Implementing Hillslope-scale Hydrology in the Community Terrestrial Systems Model: Do hillslope-scale hydrologic processes affect predictions of global environmental change?

A primary tool for projecting future changes in environmental conditions and water resources is the Earth System model (ESM). Due to computational expense, an ESM is typically operated using a global grid with spatial resolutions of tens to hundreds of km. Yet significant spatial heterogeneity exists in terrestrial hydrologic states and landscape properties at spatial scales orders of magnitude smaller.

Rather than simply increase the resolution of the model grid, which is unlikely to better capture fine scale spatial heterogeneity, we instead explicitly represent hydrologically similar areas within a model gridcell using the concept of representative hillslopes. Within each gridcell, one or more hillslopes are defined, and the relevant landscape properties and vegetation are assigned to the hillslope elements. Lateral transport of water between hillslope elements is enabled, allowing for topographically driven redistribution of water across the hillslope. Importantly, processes are modeled at the hillslope scale (100s m) and then upscaled to provide a gridcell aggregate quantity.

Identification of representative hillslopes globally has been facilitated recently by high-resolution global digital elevation datasets and associated derived quantities such as slope, aspect, and catchment delineation. Here we report on a hillslope implementation in the Community Terrestrial Systems Model (CTSM). CTSM is latest iteration of the Community Land Model (CLM), the land component of the Community Earth System Model. Using a global HAND (Height Above Nearest Drainage) dataset, we first derive geomorphic parameters for representative hillslopes on a global 1 degree grid. Global simulations are then performed to explore whether explicitly modeling hydrologic processes such as the lateral redistribution of moisture at the hillslope spatial scale can lead to a better representation of water, energy, and carbon fluxes at the spatial scale of an Earth System model gridcell.