Uncertainties of 3D soil hydraulic parameters in streamflow simulations using a distributed hydrological model system

Parameter calibration and uncertainty estimation are crucial for hydrological simulations in the distributed land surface-hydrological model. To investigate soil properties impacting hydrological processes, five conventional pedo-transfer functions (PTFs) are applied to create a 3D soil hydraulic parameter (SHP) ensemble in the Weather Research and Forecasting-Hydrological extension (WRF-Hydro), a distributed, multi-physics land surface hydrological model. The SHPs are generated, based on a high-resolution Chinese soil property dataset, over the heterogeneous Upper Huaihe River basin. The results show that the SHPs can influence the streamflow in WRF-Hydro, which is similar to the impact of the scaling parameters on the streamflow over the study basin. Analyses of the uncertainty in the SHP ensemble reveal that SHPs mainly constrain the peak flow during the flood rise and impact the baseflow during the flood recession. A hydrological Bayesian model average (BMA) method is constructed to postprocess the streamflow ensemble based on the 3D SHPs. Probabilistic streamflow estimations by the BMA method are more skillful than the simulations using the individual 3D SHP ensemble members for all five studied hydrological stations, especially for high flows. Therefore, improved estimation of the uncertainty in the 3D SHPs may enhance the spatial representation of flood processes, resulting in more accurate estimates of the streamflow in the main streams in a heterogeneous basin.