We propose to develop a new statistical model to assist agencies responsible for managing the Canadian-origin Chinook salmon (Oncorhynchus tshawytscha) stock in meeting objectives outlined in the Yukon River Salmon Agreement. This new model will improve upon and seamlessly integrate existing preseason forecast and inseason run projection models within a unified Bayesian statistical framework. Our approach will use a process whereby preseason expectations of total run size can be updated in real-time based on available stock-specific information collected inseason. A Bayesian updating model, like the one we propose to develop, addresses the challenge management agencies face when deciding how and when to transition from making management decisions based on preseason information to decisions based on inseason information. By approaching this challenge though an integrated modeling framework, management agencies will benefit from inseason projections that are transparent, objective, reproducible, statistically defensible, and address uncertainty in ways that explicitly assist with fishery management decisions.