Total Suspended Solids Concentrations Research Articles

Study Of Total Suspended Solid (TSS) Reduction In Coal Mine Water Management In Block III Of PT. Antang Gunung Meratus, South Tapin District, Tapin Regency, South Kalimantan Province

PT. Antang Gunung Meratus is a coal mining company with an area of 22,433 Ha with open pit mining method. PT. Antang Gunung Meratus has been equipped with a wastewater treatment system using active control methods, where the pH, Fe, Mn and Cd content of mine water is normal while the total suspended solid (TSS) value is more than 200 ppm in a state exceeding the water quality standard limit set by South Kalimantan Governor Regulation No.36 of 2008. The purpose of this study is to determine the results of water quality before and after it is managed and what methods are used in its management and how much costs are spent in managing the mine water. The research methods used are literature study methods, research in the field, primary and secondary data collection, data processing, data analysis and conclusions. The results showed that mining water in the WWTP area had the highest total suspended solid (TSS) content in July 2022 reaching 4.788 mg/l, while at the outlet the total suspended solid (TSS) value was 23 mg/l, the pH value was 7.22. Iron content (Fe) of 0.04 mg / l manganese content (Mn) of 0.006 and Cadmium (Cd) content of 0.004 mg / l, the content in the outlet comes from laboratory tests and costs incurred in mine water management worth Rp. 840,854,400 as of July 2022.

Estimating the concentration of total suspended solids in inland and coastal waters from Sentinel-2 MSI: A semi-analytical approach

Inland and coastal waters provide key ecosystem services and are closely linked to human well-being. In this study, we propose a semi-analytical method, which can be applied to Sentinel-2 MultiSpectral Instrument (MSI) images to retrieve high spatial-resolution total suspended solids (TSS) concentration in a broad spectrum of aquatic ecosystems ranging from clear to extremely turbid waters. The presented approach has four main steps. First, the remote sensing reflectance (Rrs) at a band lacking in MSI (620 nm) is estimated through an empirical relationship from Rrs at 665 nm. Second, waters are classified into four types (clear, moderately turbid, highly turbid, and extremely turbid). Third, semi-analytical algorithms are used to estimate the particulate backscattering coefficient (bbp) at a reference band depending on the water types. Last, TSS is estimated from bbp at the reference band. Validation and comparison of the proposed method with three existing methods are performed using a simulated dataset (N = 1000), an in situ dataset collected from global inland and coastal waters (N = 1265) and satellite matchups (N = 40). Results indicate that the proposed method can improve TSS estimation and provide accurate retrievals of TSS from all three datasets, with a median absolute percentage error (MAPE) of 14.88 %, 31.50 % and 41.69 % respectively. We also present comparisons of TSS mapping between the Sentinel-3 Ocean and Land Colour Instrument (OLCI) and MSI in Lake Kasumigaura, Japan and the Tagus Estuary, Portugal. Results clearly demonstrate the advantages of using MSI for TSS monitoring in small water bodies such as rivers, river mouths and other nearshore waters. MSI can provide more detailed and realistic TSS estimates than OLCI in these water bodies. The proposed TSS estimation method was applied to MSI images to produce TSS time-series in Lake Kasumigaura, which showed good agreements with in situ and OLCI-derived TSS time-series.

Temporal evolution of suspended solids in the management of medium-sized watersheds in the Metropolitan Region of Paraíba Valley

The demand for water to meet the needs of the population has increased with the rapid growth of urban centers. The urban expansion in Taubaté (23.03º S, 45.55º W) negatively impacts the Una River Basin, a significant tributary of the Paraíba do Sul River, resulting in issues of sedimentation, siltation, and flooding. Systematic monitoring of sediment characteristics in human-influenced areas allows for an understanding of water quality variations, watershed diagnosis, and analysis of impacts on aquatic ecosystems, with total suspended solids (TSS) being a widely used parameter in this context. This study investigated the temporal evolution of the TSS concentration in the Una River, highlighting the importance of sound management practices to reduce sedimentation in urban catchments, through the analysis of biochemical parameters obtained from the Cetesb/Infoaguas platform. From 2008 to 2022, lower TSS concentrations were observed in winter (86.2 ± 35.6 mg L-1), while higher values were obtained in summer (779.7 ± 1024.8 mg L-1). In general, statistically significant correlations were found at the 95% confidence level between TSS and turbidity (Pearson's r = 0.93), dissolved oxygen (Pearson's r = -0.46), and electrical conductivity (Pearson's r = -0.43), while other evaluated parameters (pH, dissolved solids, and precipitation) did not show significant correlations. Among the key findings, it is crucial to study the temporal evolution of TSS and to implement sustainable management strategies in urban catchments, including erosion control measures and stormwater management, to preserve water quality, aquatic ecosystems, and water supply in the urban communities of RMVale.
 Keywords: basin, management strategies, sustainable, total suspended solids.

