Real-Time Flood Forecasts using Parallel Cloud Computing and Intelligent Algorithms

This research project will develop a state-of-the-art web-based Decision Support System (DSS) for operational forecasting and visualization of flood extents (via interactive maps and plots) in watersheds in Ontario and across Canada. The proposed DSS, called ISWMS-Smart, is an extension of the ISWMSTM system, developed by the GREENLAND Group (Industry Partner). ISWMS-Smart will efficiently generate accurate short-term flood forecasts by i) using Environment Canada’s open weather forecast data as input, and ii) feeding this weather data into sophisticated hydrologic and hydraulic models. These sophisticated models would then run on supercomputers to quickly generate and visualize flood forecasts for early flood warning and mitigation. Given the rise in extreme events due to Climate Change, the envisioned ISWMS-Smart is a valuable flood warning tool that may be used by GREENLAND to provide timely and accurate flood forecast information services to relevant governments and decision makers in Canada and across the globe.

Faculty Supervisor:

Prasad Daggupati

Student:

Taimoor Akhtar

Partner:

Greenland International Consulting

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Guelph