Turbidity Range Research Articles

Production and Characterization of Traditionally Distilled Alcohol (Raksi)

Raksi is an ethnic alcoholic drink, distilled from traditional fermented cereal beverages. The objective of this work was to characterize the traditionally fermented alcohol (raksi). We processed six raksi samples at home using traditional methods, and collected four locally from hotels in various districts. During the distillation of raksi, raksi samples were physically analyzed and found to be colorless, strongly concentrated, and alcoholic in nature. While examining the collected alcohol samples, they were found to be light yellow, cloudy, with strong concentration, and unpleasantly alcoholic in nature. All the samples were acidic with a pH range of 3.6-4.5, turbidity range from 3.5-7.8, and TDS less than 14, TSS ranging from 35-850 ppm, and TA ranging from 0.016-0.234%. The alcohol percentage was found in the range 8-46%. Alcohol percentage was highest in sample LAR10, i.e., 45% using a hydrometer, 45.32% using a pycnometer, and 35.95% using HS-GC. Sample LAR4 showed a minimum alcohol % of 10% using a hydrometer, 10.11% using a pycnometer, and 8.68% using HS-GC. There was no detection of methanol and propanol from the HS-GC result; only the ethanol was detected. Almost all the distillates lied in the score panel of “good” to “very good” by using the hedonic scale. The total bacterial count was found in the range of 0-30 CFU/100 ml and 0-7 CFU/ml from the MF technique and pour plate method, respectively. Morphological and biochemical studies confirmed that the isolated organisms were Bacillus spp. We found most of the alcohol samples effective against Pseudomonas aeruginosa. The substrates used for the fermentation of alcohol and their antibacterial efficacy showed insignificant association, i.e., p = 0.82 > 0.05. But the association between the alcohol percentage of samples and their antibacterial effectiveness was significant, i.e., p = 0.01 < 0.05. These findings highlight the characterization and detection of methanol and propanol in raksi, and they enhance the further findings of any hazards.

Response of submarine braided channels to varying inflow hydrographs: Geomorphic experiments and stratigraphic implications

AbstractSubmarine channels on the seafloor experience a range of turbidity current‐flood hydrographs. The characteristics of the flood hydrograph influence channel dimensions, the number of channel threads (i.e. braiding intensity) and the depositional properties of sandbars within the channels. However, the morphodynamic response of submarine braided channels to different hydrograph patterns is poorly understood. In this study, six geomorphic experiments are used to test how varied flood hydrographs affect the braiding intensity and sandbar geometry within submarine channels. Three experiments represent the control group with constant density‐current inflow, and three experiments use different time‐varying hydrograph patterns. The experiments show that, as the inflow‐to‐sediment discharge ratio increases, multiple small channels coalesce into a few main channels, causing a decrease in active braiding intensity defined by the channel threads with flow. When the flow returns to the initial low flow rate, active braiding intensity increases again. These observations show that the inflow‐to‐sediment discharge ratio determines the value of active braiding intensity. Additionally, active braiding intensity is directly proportional to dimensionless sediment‐stream power and dimensionless stream power, in agreement with previously established trends for both submarine and fluvial braided channels. In contrast to active braiding intensity changes, the measured sandbar aspect ratio and compactness ratio (i.e. ratio of planform area to perimeter) of submarine braided channels is insensitive to changes in the hydrograph. However, when inflows reach peak discharge, the higher transport capacity erodes pre‐existing deposits, forming noticeable erosional surfaces, and subsequently depositing thicker sandbars during that stage. These observations imply that sandbar planform morphology is largely insensitive to hydrograph, but hydrograph variability induces a greater variability in the resultant stratigraphic packages. The experimental results predict that field‐scale stratigraphy should be dominated by strata deposited during intervals of high flow, but that these strata will also exhibit reduced lateral continuity compared to formation scenarios with constant discharge.