Coal mine wastes: Effective mitigation of coal waste slurry and acid mine drainage through bioflocculation using mixotrophic bacteria as bioflocculants

Acid mine drainage (AMD) and coal waste slurry, byproducts of global mining and coal processing activities, represent significant environmental pollution concerns due to their acidic nature and high total suspended solids (TSS) content. The exploration of microbial treatment methods, specifically the utilization of microorganisms and their metabolic byproducts as bioflocculants, is underway to mitigate the adverse effects of these byproducts. This investigation assessed the effectiveness of 54 mixotrophic bacterial strains in treating coal waste slurry and AMD from coal mines located in Kalimantan, Indonesia. The bacterium Citrobacter freundii (strain SKC-4), cultured in SKC1 medium (comprising 225 mL of seawater from the Java Sea and 15 g/L molasses), demonstrated superior performance, reducing the TSS value from 4998.20 ppm to 16 ppm within an hour. Fourier Transform Infrared (FTIR) analysis revealed an increase in the intensity of the CO and CN groups from protein amides and CH2 from carbohydrates, suggesting an interaction between bacteria and clay minerals in the coal waste slurry. The bacteria also played a crucial role in adjusting the pH of AMD, elevating it from 3.82 to 6.07 after one hour of conditioning with a bacterial culture to AMD ratio of 1:9. The interaction between bacteria and their metabolic products was further substantiated by scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) analysis, which detected the presence of an extracellular polymeric substance (EPS). To our knowledge, this study represents the first exploration of the potential of mixotrophic bacteria as bioflocculants in the biotreatment of coal waste slurry and AMD from coal mining operations.

Integrated analysis approach of water and solids for root cause of injectivity decline of water injection well – A case study

Accurate sampling and analysis of injection and flow back water and solids are pivotal to identify the root causes of injectivity decline of water injection well. The present paper is focussed on case study of detailed characterization of injection and flowback water and solids using combination of techniques such as X-ray diffraction (XRD), x-ray fluorescence (XRF), scanning electron microscopy, inductively coupled plasma optical emission spectroscopy, ion chromatography and water isotope analyser in investigating the cause of injectivity decline. The present study emphasizes the effect of pressurized and non-pressurized water sampling on water analysis results, their scaling tendencies and correlation with compositions of solids encountered. Surface pressurized injection water sample pH result was found acidic with a higher dissolved iron and lower total suspended solids (TSS). Non-pressurized water samples showed comparatively higher pH due to release of CO2. Langelier saturation index (LSI) and ScaleSoftPitzer™ program SI of pressurized water sample showed lower scaling tendency than the non-pressurized water sample. Non-pressurized water samples contained significantly higher concentrations of TSS than the pressurized water sample indicated precipitation of salts in non-pressurized sample. Composition of TSS revealed presence of iron-based compounds, calcite and gypsum. Geochemical and water isotope analysis showed identical composition of injection and flowback water. XRD and XRF analysis of trapped solids revealed different forms of iron oxides and iron sulphides as major phase along with appreciable amount of calcite and quartz. XRF analysis also showed traces of Cr, Mo, and Ni in trapped solids indicated corrosion of tubing/pipes. Solid composition correlates with scaling tendency predicted by ScaleSoftPitzer™ program SI. Presence of iron in pressurized injection water and iron compounds in solids indicate iron-based scale/corrosion as key reason for reduction in injectivity of the well. Systematic sampling, accurate and integrated analysis of water and solids can help to find the dominant causes of injectivity decline and direct oilfield engineers at well site to take appropriate remedial and preventive action.

