Total Suspended Matter Concentration Research Articles

Retrieval of Total Suspended Matter Concentration Based on the Iterative Analysis of Multiple Equations: A Case Study of a Lake Taihu Image from the First Sustainable Development Goals Science Satellite’s Multispectral Imager for Inshore

Inland waters consist of multiple concentrations of constituents, and solving the interference problem of chlorophyll-a and colored dissolved organic matter (CDOM) can help to accurately invert total suspended matter concentration (Ctsm). In this study, according to the characteristics of the Multispectral Imager for Inshore (MII) equipped with the first Sustainable Development Goals Science Satellite (SDGSAT-1), an iterative inversion model was established based on the iterative analysis of multiple linear regression to estimate Ctsm. The Hydrolight radiative transfer model was used to simulate the radiative transfer process of Lake Taihu, and it analyzed the effect of three component concentrations on remote sensing reflectance. The characteristic band combinations B6/3 and B6/5 for multiple linear regression were determined using the correlation of the three component concentrations with different bands and band combinations. By combining the two multiple linear regression models, a complete closed iterative inversion model for solving Ctsm was formed, which was successfully verified by using the modeling data (R2 = 0.97, RMSE = 4.89 g/m3, MAPE = 11.48%) and the SDGSAT-1 MII image verification data (R2 = 0.87, RMSE = 3.92 g/m3, MAPE = 8.13%). And it was compared with iterative inversion models constructed based on other combinations of feature bands and other published models. Remote sensing monitoring Ctsm was carried out using SDGSAT-1 MII images of Lake Taihu in 2022–2023. This study can serve as a technical reference for the SDGSAT-1 satellite in terms of remote sensing monitoring of Ctsm, as well as monitoring and improving the water environment.

Lake total suspended matter retrieval by wind speed: A machine learning model trained by time-series satellite imagery

This study aims to develop an affordable and continuous method for monitoring water quality in arid, remote areas with high erosion rates. It presents a hypothesis that establishes a link between the concentration of Total Suspended Matter (TSM) and wind speed, emphasizing its ecological importance in lakes with dry conditions and high erosion rates. Building upon this hypothesis, the study introduces Wind2TSM-Net, a machine learning model that effectively bridges between different regression and neural network algorithms. This model connects on-site wind speed measurements with TSM data obtained through a physically remote sensing approach. It accurately predicts TSM concentration values, overcoming challenges such as cloud interference and reducing reliance on satellite imagery. The model was applied to Iran's Chah-Nimeh Reservoirs (CNRs) as a case study in an arid and remote area. The results revealed a significant correlation between TSM concentration and wind speed measurements, with impressive performance metrics (coefficient of determination (R2) = 0.88, root mean square error (RMSE) = 1.97 g/m3, mean absolute error (MAE) = 1.33). These findings highlight the effectiveness of Wind2TSM-Net in monitoring TSM values in remote and dry regions, particularly during extreme weather conditions when on-site measurements are impractical or cloud cover obstructs satellite observations.

Trends in Concentration and Flux of Total Suspended Matter in the Irrawaddy River

Large rivers without hydrological data from remote sensing observations have recently become a hot research topic. The Irrawaddy River is among the major tropical rivers worldwide; however, published hydrological data on this river have rarely been obtained in recent years. In this paper, based on the existing measured the total suspended matter flux (FTSM) and discharge data for the Irrawaddy River, an inversion model of the total suspended matter concentration (CTSM) is constructed for the Irrawaddy River, and the CTSM and FTSM from 1990 to 2020 are estimated using the L1 products of Landsat-8 OLI/TIRS and Landsat-5 TM. The results show that over the last 30 years, the FTSM of the Irrawaddy River decreased at a rate of 3.9 Mt/yr, which is significant at the 99% confidence interval. An increase in the vegetation density of the Irrawaddy Delta has increased the land conservation capacity of the region and reduced the inflow of land-based total suspended matter (TSM). The FTSM of the Irrawaddy River was estimated by fusing satellite data and data measured at hydrological stations. The research method employed in this paper provides a new supplement to the existing hydrological data for large rivers.

