https://gwf.usask.ca/projects-facilities/all-projects/p1-model-uncertainty.php

This project attempts to leverage stable water isotope (SWI) data for the development of a methodology and monitoring network to aid in our understanding hydrological processes in large river basins. SWIs (δ18O, δ2H) have proven to be useful diagnostic variables for hydrological modelling, with some uncertainty as to the degree of usefulness in parameter constraint estimation. There is a need to quantify the effectiveness of isotope data from large scale monitoring networks, applied in conjunction with observed streamflow data, to enhance hydrologic model calibration and optimization. The benefit, should such soft data methods prove successful, would be enhanced knowledge of model parameter uncertainty, and more realistic parameterization of hydrologic models, and such methods could prove especially value in modelling the cold, vast and complex pan-Canadian watersheds.