Evaluation of pollutant removal efficiency of urban stormwater wet ponds and the application of machine learning algorithms

Wet ponds have been extensively used for controlling stormwater pollutants, such as sediment and nutrients, in urban watersheds. The removal of pollutants relies on a combination of physical, chemical, and biological processes. It is crucial to assess the performance of wet ponds in terms of removal efficiency and develop an effective modeling scheme for removal efficiency prediction to optimize water quality management. To achieve this, a two-year field program was conducted at two wet ponds in Calgary, Alberta, Canada to evaluate the wet ponds' performance. Additionally, machine learning (ML) algorithms have been shown to provide promising predictions in datasets with intricate interactions between variables. In this study, the generalized linear model (GLM), partial least squares (PLS) regression, support vector machine (SVM), random forest (RF), and K-nearest neighbors (KNN) were applied to predict the outflow concentrations of three key pollutants: total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP). Generally, the concentrations of inflow pollutants in the two study ponds are highly variable, and a wide range of removal efficiencies are observed. The results indicate that the concentrations of TSS, TN, and TP decrease significantly from the inlet to outlet of the ponds. Meanwhile, inflow concentration, rainfall characteristics, and wind are important indicators of pond removal efficiency. In addition, ML algorithms can be an effective approach for predicting outflow water quality: PLS, GLM, and SVM have shown strong potential to capture the dynamic interactions in wet ponds and predict the outflow concentration. This study highlights the complexity of pollutant removal dynamics in wet ponds and demonstrates the potential of data-driven outflow water quality prediction.

Water Quality Assessment of Remote Sensing Techniques: A Comparative Insight Between Yangtze of China and Porong of Indonesia

The river water quality, exceptionally the total suspended solid (TSS) in China and Indonesia, has deteriorated due to human activities. Remote sensing makes it easier for observers to monitor river water quality, especially TSS. However, measuring the river water quality by remote sensing is still in the model and algorithm development stage in China and Indonesia. This study aims to identify the river water quality on remote sensing in China's Yangtze River and Porong River, East Java, Indonesia, and to analyze comparisons of river water quality on remote sensing in Yangtze River, China, and Porong River, East Java, Indonesia. This method uses a literature review based on journals, articles, and primary sources to review related literature on TSS concentrations in rivers and remote sensing in China and Indonesia. River water monitoring methods can measure the TSS in China and Indonesia using remote sensing. Many water quality models for waterways are based on different satellite images. In the Yangtze Downstream River, the algorithm of TSS uses the latest random forest on Landsat-8. The algorithm of TSS in the Porong River estuary used linear regression on sentinel-2 imagery. These TSS algorithms can more precisely assess TSS in water quality for scientific studies. The results show that the latest random forest is a more precise remote sensing algorithm in China than Linear regression in Indonesia. The suspended solid models and remote sensing images such as China's MODIS, Landsat-8, and MERIS are accurate in China. Therefore, developing more precise remote sensing techniques, total suspended solid models composed of Wiggin's Algorithm and Markert Algorithm, NDWI Algorithm, and remote sensing imagery such as Sentinel-2 and Landsat-8 in Indonesia is crucial to determine total suspended solids. The researchers additionally contribute to advanced research toward advancing suitable remote sensing techniques in various areas in Indonesia.

Phytoremediation of a Combination of Water Clover (Marsilea crenata) and Java Fern (Microsorum pteropus) for Fecal Wastewater

The Fecal Sludge Treatment Plant (IPLT) is a wastewater treatment system that aims to treat fecal waste so it does not pollute the environment. One of the fecal waste water treatment processes at IPLT Supit Urang uses a phytoremediation process. This study aims to determine the phytoremediation ability of the combination of Water clover (Marsilea crenata) and Java fern (Microsorum pteropus) on fecal waste water in the Fecal Waste Treatment Plant. This research is an experimental research method using 3 repetitions and observed 5 times within 5 weeks with the tested parameters being total dissolved solids (TDS), Electrivc conductivity (EC), and total suspended solids (TSS). Analysis of Variance (ANOVA) was used to compare the ability of the combination of Microsorum pteropus and Marsilea crenata to reduce faecal waste between weeks of observation. The results showed that in general the combination of the two plant species was less effective in reducing TDS, EC and TSS content. There were significant differences in the content of the three physical parameters of water quality between weeks of observation.Keywords: Phytoremediation, Fecal waste treatment, Water Clover (Marsilea crenata), Java ferns (Microsorum pteropus)

Aerated lagoon/adsorption combination method for the treatment of olive mill wastewater: optimizing parameters using study design.

