Oxygen-18 and deuterium were measured in streamflow samples collected from 331 gauging stations across Canada during 2013 to 2019. This dataset includes 9206 isotopic analyses made on 4603 individual water samples, and an additional 1259 analysis repeats for quality assurance/quality control. We also include arithmetic and flow-weighted averages, and other basic statistics for stations where adequate data were available. Station data are provided including station code, name, province, latitude, longitude and drainage area. Flow data were extracted from the historical database of the Water Survey of Canada. Details on the preliminary application of these data are provided in “ 18 O and 2 H in streamflow across Canada” [1] . Overall, these data are expected to be useful when combined with precipitation datasets and analytical or numerical models for water resource management and planning, including tracing streamflow source, water balance, evapotranspiration partitioning, residence time analysis, and early detection of climate and land use changes in Canada.

Funding and in-kind support for analytical costs and logistics was provided by Environment and Climate Change Canada via a Grants and Contributions Agreement and by InnoTech Alberta via an Internal Investment Grant.

Accurate representation of flow sources in process‐based hydrologic models remains challenging for remote, data‐scarce regions. This study applies stable isotope tracers (18O and 2H) in water as auxiliary data for the calibration of the isoWATFLOOD™ model. The most efficient method of those evaluated for introducing isotope data into model calibration was the PA‐DDS multiobjective search algorithm. The compromise solutions incorporating isotope data performed slightly inferior in terms of streamflow simulation compared to the calibrated solution using streamflow data only. However, the former solution outperformed the latter one in terms of isotope simulation. Approximation of the model parameter uncertainty into internal flow path partitioning was explored. Inclusion of isotope error facilitated a broader examination of the total parameter space, resulting in significant differences in internal storage and flow paths, most significantly for soil storage and evapotranspiration loss. Isotope‐optimized calibration reduced evaporation rates and increased soil moisture content within the model, impacting soil water velocity but not streamflow celerity. Flow‐only calibration resulted in artificially narrow model prediction bounds, significantly underestimating the propagation of parameter uncertainty, while isotope‐informed calibrations yielded more reliable and robust bound on model predictions. Our findings demonstrate that the accuracy of a complex, spatially distributed, and process‐based model cannot be judged from one summative flow‐based model performance evaluation metric alone.

Calibration of hydrological models is challenging in high-latitude regions where hydrometric data are minimal. Process-based models are needed to predict future changes in water supply, yet often w...