Variation of Satellite-Based Suspended Sediment Concentration in the Ganges–Brahmaputra Estuary from 1990 to 2020

The Ganges–Brahmaputra estuary, located in the northern Bay of Bengal, is situated within the largest delta in the world. This river basin features a complex river system, a dense population, and significant variation in watershed vegetation cover. Human activities have significantly impacted the concentration of total suspended matter (TSM) in the estuary and the ecological environment of the adjacent bay. In this study, we utilised the Landsat series of satellite remote sensing data from 1990 to 2020 for TSM retrieval. We applied an atmospheric correction algorithm based on the general purpose exact Rayleigh scattering look-up-table (LUT) and the shortwave-infrared (SWIR) bands extrapolation to Landsat L1 products to obtain high-precision remote sensing reflectance. In conjunction with the normalised difference vegetation index (NDVI), precipitation, and discharge data, we analysed the variation and influencing mechanisms of TSM in the Ganges–Brahmaputra estuary and its surrounding areas. We revealed notable seasonal variation in TSM in the estuary, with higher concentrations during the wet season (May–October) compared to the dry season (the rest of the year). Over the period from 1990 to 2020, the NDVI in the watershed exhibited a significant upward trend. The outer estuarine regions of the Hooghly River and Meghna River displayed significant decreases in TSM, whereas the Baleswar River, which flows through mangrove areas, showed no significant trend in TSM. The declining trend in TSM was mainly attributed to land-use changes and anthropogenic activities, including the construction of embankments, dams, and mangrove conservation efforts, rather than to runoff and precipitation. Surface sediment concentration and chlorophyll in the northern Bay of Bengal exhibited slight increases, which means the limited influence of terrestrial inputs on long-term change in surface sediment concentration and chlorophyll in the northern Bay of Bengal. This study emphasises the impact of human activities on the river–estuary–coast continuum and sheds light on future sustainable management.

Estimating Total Suspended Matter and Analyzing Influencing Factors in the Pearl River Estuary (China)

This study on total suspended matter (TSM) in the Pearl River Estuary established a regression analysis model using Landsat 8 reflectance and measured TSM data, crucial for environmental management and engineering projects. High coefficients of determination (>0.6) were reported for the selected models. TSM concentration was notably high in 2013, peaking at 180 mg/L during the flood season and 80 mg/L in the dry season. In contrast, 2020 saw lower concentrations. Similar spatial distribution patterns were observed during dry and flood seasons, with high nearshore and low offshore TSM concentrations. Statistical analyses revealed natural factors (precipitation and runoff) as major influencers of the TSM distribution, with human activities presenting localized, limited impacts, except under long-term and large-scale conditions. Over time, the influence of large-scale water-based construction, such as the Hong Kong–Zhuhai–Macao Bridge, on TSM distribution became significant.

Remote Sensing Inversion of the Total Suspended Matter Concentration in the Nanyi Lake Based on Sentinel-3 OLCI Imagery

Remote Sensing Inversion of the Total Suspended Matter Concentration in the Nanyi Lake Based on Sentinel-3 OLCI Imagery

Spatial and seasonal dynamics of biogenic silica in a eutrophic marginal sea, the East China Sea

Biogenic silica (BSi) is a key component of the marine silicon cycle, which is mainly driven by diatom metabolism notably contributing to primary production and export of particulate organic carbon (POC), particularly in ocean margins. Based on a large data set collected in the East China Sea (ECS), including BSi, fucoxanthin (Fuco), POC, and total suspended matter (TSM), we systematically explored the distribution and control of BSi in a typical eutrophic marginal sea. Spatially, BSi concentrations generally decreased from the shelf to the slope during all seasons, because the former is largely fed by river plumes and/or coastal currents enriched in nutrients favoring diatom growth. Abundant BSi was also observed in nearshore bottom waters probably influenced by sediment resuspension indicated by high TSM concentrations. Seasonally, BSi concentrations were on average higher in summer and autumn than in spring and winter, which reflects elevated diatom productivity during warm seasons. The BSi standing stock in the shallow water column of the ECS was significantly correlated with that of Fuco demonstrating diatoms’ dominant control on BSi dynamics. In addition, significant relationships between BSi and POC standing stocks were observed in summer and autumn, indicating the major role of diatoms in C fixation. By comparing with the northern South China Sea (NSCS), we suggested relatively small seasonal variability of BSi on the ECS shelf but significant decrease during cold seasons in the ECS slope. In the latter case, diatoms are ecologically and biogeochemically more important and more sensitive to the changing physical and/or chemical conditions than in the oligotrophic NSCS slope.

