Short-term streamflow forecasting for the Oldman River

The proposed research project aims to develop accurate and user-friendly models to forecast daily streamflow for the Oldman River in Alberta. This project will involve using advanced machine learning methods, such as Artificial Neural Networks (ANNs), Extreme Gradient Boosting (XGBoost), and Long Short-Term Memory (LSTM), to improve the reliability of streamflow predictions. By enhancing the ability to predict river flow, this research will support better water resource management, including optimizing reservoir operations and flood control. The final outcome will include an interactive web application that automates data collection and updates forecasts in real-time, making it accessible for decision-makers who do not have specialized knowledge.

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: