamic and improve current management efforts for local environmental management.

A semi-analytical model for estimating total suspended matter in highly turbid waters

Total suspended matter (TSM) is related to water quality. High TSM concentrations limit underwater light availability, thus affecting the primary productivity of aquatic ecosystems. Accurate estimation of TSM concentrations in various waters with remote sensing technology is particularly challenging, as the concentrations and optical properties vary greatly among different waters. In this research, a semi-analytical model was established for Hangzhou Bay and Lake Taihu for estimating TSM concentration. The model construction proceeded in two steps. 1) Two indices of the model were calculated by deriving absorption and backscattering coefficients of suspended matter (a_p(λ) and b_bp(λ)) from the reflectance signal using a semi-analytical method. 2) The two indices were then weighted to derive TSM. The performance of the proposed model was tested using in situ reflectance and Geostationary Ocean Color Imager (GOCI) data. The derived TSM based on in situ reflectance and GOCI images both corresponded well with the in situ TSM with low mean relative error (32%, 41%), root mean square error (20.1 mg/L, 43.1 mg/L), and normalized root mean square error (33%, 55%). The model was further used for the slightly turbid Xin'anjiang Reservoir to demonstrate its applicability to derive a_p(λ) and b_bp(λ) in other water types. The results indicated that the form R_rs ^-1(λ₁) - R_rs ^-1(λ₂) could minimize the effect of CDOM absorption in deriving a_p(λ) from the total absorption. The model exploited the different relationships between TSM concentration and multiband reflectance, thus improving the performance and application range in deriving TSM.

Characterization, origin and aggregation behavior of colloids in eutrophic shallow lake

Stability of colloidal particles contributes to the turbidity in the water column, which significantly influences water quality and ecological functions in aquatic environments especially shallow lakes. Here we report characterization, origin and aggregation behavior of aquatic colloids, including natural colloidal particles (NCPs) and total inorganic colloidal particles (TICPs), in a highly turbid shallow lake, via field observations, simulation experiments, ultrafiltration, spectral and microscopic, and light scattering techniques. The colloidal particles were characterized with various shapes (spherical, polygonal and elliptical) and aluminum-, silicon-, and ferric-containing mineralogical structures, with a size range of 20-200 nm. The process of sediment re-suspension under environmentally relevant conditions contributed 78-80% of TICPs and 54-55% of NCPs in Lake Taihu, representing an important source of colloids in the water column. Both mono- and divalent electrolytes enhanced colloidal aggregation, while a reverse trend was observed in the presence of natural organic matter (NOM). The influence of NOM on colloidal stability was highly related to molecular weight (MW) properties with the high MW fraction exhibiting higher stability efficiency than the low MW counterparts. However, the MW-dependent aggregation behavior for NCPs was less significant than that for TICPs, implying that previous results on colloidal behavior using model inorganic colloids alone should be reevaluated. Further studies are needed to better understand the mobility/stability and transformation of aquatic colloids and their role in governing the fate and transport of pollutants in natural waters.

Spatiotemporal dynamics of chlorophyll-a in a large reservoir as derived from Landsat 8 OLI data: understanding its driving and restrictive factors

Chlorophyll-a (Chla) is an important indicator of water quality and eutrophication status. Monitoring Chla concentration (C _Chla ) and understanding the interactions between C _Chla and related environmental factors (hydrological and meteorological conditions, nutrients enrichment, etc.) are necessary for assessing and managing water quality and eutrophication. An acceptable Landsat 8 OLI-based empirical algorithm for C _Chla has been developed and validated, with a mean absolute percentage error of 14.05% and a root mean square error of 1.10 μg L^-1. A time series of remotely estimated C _Chla was developed from 2013 to 2015 and examined the relationship of C _Chla to inflow rate, rainfall, temperature, and sunshine duration. Spatially, C _Chla values in the riverine zone were higher than in the transition and lacustrine zones. Temporally, mean C _Chla value were ranked as spring > summer > autumn > winter. A significant positive correlation [Pearson correlation coefficient (r) = 0.88, p < 0.001] was observed between the inflow rate and mean C _Chla in the northwest segment of the Xin'anjiang Reservoir. However, no significant relation was observed between mean C _Chla and meteorological conditions. Mean (± standard deviation) value for the ratio of total nitrogen concentration to total phosphorus concentration in our in situ dataset is 75.75 ± 55.72. This result supports that phosphorus is the restrictive factor to algal growth in Xin'anjiang Reservoir. In addition, the response of nutrients to Chla has spatial variabilities. Current results show the potential of Landsat 8 OLI data for estimating Chla in slight turbid reservoir and indicate that external pollution loading is an important driving force for the Chla spatiotemporal variability.

Tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake based on GOCI imagery

Knowledge of tempo-spatial dynamics of water quality and its response to river flow is important for the management of lake water quality because river discharge associated with rainstorms can be an important source of pollutants to the estuary. Total phosphorus (TP), chlorophyll a (Chl-a), and total suspended matter (TSM) are important indexes of water quality and important factors influencing eutrophication and algal blooms. In this study, remote sensing was used to monitor these indexes to investigate the effects of river discharge on the estuary of Taihu Lake by the largest inflow river which is Chendong River using a total of 136 Geostationary Ocean Color Images (GOCI). In situ datasets collected during the four cruise experiments on Taihu Lake between 2011 and 2015 were used to develop the TP, Chl-a, and TSM inversion models based on simple empirical algorithms: 154 points for TP (mg/L), 114 for Chl-a (μg/L), and 181 for TSM (mg/L). The spatial and temporal changes of the concentration of the three parameters in the Chendong River estuary were analyzed by combining the GOCI data, the flow of the Chendong River, and meteorological data throughout the year in 2014. The several key findings are as follows: (1) In summer and autumn, TP, Chl-a, and TSM contents were significantly higher than in winter and spring. TP and Chl-a have a few similar distribution characteristics. And organic suspended matter in summer was the main reason for the increase of the TSM concentration. (2) The severe surface erosion in the rivers cannot be ignored; the high erodibility is an important factor in the increase of TP and TSM concentrations in the estuary. The concentration of the water quality parameter showed exponential decay with distance from the shore. The concentration decreased slowly after 12 km and then remained essentially constant. (3) TP content in the Chendong River estuary decreased under steady flow inputs and dramatically increased when the flow became large. The increase in Chl-a content was linked to higher levels of TP and good weather conditions after the rain event. Higher flow rates mainly play a dilution role for the Chl-a concentration. Erosion of the surface soil via rainfall is a major source of TSM to the estuary. This paper firstly analyzes tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake, helps to further understand the impact of river input on lake water quality, and is important for lake eutrophication.

Spatial identification of critical nutrient loads of large shallow lakes: Implications for Lake Taihu (China)

Ongoing eutrophication frequently causes toxic phytoplankton blooms. This induces huge worldwide challenges for drinking water quality, food security and public health. Of crucial importance in avoiding and reducing blooms is to determine the maximum nutrient load ecosystems can absorb, while remaining in a good ecological state. These so called critical nutrient loads for lakes depend on the shape of the load-response curve. Due to spatial variation within lakes, load-response curves and therefore critical nutrient loads could vary throughout the lake. In this study we determine spatial patterns in critical nutrient loads for Lake Taihu (China) with a novel modelling approach called Spatial Ecosystem Bifurcation Analysis (SEBA). SEBA evaluates the impact of the lake's total external nutrient load on the local lake dynamics, resulting in a map of critical nutrient loads for different locations throughout the lake. Our analysis shows that the largest part of Lake Taihu follows a nonlinear load-response curve without hysteresis. The corresponding critical nutrient loads vary within the lake and depend on management goals, i.e. the maximum allowable chlorophyll concentration. According to our model, total nutrient loads need to be more than halved to reach chlorophyll-a concentrations of 30-40 μg L^-1 in most sections of the lake. To prevent phytoplankton blooms with 20 μg L^-1 chlorophyll-a throughout Lake Taihu, both phosphorus and nitrogen loads need a nearly 90% reduction. We conclude that our approach is of great value to determine critical nutrient loads of lake ecosystems such as Taihu and likely of spatially heterogeneous ecosystems in general.

Long-term MODIS observations of cyanobacterial dynamics in Lake Taihu: Responses to nutrient enrichment and meteorological factors

We developed and validated an empirical model for estimating chlorophyll a concentrations (Chla) in Lake Taihu to generate a long-term Chla and algal bloom area time series from MODIS-Aqua observations for 2003 to 2013. Then, based on the long-term time series data, we quantified the responses of cyanobacterial dynamics to nutrient enrichment and climatic conditions. Chla showed substantial spatial and temporal variability. In addition, the annual mean cyanobacterial surface bloom area exhibited an increasing trend across the entire lake from 2003 to 2013, with the exception of 2006 and 2007. High air temperature and phosphorus levels in the spring can prompt cyanobacterial growth, and low wind speeds and low atmospheric pressure levels favor cyanobacterial surface bloom formation. The sensitivity of cyanobacterial dynamics to climatic conditions was found to vary by region. Our results indicate that temperature is the most important factor controlling Chla inter-annual variability followed by phosphorus and that air pressure is the most important factor controlling cyanobacterial surface bloom formation followed by wind speeds in Lake Taihu.

