Guidance on large scale hydrologic model calibration with isotope tracers

Abstract

Standard hydrologic model evaluation and calibration approaches focus on the accurate simulation of streamflow, disregarding internal process simulations. Stable isotope tracers can provide additional information on water sources, and process flux and storage, which can be used to inform model calibration. This study assesses the added value of isotope data in comparison to current best-practice flow-only calibration methods and evaluates the merits and limitations of isotope simulation performance metrics for the purposes of hydrological model calibration. Following several years of regular isotope sampling and measurement, an isotope-enabled process-based hydrologic model was tested on a large watershed in western Canada (Athabasca River), which allowed model calibration using global sensitivity analyses, Monte Carlo simulations, and multi-objective optimizations. Isotope tracer data were found to improve both process and streamflow component identifiability and produced some minor improvement in individual parameter value identifiability. Calibrating to optimize both flow and isotope simulation performance produced better flow simulation ensembles, with improved observation capture and validation performance, relative to calibrating to optimize flow simulations alone. Using an isotope simulation performance metric which includes timing error as a secondary optimization objective led to more robust streamflow modeling, even in mesoscale watersheds with limited isotope observation datasets.