Real-time salivary turbidity measurement with a mouthguard-type wearable sensor

Unconstrained and continuous oral hygiene monitoring is effective not only in diagnosing oral health status but also in diagnosing systemic health status. A mouthguard-type wearable sensor was proposed to measure salivary turbidity as an indicator of oral hygiene, however, the feasibility of intraoral salivary turbidity measurement was not well investigated. In this study, a mouthguard-type sensor with embedding LED, phototransistor, and wireless module was developed for optical measurement of salivary turbidity. The shape of the turbidity-sensing part of the sensor was designed based on the results of experiments on water-retention capability and measurement sensitivity. In vivo experiments using diluted milk as an ingestible turbidity standard solution showed that the sensor has sufficient quantitative capability (100–1000 FTU) and repeatability in the standard range of salivary turbidity. In addition, by continuously measuring the fluctuation in salivary turbidity using the sensor, clinically useful intraoral information such as salivary secretion and oral dryness status could be obtained. These results demonstrate that the developed mouthguard-type sensor is effective for the unconstrained and continuous evaluation of oral hygiene.

Physicochemical and microbiological assessment of multi‐village drinking water source in diarrheal hotspot areas of north Shoa zone, Amhara region, Ethiopia

AbstractQuality water is essential to people's health and social and economic well‐being. Evaluation of the quality of the water sources provides benchmark data on quality status and insights into the development of further protective measures. A laboratory‐based cross‐sectional study design was conducted in the diarrheal hotspot area of the North Shewa zone. The contamination risks of water sources were assessed using the World Health Organization (WHO) sanitary inspection checklist. A grab water sample was collected from 138 multi‐village drinking water sources according to WHO guidelines. The collected sample was processed for physicochemical and microbiological analysis. Data were recorded and analyzed using SPSS version 25 software. The inspection survey indicated there was no proper handling of the water sources. The water temperature range was between 7 and 32°C, while the turbidity values ranged from 1.8 to 6 NTU. Electrical conductivity, pH, and total dissolved solutes were 100% within the acceptable limits of WHO and the Ethiopian Ministry of Health (EMoH) water quality guidelines. However, only (77/138, 55.79%) and (101/138, 73.29%) drinking water sources were within the acceptable range of temperature and turbidity, respectively. The mean bacteriological counts in multi‐village drinking water sources were a mean value of 72.14, 29.78, 21.09, and 15.64 for TMC, TCC, FC, and FSC, respectively. A total of (19/138, 13.8%) drinking water samples were positive for total coliform (Tc) and/or fecal coliforms (Fc). The remaining (119/138, 86.2%) water samples were bacteriologically potable. The physicochemical quality of the drinking water sources was consistent with WHO and national water quality standards, except that turbidity exceeded the acceptable range. The results also showed that some water sources were contaminated with fecal and total coliform, which was supported by an inspection survey in which most water sources were poorly protected. These research findings can serve as a valuable evidence base for informing policy decisions and guiding practical interventions aimed at ensuring access to safe drinking water in diarrheal hotspot areas.

Assessment of water quality from selected borehole locations in Ado Ekiti, Ekiti State, Southwest Nigeria.

Borehole water is commonly believed to be pure and safe to drink. The present study assessed the quality of ten selected borehole locations within Ado -Ekiti. This was carried out by assessing the physicochemical parameters, microbial and heavy metal contamination using standard procedures. The physicochemical parameter results showed that Temperature range between 25.99 oC - 26.60 oC, Electrical conductivity range between 41.62 µs/cm - 202.54 µs/cm, pH range between 6.81-7.57, Total dissolved solids range between 28.15 mg/L - 116.22 mg/L, Total suspended solids range between 0.09 mgl -1.27 mgl, Turbidity range between 0.12 NTU-0.71 NTU, Total Hardness range between 29.64 mg/l -80.61 mg/l, Total Alkalinity range between 20.97 mg/l - 65.42 mg/l and all values were within World Health Organisation (WHO) permissible limits. The bacteria count of borehole water sample range from 10.66 ± 0.03 Cfu/ml to 12.56 ± 0.03 Cfu/ml. Highest fungi count of the borehole water sample was in the value range from 8.27 ± 0.00 Sfu/ml to 9.63 ± 0.02 Sfu/ml. The highest coliform detected in the borehole sample range from 5.33 ± 0.58 Cfu/ml to 8.67 ± 8.56 Cfu/ml. The bacteria, fungi and coliform count result observed in this study was higher than the WHO recommended limits. The metals occurred in the samples in this order Cr >Fe > Pb > As > Cd. The heavy metals were present in quantities higher than WHO recommended limit in some of the samples which is an indication of potential health hazards through the water consumption.

