Performance Of Water Treatment Plants Research Articles

Simulation and Modeling of Water Treatment Plant with GPS-X Software for Health and Water Quality

Background: Waterborne diseases are infectious in nature, significantly impacting global health related to water quality and disease prevalence globally. In this study, GPS-X was used to design and simulate water treatment plants to determine the effectiveness of different mechanisms in water treatment. Method: The GPS-X water treatment software was utilized to evaluate raw and treated water performance at the Al-Kadhmaya Water Treatment Plant. Three scenarios were designed to assess the impact of varying flow rates and water parameters such as pH, alkalinity, turbidity, total dissolved solids (TDS), and total suspended solids (TSS) on the plant's performance. Results: The evaluation of the operational performance of the water treatment plant revealed that the concentrations of all contaminants in the effluent water consistently met the established Iraqi and WHO standards across all scenarios. This indicated the effectiveness of the plant's treatment processes in producing safe drinking water. The findings of this study held significance for water authorities, decision-makers in Iraq, and national and international environmental agencies, providing valuable information for improving water treatment practices and ensuring compliance with water quality standards. Conclusion: The study demonstrated the effectiveness of the GPS-X water treatment software in assessing the performance of the Al-Kadhmaya Water Treatment Plant. The results highlighted the plant's ability to consistently meet water quality standards, underscoring the importance of robust water treatment processes. These findings contributed to the body of knowledge regarding water treatment plant design and operation, offering insights that can inform decision-making processes to enhance water quality and ensure public health.

Evaluation of the operational performance of Karbala waste water treatment plant under variable flow using GPS-X model

Abstract As Karbala City is a religious tourism destination, millions of tourists visit the city annually, so there is a high fluctuation of flow in the wastewater between the plants during the year. The aim of this study is to evaluate the performance of the wastewater treatment plant (WWTP) in Karbala, Iraq, in removing pollutants for different flow rates in five scenarios using the GPS-X model. The most important phase in modeling, which greatly impacts simulation accuracy, is characterizing the influent composition to meet the mass balance. As a result, the influent wastewater was initially described and thoroughly examined. The model has been calibrated, followed by the collected data’s validation. The sensitivity of different stoichiometric and kinetic factors in the GPS-X was examined and screened to calibrate the model. To demonstrate the consistency between the simulated and measured data, the route mean square error was used in this instance. The result showed that the Karbala WWTP complies with Iraqi environmental regulations for water discharged to surface water or water for other uses and has an appropriate efficiency of wastewater treatment even if the flow entering the plant reaches the peak flow rate of 180,000/day. An improvement in orthophosphate removal efficiency was observed as the flow rate increased because of the contact time in the anaerobic basins, which gradually decreased as the flow increased until it reached the appropriate time for PO 4 3 − {\text{PO}}_{4}^{3-} removal. The outcomes of the present study provide an impression to the operators of the treatment plant of the impact of fluctuating flow on the treatment plant. The developed model can also be used for future studies.

Study of the influence of raw water infrastructure performance on drinking water

Water utilities are assessed on financial, customer service, operational, and HR performance, according to Government Regulation 122/2015. Environmental, operational, and physical factors impact cooling system performance. Local governments and water utilities assess water supply efficiency using distribution networks. In West Nusa Tenggara, researchers explored Lombok and Sumbawa. Water is abundant in Lombok but insufficient in Sumbawa. Despite the continual requirement for drinking water, this study concentrates on these two criteria since regional climates fluctuate. The former has superior local government water supplies, which affect Lombok and Sumbawa citizens’ health. This research outlines a single drinking water system’s two most important performance criteria. Researchers employ fuzzy c-means clustering, statistical regressive analysis, and questionnaire combinations for indeterminate parameters. The survey concluded that a water distribution authority has a good performance value if its intake and distribution network works effectively and the negative balance decreases. PDAM control will be less effective and the body less healthy if one portion fails, especially if fluctuations of water discharge. This research may result from an integrated drinking water collection and distribution performance model. The study found that water treatment plant performance, especially water discharge, increases water usage.

Performance of Conventional Drinking Water Treatment Plants in Removing Microplastics in East Java, Indonesia

Performance of Conventional Drinking Water Treatment Plants in Removing Microplastics in East Java, Indonesia

Optimization of water reuse and modelling by saline composition with nanoparticles based on machine learning architectures.

