NJS Leverages Bentley Systems’ SewerGEMS to Design an 800 KM Sewer Network in Varanasi, India
NJS Engineers leverage Bentley Systems’ SewerGEMS to design an 800-kilometer sewer network in Uttar Pradesh, India.
Located on the Ganga River, the ancient city of Varanasi discharges 67 percent of its sewerage directly into the river and its tributary, resulting in significant pollution. Uttar Pradesh Jal Nigam, the government corporation responsible for water supply and sewerage services in the state of Uttar Pradesh, India, retained NJS Engineers India to participate in an INR 4.96 billion project to construct new and rehabilitate existing sewerage treatment facilities to improve the quality of sanitation while simultaneously boosting tourism.
NJS Engineers India leveraged Bentley software to develop the rehabilitation and improvement plan, and perform design review, construction supervision, and operations planning. A GIS-based spatial database of assets was developed, and SewerGEMS was used to review the design of the sewer system. Bentley’s interoperable software provided a platform for exchanging and updating spatial, non-spatial, and engineering data and models with global team members.
Using Bentley software, the engineering team was able to develop an optimal design for the new, 800-kilometer sewer network while saving 60 resource hours and reducing the number of large-scale drawings produced by 30 percent. The new sewer network will improve the water quality of rivers and tributaries, which will ultimately enable a higher quality of life for people living in the area, as well as encourage more tourism, improve irrigation, and increase employment opportunities.
The project team automatically created hydraulically coherent models from CAD drawings by using SewerGEMS’ Network Navigator to discover model problems, such as dead-end pipes. SewerGEMS was also instrumental in the analysis of the new sewer network. For example, using the scenario management functionality, managers analyzed various design and operation what-if scenarios improving the decision-making process.