Automation System Architecture of pH Neutralization Process in Batik Wastewater Treatment Plant

Batik production in home industries needs support wastewater treatment in a limited space. Therefore, a modular-type, lab-scale wastewater treatment plant (WWTP) with a capacity of 87.75 liters and a dimension of 1.5 m × 0.75 m × 1 m has been constructed. The WWTP combines three significant processes: equalization, neutralization, and adsorption. This study focuses on the monitoring systems for the pH neutralization process. The system uses four microprocessors in a Master/Slave architecture and the I2C protocols for data communication between processors. The measuring instruments include pH, temperature, turbidity, and flow rate sensors. The actuators consist of submersible and peristaltic pumps. The operating range of pH, temperature, turbidity, and flow rate sensors are 0–14, 25–81.44℃, 0–3000 NTU, and 6.49–20.84 ml/s respectively. The pumps work in Pulse Width Modulation (PWM) mode with an operating range of 125–225 PWM. All sensors and actuators operate linearly within the operating range with a correlation coefficient of 0.97–1.

IOT BASED WATER QUALITY MONITORING SYSTEM

Water is one of the most vital resources for life, and protecting its quality is crucial for both the environment's health and the well-being of people. Monitoring and preserving the quality of the water is now essential given the mounting problems caused by pollution, climate change, and expanding populations. In this environment, the Internet of Things (IoT) has emerged as a ground-breaking innovation that has the potential to revolutionize the way we manage and monitor water quality. An IoT-based water quality monitoring system's relevance, components, advantages, and prospective applications are highlighted. It offers a chance to proactively address problems with water quality, protecting both the environment and the general people. Sensors used in IoT-based water quality monitoring systems can measure a wide range of factors, including temperature, dissolved oxygen, turbidity, pH levels, and chemical concentrations. These sensors are interfaced with the microcontroller unit. The sensors are positioned in pipelines, treatment facilities, or water bodies. Through wireless communication protocols like Wi-Fi or cellular networks, the data gathered by sensors is sent to a central server or cloud platform. This makes it possible to access and analyses data in real time. Users can use online or mobile applications to get the data on the quality of the water. These intuitive user interfaces offer up-to-the-minute data, historical trends, and alarms if water quality measurements differ from predetermined criteria. Urban populations can have access to safe drinking water by using IoT systems at water treatment facilities to monitor and manage water quality indicators. Aquaculture farms' production is increased by IoT- based systems' assistance in maintaining ideal water conditions for fish and other aquatic species. Monitoring soil and water quality helps farmers improve irrigation operations, which increases agricultural yields and decreases water waste. IoT is an excellent instrument for preserving water resources, defending the environment, and delivering real-time data, affordable solutions, and data-driven decision-making. Key Words: Microcontroller, Pumping station, Sensor, IoT, data, aquaculture.

Magnetic coagulation and flocculation of kaolin suspension using Fe3O4 with plant polyphenol self-assembled flocculants

In this work, magnetic flocculant (Fe3O4@PP) was synthesized using plant polyphenol (PP) as a shaping ligand via in situ self-assembly. Characterization results revealed that Fe3O4@PP exhibited uniform particle size and excellent dispersibility with PP coating amount of 16.4 %. Experimental results suggested that Fe3O4@PP showed excellent turbidity removal efficiency in a wide pH range (3.0–10) and initial turbidity range (50–2000 NTU). Under the optimal conditions, Fe3O4@PP achieved 95.2 % of turbidity removal for simulated kaolin suspension and 96.9 % for actual wastewater. Fe3O4@PP exhibited excellent recycling and reusability properties, with high recycling efficiency of 93.3 % even after the fifth cycle. Microscopic observation revealed the formation process of magnetic flocs, involving particle aggregation, chain and cluster formation, and dense network aggregate formation. The structural characteristics and size of magnetic flocs were found to be significantly influenced by the combined effects of magnetic force, electric charge, van der Waals force, and functional groups on the surface of PP. The extended Deryaguin-Landau-Verwey-Overbeek models indicated that magnetic interactions were the primary mechanism for magnetic flocculation, accompanied by charge neutralization, adsorption bridging, sweeping, and net trapping.

