Resumen
Using d18O and d2H in mean transit time (MTT) modeling can ensure the verifiability of results across catchments. The main objectives of this study were to (i) evaluate the d18O- and d2H-based behavioral transit time distributions and (ii) assess if d18O and d2H-based MTTs can lead to similar conclusions about catchment hydrologic functioning. A volume weighted d18O (or d2H) time series of sampled precipitation was used as an input variable in a 50,000 Monte Carlo (MC) time-based convolution modeling process. An observed streamflow d18O (or d2H) time series was used to calibrate the model to obtain the simulated time series of d18O (or d2H) of the streamflow within a nested system of eight Prairie catchments in Canada. The model efficiency was assessed via a generalized likelihood uncertainty estimation by setting a minimum Nash?Sutcliffe Efficiency threshold of 0.3 for behavioral parameter sets. Results show that the percentage of behavioral parameter sets across both tracers were lower than 50 at the majority of the studied outlets; a phenomenon hypothesized to have resulted from the number of MC runs. Tracer-based verifiability of results could be achieved within five of the eight studied outlets during the model process. The flow process in those five outlets were mainly of a shallow subsurface flow as opposed to the other three outlets, which experienced other additional flow dynamics. The potential impacts of this study on the integrated use of d18O and d2H in catchment water storage and release dynamics must be further investigated in multiple catchments within various hydro-physiographic settings across the world.