Coupling of hydrography and bio-optical constituents in a shallow optically complex region using ten years of in-situ data

Using ten years of in-situ data from a shallow optically complex coastal ecosystem, this study unravels the coupling between bio-optical variability and seasonally changing hydrography. The data presented is novel, as these are long-term simultaneous measurements of bio-optical properties and constituents covering a wide range of hydrographic conditions at different sampling stations in riverine, estuarine, and coastal shelf. The data represent all three seasons experienced in the region, i.e., Indian Summer Monsoon (ISM), post-ISM, and pre-ISM. It allowed us to conduct a baseline study to characterize the bio-optical variability (absorption or scattering dominated) coupled with stratification for remote sensing applications on ecological health. Four groups of sampling stations, representing varying hydrography, were identified as riverine, maximum stratification, maximum chlorophyll-a (Chl-a) concentration, and estuarine/shelf. The maximum concentrations of total suspended matter (TSM) were always collocated with the strongest stratification site, while maximum Chl-a was always located downstream of maximum stratification. Surprisingly, colored dissolved organic matter (CDOM) values were negligible in the ISM season and increased manifold in other seasons. The source of CDOM (either land-derived or in situ generated) inferred from the spectral slope revealed the dominance of land-derived CDOM in the post-ISM season. Combining the entire data into the same groups showed that groups with maximum TSM and samples from estuarine locations were scattering-dominated. In contrast, the group with maximum Chl-a was absorption dominated. The analysis revealed that the optical behavior of the sampling locations being either absorption or scattering dominated depended on the state of stratification and contribution of Chl-a to the absorption budget.

A spatiotemporal monitoring model of TSM and TDS in arid region lakes utilizing Sentinel-2 imagery

The assessment of lake water quality is crucial for protecting and managing natural resources. Total suspended matter (TSM) and total dissolved solids (TDS) are significant parameters in evaluating lake water quality, and their concentration levels provide useful information about the health of the ecosystem. However, measuring TSM and TDS concentrations in remote arid areas can be challenging, necessitating the development of a simple, efficient, and cost-effective monitoring system. In this study, the aim was to retrieve TDS and TSM concentrations in the arid region using an empirical and physics-based method simultaneously. Measured data and remote sensing images for Chah-Nimeh Reservoirs (CNRs), Iran, were used to establish the TSM and TDS concentration model. Twenty-seven Sentinel-2 multispectral instrument (MSI) data acquired from 2018 to 2021 were employed to determine the spatiotemporal distribution of TDS and TSM concentrations. The results indicate that Sentinel-2 MSI data is a productive tool for retrieving TSM concentration using the Case-2 Regional/Coastal Color (C2RCC) processor, with a high level of performance in the dry ecosystem of CNRs (R2 = 0.92). Furthermore, the Bayesian regularization artificial neural network (BRANN) algorithm was used to evaluate TDS concentration, and the results demonstrated that the BRANN algorithm outperforms other models, with a high level of performance (R2 = 0.89). It is noteworthy that evaluating TDS concentration is generally more challenging than TSM. The study provides a valuable model for monitoring TSM and TDS concentrations in remote arid areas using Sentinel-2 MSI data. The proposed approach can facilitate effective spatiotemporal monitoring of TSM and TDS concentrations and aid in the evaluation of lake water quality, specifically in regions where in-situ measurements are not feasible. The findings have significant implications for the management and conservation of natural resources in arid and remote regions.

