Quantifying the spatiotemporal variability in evapotranspiration is critical to accurately predict vegetation health, groundwater recharge, and streamflow generation. Differences in hillslope aspect, the direction a hillslope faces, result in variable incoming solar radiation and subsequent vegetation water use that influence the timing and magnitude of evapotranspiration. Previous work in forested landscapes has shown that equator-facing slopes have higher evapotranspiration due to more direct solar radiation and higher evaporative demand. However, it remains unclear how differences in plant functional groups (i.e., grasses and trees) influence evapotranspiration and water partitioning between hillslopes with opposing aspects. Here, using field-based measurements of soil water storage and oak tree and grass transpiration, and remotely-sensed evapotranspiration and normalized vegetation difference index, we quantified evapotranspiration and subsurface water storage deficits between a pole-facing and equator-facing hillslopes with contrasting vegetation types within central coastal California. Our results suggest that cooler pole-facing slopes with oak trees have higher evapotranspiration than warmer equator-facing slopes dominated by grasses, which is counter to previous work done in landscapes with singular vegetation types. Our water storage deficit calculations indicate that the pole-facing slope has a higher subsurface storage deficit and a larger seasonal dry down than the equator-facing slope. This aspect difference in subsurface water storage deficits may influence subsequent deep groundwater recharge and streamflow generation. In addition, larger root-zone storage deficits on pole-facing slopes may reduce their ability to serve as hydrologic refugia for oaks during periods of extended drought. This research provides a novel integration of field-based and remotely-sensed estimates of evapotranspiration required to properly quantify hillslope-scale water balances. These findings emphasize the importance of resolving hillslope-scale vegetation structure within Earth system models, especially in landscapes with diverse plant functional groups.