An overview of water quality within the Colombo Municipal Council area; A retrospective report analysis

Access to safe and quality drinking water is a fundamental requirement and a basic human right. Water quality is determined by its biological, physical, and chemical properties. Colombo Municipal Council (CMC) area consists of the largest population who utilize pipe-borne water supplied by the National Water Supply and Drainage Board (NWS&DB) Sri Lanka. The objective of the study was to assess the water quality of the drinking water under selected parameters within the Colombo Municipal Council area. In this quantitative, retrospective, cross-sectional study, 268 water analysis reports from 1st July to 30th November 2021 were considered with the permission of the Ethics Review Committee of KIU (KIU_ERC_21_194A) and relevant authorities of NWS&DB. Data on selected parameters such as color, turbidity, pH, Total Dissolved Solids (TDS), Free Residual Chlorine (FRC), the total number of coliform bacteria, and the total number of Escheretia-Coli (E-Coli) were extracted. Data analysis was done using SPSS (Version 25). All values were considered based on reference ranges of Sri Lanka Standards (SLS) guidelines. The study indicated that, among nine water schemes and four water reservoirs, the highest contributions for purification were from the Maligakanda water scheme (15.9% n =56) and Maligakanda water reservoir (51.6%, n=139). All the samples were fully treated water and the mean of the color was 4.03 Hazen Units which was within the permissible level, though ( 3.7 % n=10) of samples exceeded the range. The mean value of the turbidity was 0.49 Nephelometric Turbidity Unit (NTU) which was within the permissible level and only one sample had deviated from the maximum permissible level. The mean pH value was 7.33 and except for one, all other samples were within the permissible level. The mean value of the TDS was 24.51mg/L and the majority (95.8 %, n= 257) of FRC values varied between 0.6-0.8mg/L which was within the permissible level, while 3.39% (n=10) of samples had 0 mg/L. All samples were free from coliform and E-Coli. Most of the samples were within the permissible range of color, pH, turbidity, TDS, FRC, and free from Coliform and E-Coli which can be recommended for use.

Application of tannin-based coagulant for high-range turbidity surface water clarification

Abstract This study aimed to evaluate the performance of a tannin-based coagulant in clarifying drinking water from a high-range turbidity river and characterizing the sludge. Tanfloc MTH product was selected for this investigation. The study site was surface water located in southern Brazil (Caveiras River, Brazil). Samples were collected just before the Parshall flume in the municipal water treatment plant in Lages (Brazil) for nine months, at least once a week. Jar testing evaluated turbidity removal, alkalinity consumption, optimal coagulant dosage, and settling velocity. After flocculation and settling, the sludge generated from the jar test was submitted to metal and thermogravimetric analyses. The use of tannin reduced the average water turbidity from 26.1 ± 56.1 to 0.94 ± 0.26 NTU, apparent color from 145 ± 190 to 3 ± 3 Pt-Co, and there was no variation in the pH. Additionally, the settling velocity of the flocs reached a maximum turbidity removal at 3.5 cm·min−1. Furthermore, the metal concentrations in the sludge showed a majority of aluminum and iron, and thermogravimetric analysis revealed 64% weight loss. In conclusion, Tanfloc presented the potential to be used in surface water clarification from the Caveiras river, and the extensive turbidity range observed during this study did not affect the operational stability.

Optical Fiber Multiparameter Detection and Numerical Simulation and Characteristics of Water Quality Particulate Matter Based on Single-Photon Detection Technology

Water quality testing is of great significance for daily water use or water use in high precision manufacturing. The use of single-photon detection technology to detect water particles is one of the important methods of physical water quality detection. However, the current water quality particle detection technology needs to be improved in the range and accuracy of turbidity detection. The paper aims to use single-photon detection technology to design a fiber optic turbidity detection system to solve the current problems of small turbidity detection range and low accuracy in a large range. In response to this, this paper has made an in-depth understanding of single-photon detection technology and designed two sets of detection schemes using the performance of photons. The first set is the transmission optical fiber turbidity detection, which can effectively detect the ultralow turbidity range and a wide range of water quality particles. The second set is a scattering optical fiber turbidity detection system, which can effectively detect water particles in the low and medium turbidity range. In this paper, the two systems were integrated into a whole system, so the results of the two detection methods can also be compared, and the detected turbidity can be obtained more accurately. The experimental results showed that for the transmission optical fiber turbidity detection system, the detection effect of the system was the best under the incident light intensity of 11 wm, and the fitting value was 0.99; for the scattering optical fiber turbidity detection system, the detection effect of the system was the best under the incident light intensity of 4 wm, and the fitting value was 0.99.