Impact of extreme climatic events on the total suspended matter concentrations in coastal waters using OceanSat-2 observations

Variations in rainfall and associated erosion levels on the land are the main factor that determines seasonal shifts in coastal ocean color variables. Extreme climate and weather events such as floods and rainfall induced landslides can cause significant impact on water quality property in coastal areas. Studies showing quantitative variability of total suspended matter (TSM) in coastal waters in response to extreme rainfall events are rarely attempted due to the lack of observational and cloud free satellite data products. Here, we investigate the effects of extreme floods that occurred during 14–19 August 2018 in the Western Ghats, and their impacts on TSM concentrations in coastal waters by analyzing OceanSat-2 images. Our results show that the TSM level during the flood stages was more than twice that of normal periods. The excess amount of sediment load from terrigenous sources transported through the rivers has impacted in high TSM concentrations (>23 mg/l) in the coastal waters as compared to normal conditions (<10 mg/l). Furthermore, we noticed that the strong wind mixing and its directionality had a significant impact on resuspension of TSM distributions and their dispersal pathways in Kerala coast.

Nanoparticles containing hazardous elements and the spatial optics of the Sentinel-3B OLCI satellite in Amazonian rivers: a potential tool to understand environmental impacts.

The Amazon River is the longest river in the world. The Tapajós River is a tributary to the Amazon. At their junction, a marked decrease in water quality is evident from negative impacts from the constant activity of clandestine gold mining in the Tapajós River watershed. The accumulation of hazardous elements (HEs), capable of compromising environmental quality across large regions is evident in the waters of the Tapajós. Sentinel-3B OLCI (Ocean Land Color Instrument) Level-2 satellite imagery with Water Full Resolution (WFR) of 300m was utilized to detect the highest potential for the absorption coefficient of detritus and gelbstoff in 443m-1 (ADG443_NN), chlorophyll-a (CHL_NN) and total suspended matter concentration (TSM_NN), at 25 points in the Amazon and Tapajós rivers (in 2019 and 2021). Physical samples of riverbed sediment collected in the field at the same locations were analyzed for NPs and ultra-fine particles to verify the geospatial findings. The riverbed sediment samples collected in the field were studied by Transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM), with selected area electron diffraction (SAED), following laboratory analytical procedures. The Sentinel-3B OLCI images, based on the Neural Network (NN) were calibrated by the European Space Agency (ESA), with a standard average normalization of 0.83µg/mg, containing a maximum error of 6.62% applied to the sampled points. The analysis of the riverbed sediment samples revealed the presence of the following hazardous elements: As, Hg, La, Ce, Th, Pb, Pd, among several others. The Amazon River has significant potential to transport ADG443_NN (55.475m-1) and TSM_NN (70.787 gm-3) in sediments, with the possibility of negatively impacting marine biodiversity, in addition to being harmful to human health over very large regions.

Impacts of COVID-19 lockdowns on water quality along the coast of Morocco

Abstract Due to the COVID-19 pandemic, most of the marine activities and all the anthropogenic activities along the coast have been shut off for several months. The total suspended matter (TSM) was analyzed before and during COVID-19 lockdown in the coast of Morocco. Therefore, the aim of this study was to assess all the changes reflected through the coast in April of 2018, 2019, 2020 and 2021. In the absence of the ground observations during this period, the remote sensing data was used in this study. The results showed a gradual reduction in TSM concentration, indicating a positive improvement during the lockdown period. The TSM concentrations during this period decreased by 40.59% on average compared with the pre-lockdown period. Further, the turbidity in the water has reduced at each stretch of the rivers. Remote sensing is a powerful tool for analyzing turbidity over the whole littoral areas, even in the absence of field observations. The ongoing pandemic shows that an ocean with cleaner water is possible. These findings provide a general reference on the state of the Moroccan coast that could contribute to improve policy and future monitoring program.