The current study focuses on investigating how to improve the efficacy of the combined process of aerated lagooning and adsorption for the treatment of olive mill wastewater (OMWW) from the olive industries in the Loukkos region using the design of experiments approach. The latter made it possible to optimize the experimental conditions, such as the mass concentration of lime, the mass concentration of powdered activated carbon (AC), and the speed of agitation (Va), which are required for the envisaged treatment, in order to control the results after the evaluation of the necessary physicochemical parameters, namely pH, total suspended solids (TSS), chemical oxygen demand (COD), rate of discoloration, and content of polyphenols. The experimental conditions necessary to carry out this study were between 1.4 and 1.75 g/l for AC, between 23 and 32 rpm for the stirring speed, and between 0.88 and 1.3 g/l for the mass concentration of lime. The results of this experiment showed that treating OMWW with the prototype II after adding lime to the mixture resulted in an estimated 85% reduction in the analyzed parameters. The pH, TSS, COD, discoloration rate, and polyphenol content were all reduced from initial values of 4.87, 0.63 (g/l), 80.3 (g (O2/l)), 0.8%, and 1.45 (g/l), respectively, to final values of 6.92, 0.12 (g/l), 12, 0.16%, and 0.25 (g/l). These results are highly significant when compared to those obtained during the treatment of prototype I using only powdered activated carbon, which showed a reduction rate of around 70%.

Primary filtration of municipal wastewater with sludge fermentation – Impacts on biological nutrient removal

Primary filtration is a compact pre-treatment process for municipal wastewater, which can lead to high removal of total suspended solids (TSS) if polymer is added prior to filtration. Extensive carbon removal with rotating belt filter (RBF) can be combined with filter primary sludge fermentation at ambient temperature, in order to produce volatile fatty acids (VFAs) as carbon source for biological nutrient removal (BNR). This process was implemented at large pilot-scale and operated for more than a year. The results showed that the RBF efficiently removed particles >10 μm, and that the TSS removal had a strong linear correlation to the influent TSS concentration. Fermentation of the sludge at ambient temperature and five days retention time and addition of the fermentate to the wastewater could nearly double the VFA concentration in the wastewater by adding 31 ± 9 mg VFA-COD/L. Meanwhile, an increase of 2 mg/L of ammonium nitrogen, and 0.7 mg /L of phosphate phosphorus would be added to the wastewater with the fermentate. Adding the fermented sludge to the wastewater stream and removing the particles with RBF makes it possible to utilize nearly all the produced VFAs for BNR, and the feasibility of this configuration was shown at pilot-scale. According to simulations of subsequent BNR, the pre-treatment would lead to lower effluent total nitrogen concentrations. Alternatively, the required BNR volume could be reduced by 11–18 %. The estimated total biogas production was similar for pre-treatment with primary settler and RBF with fermentation. RBF without fermentation gave the most favourable energy balance, but did not reach the same low effluent value for total nitrogen as RBF with fermentation.

Sustainable use of wastes as reactive material in permeable reactive barrier for remediation of acid mine drainage: Batch and continuous studies

The aim of this work was to evaluate the feasibility of the use of different industrial and agricultural wastes as reactive materials in Permeable Reactive Barriers (PRB) for Acid Mine Drainage (AMD) remediation. Sugar foam (SF), paper mill sludge (PMS), drinking water sludge (DWS) and olive mill waste (OMW) were evaluated in terms of pH neutralization and metal removal from AMD. Laboratory batch tests and continuous pilot scale up-flow columns containing 82% of Volcanic Slag (VS), as porous fill material, and 18% w/w of one of the industrial and agricultural wastes previously indicated, were tested.From the batch tests it was observed that the reactive material presenting the best results were the SF and the PMS. The results obtained in all the PRB were accurately described by a pseudo-first order model, presenting coefficient of determination higher than 0.96 in all the cases.During the continuous operation of the PRB, the porosity and hydraulic retention time (HRT) of most of the up-flow columns strongly decreased due to chemical precipitation and biofilm growth. The SF presented a significant number of fine particles that were washed out by the liquid flow, generating an effluent with very high total suspended solid concentration. Despite SF was the material with the highest alkalinity potential, the reduction of the HRT limited its neutralization and metal removal capacity. PMS and DWS presented the best pollutant removal yields in the continuous operation of the PRB, ranging from 55 to 99% and 55–95% (except in the case of the Mn), respectively. These results allowed the metal removal from the AMD. Additionally, these wastes presented very good biological sulphate reduction.Based on these results, the use of PMS and DWS as reactive material in PRB would allow to simultaneously valorise the industrial waste, which is very interesting within the circular economy framework, and to remove metals from the AMD by means of a low-cost and environmentally sustainable procedure.

