VIRTUAL EVENT from MAY 11 to 14 2021

Given the global and local situation related to COVID-19, the CIGR 2020 Local Organizing Committee has decided to hold the event in virtual mode from May 11 to 14, 2021. We are currently in the development phase of the virtual program.


Guidelines to transfer your abstract

Register  now

You have until April 10, 2021 to transfer your contribution and register to the conference to secure your place in the program. See our Continuity plan for more information about contributions and registrations transfer. NO NEW SUBMISSION WILL BE ACCEPTED.

Instructor: Dr. Prasad Daggupati
School of Engineering, University of Guelph, Canada

Date (Part 1): Thursday May 20, 2021. 10:00 am to 2:00 pm EDT
Date (Part 2): Friday May 21, 2021. 10:00 am to 2:00 pm EDT
Location: Online
Language: This workshop will be in english
Cost: see Registration

Workshop description:

The Soil & Water Assessment Tool (SWAT) is a basin scale hydrological model developed to quantify the impacts of different land management practices in large, complex watersheds. SWAT is a public domain model and is actively supported by USDA Agricultural Research Service, and Texas A& M University, USA. The model accounts multiple hydrological and water quality components such as: weather, surface runoff, return flow, percolation, evapo-transpiration, transmission losses, pond and reservoir storage, crop growth and irrigation, groundwater flow, reach routing, nutrient and pesticide loading, and water transfer. The various application of SWAT has been noted throughout the globe, as is evident by the number of peer-reviewed articles till 2019 (>3500).

The workshop is expected to provide an overview (approx. 20%) and a hands-on session (approx. 80%) of state-of-the-art SWAT (SWAT2012) model to academicians and practitioners in hydrology, watershed management, water resources engineering and agricultural water quality management. In this workshop, we will be demonstrating QSWAT which is a QGIS (open source, publicly accessible) plugin that enables us to run SWAT through a GIS desktop/ interface

What will be delivered?

  • An overview of hydrological models (Theory)
  • An overview on the various applications of SWAT (Theory)
  • Introduction to QSWAT interface (Hands-On/Theory)
  • Watershed delineation using Q-SWAT (Hands-On)
  • Landuse, soil overlay and delineate Hydrological Response Units (HRUs) (Hands-On)
  • Weather/weather generator and remaining inputs (including point sources) to develop SWAT model (Hands-On)
  • SWAT simulations and saving results (Hands-On)
  • Visualization and interpretation of SWAT outputs (Hands-On)

Who can attend?

Anyone who wants to learn about SWAT model can attend the workshop. However, the prospective participants are expected to have a working knowledge (loading vector and raster maps, panning, zooming, selecting features) of QGIS. We will not have time to review basic concepts of QGIS. Please note that the participants should bring their own laptops with minimum specifications as described in following section.

Technical requirements:

Participants are requested to bring their own laptops (Windows 10 OS, Microsoft .Net Framework 3.5, at least 4GB RAM, 20GB free hard disk space, Adobe Reader, Microsoft Office with MS ACCESS. Please go the SWAT model website ( and install the following software before training:

  • QGIS (QGIS Brighton 2.6)
  • QSWAT 1.9
  • SWAT Editor 2012.10.18

About the instructor

headshot daggupatiDr. Daggupati is an Assistant Professor (Water Resource Engineering) in the School of Engineering at the University of Guelph, Canada. He received his BS degree (2012) from the College of Agricultural Engineering in India, Masters (2007) and Ph.D. (2012) degrees from Kansas State University in USA. He worked as a Post-Doctoral Research Associate and Assistant Research Scientist at Texas A&M University, USA before joining the University of Guelph. Dr. Daggupati’s major contributions to research and practical applications are towards solving emerging water quality and quantity issues using GIS, hydrological modeling, machine learning, and field experimentation at various scales (e.g. field scale, watershed scale) across multiple countries around the world. 

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