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Abstract. Hydraulic redistribution (HR), the movement of water via plant root systems that connect soil compartments with different water potential, should influences soil moisture dynamics particularly in water-limited ecosystems. Realistic representation of HR in ecosystem models is essential to improve the ability of these models to predict ecosystem function in dryland regions. In this study, we integrated HR into the Terrestrial ECOsystem model and employed a Bayesian Markov Chain Monte Carlo technique to optimize soil hydraulic parameters and root conductance using four years of soil moisture observations from a piñon-juniper woodland. We found that (i) integrating HR generally improved model prediction of soil moisture during dry periods, particularly in the top 30 cm of the soil profile, where more than 50 % of root biomass exists, mostly during dry periods; (ii) HR increased surface soil moisture by up to 60 % during dry periods; (iii) HR decreased with increasing precipitation magnitude and frequency, however, the length of dry spells between rainfall events also influenced HR rates; and (iv) upward HR in the top 60 cm soil profile became more pronounced as dry conditions progressed, with rates ranging from 0.10 to 0.50 mm d⁻¹. These findings highlight that HR plays a likely role in sustaining soil moisture during extended dry periods and has a limited effect during precipitation events. Future research should investigate the effect of HR on other ecosystem processes, such as net ecosystem exchange of carbon and evapotranspiration under varying climatic conditions.