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Water is undeniably among the most important natural resources and the most critical in semi-arid regions like the Intermountain West of the United States. Such regions are characterized by low precipitation, the majority of which is transferred to the atmosphere from the soil and vegetation as evapotranspiration (ET). Quantification of ET is thus crucial for understanding the balance of water within the region, which is important for efficiently planning the available water resources. This study was motivated towards advancing the estimation of actual ET (ETA) in mountain ecosystems, where the variation in different types of vegetation and non-uniformity of soil including considerable stone content creates challenges for estimating water use as ET. With the aim of addressing the effect of stone content in controlling soil moisture and ET, this study examined the influence of stone content on bulk soil hydraulic properties. An averaging model referred to as a binary mixing model was used to describe the way in which water is held and released in stony soil. This approach was based on the individual hydraulic behavior of the background soil and of the stones within the soil. The effect of soil stone content on ETA was evaluated by accounting for the water retention properties of stones in the soil using a numerical simulation model (HYDRUS-1D). The results revealed overestimation of simulated ETA when effects of stone content were not accounted for in comparison to ETA vi measured by the state-of-the-art “eddy covariance” measurement method for ETA. An even larger-scale model was evaluated, named the Noah-Multiphysics (Noah-MP) land surface model. The land surface model was run using different arrangements of complexity to determine the importance of stone content information on simulation results. The version of the model with information about stone content along with detailed soil properties was able to provide the best Noah-MP prediction of ET. The study suggests that improvement in representation of soil properties including stone content information, can substantially advance the ability of numerical and land surface models to more accurately simulate soil water flow and ETA.