Water is a necessary resource that enables the existence of all life forms, including humans. Freshwater usage has become increasingly necessary in recent years. Facilities for treating seawater are less dependable and effective. Deep learning methods have the ability to improve salt particle analysis in saltwater's accuracy and efficiency, which will enhance the performance of water treatment plants. This research proposes a novel technique in optimization of water reuse with nanoparticle analysis based on machine learning architecture. Here, the optimization of water reuse is carried out based on nanoparticle solar cell for saline water treatment and the saline composition has been analyzed using a gradient discriminant random field. Experimental analysis is carried out in terms of specificity, computational cost, kappa coefficient, training accuracy, and mean average precision for various tunnelling electron microscope (TEM) image datasets. The bright-field TEM (BF-TEM) dataset attained a specificity of 75%, kappa coefficient of 44%, training accuracy of 81%, and mean average precision of 61%, whereas the annular dark-field scanning TEM (ADF-STEM) dataset produced specificity of 79%, kappa coefficient of 49%, training accuracy of 85%, and mean average precision of 66% as compared with the existing artificial neural network (ANN) approach.

Using machine learning architecture to optimize and model the treatment process for saline water level analysis

AbstractWater is a vital resource that makes it possible for human life forms to exist. The need for freshwater consumption has significantly increased in recent years. Seawater treatment facilities are less dependable and efficient. Deep learning systems have the potential to increase the efficiency as well as the accuracy of salt particle analysis in saltwater, which will benefit water treatment plant performance. This research proposed a novel method for optimization and modelling of the treatment process for saline water based on water level data analysis using machine learning (ML) techniques. Here, the optimization and modelling are carried out using molecular separation-based reverse osmosis Bayesian optimization. Then the modelled water saline particle analysis has been carried out using back propagation with Kernelized support swarm machine. Experimental analysis is carried out based on water salinity data in terms of accuracy, precision, recall, and specificity, computational cost, and Kappa coefficient. The proposed technique attained an accuracy of 92%, precision of 83%, recall of 78%, specificity of 81%, computational cost of 59%, and Kappa coefficient of 78%.

Analysis and Simulation of Waste Water Treatment Plant by Using GPS-X Software

Abstract: Kerala is rich in water resources, which helps to achieve the state to meet most of the water requirements. Due to increased population, most of the water resources are getting depleted. Among the types of water generated according to source , there is a big gap in the treatment of water. The proposed work present is planning to do a review about the modeling of water treatment plants with the help of GPS – X simulation softwares available in the industry . Also it focuses on the role of simulation tools for a better understanding of the treatment process and major trends emerging in the field of water treatment process .water supply and treatment often received more priority than waste water collection and treatment. However, water treatment deserves greater emphasis and should receive greater attention. The purpose of this project is to study the efficiency of the waste water Treatment Plant at karanthoor markaz, calicut This is done by monitoring the main physical, chemical water quality parameters, and comparing them with standards for effluents discharged into surface water. And simulation with the GPS-X software is used and results shows the performance of water treatment plant. In addition, with the software GPS-X, we are trying to improving capacity, operating efficiency and effluent quality by properly optimizing the existing facility can be obtained. This program has a clear-cut graphical interface and uses a specialized translator that converts the graphical process into material balance equations, based on dynamic models. These models allow, besides the kinetic descripton of the treatment process carried out at the water treatment plant, to simulate new scenarios towards the study of critical parameters for the process as well as optimization and control of the water treatment plant. For the modelling of the process it was necessary to collect historical data related to the water treatment plant’s performance over the last 3 years. This data was used as input values for the influent characterisation and as output values to achieve the treated effluent characterisation. Since the first simulation did not lead to the desired output results, it was necessary to proceed to the model calibration, by means of a more detailed study concerning the nutrient and organic fractions of the influent.

Assessment of drinking water treatment and disinfection by-products

Water treatment plants and disinfection by-products are a worldwide problem in the provision of drinking water with disinfectants. However, in countries like Ethiopia, studies on the condition of water treatment plants and the risks they pose are scarce. Hence, this study was designed to evaluate the drinking water treatment plants of Jimma Town. The WatPro v4 simulation was used to evaluate the performance of the water treatment plant and disinfection. The results show that the treatment efficiency of the study was estimated to be 69.75%, while giardia and virus were reduced by 22.6% and 75.34%, respectively, and did not meet the requirements for surface water treatment. Furthermore, the contact time of the water system did not meet the contact time requirement (it should be great than one), but it was 0.476 for this study, and the current water distribution network and treatment plant of Jimma town were underperforming and did not provide adequate water to the various demand categories. Due to the poor performance of water treatment plants, the health and economic well-being of the majority of the population is seriously affected, and some people refuse to drink it, preferring to treat it at home instead. Disinfection of drinking water (chlorination) causes some to react with naturally occurring organic matter or waterborne diseases, while others exist as free chlorine or residual chlorine, producing the disinfection by-products (DBP), increased risk of bladder cancer and other human health effects. Therefore, the study strongly suggests that DBP and their precursors be removed following chlorination. We believe that the study provided new and updated insights on the treatment condition and DBP risk, which could aid decision-makers, planners and stakeholders in monitoring actions to reduce the health risks associated with DBPs in drinking water.

