On-demand streamflow projections in the context of the Covid-19 pandemic – RES0054182

The streamflow forecasting tool proposed here will automate data collection and processing for machine learning (data-driven) models by querying online databases from Alberta Agriculture and the National Oceanic and Atmospheric Administration (NOAA), and then using the received data to predict the current year’s average monthly and seasonal streamflow with minimal input from users. Of relevance during Covid-19, the proposed web-based tool will ensure rapid, online and “on demand” delivery of monthly and seasonal streamflow forecasts for irrigation districts, provincial agencies and other stakeholders. Previously, predictions were delivered in-person in workshops or through infrequent individual emails. From a business perspective, access to the online streamflow projection tool will be combined with access to a powerful reservoir management model called WEB.BM (Optimal Solutions Ltd.), which will provide beneficial exposure to both products. The PhD student will learn about water resources planning and management at a river basin scale, data-driven modeling, and developing web-based forecasting tools. Further, through collaboration with our partner organization and user community, the PhD student will be well prepared for interdisciplinary water resources management, water policy and academic work, which – like Alberta with its Water for Life strategy – are moving towards an interdisciplinary, integrated watershed management approach.

Faculty Supervisor:

Evan Davies

Student:

Partner:

Optimal Solutions Ltd

Discipline:

Engineering

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Alberta

Program: