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Estimating spatially distributed parameters remains one of the biggest challenges for large-domain hydrologic modeling. Many large-domain modeling efforts rely on spatially inconsistent parameter fields, e.g., patchwork patterns resulting from individual basin calibrations, parameter fields generated through default transfer functions that relate geophysical attributes to model parameters, or spatially constant, default parameter values. This paper provides an initial assessment of a multiscale parameter regionalization (MPR) method over large geographical domains to derive seamless parameters in a spatially consistent manner. MPR applies transfer functions at the native scale of the geophysical data, and then scales these model parameters to the desired model resolution. We developed a stand-alone framework called MPR-flex for multimodel use and applied MPR-flex to the variable infiltration capacity model to produce hydrologic simulations over the contiguous United States (CONUS). We first independently calibrate 531 basins across CONUS to obtain a performance benchmark for each basin. To derive the CONUS parameter fields, we perform a joint MPR calibration using all but the poorest behaved basins to obtain a single set of transfer function parameters that are applied to the entire CONUS. Results show that CONUS-wide calibration has similar performance compared to previous simulations using a patchwork quilt of partially calibrated parameter sets, but without the spatial discontinuities in parameters that characterize some previous CONUS-domain model simulations. Several avenues to improve CONUS-wide calibration remain, including selection of calibration basins, objective function formulation, as well as MPR-flex improvements including transfer function formulations and scaling operator optimization.

Plain Language Summary Hydrologic models compute surface and subsurface water transmission and storage using many equations with parameters that vary spatially. Many parameter values are commonly estimated through systematic adjustment of parameter values to match historical streamflow over a watershed where a stream gauge is available. This method is difficult to apply to large domains contiguously. Consequently, many current large scale hydrologic assessments rely on spatially inconsistent parameter fields such as a patchwork quilt resulting from individual basin calibration or spatially constant parameters resulting from the adoption of default estimates. Facing this challenge, we developed a parameter estimation methodology that incorporates effects of landscape properties on parameter values to enable continental-domain applications of hydrologic models in a spatially consistent way. We applied this methodology to a model that has been used for many hydrologic studies such as climate impact studies to generate a spatially smooth parameter set over the contiguous United States. Simulations using this parameter set produce similar accuracy to the previously developed parameter set.