Statistical assessment for performance of Al-Mussaib drinking water treatment plant at the year 2020

Abstract Assessment of water quality is a major step in the water industry to ensure the suitability of water for human use. In this study, statistically evaluate the quality of raw and treated drinking water of the Al-Mussaib drinking water treatment plant, Babylon city, Iraq, from January to December 2020. Additionally, the water quality of treated water was assessed according to World Health Organization (WHO) and Iraqi standards for drinking water. The results showed the plant has a good efficiency in removing the studied parameters, such as alkalinity, calcium and hardness. It is noteworthy to mention that although the measured concentrations/levels met the WHO and Iraqi standards, they were higher than the favourable limits. For example, the measured sulphate concentration in the produced water was 248 mg/L, which is higher than the favourable concentration (200 mg/L) (WHO). The statistical analysis indicated significant differences between the quality of raw and treated water (p-value <0.05) in terms of turbidity, hardness, magnesium and dissolved solids concentrations, but there was no significant difference (p-value >0.05) in terms of alkalinity, pH, calcium and sulphates concentrations. The results of this work could be useful for water authorities and decision-makers in Iraq and national and international environmental agencies.

Assessment the performance of water treatment plants in Baghdad governorate using GIS

Water is essential to a solid society and feasible growth. Water demand is increasing due to increasing population density, fast urbanization, industrialization, and agriculture. The Tigris River supplies drinking water to nine water treatment plants in Baghdad, therefore monitoring their chemical and physical properties is important. 15 parameters (pH, Tur., TDS, EC, TH, Alk., Ca+2, Mg+2, Fe+2, Cl-, SO4-2, NH3, NO3-, NO2-, PO43) from treated water were measured in 2009 and 2019 and compared their values to Iraqi and WHO findings. The results show The value of turbidity in 2009 at center 8 was 11.2 which is exceeded the allowable limits this is might be absent the coagulation process, as well as the high concentration of the turbidity in the Tigris river at that time, meanwhile the value of alkalinity, was 159.75(mg/l) in 2019 at center 2 . however the remaining results were inside as far as possible.

Dual-stage attention-based LSTM for simulating performance of brackish water treatment plant

The remarkable increment in the demand for freshwater in water-resource-stressed regions increases the necessity of saltwater desalination and the application of a brackish water treatment plant (BWTP). In that respect, model-based process analysis can play an essential role in optimizing BWTP operation and maintenance (O&M) and reducing costs. In modeling, it is challenging for either theoretical or numerical methods to sufficiently account for the complex causality and various correlations among the numerous process parameters or variables in the BWTP system. Contrastively, deep learning approaches are capable of modeling such a BWTP system as it can describe the complexity and nonlinearity of its variables with robust autonomous learning. In this study, we modeled an RO unit process of BWTP using conventional long short-term memory (Conv-LSTM) and dual-stage attention-based LSTM (DA-LSTM) based on hourly time-series data obtained from the actual BWTP operation during a one-year period. Hyperparameter optimization for Conv-LSTM and DA-LSTM was individually conducted to enhance the model prediction performance. The model prediction results demonstrated the superiority of DA-LSTM (R2 > 0.99) over Conv-LSTM (0.531 ≤ R2 ≤ 0.884). The sensitivity analysis offered straightforward interpretations of how the attention mechanisms of DA-LSTM used time-series data of the model input and output parameters for prediction.

