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Suresh Babu Parasuraman

Suresh Babu Parasuraman
Kalingu Consultancy

Ph.D., M.E., B.E. (civil engg)

About

13
Publications
18,385
Reads
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244
Citations
Citations since 2017
1 Research Item
150 Citations
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2017201820192020202120222023051015202530
2017201820192020202120222023051015202530
2017201820192020202120222023051015202530
Introduction
Dr. P. Suresh Babu is currently heading the Water Resources Section (Team of 7+) since 1 Jan 2013 after Joined DHI in Nov 2010. His primary research interests with 14+ years of experience, include Urban Planning and Water Management, Surface Water and Ground Water Hydrology, Urban Flood Modelling, Monitoring and Management, Flood Risk Assessments, Remote Sensing, GIS, and Water Quality Monitoring and Modelling.
Additional affiliations
December 2017 - present
Kalingu Consultancy
Position
  • Managing Director
Description
  • Owner of the Consulting Company registered in Singapore http://www.kalinguconsultancy.com
November 2010 - February 2018
DHI Water & Environment (S) Pte Ltd
Position
  • Head (Water Resources Section)
Description
  • Heading the Water Resources Section in the DHI Singapore office
December 2006 - October 2010
Public Utilities Board (PUB) Singapore
Position
  • Engineer/Hydrologist
Description
  • Hydraulic and hydrologic modelling, reservoir water quality modelling.
Education
July 2003 - September 2006
College of Engineering Guindy, Anna University, Chennai, India
Field of study
  • Civil Engineering
December 1999 - September 2001
Centre for Water Resources, Anna University, Chennai, India
Field of study
  • Hydrology and Water Resources Engineering
January 1995 - December 1999
University of Madras, Chennai, India
Field of study
  • Civil Engineering

Publications

Publications (13)
Article
Singapore has adopted a low impact development equivalent of stormwater management philosophy under a national program called ‘Active, Beautiful and Clean’ (ABC) employing soft-engineering techniques to manage rainfall runoff in the face of climate change and rapid urbanisation. This study makes use of the MIKE URBAN modelling tool to evaluate the...
Article
Full-text available
The present study enhances the Soil Conservation Service curve number (SCS-CN) predictions by improving the model structure, considering the following issues of concern: implementation of antecedent moisture condition procedure, fixation of initial abstraction ratio (lambda) at 0.2, usage of the potential maximum retention parameter, and incorporat...
Article
The available antecedent moisture condition (AMC)-dependent runoff curve number (CN) (SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10, Soil Conservation Service, USDA, Washington, DC, 1956) conversion formulae due to Sobhani (M.S. Thesis, Utah State University, Logan, UT, 1975), Hawkins et al. (J Irrig Drain Eng, ASCE 111:33...
Article
Full-text available
Incorporating the storm duration and a nonlinear relation for initial abstraction (I-a), this paper presents an enhanced version of the Soil Conservation Service curve number-based Mishra-Singh model. The proposed version is compared with existing formulations using a large set of storm rainfall-runoff events derived from the water database of the...
Article
Full-text available
The initial abstraction (I-a) versus maximum potential retention (S) relation in the Soil Conservation Service Curve Number (SCS-CN) methodology was revisited, and a new non-linear relation incorporating storm rainfall (P) and S was proposed and tested on a large set of storm rainfall-runoff events derived from the water database of United States D...

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Projects

Projects (2)