Benchmarking historical performance and future projections from a large-scale hydrologic model with a watershed hydrologic model

Abstract

Large-scale hydrologic models (LHMs) are increasingly relied upon for assessing climate-driven hydrologic changes from watershed to global scales. However, their ability to provide robust projections for a range of hydrologic variables remains unclear. Here, we evaluate the historical performance and future projections from the Community Water Model (CWatM) LHM against the Variable Infiltration Capacity (VIC) watershed hydrologic model for the Liard River basin (drainage area of ∼ 275 000 km2) in subarctic Canada. The model setups have key differences in terms of model configuration (CWatM is set up with two subbasins, and VIC is set up with 28 subbasins) and model structure (e.g., snowmelt and frozen soil representation). We drive both models with an ensemble of eight global climate models from the Coupled Model Intercomparison Project Phase 6, downscaled and bias-corrected with a multivariate method. We analyze a range of hydrologic projections at 1.5 to 4.0 °C global warming levels (GWLs) above the preindustrial period. The historical performance benchmarking shows reasonable goodness-of-fit metrics for both models, with a slightly better performance for VIC. Projected hydrologic responses from CWatM are generally consistent with VIC in terms of annual water balance, as well as monthly snow water equivalent and flow changes, suggesting the robustness of the projections. Both models project coherent hydrologic changes, including progressively higher annual evapotranspiration; increased annual, winter, spring, and maximum flows; increased frequency of extreme flow; and earlier timing of maximum flow, with higher GWLs. However, the magnitudes of maximum flow and late-summer flow diverge between the two models, which can be explained by structural uncertainties associated with the representation of frozen soil and groundwater processes. Thus, our study provides insights into the robustness of hydrologic projections from an LHM and offers a basis for model improvements.