Hydrocarbons Utilizing Coliform from Polluted Soil (Sandy, Clay and Loamy) in Jega, Nigeria

Environmental pollution with spilled oil and waste hydrocarbons has become a problem of major concern on the global scale. The study determined the biodegradation potentials of coliform from soil treated with petrol in Jega metropolis. A total of nine (9) soil samples were collected and analyzed using Physicochemical and Microbiological standard techniques. The mean values of the physicochemical parameters tested ranged; pH (6.8-7.8), Temperature (–32.6b), Electrical conductivity (-), Dissolved oxygen (2.4-8.9), Biological oxygen demand ( -), Chemical oxygen demand (), Nitrogen content (1.30.2 -) and Phosphorous contents (2.90.- ). The spectrophotometric biodegradation potential of the soil samples reveals the turbidity range of 2.3-7., after which the bacterial isolates as scoliform were obtained, the isolates were further biochemically characterized, their percentage of occurrence show; Pseudomonas aeruginosa with 5 (29.4%), Escherichia coli with 3 (17.6%), Proteus vulgaris with 3 (17. 6%), Citrobacter koseri with 2 (11.8%), Citrobacter freundii with 2 (11.8%), while Proteus mirabilis with 2 (11.8%). The bacteria isolated fit for utilizing hydrocarbons as energy source. Therefore, microbes can be considered as a key component in the cleanup strategy for petroleum hydrocarbons remediation.

Studies of Food Ecology of Great Cormorant Phalacrocorax carbo in Relation to Water Transparency Require System-Adjusted Data: An Example from Two Polish Reservoirs

Water transparency is an important factor affecting fish availability (underwater visibility) for diving birds. The diet of Great Cormorants Phalacrocorax carbo in relation to water transparency (range 1.4–4.0 m) was studied by pellet analyses at the submontane reservoir Dobczyce, Poland, from June to November. Although water transparency proved to be related to the birds' distribution, in the range of turbidities studied, no relationship was found with either fish species and fish size taken. Of 14 species in the diet, Roach Rutilus rutilus was dominant in all monthly samples (35–91% in 2002, 56–82% in 2004). Numbers of Great Cormorants and water transparency (range 0.4–1.4 m) were studied in the turbid lowland reservoir Goczałkowice during the migration period in autumn (August–November 2011 and 2012). Observations here suggest that the effect of water transparency on food uptake and habitat choice was only apparent below 0.6 m Secchi depth. The number of foraging Great Cormorants was not only affected by Secchi depth, but by a complex of factors (year, month, place, Secchi depth and water depth). We argue that, especially when the number of Great Cormorants is low, only highly detailed measurements of these factors (both spatially and as time series) can show the complex relationship between prey distribution, environmental conditions and the predator's behaviour.

Sensor Fusion with Deep Learning for Autonomous Classification and Management of Aquatic Invasive Plant Species

Recent advances in deep learning, including the development of AlexNet, Residual Network (ResNet), and transfer learning, offer unprecedented classification accuracy in the field of machine vision. A developing application of deep learning is the automated identification and management of aquatic invasive plants. Classification of submersed aquatic vegetation (SAV) presents a unique challenge, namely, the lack of a single source of sensor data that can produce robust, interpretable images across a variable range of depth, turbidity, and lighting conditions. This paper focuses on the development of a multi-sensor (RGB and hydroacoustic) classification system for SAV that is robust to environmental conditions and combines the strengths of each sensing modality. The detection of invasive Hydrilla verticillata (hydrilla) is the primary goal. Over 5000 aerial RGB and hydroacoustic images were generated from two Florida lakes via an unmanned aerial vehicle and boat-mounted sonar unit, and tagged for neural network training and evaluation. Classes included “HYDR”, containing hydrilla; “NONE”, lacking SAV, and “OTHER”, containing SAV other than hydrilla. Using a transfer learning approach, deep neural networks with the ResNet architecture were individually trained on the RGB and hydroacoustic datasets. Multiple data fusion methodologies were evaluated to ensemble the outputs of these neural networks for optimal classification accuracy. A method incorporating logic and a Monte Carlo dropout approach yielded the best overall classification accuracy (84%), with recall and precision of 84.5% and 77.5%, respectively, for the hydrilla class. The training and ensembling approaches were repeated for a DenseNet model with identical training and testing datasets. The overall classification accuracy was similar between the ResNet and DenseNet models when averaged across all approaches (1.9% higher accuracy for the ResNet vs. the DenseNet).

Coregistration of projections and extended unsharp masking filtering for improving the reconstruction of targets hidden in turbid media

We experimentally demonstrate an integrated approach for improving reconstruction quality of targets embedded within a turbid media by integrating multiple viewpoints (projections) together with an extended unsharp masking (eUSM) algorithm recently demonstrated in atmospheric solar images. In the setup, objects with differing geometrical shapes and sizes were embedded within media with a range of turbidity and varying attenuation and viscosity values. The medium was illuminated with a laser beam after which multiview images, obtained by lens array, were captured with a camera. In offline processing, each sub-image (viewpoint) was digitally cropped, extracted from the array, eUSM filtered, and qualitatively evaluated by contrast metrics. After sub-images were sorted and ranked based on metric values, the selected ‘best’ sub-images were shifted to a common center and co-added with others using a shift-and-add (SAA) method to form a single average image revealing the shape of the object. Linear polarization was also introduced into the setup to give higher contrast image quality. Moreover, by optimizing eUSM parameters, further improvement was achieved in the reconstruction. Experimental results illustrate the improvement of the proposed approach as compared to the previously described SAA method alone.

Environmental factors associated with the filamentous green algae Cladophora blooms: A mesocosm experiment in a shallow eutrophic lake

The process of ecological restoration in eutrophic lakes, often results in the blooming of the filamentous green algae Cladophora. This consequently affects the growth of submerged plants and the restoration of vegetation. However, the blooming process of Cladophora and the environmental factors affecting their growth are poorly understood. This has become a difficult problem in the management of lakes. The study therefore focused on succession process of Cladophora blooms and their driving factors through mesocosm experiments in Caohai Lake. The results of our experiment indicated that Cladophora growth was mainly affected by water temperature, turbidity and soluble reactive phosphorus concentration of the habitat where Elodea nuttallii and Cladophora coexist. Nuisance Cladophora was mainly affected by turbidity (>19.24 NTU) when the water temperature was above 15.7 °C. With increasing Cladophora biomass and decreasing turbidity (<4.88 NTU), Cladophora biomass accumulation was mainly limited by the soluble reactive phosphorus concentration (<3.2 μg/L). Recorded turbidity range of 9.54–13.19 NTU was found to cause dramatic changes in the biomass of Cladophora. The results also showed that the outbreak of Cladophora blooms was mainly attributed to turbidity when the water temperature was appropriate in eutrophic lakes. These findings suggest that successful management efforts should strengthen the monitoring of transparency change in addition to controlling the phosphorus concentration to limit the Cladophora overgrowth on lake ecological restoration.

Spatial and Temporal Variation of Selected Water Quality Parameters in the Tanzanian Side of Lake Victoria

Lake Victoria’s water quality is increasingly becoming under heavy pressure mainly due to land based activities and aerial inputs which are taking place within the basin. This study was carried out to assess the spatial, including vertical and temporal, variation of the water quality of Lake Victoria on the Tanzanian side. Historical water quality data for the period from 2000 to 2016 was collected. Temperature, pH, Dissolved Oxygen (DO) and Turbidity were selected for study since they are the mostly measured and monitored water quality parameters. Land use-land cover changes were analysed using ArcGIS. ILWIS 3.7 software was used to classify the land use and land cover for the years 2000, 2010 and 2014. MERIS was used to analyse the spatial variation. One-way ANOVA was employed to test the significant variation between different parameters. The results showed that, for the pelagic zone, the range of temperature, pH, DO, and turbidity were 22.8 oC-28.68 oC, 6.3-10.52, 3.42-10.21 mg/l, 1.0 NTU-15.8 NTU respectively. The corresponding values for the littoral zones were 22.3 oC-26.8 oC, 6.47-10.16, 3.99-8.6 mg/l, 1.3-347 NTU respectively. The ANOVA analysis results show that there was a significant variation of NO3(p&lt;0.01). Temperature, pH and DO decreased with the lake depth to the bottom for both zones. For the littoral zone, a strong correlation was observed between temperature and depth, temperature and DO, and between temperature and pH with R2=0.6, p&lt;0.03, R2=-0.78, p&lt;0.01 and R2=0.96, p&lt;0.01, respectively. The bare soil, urban settlements and farm land increased by 38.9%, 8.4% and 10.7% respectively from the year 2000 to 2014 on the Tanzanian side. This could have led to water quality changes. Water quality parameters varied significantly between pelagic and littoral zones. Littoral zones are mostly polluted and thus should be the priority pollution control intervention areas.

