Evaluating input data sources for isotope-enabled rainfall-runoff models

Isotope-enabled models provide a means to generate robust hydrological simulations. However, daily isotope-enabled rainfall-runoff models applied to larger spatial scales (>100 km²) require more input data than conventional non-isotope models in the form of precipitation isotope time series, which are difficult to generate even with point station measurements. Spatially distributed isotope data can be circumvented by isotope-enabled climate models. Here, we evaluate the hydrological simulations of the J2000-isotope enabled hydrological model driven with data from corrected and un-corrected isotope-enabled global and regional climate models (isotope-enabled global spectral model [IsoGSM] and isotope-enabled regional spectral model [IsoRSM], respectively) compared with 1 year of measured reference station and a yearly average precipitation isotope input for a pilot site, the data-scarce sub-humid Eerste River catchment in South Africa. The models driven by all input products performed well for upstream and downstream discharge gauges with Nash Sutcliffe efficiency (NSE) from 0.58 to 0.85 and LogNSE of 0.66 to 0.93. The simulated δ²H stream isotopes using the reference J2000-iso and J2000-isoRSM were good for the main river with a stream Kling Gupta efficiency (KGE) of between 0.4–0.9 and the top 100 Monte Carlo simulations varying by around 5‰ for δ²H. For smaller tributaries the model was unable to capture the measured stream isotopes due to biased precipitation isotope inputs. Adjusting the J2000-iso with a bias corrected IsoRSM improved the stream and groundwater isotope simulation and outperformed the model driven by an average yearly precipitation isotope input. Differences in simulated hydrological processes were only evident between the models when evaluating percolation with unrealistic simulations for the standard J2000 model. While the regional climate model is computationally more intensive than its global counterpart, it provided better stream isotope simulations and improvements to simulated percolation. Our results indicate that isotope-enabled climate models can provide useful input data in data scarce regions for hydrological models, where improved water management to address climate change impacts is needed.