Using sensitivity analysis and soft calibration of geological regions to improve the representation of hydrological processes in a SWAT+ model

Robust hydrological models require an accurate representation of hydrological processes, but modellers often rely solely on the streamflow simulation performance. This work presents an innovative zonal calibration workflow developed for a geologically heterogeneous basin, the Upper Tagus River Basin (Spain), towards achieving a realistic simulation of hydrological processes. A detailed SWAT+ model was built, and four geological regions were defined. The sensitivity of 10 parameters for two hydrological indices, runoff coefficient and groundwater contribution to the streamflow, was explored. Then, parameters were optimized for each region through a soft calibration to achieve an accurate simulation of these variables. Some parameters were identified as the most sensitive (<i>cn2</i> and <i>awc</i> for runoff coefficient and <i>perco</i> for groundwater contribution). Sensitivity rankings and parameter adjustment varied among regions, revealing differences in the hydrological processes. The target values of the hydrological variables, previously estimated, were reached in every region, subsequently improving streamflow simulation performance.