Probing the dynamics of turbid colloidal suspensions using differential dynamic microscopy.

Few techniques can reliably measure the dynamics of colloidal suspensions or other soft materials over a wide range of turbidities. Here we systematically investigate the capability of Differential Dynamic Microscopy (DDM) to characterise particle dynamics in turbid colloidal suspensions based on brightfield optical microscopy. We measure the Intermediate Scattering Function (ISF) of polystyrene microspheres suspended in water over a range of concentrations, turbidities, and up to 4 orders of magnitude in time-scales. These DDM results are compared to data obtained from both Dynamic Light Scattering (DLS) and Two-colour Dynamic Light Scattering (TCDLS). The latter allows for suppression of multiple scattering for moderately turbid suspensions. We find that DDM can obtain reliable diffusion coefficients at up to 10 and 1000 times higher particle concentrations than TCDLS and standard DLS, respectively. Additionally, we investigate the roles of the four length-scales relevant when imaging a suspension: the sample thickness L, the imaging depth z, the imaging depth of field DoF, and the photon mean free path . More detailed experiments and analysis reveal the appearance of a short-time process as turbidity is increased, which we associate with multiple scattering events within the imaging depth of the field. The long-time process corresponds to the particle dynamics from which particle-size can be estimated in the case of non-interacting particles. Finally, we provide a simple theoretical framework, ms-DDM, for turbid samples, which accounts for multiple scattering.

SYSTEM PENDETEKSI KELAYAKAN KOLAM IKAN NILA MENGGUNAKAN METODE SAW (SIMPLE ADDITIVE WEIGHTING) BERBASIS IoT (INTERNET OF THINGS)

Tilapia (Oreochromis niloticus) is a type of freshwater fish consumption with elongated and flattened body shape laterally and blackish white color. Tilapia originated from the Nile River and surrounding lakes. Now this fish has spread to countries on five continents with tropical and subtropical climates. Whereas in cold climates, tilapia cannot live well. ideal water temperature in tilapia enlargement ponds ranges between 27.7-29.3 ° C, where fish will grow optimally at water temperatures around 25-32 ° C.for the pH of the tilapia enlargement ponds range between 6, 4-8.5 and turbidity range of 3-19 NTU, because this high turbidity level has an effect on the amount of tilapia mortality. With the system that the researchers created, it was easier to determine a suitable fish pond to maintain as a life of tilapia with the help of the Internet of Things network system and reduce the failure rate in breeding and implementation of Thingspeak as a platform to display the results of data obtained by sensors and calculated with method calculation.&#x0D; This system takes data with temperature sensors, pH and Turbidity, to find water temperature, acidity and alkalinity in water and turbidity of water. Then the data obtained is sent to the ESP8266 module network and sent to the thingspeak platform, the data that appears is inputted into the database to be processed using the SAW method, the results of the SAW method calculation are displayed by the system.&#x0D; Implementation of the SAW (Simple Additive Weighting) Method for Detecting the Feasibility of Iot-Based Fish Ponds (Internet of Things) has been successfully implemented. So that it can rank tilapia ponds based on parameters of temperature, pH, turbidity.

Application of soft computing in water treatment plant and water distribution network

Analysis of traditional water distribution network (WDN) is more time-consuming and less effective to predict the problem related to water supply systems such as water quality, coagulant dose, and residual chlorine in developing countries. In the present paper water quality neural network, coagulation dose neural network, and residual neural network model were implemented. The performance of the Cascade Feed Forward Neural Network (CFFNN) and Feedforward neural network (FFNN) was excellent for the prediction of water quality parameters and residual chlorine respectively during the training and testing period. CFFNN water quality model (27-30-27) with R = 0.989 produced an excellent prediction of outlet water quality parameters. In coagulant dose modelling, CFFNN (2-40-1) yielded a good prediction with R = 0.947 for a broad range of turbidities as compared to other models. Similarly in residual chlorine modelling, FFNN (2-25-1) delivered the best prediction with R = 0.988 as compared to other models.