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Abstract The estuaries of Banten Bay have sandy sediment, and their main activity is fisheries. In order to maintain fishery productivity, good water quality is required. The sandy sediment in this location can affect water conditions at the point of the residue content. This study aims to reveal solids content in the estuaries of Banten Bay. A survey was conducted in four estuaries, namely Karangantu, Wadas, Cengkok, and Pamong. TDS were measured in situ in April and October 2021. TSS was analyzed in May, July, and October 2013, as well as in April and October 2021. Other physical and chemical parameters were analyzed in the laboratory or in situ. The results were compared with the standard for sea aquatic biota. Furthermore, the regression method was used to determine the correlation of TSS and TDS with other parameters. The physical and chemical parameters that affect TDS and TSS were analyzed using Principal Component Analysis (PCA). The results show that TSS correlated with Oxidative Reductive Potential (ORP) and turbidity. PCA showed that TSS correlated with TDS, nitrate, ammonium, ORP, water depth, and water current. Although TSS exceeded the threshold, sufficient dissolved oxygen and higher nutrient still maintained water quality for fisheries in four estuaries.

This study provides a comprehensive review of the efforts utilized in the measurement of water quality parameters (WQPs) with a focus on total dissolved solids (TDS) and total suspended solids (TSS). The current method used in the measurement of TDS and TSS includes conventional field and gravimetric approaches. These methods are limited due to the associated cost and labor, and limited spatial coverages. Remote Sensing (RS) applications have, however, been used over the past few decades as an alternative to overcome these limitations. Although they also present underlying atmospheric interferences in images, radiometric and spectral resolution issues. Studies of these WQPs with RS, therefore, require the knowledge and utilization of the best mechanisms. The use of RS for retrieval of TDS, TSS, and their forms has been explored in many studies using images from airborne sensors onboard unmanned aerial vehicles (UAVs) and satellite sensors such as those onboard the Landsat, Sentinel-2, Aqua, and Terra platforms. The images and their spectral properties serve as inputs for deep learning analysis and statistical, and machine learning models. Methods used to retrieve these WQP measurements are dependent on the optical properties of the inland water bodies. While TSS is an optically active parameter, TDS is optically inactive with a low signal–noise ratio. The detection of TDS in the visible, near-infrared, and infrared bands is due to some process that (usually) co-occurs with changes in the TDS that is affecting a WQP that is optically active. This study revealed significant improvements in incorporating RS and conventional approaches in estimating WQPs. The findings reveal that improved spatiotemporal resolution has the potential to effectively detect changes in the WQPs. For effective monitoring of TDS and TSS using RS, we recommend employing atmospheric correction mechanisms to reduce image atmospheric interference, exploration of the fusion of optical and microwave bands, high-resolution hyperspectral images, utilization of ML and deep learning models, calibration and validation using observed data measured from conventional methods. Further studies could focus on the development of new technology and sensors using UAVs and satellite images to produce real-time in situ monitoring of TDS and TSS. The findings presented in this review aid in consolidating understanding and advancement of TDS and TSS measurements in a single repository thereby offering stakeholders, researchers, decision-makers, and regulatory bodies a go-to information resource to enhance their monitoring efforts and mitigation of water quality impairments.

Water quality parameters like temperature, pH, total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (DO), oil and grease, etc., are calculated from the field while parameters like biological oxygen demand (BOD) and chemical oxygen demand (COD) are interpreted through the laboratory tests. On one hand parameters like temperature, pH, DO, etc., can be accurately measured with the exceeding simplicity, whereas on the other hand calculation of BOD and COD is not only cumbersome but also inaccurate many times. A number of previous researchers have tried to use different empirical methods to predict BOD and COD but these empirical methods have their limitations due to their less versatile application. In this paper, an attempt has been made to calculate BOD and COD from simple field parameters like temperature, pH, DO, TSS, etc., using Artificial Neural Network (ANN) method. Datasets have been obtained from analysis of mine water discharge of one of the mines in Jharia coalfield, Jharkhand, India. 73 data sets were used to establish ANN architecture out of which 58 datasets were used to train the network while 15 datasets for testing the network. The results show encouraging similarity between experimental and predicted values. The RMSE values obtained for the BOD and COD are 0.114 and 0.983 %, respectively.

