Bids Are Invited For Water Demand Forecasting Model For The South Saskatchewan River Basin in Canada

Work Detail

This Project Is To Develop An Integrated Watershed-Scale Water Demand Forecasting Model (Wdfm) For The South Saskatchewan River Basin (Ssrb) Of Alberta. The Wdfm Will Support Environment And Protected Areas Efforts To Enhance Water Availability For Albertans By Accurately Simulating And Forecasting Water Demands For And Across Various Sectors. The Model Will Facilitate Timely Demand Estimation For Operational Planning, Particularly During Drought Conditions, And Will Inform Long-Term Strategies Through The Incorporation Of Climate Change Impact Scenarios And Other Factors Influencing Water Demand And Usage. The Model Will Be A Basin-Wide, Multi-Sector Water Demand Forecasting Model For The Region.Phase I Of The Project Involved A Comprehensive Review And Evaluation Of Alternative Approaches For Wdfm Development. The Assessment Concluded That No Single Model Could Fully Address The Complex Water Demand Forecasting Needs Of The Ssrb. Consequently, A Hybrid Approach, Leveraging The Strengths Of Multiple Modeling Techniques, Was Identified As The Most Effective Solution. The Recommended Model Framework For The Wdfm Is Thus Designed To Be Modular And Flexible, Enabling The Incorporation Of Diverse Assumptions And Scenarios To Generate Sector-Specific Water Demand Estimates Using The Most Appropriate Methodology For Each Sector.This Request For Proposals (Rfp) Seeks The Development Of The Ssrb Wdfm Utilizing The Goldsim Platform, In Accordance With The Recommended Model Framework Detailed In Appendix B, Subsection 3. This Project Will Explore The Application Of Machine Learning (Ml) And Artificial Intelligence (Ai) Techniques To Build Predictive Water Demand Models For Key Sectors, Including, But Not Limited To, Municipal, Irrigation, Stock Watering, Industrial, And Commercial Uses. The Scope Of Work Encompasses The Building, Training, And Rigorous Testing Of At Least One Ml/Ai Model For Each Identified Water Use Sector, Drawing Upon Available Datasets.

Contact Information