Summer-season streamflow prediction model for the Oldman River Basin

Reliable monthly and seasonal streamflow predictions are essential for optimal planning of water resources, particularly for reservoir operation and planning applications. Streamflow predictions can also improve water use efficiency and provide early drought and flood warning. The importance of streamflow forecasting is rising with climate change, causing more frequent and hazardous flood and drought events. Current streamflow forecasts in the Oldman River Basin are uncertain, which poses a risk to irrigators, who rely on them to plan for the next irrigation season.
Our project aims to develop machine learning models for reliable summer-season and monthly streamflow predictions in the Oldman River Basin of Alberta. We will also study the risks associated with issuing predictions earlier in the year, up to three months ahead of the irrigation season. Reliable summer-season streamflow predictions in Alberta can help water managers and stakeholders make better-informed decisions on seasonal water allocation, flood and drought mitigation strategies, and environmental flow management.

Faculty Supervisor:

Evan Davies

Student:

Amr Gharib

Partner:

Optimal solutions

Discipline:

Engineering - civil

Sector:

Professional, scientific and technical services

University:

University of Alberta