The deposition of suspended sediment is an important process that helps wetlands accrete surface material and maintain elevation in the face of sea level rise. Optical remote sensing is often employed to map total suspended solids (TSS), though algorithms typically have limited transferability in space and time due to variability in water constituent compositions, mixtures, and inherent optical properties. This study used in situ spectral reflectances and their first derivatives to compare empirical algorithms for estimating TSS using hyperspectral and multispectral data. These algorithms were applied to imagery collected by NASA’s Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over coastal Louisiana, USA, and validated with a multiyear in situ dataset. The best performing models were then applied to independent spectroscopic data collected in the Peace–Athabasca Delta, Canada, and the San Francisco Bay–Delta Estuary, USA, to assess their robustness and transferability. A derivative-based partial least squares regression (PLSR) model applied to simulated AVIRIS-NG data showed the most accurate TSS retrievals (R2 = 0.83) in these contrasting deltaic environments. These results highlight the potential for a more broadly applicable generalized algorithm employing imaging spectroscopy for estimating suspended solids.

Abstract This study investigated the impact of sedimentation on rainwater storage system using a case study at the Ikorodu area of Lagos state, a rural area in Nigeria. In this investigation, the proportions of Escherichia coli (E. coli) that were settleable (due to sedimentation) and those that were at the free phase have been studied. Water samples were collected from different depths in the inspected rainwater storage tank at two different periods (i.e. rainy and dry periods) for 20 days. The samples collected from these periods have been analysed for physical and microbial measures before passing it through the serial filters with pore sizes of 500 μm, 100 μm, 10 μm and 1.5 μm to measure the retained particle mass. From the results, it was observed that: (1) the water quality at the free-phase zone was better than that at the tank's bottom; (2) the settleable bacteria rapidly sank to bottom; (3) the correlation of turbidity, E. coli and total suspended solids (TSS) for all the rain events showed a relatively high Pearson's coefficient of 0.9 to one another; and (4) over 70% of settling TSS occurred within first 36 h. Finally, it has been found that the physical sedimentation process can significantly reduce the microbial measures.

The current study aimed at fostering bacterial growth in BFT aquaculture tanks by early Nile tilapia stocking. Control tanks had no tilapia but received daily applications of dry molasses (NT+) or had tilapia but no C:N ratio adjustment (T-). Experimental tanks had tilapia and received daily application of molasses to adjust the C:N ratio of water to 15:1 (T+). The development of bioflocs in NT+ was insignificant as demonstrated by low levels of settleable solids (SS) and total suspended solids (TSS). Total ammonia nitrogen (TAN) was significantly higher in NT+ than in T+. In the C:N-ratio adjusted tanks, the presence of fish shortened the control of TAN in several days. As nitrite declined in T+, it increased in NT+. The final concentrations of TSS in T+, T- and NT+ were 236 ± 29 mg L-1, 100 ± 32 mg L-1, and 40 ± 22 mg L-1, respectively (p < 0.05). It can be concluded that stable nitrifying and heterotrophic bacterial communities could be attained in BFT aquaculture tanks, before the end of the 4th week of culture, if the bacterial growth is fostered by early Nile tilapia stocking.

Conventional water quality measurements are nearly impossible during and immediately after extreme storms due to dangerous conditions. In this study, remotely sensed reflectance is used to develop a regression equation that quantifies total suspended solids (TSS) in near real-time after Hurricane Harvey. The application focused specifically on sediment loading and deposition and its potential impacts on the Houston Ship Channel and Galveston Bay riverine-estuarine system. The European Space Agency’s Sentinel-2 satellite captured images at critical points in the storm’s progression, necessitating the development of a new algorithm for this relatively new satellite mission. Several linear regressions were analyzed with the goal of developing a simple one- or two-band equation, and the final model uses the red and near infrared bands (R 2  = 0.74). Results show that record flows during Harvey delivered unprecedented suspended sediment loads to the Gulf of Mexico at concentrations above 125 mg/L with a mean concentration of 43 mg/L across the bay. The study findings demonstrated that it took up to 11 days after the storm for sediment transport to abate.

The Colorado River is a principal source of water for 40 million people and farmlands in seven states in the western US and the Republic of Mexico. The river has been under intense pressure from the effects of climate change and anthropogenic activities associated with population growth leading to elevated total dissolved solid (TDS) and total suspended solid (TSS) concentrations. Elevated TDS- and TSS-related issues in the basin have a direct negative impact on the water usage and the ecological health of aquatic organisms. This study, therefore, analyzed the spatiotemporal variability in the TDS and TSS concentrations along the river. Results from our analysis show that TDS concentration was significantly higher in the Upper Colorado River Basin while the Lower Colorado River Basin shows a generally high level of TSSs. We found that the activities in these two basins are distinctive and may be a factor in these variations. Results from the Kruskal–Wallis significance test show there are statistically significant differences in TDSs and TSSs from month to month, season to season, and year to year. These significant variations are largely due to seasonal rises in consumptive use, agriculture practices, snowmelts runoffs, and evaporate rates exacerbated by increased temperature in the summer months. The findings from this study will aid in understanding the river’s water quality, detecting the sources and hotspots of pollutions to the river, and guiding legislative actions. The knowledge obtained forms a strong basis for management and conservation efforts and consequently helps to reduce the economic damage caused by these water quality parameters including the over USD 300 million associated with TDS damages.

The quality of water has deteriorated due to urbanization and the occurrence of urban stormwater runoff. To solve this problem, this study investigated the pollutant reduction effects from the geometric and hydrological factors of green infrastructures (GIs) to more accurately design GI models, and evaluated the factors that are required for such a design. Among several GIs, detention basins and retention ponds were evaluated. This study chose the inflow, outflow, total suspended solids (TSS), total phosphorus (TP), watershed area, GI area (bottom area in detention basins and permanent pool surface area in retention ponds), and GI volume (in both detention basins and retention ponds) for analysis and applied both ordinary least squares (OLS) regression and multiple linear regression (MLR). The geometric factors do not vary within each GI, but there may be a bias due to the number of stormwater events. To solve this problem, three methods that involved randomly extracting data with a certain range and excluding outliers were applied to the models. The accuracies of these OLS and MLR models were analyzed through the percentage bias (PBIAS), Nash-Sutcliffe efficiency (NSE), and RMSE-observations standard deviation ratio (RSR). The results of this study suggest that models which consider the influent concentration combined with the hydrological and GI geometric parameters have better correlations than models that consider only a single parameter.

We studied the effect of sand filtration with natural esker material on the removal of total organic carbon (TOC), total suspended solids (TSS), and turbidity from the effluent of an experimental recirculating aquaculture system (RAS) farm. Separate experiments were performed with the same esker sand: (1) a soil column experiment in 2017 where the effluent (mean TOC 8.14 mg L −1 ) was percolated vertically through a 50-cm-thick sand column with the infiltration 1 m day −1 ; (2) a sand filtration experiment with water-saturated conditions in 2018 where the effluent from the woodchip denitrification (mean TOC 26.84 mg L −1 ) was infiltrated through a sand layer with the retention time of 1.2 days. In experiment 2, infiltration of 25 L day −1 through a 31-cm sand layer and 40 L day −1 through a 50-cm sand layer were studied. Both experiments were performed in association with rainbow trout ( Oncorhynchus mykiss ) grow-out trials. In sand filtration with vertical water flow through a soil column, the removal of TSS was 40%, while of TOC 6%, partly due to the small thickness of the soil column and coarse sand material. In water-saturated conditions, mean removal of TOC (3 mg L −1 1.2 day −1 ), TSS (1.2 mg L −1 1.2 day −1 ), and turbidity (0.4 FTU 1.2 day −1 ) reached 11% (TOC), 18% (TSS), and 15% (turbidity), even with the retention time of only 1.2 days. The removal of TOC in water-saturated conditions correlated with the removal of TSS and turbidity.