Evaluation of Eutrophication in Jiaozhou Bay via Water Color Parameters Determination with UAV-Borne Hyperspectral Imagery

The continued increase in greenhouse gas emissions as a result of unprecedented eutrophication has resulted in a rising trend of red tides in the sea, which may be responsible for ecological degradation in the surrounding environment. Studies rarely investigate the accurate concentration of seawater eutrophication substances in offshore aquaculture areas, which may lead to the exacerbated pollution of inshore aquaculture. We examined whether offshore seawater quality monitoring can be effectively performed through unmanned aerial vehicles’ (UAVs) airborne hyperspectral remote sensing technique at Jiaozhou Bay, a water body associated with eutrophication. We used the UAV airborne hyperspectral imager to detect and measure typical marine aquaculture areas in Jiaozhou Bay and selected the key parameters of seawater quality, chlorophyll-a (Chl-a) concentrations, and total suspended matter (TSM) concentrations as indicators of seawater eutrophication. The hyperspectral inversion model of the Jiaozhou Bay seawater (JZBZ) was established with the optimal sensitive band of parameters. Results showed that in comparison with the traditional inversion model, the inversion R2 of the Chl-a was 0.712, the RPD was 3.72, and the inversion R2 of the TSM concentration was 0.756 while the RPD was 5.83. We found that this model is more suitable for the retrieval of water color parameters in Jiaozhou Bay. Additionally, by actual measurement, it can be seen that the concentration ranges of Chl-a in the observation area are 0.380–1.74 mg/m3, and the concentration range of TSM is 12.6–131 mg/L. The results of this study indicate that the Jiaozhou Bay Water Quality Translation Model (JZBM), based on the UAV airborne hyperspectral imager, performs well in the inversion of the concentration of chlorophyll and suspended particulate matter in offshore water, which advances our understanding with a new method to assess the degree of eutrophication in coastal waters.

Estimation of Chlorophyll-a, TSM and salinity in mangrove dominated tropical estuarine areas of Hooghly River, North East Coast of Bay of Bengal, India using sentinel-3 data

The study aims to assess variations in spatio-temporal characteristics of water quality parameters from three tropical estuaries, namely Muri-Ganga, Saptamukhi, and Hooghly, in the western portion of the Indian Sundarbans. Reliable retrieval of near-surface concentration of water quality parameters such as Chlorophyll-a, SST & TSM from diverse aquatic ecosystems with broad ranges of tropical requirements has always remained a complex issue. In this study, application of Case 2 Regional Colour Correction (C2RCC) processor has been tested for its accuracy across different bio-optical regimes in both inland and coastal waters. Satellite images for the same period were also collected and analysed using the C2RCC processing sequence to retrieve parameters like the depth of water, surface reflectance, water temperature, inherent optical properties (IOPs), chlorophyll-a, salinity, total suspended matter (TSM), etc., using the SNAP software. In situ sampling from specific locations within these estuaries and water quality analysis were conducted for the period 2017–2019. The OLCI retrieved datasets were compared and corroborated with field survey datasets. It was observed that the highest amount of TSM was recorded at Diamond Harbour during the 2018 pre-monsoon season (301.40 mg/L field-based value and 308.54 mg/L estimated value). Similarly, chlorophyll-a had higher concentrations throughout the monsoon season (3.03 mg m−3, (field survey), and 2.96 mg m−3, (estimated) at Fraserganj and Sagar south points. A very good correlation was observed for all seasons for Chl-a (r = 0.829) and TSM (r = 0.924) between the OLCI data and in situ measurements. Higher correlation and significant ‘r’ values highlight the importance of having both field-based as well as remotely-sensed information in understanding any dynamic system in a sustained manner. Results also confirm that the water quality model using OLCI Chl-a and TSM products outperforms conventional techniques. The study demonstrates the efficacy of using Sentinel 3 OCLI data for shallow marine and estuarine remote sensing applications, especially for monitoring TSM and Chl-a concentrations.

