Land models are increasingly used in terrestrial hydrology due to their process-oriented representation of water and energy fluxes. A priori specification of the grid size of the land models is typically defined based on the spatial resolution of forcing data, the modeling objectives, the available geospatial information, and computational resources. The variability of the inputs, soil types, vegetation covers, and forcing is masked or aggregated based on the a priori grid size. In this study, we propose an alternative vector-based implementation to directly configure a land model using unique combinations of land cover types, soil types, and other desired geographical features that have hydrological significance, such as elevation zone, slope, and aspect. The main contributions of this paper are to (1)?implement the vector-based spatial configuration using the Variable Infiltration Capacity (VIC) model; (2)?illustrate how the spatial configuration of the model affects simulations of basin-average quantities (i.e., streamflow) as well as the spatial variability of internal processes (snow water equivalent, SWE, and evapotranspiration, ET); and (3)?describe the work and challenges ahead to improve the spatial structure of land models. Our results show that a model configuration with a lower number of computational units, once calibrated, may have similar accuracy to model configurations with more computational units. However, the different calibrated parameter sets produce a range of, sometimes contradicting, internal states and fluxes. To better address the shortcomings of the current generation of land models, we encourage the land model community to adopt flexible spatial configurations to improve model representations of fluxes and states at the scale of interest.
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