Deep Learning Based Approach to Classify Saline Particles in Sea Water

Water is an essential resource that facilitates the existence of human life forms. In recent years, the demand for the consumption of freshwater has substantially increased. Seawater contains a high concentration of salt particles and salinity, making it unfit for consumption and domestic use. Water treatment plants used to treat seawater are less efficient and reliable. Deep learning systems can prove to be efficient and highly accurate in analyzing salt particles in seawater with higher efficiency that can improve the performance of water treatment plants. Therefore, this work classified different concentrations of salt particles in water using convolutional neural networks with the implementation of transfer learning. Salt salinity concentration images were captured using a designed Raspberry Pi based model and these images were further used for training purposes. Moreover, a data augmentation technique was also employed for the state-of-the-art results. Finally, a deep learning neural network was used to classify saline particles of varied concentration range images. The experimental results show that the proposed approach exhibited superior outcomes by achieving an overall accuracy of 90% and f-score of 87% in classifying salt particles. The proposed model was also evaluated using other evaluation metrics such as precision, recall, and specificity, and showed robust results.

Evaluation of Regional Domestic Waste Water Treatment Plant Performance in Cimahi City

Domestic wastewater treatment plant performance (WWTP) currently refers to stringent wastewater quality standards (Minister of Environment and Forestry Regulation No. 68 of 2016) considering potential environmental degradation because of pollutants in the wastewater. This study evaluated the performance of the Regional Domestic WWTP in Cimahi City. Cimahi has 10 WWTPs which were operated by an Anaerobic Baffled Reactor system. Periodic monitoring only measured the wastewater characteristics after treatment with parameters: total suspended solids (TSS), ammonia, chemical oxygen demand(COD), biological oxygen demand(BOD), and oil and grease. Therefore, wastewater characteristics were measured before and after treatment at selected WWTP during peak and non-peak hours, with TSS, ammonia, and COD. Important hydraulic factors were also measured: flow velocity at peak and non-peak hours, hydraulic detention time, and sludge height. Effluent from all WWTPs did not meet the standard. However, WWTPs with detention time >2 days produced parameter concentrations closed to the maximum value. The selected WWTP has a 5.7days detention time with removal efficiency for COD 57.52%, and TSS 42.56%, during peak period and COD 60.19% and TSS 34.84% for a non-peak period, but ammonia concentration did not decrease. Overall, WWTP has not been able to meet quality standards and the quality.

Development of Bench Scale Water Treatment Unit for the Treatment of Medium Turbid Water: The Use of Natural Coagulant

Water purification is a process used to enhance water quality and make it more acceptable for specific end-use. The rising increase for portable drinking water has made natural coagulant application for water purification a welcome development. Most reported researches were on the use of natural coagulants in a laboratory batch scale. Because of those above, a bench-scale laboratory study was carried out on the application of Balanites Aegyptiaca seed as a natural coagulant. The outcome showed its usefulness toward water purification. This paper reported the developed bench-scale water treatment plant's performance utilising Balanites Aegyptiaca seed stock solution and the powdered kennel as bio-coagulant. Some design equations were adopted. The treatment units considered include coagulation/flocculation, sedimentation, and filtration. The total tank design capacity was 20 litres with the overflow area's actual size for sedimentation of 7.46 litres. 0.5 Hp electric motor with a speed of 600 rpm and a speed gear drop of 120 rpm were selected. 0.0127 m pipe flow line diameter connecting the tanks with a corresponding pipe flow velocity of 0.108 m/s was obtained from the design. However, in both the coagulation, sedimentation and filtration units, the material balance obtained showed a steadiness in the material flow across sedimentation and filtration units. However, among the parameters tested in the raw turbid water, the turbid water revealed turbidity of 514 NTU, the colour of 5600 CTU, the conductivity of 276 µs/cm, pH of 7.10 and total coliform bacteria count of 85 CFU/100 mL which were above the recommended set standard of WHO and NIS. The result of the treated water using the stock solution and the powdered kennel (bio-coagulant) on the developed water treatment unit showed a remarkable reduction in the tested parameters in the raw turbid water used for the treatment process. Total coliform count reduces from 85 CFU/100 ml to 10 CFU/ml in both cases. It was observed that conductivity increases after the treatment, but other inorganic constituents reduce significantly though not to WHO and NIS's recommended set standard. The 0-dosage treatment conducted also showed a reduction in all the tested parameters.