Dynamics of chromophoric dissolved organic matter influenced by hydrological conditions in a large, shallow, and eutrophic lake in China

High concentrations of chromophoric dissolved organic matter (CDOM) are terrestrially derived from upstream tributaries to Lake Taihu, China, and are influenced by hydrological conditions of the upstream watershed. To investigate how the dynamics of CDOM in Lake Taihu are influenced by upstream inflow runoff, four sampling cruises, differing in hydrological conditions, were undertaken in the lake and its three major tributaries, rivers Yincun, Dapu, and Changdou. CDOM absorption, fluorescence spectroscopy, chemical oxygen demand (COD), and stable isotope δ(13)C and δ(15)N measurements were conducted to characterize the dynamics of CDOM. The mean absorption coefficient a(350) collected from the three river profiles (5.15 ± 1.92 m(-1)) was significantly higher than that of the lake (2.95 ± 1.88 m(-1)), indicating that the upstream rivers carried a substantial load of CDOM to the lake. This finding was substantiated by the exclusively terrestrial signal exhibited by the level of δ(13)C (-26.23 ± 0.49‰) of CDOM samples collected from the rivers. Mean a(350) and COD in Lake Taihu were significantly higher in the wet season than in the dry season (t test, p < 0.0001), suggesting that the abundance of CDOM in the lake is strongly influenced by hydrological conditions of the watershed. Four components were identified by parallel factor analysis, including two protein-like components (C1 and C2), a terrestrial humic-like component (C3), and a microbial humic-like (C4) component. The contribution percentage of the two humic-like components relative to the summed fluorescence intensity of the four components (C humic) increased significantly from the dry to the wet season. This seasonal difference in contribution further substantiated that an enhanced rainfall followed by an elevated inflow runoff in the lake watershed in the wet season may result in an increase in humic-like substances being discharged into the lake compared to that in the dry season. This finding was further supported by an elevated a(250)/a(365) of CDOM samples collected in the lake in the wet season than in the dry season. Significantly higher mean levels of C3 and a(350) were recorded for CDOM samples collected from River Yincun than those from rivers Dapu and Changdou, differing in seasons, suggesting the significance of terrestrial CDOM input from River Yincun.

Long-Term Satellite Observations of Microcystin Concentrations in Lake Taihu during Cyanobacterial Bloom Periods

Microcystins (MCs) produced by cyanobacteria pose a serious threat to public health. Intelligence on MCs distributions in freshwater is therefore critical for environmental agencies, water authorities, and public health organizations. We developed and validated an empirical model to quantify MCs in Lake Taihu during cyanobacterial bloom periods using the atmospherically Rayleigh-corrected moderate resolution imaging spectroradiometer (MODIS-Aqua) (Rrc) products and in situ data by means of chlorophyll a concentrations (Chla). First, robust relationships were constructed between MCs and Chla (r = 0.91; p < 0.001; t-test) and between Chla and a spectral index derived from Rrc (r = -0.86; p < 0.05; t-test). Then, a regional algorithm to analyze MCs in Lake Taihu was constructed by combining the two relationships. The model was validated and then applied to an 11-year series of MODIS-Aqua data to investigate the spatial and temporal distributions of MCs. MCs in the lake were markedly variable both spatially and temporally. Cyanobacterial bloom scums, temperature, wind, and light conditions probably affected the temporal and spatial distribution of MCs in Lake Taihu. The findings demonstrate that remote sensing reconnaissance in conjunction with in situ monitoring can greatly aid MCs assessment in freshwater.

The influence of macrophytes on sediment resuspension and the effect of associated nutrients in a shallow and large lake (Lake Taihu, China)

A yearlong campaign to examine sediment resuspension was conducted in large, shallow and eutrophic Lake Taihu, China, to investigate the influence of vegetation on sediment resuspension and its nutrient effects. The study was conducted at 6 sites located in both phytoplankton-dominated zone and macrophyte-dominated zone of the lake, lasting for a total of 13 months, with collections made at two-week intervals. Sediment resuspension in Taihu, with a two-week high average rate of 1771 g·m(-2)·d(-1) and a yearly average rate of 377 g·m(-2)·d(-1), is much stronger than in many other lakes worldwide, as Taihu is quite shallow and contains a long fetch. The occurrence of macrophytes, however, provided quite strong abatement of sediment resuspension, which may reduce the sediment resuspension rate up to 29-fold. The contribution of nitrogen and phosphorus to the water column from sediment resuspension was estimated as 0.34 mg·L(-1) and 0.051 mg·L(-1) in the phytoplankton-dominated zone. Sediment resuspension also largely reduced transparency and then stimulated phytoplankton growth. Therefore, sediment resuspension may be one of the most important factors delaying the recovery of eutrophic Lake Taihu, and the influence of sediment resuspension on water quality must also be taken into account by the lake managers when they determine the restoration target.