Short Term Course on Urban Flood Modeling- 2016

Water & Environment Division, Department of Civil Engineering, National Institute of Technology organised a short-term course on ‘Urban Flood Modelling’ during November 21-26, 2016. This course was organised as an outreach activity of the project titled ‘Integrated Urban Flood Management in India: Technology Driven Solutions’ sponsored by Information Technology Research Academy (ITRA), Ministry of Information and Technology, Government of India. The short term course comprised of lectures and tutorials on following topics.

Analysis of meteorological data and development of IDF curves

  • Remote Sensing and GIS applications in urban flooding
  • Urban hydrological models including SWMM and MIKE-Urban, MIKE-Flood and HEC-RAS
  • Design of drainage systems
  • Management of storm water
  • Water Quality Issues in Urban Storm water Management

In addition to the faculty members of NIT, Warangal, experts from IISc, Bangalore, BITS Pilani Hyderabad Campus and NRSC, Hyderabad delivered lectures during the course. Laboratory sessions were also arranged to give the participants hands on experience on the relevant software and methodologies. The course targeted at young faculty members and researchers from academic institutions and practicing engineers.

About 30 participants from different backgrounds including Scientist from NIH Roorkee, IMD Kakinada,CSIR-NEERI, Nagpur, Engineer from WAPCOS Ltd., Faculty members from various private engineering colleges and graduate and research scholars from different premium educational institutes such as VNIT Nagpur, NIT Raipur and VIT University partaken in the short-term course. Lectures were conducted in the Seminar Hall, Department of Civil engineering and laboratory sessions were conducted in the Water Resources computer lab and Remote Sensing and GIS lab, Department of Civil engineering.

List of lectures and laboratory sessions conducted during the short-term course is as follows.

A glimpse of the short term course is shown below.