Opportunity
Alberta Purchasing #27TDRWCE815
Water Demand Forecasting Model Development for Alberta's South Saskatchewan River Basin
Posted
May 28, 2026
Respond By
June 18, 2026
Identifier
27TDRWCE815
NAICS
541511, 541690
The Government of Alberta's Environment and Protected Areas agency is soliciting proposals for a comprehensive water demand forecasting solution for the South Saskatchewan River Basin (SSRB): - Government Buyer: - Alberta Environment and Protected Areas agency - Contracting office located in Calgary, Alberta - Products/Services Requested: - Development of an integrated, watershed-scale Water Demand Forecasting Model (WDFM) - Model must be built on the GoldSim platform - Incorporation of machine learning (ML) and artificial intelligence (AI) for predictive modeling - Sector-specific forecasting for municipal, irrigation, stock watering, industrial, and commercial water use - Modular and flexible design to support diverse assumptions and scenario analysis - Unique/Notable Requirements: - Strict adherence to the Recommended Model Framework detailed in the solicitation appendix - Use of advanced ML/AI techniques for model training and testing - No specific OEMs or vendors are named; open to qualified solution providers - Place of Performance: - Work to be performed in Alberta, with the contracting office in Calgary - No product part numbers or quantities specified, as this is a custom development project
Description
This solicitation is a request for proposals to develop an integrated watershed-scale Water Demand Forecasting Model (WDFM) for the South Saskatchewan River Basin in Alberta. The model will support water availability efforts by simulating and forecasting water demands across various sectors, including municipal, irrigation, stock watering, industrial, and commercial uses. The project involves building, training, and testing machine learning and artificial intelligence models for each sector using available datasets. The model will be modular and flexible, designed to incorporate diverse assumptions and scenarios for sector-specific water demand estimates.