Land Surface Models (LSMs) are used to predict heat, energy, and momentum fluxes occurring at the land surface and the resulting effects in the soil and atmosphere at various scales. Evaporation from bare soil is an integral component of the water balance that is very difficult to accurately predict since it is complexly affected by the coupled effects of atmospheric conditions and soil properties. Inaccurate or simplifying assumptions can have drastic effects on regional and global LSM predictions and cause available LSMs to predict conflicting values for the soil moisture conditions and surface fluxes (e.g. evapotranspiration, infiltration, run off). The goal of this work is to see how heterogeneities in soil properties can be properly represented with a soil resistance term that accounts for physically based parameters of the soil system at the land-atmosphere interface. Utilizing a comprehensive, experimental dataset generated from a soil with known, heterogeneous properties under highly controlled atmospheric conditions, we are able to compare the effectiveness of various parameterizations in two different models. The first being a multiphase, non-equilibrium, and non-isothermal model that minimizes the dependence on fitting parameters. The effects of certain mechanisms are better understood at this fine scale and incorporated into the land surface component of the Accelerated Climate Modeling for Energy project (ALM), which is focused on capturing the interactions between the surface and the atmosphere at larger scales. The formulations of the resistance parameter, soil water retention curve (SWRC), and diffusivity through partially saturated porous media are of particular interest. The fine scale model was used in conjunction with the experimental data to test formulations before implementing them into the ACME Land Model (ALM). Effects of these alterations were compared to the existing mechanisms in ALM and then tested against lab and field scale data sets. Initial findings suggest the Tang and Riley (2013a) soil resistance more accurately reproduces results lab and field results on multiple scales where heterogeneity is present. Further understanding of soil resistance will lead to more robust land surface models which decrease the reliance on such empirical relationships.