Performance and reliability analysis of a multi-stage filtration (MSF) system in the treatment of urban pond water: a case study of kolkata city

Abstract

This research evaluates the critical missing data optimization during water filtration. The research offers valuable insights for improving water quality and managing excess parameters in this location. Filtration constitutes a fundamental component of most water treatment systems, with filtration emerging as a novel and promising method for filtering potable water in developing regions. This research Optimization by providing a detailed analysis of interpolation methods for handling missing turbidity data and their implications for Multi-Stage Filtration processes. It mainly explores the application of interpolation techniques (Linear Interpolation) to address the issue of missing turbidity data in Filtration Model. Turbidity, a key parameter in assessing water quality, often suffers from incomplete data sets due to Missing data, data transmission errors, or other disruptions. Missing data can significantly impact the accuracy of water quality assessments and subsequent decision-making processes. The study integrates this interpolation approach with a filtration model that employs a Multi-Stage Filtration system, incorporating a Slow Sand Filter as a key component. The study found that the SSF model was effective in removing turbidity, with an overall removal efficiency of about 91%. The study also highlighted the importance of sand depth in increasing the removal efficiency of the SSF model. Based on the findings, a field-scale SSF unit was designed for a critical point identified in the study. Future research could also explore the integration of interpolation with advanced statistical and machine learning techniques to further enhance the accuracy and robustness of missing data estimation. Water samples were collected daily from both the inlet water tank and outlet pipe for laboratory analysis parameters such as Turbidity, pH, TDS, DO etc. Jadavpur University Jheel’s water is highly contaminated in high turbidity which may have effects on the health of local inhabitants and aquatic ecosystems, which is almost removed in Multi Stage Filtration Model. interpolation proves to be an indispensable tool for handling missing data, and its significance in future studies cannot be overstated so the study concludes that Interpolation is the best process if any of day’s data are missing or disrupt.