Examining the impacts of precipitation isotope input (δ18Oppt) on distributed, tracer-aided hydrological modelling

• Published in: Hydrology and Earth System Sciences
• Main Authors: C. J. Delavau, T. Stadnyk, T. Holmes
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2017
• Subjects: geo; envir; Canada; Fort Simpson; Klaus
• Online Access: https://doi.org/10.5194/hess-21-2595-2017; http://www.hydrol-earth-syst-sci.net/21/2595/2017/hess-21-2595-2017.pdf; https://doaj.org/article/6625f26a53844910be45412169ee4cbf

Tracer-aided hydrological models are becoming increasingly popular tools as they assist with process understanding and source separation, which facilitates model calibration and diagnosis of model uncertainty (Tetzlaff et al., 2015; Klaus and McDonnell, 2013). Data availability in high-latitude regions, however, proves to be a major challenge associated with this type of application (Tetzlaff et al., 2015). Models require a time series of isotopes in precipitation (δ18Oppt) to drive simulations, and throughout much of the world – particularly in sparsely populated high-latitude regions – these data are not widely available. Here we investigate the impact that choice of precipitation isotope product (δ18Oppt) has on simulations of streamflow, δ18O in streamflow (δ18OSF), resulting hydrograph separations, and model parameters. In a high-latitude, data-sparse, seasonal basin (Fort Simpson, NWT, Canada), we assess three precipitation isotope products of different spatial and temporal resolutions (i.e. semi-annual static, seasonal KPN43, and daily bias-corrected REMOiso), and apply them to force the isoWATFLOOD tracer-aided hydrologic model. Total simulated streamflow is not significantly impacted by choice of δ18Oppt product; however, simulated isotopes in streamflow (δ18OSF) and the internal apportionment of water (driven by model parameterization) are impacted. The highest-resolution product (REMOiso) was distinct from the two lower-resolution products (KPN43 and static), but could not be verified as correct due to a lack of daily δ18Oppt observations. The resolution of δ18Oppt impacts model parameterization and seasonal hydrograph separations, producing notable differences among simulations following large snowmelt and rainfall events when event compositions differ significantly from δ18OSF. Capturing and preserving the spatial variability in δ18Oppt using distributed tracer-aided models is important because this variability impacts model parameterization. We achieve an understanding of tracer-aided modelling and ...