Untangling the impacts of land cover representation and resampling in distributed hydrological model predictions

Abstract

Accurate land cover information is essential for hydrometeorological modeling, as it defines parameters governing land-atmosphere-vegetation interactions, water partitioning, and routing. This study presents a controlled sensitivity analysis that evaluated the impact of land cover resampling methods on hydrologic simulations within the WRF-Hydro/NWM framework. The choice of resampling algorithms affected simulations but was generally limited to arid environments, catchments featuring minor land cover classes with high hydrologic impact, or low-flow predictions. We tested two distinct spatial aspects: areal proportions of land cover classes and spatial patterns in land cover. Areal proportions influenced vertical hydrologic fluxes at the catchment scale and subsequently affected streamflow characteristics. In contrast, spatial arrangement alone had a marginal impact on vertical fluxes but could still induce limited alterations in streamflow characteristics through routing processes. These results suggest that spatially distributed land cover, as used in physics-based model structures, has a limited impact on watershed-scale hydrologic simulations.