Simulating the performance of Kerbala wastewater treatment plant using GPS-X

Abstract The treatment process in sewage plants is applied to wastewater to improve its quality for multi-purpose uses. Sewage treatment plants are designed to treat wastewater under different conditions. The Karbala Main Wastewater Treatment Plant is one of the largest wastewater treatment plants in Iraq, designed to handle a discharge of 100,000 cubic meters per day. It can serve up to two million people and accommodate the city’s population growth. The station also operates with modern treatment systems (tertiary treatment) and an electronic command and control system. The study aims to develop a simulation model for the main wastewater treatment plant in Karbala. The model includes calibration and analysis of data from the plant’s inputs and outputs, such as biological oxygen demand, chemical oxygen demand, the amount of suspended matter, phosphorus, nitrogen, and discharge value. The results showed that the model predicts the quality of treated water through the station’s output values. After entering the actual values of chemical oxygen demand with the discharge value and adjusting the practical fractional values, the output values show a clear sensitivity to the input values, especially the COD value on the station’s outputs from BOD and TSS, which helps to understand the performance and improve the system.

Authors

Institutions

Publication Details

Journal
IOP Conference Series Earth and Environmental Science
Published
2024-08-01
DOI
https://doi.org/10.1088/1755-1315/1374/1/012064
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulating the performance of Kerbala wastewater treatment plant using GPS-X

Basim K. Nile, Muhammad Abduredha, Sara Galb Salman
IOP Conference Series Earth and Environmental Science
Water Quality Monitoring Technologies
article

Simulating the performance of Kerbala wastewater treatment plant using GPS-X

Basim K. Nile, Muhammad Abduredha, Sara Galb Salman
article en

Abstract

Abstract The treatment process in sewage plants is applied to wastewater to improve its quality for multi-purpose uses. Sewage treatment plants are designed to treat wastewater under different conditions. The Karbala Main Wastewater Treatment Plant is one of the largest wastewater treatment plants in Iraq, designed to handle a discharge of 100,000 cubic meters per day. It can serve up to two million people and accommodate the city’s population growth. The station also operates with modern treatment systems (tertiary treatment) and an electronic command and control system. The study aims to develop a simulation model for the main wastewater treatment plant in Karbala. The model includes calibration and analysis of data from the plant’s inputs and outputs, such as biological oxygen demand, chemical oxygen demand, the amount of suspended matter, phosphorus, nitrogen, and discharge value. The results showed that the model predicts the quality of treated water through the station’s output values. After entering the actual values of chemical oxygen demand with the discharge value and adjusting the practical fractional values, the output values show a clear sensitivity to the input values, especially the COD value on the station’s outputs from BOD and TSS, which helps to understand the performance and improve the system.

IOP Conference Series Earth and Environmental ScienceVol. 1374(1)
University of Kerbala (IQ)
Clean water and sanitation
Openalex Percentile: Top 72%
Water Quality Monitoring Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.