We consider the problem of determining water withdrawal depth in water supply reservoirs with multilevel intakes in an effective and systematic manner. In the traditional way, operators decide which intake port to use based on their own experience and water samples taken from various depths. Our goal is to provide assistance to operators in the decision-making process and establish a systematic approach for determining the appropriate water withdrawal level in a stratified reservoir. To achieve this, we propose an algorithmic approach as a decision support system for estimating the water withdrawal level. We validate our approach using long-term data collected from a water supply reservoir and compare the results with those of the operator's decisions. The results reveal that when the depth tolerance is set to 10 m, the approach and operator's decisions match at an 80% rate. However, when the depth tolerance is increased to 15 m, the matching percentage improves to over 90%.

Particle capture, head loss development, and efficiency of in-line coagulation in contact filtration were studied using two types of laboratory filters with varying coagulants. One filter consisted of sand and anthracite, whereas the other filter contained crushed glass and anthracite. Effects of in-line coagulation on filter performance were evaluated using a charge measuring device. Performance of filters was monitored in terms of effluent quality as a function of time and development of head loss by anthracite layer and by the entire filter bed. Filterability index was used to provide a measure of effectiveness of filter media and/or operational variables such as coagulant type and dosage. This study found that the crushed glass–anthracite filter was as effective at removal of particles and metals (Fe and Al) as sand–anthracite filters.

Determining optimum withdrawal depth for selective water withdrawal is crucial for managing the water quality of withdrawn water or reservoir. In this paper, we consider non-stratified periods, relatively less studied, and develop an algorithmic decision-making system based on water quality index. Our approach takes three inputs (depth profile data, current withdrawal depth, and weights in water quality index) and determines the water withdrawal depth. Finding the weights associated with these parameters in the index is formulated as an optimization problem in which the matching between our recommended depth and operator’s decision is maximized. Historical operator decisions over a 14-year period from a real water treatment plant were used to optimize these weights. We utilized surrogate optimization, genetic algorithm, pattern search, and brute-force solvers for this optimization problem. Brute-force solver achieved a 93.8% matching accuracy in predicting the water withdrawal depth. As the other three solvers require an initial solution, which can influence the quality of their results, the brute-force solver was selected as the most reliable approach. Our approach accurately predicts the decisions made by water treatment plant operators regarding water withdrawal from a reservoir with a multi-level intake structure during periods without thermal stratification.

In this study, we experimentally investigate the production and characterization of CaCO3 particles through the carbonation process of Ca(OH)(2) and evaluate their potential application in removing organic matter. The CaCO3 particles were characterized using BET, SEM-EDX, FT-IR, particle size, and XRD techniques. Adsorption of organic matter was studied using synthetic solutions and samples from two surface water sources. Experiments were conducted at room temperature with adsorbent dosages ranging from 1.3 to 21.5 g/L, initial dissolved organic carbon concentrations between 2.5 and 20 mg/L (initial loading: 0.1-14.6 mgDOC/gCaCO(3)), and a contact time of at least 5 minutes. We observed a removal efficiency of 70-80% for DOC and 90-95% for UV254 at a low concentration of organic matter (humic acids, 2.5 mgDOC/L). At a concentration of 5.0 mg DOC/L, we achieved (i) 70-90% DOC removal for humic acid, (ii) 50-65% DOC removal for one surface water sample with SUVA(254) of 2.4 L/mgm, and (iii) 20-35% DOC removal for another surface water sample with SUVA(254) of 4.3 L/mgm. Furthermore, we investigated the performance of the prepared particles in repeated usage for organics removal. In conclusion, our findings propose areas for future research including optimizing particle cycling within the reaction environment, exploring particle utilization in reactors such as an up-flow particle bed, and assessing potential applications in a membrane contactor. The environmentally friendly and non-toxic nature of CaCO3 particles emphasizes their significance in future research and applications.

In this research the adsorption of organic matter onto calcium carbonate (CaCO₃) nanoparticles was studied. CaCO₃ nanoparticles were prepared by purging CO₂ gas into lime slurry. Progress of the reaction was monitored by online measurement of pH and conductivity. Prepared particles were contacted with organic matter synthetic solutions. Organic matter removal rates during adsorption were higher in samples with a high initial organic matter concentration. This result would be a promising solution strategy for the problem of management of flows collected in the treatment concentrates of membrane filtration plants.