Densification of Synechococcus subsalsus biomass by chitosan coagulation for biogas production

ABSTRACT This study evaluated the coagulation/flocculation process using chitosan as a natural coagulant to concentrate suspensions of the cyanobacterium Synechococcus subsalsus and enable biogas production from concentrated biomass. The chitosan performance was tested and compared with the inorganic ferric chloride (FeCl3) coagulant. Using the liquid fraction of the coagulation/flocculation process in subsequent biomass cultivations proved viable, with similar growths in culture media with up to 80% of the liquid fraction. At pH 6 and 400 mg/L FeCl3, the biomass concentrated almost seven times, increasing the total suspended solids (TSS) of the suspension from 0.4–0.6 g/L to 2.6–4.0 g/L. With 80 mg/L chitosan and pH 7, the TSS concentration attained values in the range of 7.0–9.7 g/L, an increase of more than 30 times, clearly showing that chitosan has a much higher capacity for biomass concentration at a lower concentration. A ratio of 0.3 g chitosan/g dry mass of the biomass was established to reach the maximum densification. The production of methane from chitosan-densified biomass proved to be feasible. Chitosan-densified biomass showed a two-phase cumulative methane production when digested, with slower methane production and 23% lower methane yield after 30 days of digestion (207 NmL CH4/g CODi) compared to the biomass from cultivation (non-densified, 270 NmL CH4/g CODi). However, optimizing the digestion conditions of the densified biomass should increase the methane yield and reduce process time.

Monitoring total suspended solids concentration in Poyang Lake via machine learning and Landsat images

Study regionPoyang Lake, Jiangxi Province, China. Study focusTotal suspended solids (TSS) represents an important water quality parameter in inland waters. This study compared the performance of empirical models, semi-analytical models, and four machine learning models. Then, based on field-measured data, the back propagation neural network (BPNN) model with best performance (R2 = 0.89, RMSE = 20.03 mg/L, MAE = 10.8 mg/L, MAPD = 24.89%) was established and applied to Landsat images for retrieval. The spatial-temporal distribution of TSS in Poyang Lake from 1988 to 2022 was obtained. The various effects of driving forces on temporal and spatial variations of TSS concentration in Poyang Lake were analyzed. New hydrological insights for the regionThe BPNN model proposed in this study has good performance in the testing dataset and two independent datasets, indicating good generalization ability and spatial portability. The TSS concentration showed an increasing trend over the past 35 years. The seasonal characteristics of TSS are distinct, with higher concentrations in the dry season and obvious variation in summer months. Before 2001, the TSS concentration was highly correlated with precipitation (r = −0.74) and wind speed (r = 0.60). Thereafter, sand mining (r = 0.66) became the main driving force underlying interannual variations in TSS concentration.

Analysis of water condition based on suspended sediment distribution and phytoplankton abundance in Lasolo Bay, Southeast Sulawesi Province

Lasolo Bay is a part of water in North Konawe Regency that connects the Lasolo River and sea waters. Several activities from Nickel mining activities that have been carried out around the bay have caused the physical condition of Lasolo Bay to change, namely an increase in turbidity and Total Suspended Solids (TSS) in marine waters. TSS and phytoplankton are among the indicators for determining the level of productivity of water. The purpose of this study was to determine the effect of TSS, nitrate and phosphate on phytoplankton abundance as an indicator of the level of aquatic productivity. The study was conducted in August 2021. Determination of sampling location based on purposive sampling method at 9 stations based on three layers of light penetration depth of 100%, 50% and 25% of surface light intensity. TSS analysis using gravimetric methods and phytoplankton abundance analysis using the Sedgwick Rafter Counting Chamber tool at the Biological Laboratory of FMIPA University of Halu Oleo. The results showed that TSS concentrations ranged from 160–390 mg/l and phytoplankton abundances at each station ranged from 1208–3040 cells/l. Increased TSS concentrations affect phytoplankton abundance. In general, high TSS values were at stations close to the mouth of the Lasolo river and high phytoplankton abundances were in the central part of Lasolo Bay. The abundance of phytoplankton in the waters of Lasolo Bay falls into the moderate category.

Total Suspended Solids (TSS) Spatial Distribution of Manganese in Resident Well Impacted by Residential Activity: A Case Study of Medokan Ayu District-Surabaya

TSS (Total Suspended Solid) is an optical turbidity parameter to assess water quality and provide essential information for the water environment. Particularly, the degradation of watersheds creates immense pressure on water quality, especially in arid and semiarid regions. However, concentrations of TTS in water are also due to the effects of pollution, and activities on the surface. Therefore, factual information regarding determining the effective depth of TSS is essential for the estimation of the water column. To address this problem, we collected 100 water samples from 10 different sites of the wells at Medokan Ayu District, Surabaya (Indonesia). To investigate the TSS concentrations. The results showed that the quality of well water for the turbidity parameter did not exceed the standard of clean water quality, where the highest value was found in well 7: 17.97 NTU, for the Manganese parameter in wells that exceeded the quality standard, it was found in Well 2: 1.4 mg/L. , well 5: 1.7 mg/L, well 6: 1.8 mg/L, well 7 : 8.6 mg/L and well 9: 4.3 mg/L. Well TSS parameters that exceed quality standards are found at Well 1: 1,200 mg/L, Well 3: 1,200 mg/L, Well 5: 800 mg/L, Well 6: 1,600 mg/L, Well 7: 1,600 mg/L, Well 8 : 1,200 mg/L, Well 9 : 1,200 mg/L, and Well 10 : 1,200 mg/L. The pattern of distribution of pollution levels using surfer software mapping, three wells have the highest concentrations of Manganese, TSS, and Turbidity found in wells number 6, 7, and 9.

HydroPol2D — Distributed hydrodynamic and water quality model: Challenges and opportunities in poorly-gauged catchments

Floods are one of the deadliest natural hazards and are exacerbated by changes in land-use and climate. Urban development decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry weather. It also decreases infiltration by reducing pervious areas and increases the accumulation of pollutants during dry periods. During rainy events, there is an increase in pollution concentrations and runoff that may be a source of water supply during drought periods. Modeling the quantity and quality dynamics of stormwater runoff requires a coupled hydrodynamic module capable of estimating the transport and fate of pollutants. In this paper, we evaluate the applicability of a distributed hydrodynamic model coupled with a water quality model (HydroPol2D). First, the model is compared to GSSHA and WCA2D in the V-Tilted catchment, and the limitation of the critical velocity of WCA2D is investigated. We also applied the model in a laboratory wooden board catchment, focusing on the validation of the numerical approach to simulate water quality dynamics. Then, we apply HydroPol2D in the Tijuco Preto catchment, in São Carlos - Brazil, and compare the modeled results with the full momentum solver of the HEC-RAS 2D. This catchment shares similar characteristics with many poorly-gauged and human-impacted catchments worldwide. The implementation of the model, the governing equations, and the estimation of input data are discussed, indicating the challenges and opportunities to scale HydroPol2D into the reality of data scarcity of larger poorly-gauged catchments. For a 1-yr return period of rainfall and antecedent dry days, and assuming an uncertainty of 40% in the water quality parameters, the results indicate that the maximum concentration of total suspended solids (TSS), the maximum load and the mass of the pollutant washed in 30% of the volume are, 456±260 mgL-1km-2, 2.56±0.4 kgs-1km-2, and 89%±10%, respectively.

Remote sensing-enabled machine learning for river water quality modeling under multidimensional uncertainty

Two fundamental problems have inhibited progress in the simulation of river water quality under climate (and other) uncertainty: 1) insufficient data, and 2) the inability of existing models to account for the complexity of factors (e.g., hydro-climatic, basin characteristics, land use features) affecting river water quality. To address these concerns this study presents a technique for augmenting limited ground-based observations of water quality variables with remote-sensed surface reflectance data by leveraging a machine learning model capable of accommodating the multidimensionality of water quality influences. Total Suspended Solids (TSS) can serve as a surrogate for chemical and biological pollutants of concern in surface water bodies. Historically, TSS data collection in the United States has been limited to the location of water treatment plants where state or federal agencies conduct regularly-scheduled water sampling. Mathematical models relating riverine TSS concentration to the explanatory factors have therefore been limited and the relationships between climate extremes and water contamination events have not been effectively diagnosed. This paper presents a method to identify these issues by utilizing a Long Short-Term Memory Network (LSTM) model trained on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite reflectance data, which is calibrated to TSS data collected by the Ohio River Valley Water Sanitation Commission (ORSANCO). The methodology developed enables a thorough empirical analysis and data-driven algorithms able to account for spatial variability within the watershed and provide effective water quality prediction under uncertainty.

