Scaling Point-Scale (Pedo)transfer Functions to Seamless Large-Domain Parameter Estimates for High-Resolution Distributed Hydrologic Modeling: An Example for the Rhine River

Moving toward high-resolution gridded hydrologic models asks for novel parametrization approaches. A high-resolution conceptual hydrologic model (wflow_sbm) was parameterized for the Rhine basin in Europe based on point-scale (pedo)transfer functions, without further calibration of effective model parameters on discharge. Parameters were estimated on the data resolution, followed by upscaling of parameter fields to the model resolution. The method was tested using a 6-hourly time step at four model resolutions (1.2, 2.4, 3.6, and 4.8 km), followed by a validation with discharge observations and a comparison with actual evapotranspiration (ET_act) estimates from an independent model (DMET Land Surface Analysis Satellite Application Facility). Additionally, the scalability of parameter fields and simulated fluxes was tested. Validation of simulated discharges yielded Kling-Gupta Efficiency (KGE) values ranging from 0.6 to 0.9, except for the Alps where a volume bias caused lower performance. Catchment-averaged temporal ET_act dynamics were comparable with independent ET estimates (KGE ≈ 0.7), although wflow_sbm model simulations were on average 115 mm yr⁻¹ higher. Spatially, the two models were less in agreement (SPAEF = 0.10), especially around the Rhine valley. Consistent parameter fields were obtained, and by running the model at the different resolutions, preserved ET_act fluxes were found across the scales. For recharge, fluxes were less consistent with relative errors around 30% for regions with high drainage densities. However, catchment-averaged fluxes were better preserved. Routed discharge in headwaters was not consistent across scales, although simulations for the main Rhine River were. Better processing (scale independent) of the river and drainage network may overcome this issue.