SPATIO-TEMPORAL CHARACTERIZATION OF MANILA BAY USING OPTICAL WATER TYPE AND WATER QUALITY MAPPING USING SENTINEL-3 OLCI IMAGES

Abstract. Optical water type (OWT) classification provides a way to delineate surface waters according to spectral properties caused by optically active constituents. This classification is useful in mapping out spatial variability and describing changes in water quality over time as it uses inherent optical properties to discriminate areas of a water body. We used Sentinel-3 OLCI images from July 2017 to December 2020 to classify OWT in Manila Bay and to generate chlorophyll-a and total suspended matter (TSM) concentration layers using C2RCC algorithm. Nine coastal OWT classes for Manila Bay having consistent presence and spatial distribution seasonally were identified. The most dominant class, OWT 6, (3.50 µg/cm3 chlorophyll-a; 4.93 g/m3 TSM) was concentrated around the central area of the bay, covering as much as 79% of it. Chlorophyll-a and TSM concentrations were higher in the nearshore areas and were decreasing offshore. The class with the second highest concentrations, OWT 7, (9.11 µg/cm3 chlorophyll-a; 26.80 g/m3 TSM) were found near river outlets, where high nutrient and sediment loadings coming from the watershed enter the bay. Lowest concentrations (0.26–0.70 µg/cm3 chlorophyll-a; 0.64–1.10 g/m3 TSM) were found in OWT 1, OWT 2, and OWT 3, all located farthest from the shore, such as the mouth of the bay leading to the open sea. Validation using in situ observations showed that C2RCC produced relatively good estimates for chlorophyll-a concentrations of up to 12 µg/cm3 (RMSE=1.71 µg/cm3). No conclusion was drawn for TSM due to insufficient data.

The potential for large-scale kelp aquaculture to counteract marine eutrophication by nutrient removal

Large-scale kelp aquaculture offers several opportunities to counteract eutrophication. Here, six sites from Ailian Bay to its offshore waters in Rongcheng, northern China, were selected to investigate the spatiotemporal variations of kelp (Saccharina japonica) and seawater concentrations of C, N, and P in 2017 and 2019 in order to assess nutrient removal by kelp farming. Variations in biological parameters and elemental nutrient concentrations of whole thalli were also quantified in 2015 and 2016. We found that kelp farming in Ailian Bay can remove 1309 tons of C, 104 tons of N, and 12 tons of P. The increase of total suspended matter and nutrient concentrations from the coast to offshore waters supports the hypothesis of nutrient removal by farmed kelp. This study provides evidence of the bioremediation potential of farmed kelp.

Satellite Remote Sensing of Total Suspended Matter Concentration in Hangzhou Bay and Its Adjacent Waters

Satellite Remote Sensing of Total Suspended Matter Concentration in Hangzhou Bay and Its Adjacent Waters

Regional Satellite Algorithms to Estimate Chlorophyll-a and Total Suspended Matter Concentrations in Vembanad Lake

A growing coastal population is leading to increased anthropogenic pollution that greatly affects coastal and inland water bodies, especially in the tropics. The Sustainable Development Goal-14, ‘Life below water’ emphasises the importance of conservation and sustainable use of the ocean and its resources. Pollution management practices often include monitoring of water quality using in situ observations of chlorophyll-a (chl-a) and total suspended matter (TSM). Satellite technology, including the MultiSpectral Instrument (MSI) sensor onboard Sentinel-2, enables the continuous monitoring of these variables in inland waters at high spatial and temporal resolutions. To improve the monitoring of water quality in the tropical Vembanad-Kol-Wetland (VKW) system, situated on the southwest coast of India, we present two regionally tuned satellite algorithms developed to estimate chl-a and TSM concentrations. The new algorithms estimate the chl-a and TSM concentrations from the simulated reflectance values as a function of the inherent optical properties using a forward modelling approach. The model was parameterised using the National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) and in situ measurements collected in the VKW system. To assess model performance, results were compared with in situ measurements of chl-a and TSM and other existing satellite-based models of chl-a and TSM. For satellite application, two different atmospheric correction methods (ACOLITE and POLYMER) were tested and satellite matchups were used to validate the new chl-a and TSM algorithms following standard validation procedures. The results demonstrated that the new algorithms were in good agreement with in situ observations and outperform existing chl-a and TSM algorithms. The new regional satellite algorithms can be used to monitor water quality within the VKW system to support the sustainable management under natural (cyclones, floods, rainfall, and tsunami) and anthropogenic pressures (industrial effluents, agricultural practices, recreational activities, construction, and demolishing concrete structures) and help achieve Sustainable Development Goal 14.