Risk Assessment of Water Treatment Plants Using Fuzzy Fault Tree Analysis and Monte Carlo Simulation

Urban water supply, transmission, and distribution systems are considered as the basic infrastructures of each community. Deficiency of water resources in system leads to lack of some subscribers’ access to safe water at any time. The water treatment units have a high potential for massive crisis and importance of sustainable performance in water treatment plants, due to their special role in high quantity and quality water supply even in critical situations, requires a comprehensive approach in assessing and increasing the reliability. A comprehensive approach in assessing the performance of water treatment plants and reducing their vulnerability can lead to cost reduction of inappropriate performance in critical situations and also a focus on the most important vulnerable parts of water treatment plants to decrease their vulnerability, as well as cost-effective budgeting in recovery programs. In this research, due to the uncertainties in the input information, two methods of fuzzy fault tree analysis (FFTA) and fault tree analysis (FTA) based on Monte Carlo simulation were evaluated in Jalaliyeh water treatment plant in Tehran, and results of both approaches were compared in terms of uncertainty analysis. The results indicate the low to moderate failure risk in the treatment plant in both approaches and a small difference between results in both cases. Failure probability of top event for FFTA and Monte Carlo-based FTA methods is 0.194 and 0.27, respectively. In the basic event rating, it was found that threats such as inappropriate reservoir design, power equipment failure, transfer pipe failure, and inappropriate maintenance of the pumps play the major role in treatment plant failure.

Applicability of statistical analysis for performance and reliability evaluation of large-scale water treatment plants with direct filtration systems.

Water treatment plants (WTPs) are extremely important in basic sanitation services because of their association with human health by producing safe drinking water. Thus, their proper operation is of utmost relevance and has led to the development of distinct performance evaluation methodologies. Direct filtration is a leading technology applied in WTPs. However, although it costs less than conventional treatment, it might also be less flexible and robust. To evaluate performance with data from real-scale WTPs with direct filtration systems, the use of a statistical analysis methodology for turbidity, apparent color, and pH data from raw and effluent water is proposed. Reliability analysis, a probabilistic-based methodology, was applied for turbidity alongside evaluating the compliance of the treated water with different potability standards. The parameters pH (between 6.0 and 8.0) and apparent color (< 15 HU) showed almost complete compliance (> 99%). Reliability analysis could not be applied for apparent color and pH, while apparent color did not adhere to the lognormal distribution frequency. The turbidity results show high variability in the coefficients of variation and reliability among various plants and a general difficulty in complying with stricter standards, such as the 0.1 and 0.3 NTU defined by the United States Environmental Protection Agency. All WTP studies show a 95% compliance with the World Health Organization standard of 5.0 NTU. A higher value for the coefficient of reliability and a lower value for the variation coefficient could indicate a more stable process, regardless of the treated water quality, highlighting the relevance of applying combined methods for performance evaluation, such as compliance with established standards.

Using excitation-emission matrix fluorescence to evaluate the performance of water treatment plants for dissolved organic matter removal

This study is aimed at assessing the performance of water treatment plants (both wastewater and drinking water treatment plants) for dissolved organic matter (DOM) removal using excitation-emission matrix fluorescence (EEMF) as the monitoring technique.The influent from the wastewater treatment plant (WWTP) of Burgos (Spain) is characterized from the presence of protein-like peaks (T1 and T2) and humic-like peaks (A and C), T2 and A showing the highest fluorescence intensity. The percentages of total removal in the effluent were in the following order: peak T1 (65%) > peak A (45%) > peak C (34%) > peak T2 (26%). The humic-like peaks were the most removed at the primary sedimentation stage, whereas peak T1 was by far the most removed in the biological reactor. Protein-like peaks T1 and T2 experienced a slight increase in the final effluent in comparison to their fluorescence at the previous stage (the exit of the biological reactor), an increase that can be explained by the release of SMP (soluble microbial products) from the biomass in the secondary clarifier. A poor correlation was obtained between peak T2 fluorescence and COD, BOD (r2 = 0.34–0.38).The natural water from the Úzquiza reservoir in Burgos (Spain) is characterized by the only presence of humic substances: a majority peak A (fulvic-like) and a weak peak C (humic-like). The whole fluorescent DOM was removed by coagulation-flocculation but a low fluorescence peak T2 appeared at the final stage, coming from protein-like SMPs released by the biomass attached to the filters.