Monitoring the spatial distribution of water quality of an urban stormwater pond using satellite images

Stormwater ponds play a critical role in managing urban runoff and mitigating the impact of pollutants on receiving water bodies. This study investigates the potential of remote sensing (RS) techniques in retrieving water level and key water quality parameters in urban stormwater wet ponds. Specifically, the focus is on water level, chlorophyll-a (Chl-a), total suspended solids (TSS), turbidity, and Secchi depth (SD). The results indicate that RS techniques can provide reliable estimates of water level, Chl-a, turbidity, SD, and TSS in urban stormwater wet ponds. Results revealed that Chl-a concentrations are higher near the inlets and within the forebay, with a significant decrease downstream of the forebay. TSS and total dissolved solids (TDS) concentrations follow a similar pattern to Chl-a, being higher near the inlet and within the forebay, but significantly lower downstream. Notably, the highest concentrations of TSS, TDS, and Chl-a are observed in July, likely due to heavy rainfall events during that period. Through principal component analysis (PCA) and correlation analysis, the study effectively captured the interrelationships among the water quality parameters in the stormwater pond. The spatial distribution of TSS and Chl-a shows a correlation. Furthermore, the study uncovers a relationship between water temperature and Chl-a concentration, with Chl-a decreasing as the temperature exceeds 20 °C and increasing when it drops below 20 °C. This relationship is influenced by sunlight availability, which affects Chl-a growth, as evidenced by variations in Chl-a concentration between the water column's bottom layers and surface. Overall, this research highlights the potential of utilizing RS techniques to retrieve water quality parameters, providing valuable information for water managers and decision-makers. The ability to generate maps of these parameters using reflected light measurements above stormwater wet ponds also contributes to effective water quality management strategies.

A novel framework for turbidity source apportionment of the urban lakeside river network

Turbidity source apportionment is essential but complex for precise environmental rehabilitation of worldwide urban lakeside river networks impaired by turbidity. A new turbidity source analysis framework including in-situ sampling, vessel monitoring, remote sensing, and hydrodynamic modelling was proposed, where the critical processes of flow reversal from the turbid lake, navigation, and urban non-point source in urban lakeside river networks were explicitly considered. The case study results showed that the turbidity problem (mean value was 211.3 nephelometricturbidityunits (NTU)) was primarily led by suspended inorganic matter (58%), followed by suspended organic matter (19%) and other matter. The Tiaoxi River and busy shipping contributed most to the annual total suspended solids load of the target river, with the same percentage of 34%. The turbid Lake Taihu provided 64,663 tonnes and 31% of the total suspended solids load, focusing on the autumn and winter months. Tiaoxi River load was highly concentrated on the storm events, which accounted for 71.4% of the annual Tiaoxi River source (209846 tonnes). The large water volume of reverse flow and the high TSS concentration of Lake Taihu in the autumn and winter months accounted for the seasonal change in Lake Taihu’s TSS load. The coronavirus disease lockdown reduced the mean monthly total suspended solids concentration of 152.4 mg/L in November and December 2019 to 49.2 mg/L in January and February 2020, by limiting the waterway transportation and the market demand for building materials. The river estuary’s vegetation interception belt, shipping restriction and rerouting, and integrated catchment management were advised to mitigate the urban river network turbidity.

Total suspended solid distribution as impact tin mining at surrounded Pangkalpinang seawater Bangka Island

Bangka Belitung Archipelago is well known as tin mining production in Indonesia. The mining activity was performed on land and offshore area which affect the shoreline and total suspended solid distribution especially at Pangkalpinang sea water. The aim of this study is to evaluate total suspended solid (TSS) distribution and compare with oceanography parameters (current and wave). The concentration of TSS was analysed in the laboratory by gravimetric total suspended solids. This study was conducted in June- July 2022 by using survey method and IDW Interpolation. The result showed that total suspended solid have various value, ranging from 56.3 mg/l – 93.3 mg/l. Based on PP No.22 in 2021, several stations on Pangkalpinang sea waters have passed the sea water quality standard. Prolonged exposure of sedimentation will lead to shoreline changes.