Water Quality and Water Hyacinth Monitoring with the Sentinel-2A/B Satellites in Lake Tana (Ethiopia)

Human activities coupled with climate change impacts are becoming the main factors in decreasing inland surface water quantity and quality, leading to the disturbance of the aquatic ecological balance. Under such conditions, the introduction and proliferation of aquatic invasive alien species are more likely to occur. Hence, frequent surface water quality monitoring is required for aquatic ecosystem sustainability. The main objectives of the present study are to analyze the seasonal variation in the invasive plant species water hyacinth (Pontederia crassipes) and biogeochemical water quality parameters, i.e., chlorophyll-a (Chl-a) and total suspended matter (TSM), and to examine their relationship in Lake Tana (Ethiopia) during a one-year study period (2020). Sentinel-2A/B satellite images are used to monitor water hyacinth expansion and Chl-a and TSM concentrations in the water. The Case 2 Regional Coast Colour processor (C2RCC) is used for atmospheric and sunglint correction over inland waters, while the Sen2Cor atmospheric processor is used to calculate the normalized difference vegetation index (NDVI) for water hyacinth mapping. The water hyacinth cover and biomass are determined by NDVI values ranging from 0.60 to 0.95. A peak in cover and biomass is observed in October 2020, just a month after the peak of Chl-a (25.2 mg m−3) and TSM (62.5 g m−3) concentrations observed in September 2020 (end of the main rainy season). The influx of sediment and nutrient load from the upper catchment area during the rainy season could be most likely responsible for both Chl-a and TSM increased concentrations. This, in turn, created a fertile situation for water hyacinth proliferation in Lake Tana. Overall, the freely available Sentinel-2 satellite imagery and appropriate atmospheric correction processors are an emerging potent tool for inland water monitoring and management in large-scale regions under a global change scenario.

Understanding the changes of optically active substances (OACs) in Hulun Lake in the past 35 years and its indication to the degradation of aquatic ecology

Lake eutrophication and ecological degradation are among the most serious environmental problems in the world and identifying changes in key water quality parameters and associated drivers is critical for lake management. Optically active substances (OACs) are important water quality indicators that affect lake water ecology and evaluate lake eutrophication. Climate change and human activities are important factors driving the changes of OACs in lakes. Understanding how and why OACs varies in long-term trend in response to different influencing factors and its driving mechanism is needed to understand. In this study, based on the Landsat series satellite data, this study investigated the historical changes of OACs in Hulun Lake, quantitatively explained the response relationship of OACs to meteorological, hydrological and human activity elements, and discussed their indicative role in the degradation of water ecology. The results showed that during 1986–2020, OACs had obvious periodic changes; from 1986 to 1999, Chla, CDOM and TSM are relatively stable at lower values; during 2000–2009, the concentration of total suspended matter (TSM) and coloured dissolved organic matter (CDOM) increased, and the concentration of chlorophyll a (Chla) decreased; during 2010–2020 The annual TSM and CDOM concentration decreased, and the Chla concentration increased. The results showed that among the hydrometeorological and anthropogenic variables selected to explain changes in the OAC, gross domestic product (GDP) is the key factor influencing changes in the OACs, explaining 39.3%, 71.8% and 60.6% of the changes in Chla, CDOM and TSM, respectively. Air temperature (AT) can explain 24.0% of the variation in Chla, evapotranspiration (Eva) can explain 19.1% and 5.52% of the variation in CDOM and TSM, and precipitation (P) can explain 13.8% and 7.5% of the variation in Chla and TSM. Water level is an important pathway affecting OACs in Hulun Lake, explaining 50.7% of the variation in CDOM, 48.0% of the variation in TSM and 23.1% of the variation in Chla. Warming and drought in the Hulun Lake basin and human activities ultimately lead to changes in OACs. Finally, a pattern diagram to assess the degree of ecological degradation of lake was proposed. This study has substantial implications to monitor and assess the ecological degradation status of lake and maintain the sustainable development of lakes in cold and arid regions.