Water purification from metal ions in the presence of organic matter using electromagnetic radiation-assisted treatment

Organic matter is a widely occurring pollutant in freshwater sources due to the extensive use of synthetic organic compounds in industry and the natural occurrence of organic matter in the Earth’s crust. Organic matter causes adverse effects on the performance of water treatment plants, such as accelerated bacterial growth and increased consumption of chemical coagulants. Organic matter also has the ability to chelate some heavy metals forming refractory complexes that resist coagulation. The current research combines electromagnetic radiation (microwave) and electrocoagulation technologies to purify water from OM-heavy metal complexes created using iron and ethylenediaminetetraacetic acid (EDTA). The organic matter-iron solution was introduced to a microwave field to break down the complex, followed by electrolysis of the solution using an aluminum-base EC cell. Microwave power (50.0–300.0 W), temperature (50.0–150.0 °C) and irradiation period (5.0–15.0 min) were measured. During the electrolysing stage, initial pH (4.0–8.0), current density (1.0–2.0 mA cm−2) and space between electrodes (5.0–20.0 mm), were examined. The results showed that the electromagnetic radiation-electrocoagulation technology removed up to 92% of the organic matter-iron complex in comparison to 69.6% removal using a traditional electrocoagulation method. The best operational conditions were established as follows: 10 min of microwave irradiation at 100 Wat a temperature of 100 °C, followed by 20.0 min of electrolysing at an initial pH of 6.0, the space between electrodes 5.0 mm and current density of 1.50 mA cm−2.

Evaluating the Performance of a Lab-Scale Water Treatment Plant Using Non-Thermal Plasma Technology

In this study, a lab-scale plant was designed to treat water in continuous flow condition using non-thermal plasma technology. The core was an electrode system with connected high-voltage (HV) pulse generator. Its potentials and limitations were investigated in different experimental series with regard to the high-voltage settings, additions of oxygen-based species, different volume flow rates, and various physical-chemical properties of the process water such as conductivity, pH value, and temperature. Indigo carmine, para-Chlorobenzoic acid, and phenol were chosen as reference substances. The best HV settings was found for the voltage amplitude Û = 30 kV, the pulse repetition rate f = 0.4–0.6 kHz, and the pulse duration tb = 500 ns with an energy yield for 50% degradation G50, which is of 41.8 g∙kWh−1 for indigo carmine, 0.32 g∙kWh−1 for para-Chlorobenzoic acid, and 1.04 g∙kWh−1 for phenol. By adding 1 × 10−3 mol∙L−1 of oxygen, a 50% increase in degradation was achieved for para-Chlorobenzoic acid. Conductivity is the key parameter for degradation efficiency with a negative exponential dependence. The most important species for degradation are hydroxyl radicals (c ≈ 1.4 × 10−8 mol∙L−1) and solvated electrons (c ≈ 1.4 × 10−8 mol∙L−1). The results show that the technology could be upgraded from the small-scale experiments described in the literature to a pilot plant level and has the potential to be used on a large scale for different applications.

Use environmentally friendly hydraulic power to design a hydraulic rapid mixing basin in the drinking water treatment plant

Most cities in Iraq provide drinking water by purifying river water of physical and chemical contaminants. It uses energy from petroleum (electricity). As it seeks to get drinking water from the rivers with clean and renewable technologies and energy, the State of Iraq plans to use one of its most abundant resources to address the shortage of fresh water, namely hydropower. This study is based on the use of hydraulic energy (environmentally friendly) in the purification of water instead of the use of electricity. The use of electrical energy in water purification has a lot of problems, including the continuous interruption of the current and therefore stop the station from work and that it needs periodic maintenance and need to staff specialized for operation and maintenance, so it is expensive while the use of hydraulic energy will help to solve most of these problems. The possibility of replacing the rapid-mechanical mixing basin to the rapid hydraulic mixing, which operates according to the principle of forced forexes, where the study of the performance of the drinking water treatment plant in the eastern district of Al-Hamzah On the ADiwaniyah River in the southern province of ADiwaniyah, where concentrations of pollutants in the river are high in the study area. Where samples were taken from different locations for water in the drinking water treatment plant of Al-Hamzah for different treatment stages. Where the pollutants were examined in the laboratories of the Environment Directorate of ADiwaniyah and the laboratories of the Faculty of Engineering. All concentrations of physical and chemical contaminants were higher than the standards of Iraqi standards and the efficiency of treatment was not as low as 83%. This is due to the continuous interruption of electrical current and the failure of the mechanical equipment of the rapid mechanical mixing basin, which requires periodic maintenance and the continuation of the addition of high coagulant doses which cause high processing costs as well as the high concentration of aluminum used for coagulation. Therefore, a hydraulic mixing basin was used by conducting experiments in the fluid laboratory In the Faculty of Engineering using the Free and Forced Vortex, which has been developed and adjust suit the requirements of the study. There have been various experiments to obtain the best dimension of hydraulic mixer and best amount of coagulant to remove the turbidity and the best mixing speed and the best value of the pH, which achieved processing efficiency of up to 98.0%.