Integrating MODIS and SMAP data for spatially calibrated SWAT+ modeling in a forested watershed of South Korea

This study establishes a spatially, multi-variable calibrated SWAT+ methodology integrating Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) and evapotranspiration (ET) with Soil Moisture Active Passive (SMAP) soil moisture for the Yongdam Dam watershed, South Korea. Satellite datasets were aggregated by landscape units for parameter calibration and validation. The model reproduced spatial patterns of satellite observations (R 2 > 0.94 for LAI, 0.80 for ET, 0.65 for soil moisture). While utilizing satellite products involves inherent data uncertainties, their integration significantly enhances the physical realism of the SWAT+. The satellite constrained calibration improved the representation of hydrograph dynamics more accurately than conventional calibration. Spatial calibration increased ET (+3.4%) and surface runoff (+1.8%) and decreased groundwater flow (−0.8%), revealing improved representation of surface water processes and energy–water interactions. The methodology demonstrates the utility of remote sensing integration in SWAT+ to enhance spatial realism and reduce parameter equifinality.