Catchment-scale representation of the groundwater and its interaction with other parts of the hydrologic cycle is crucial for accurately depicting the land water–energy balance in Earth system models (ESMs). Despite existing efforts to describe the groundwater in the land component of ESMs, most ESMs still need a prognostic framework for describing catchment-scale groundwater based on its emergent properties to understand the implications for the broader Earth system. To fill this gap, we developed a new parameterization scheme to resolve the groundwater and its two-way interactions with the unsaturated soil and stream at the catchment scale. We implemented this new parameterization scheme (SHARC, or the soil–hillslope aquifer–river continuum) in the Geophysical Fluid Dynamics Laboratory (GFDL) land model (i.e., LM4-SHARC) and evaluated its performance. By bridging the gap between hydraulic groundwater theory and ESM land hydrology, the new LM4-SHARC provides a path to learning groundwater emergent properties from available streamflow data (i.e., recession analysis), enhancing the representation of subgrid variability in water–energy states induced by the groundwater. LM4-SHARC has been applied to the Providence headwater catchment at Southern Sierra, NV, and tested against in situ observations. We found that LM4-SHARC leads to noticeable improvements in the representation of key hydrologic variables such as streamflow, near-surface soil moisture, and soil temperature. In addition to enhancing the representation of the water and energy balance, our analysis showed that accounting for groundwater convergence can induce a more significant hydrologic contrast, with higher sensitivity of soil water storage to groundwater properties in the riparian zone. Our findings indicate the feasibility of incorporating two-way interactions among groundwater, unsaturated soil, and streams into the hydrological components of ESMs and show a further need to explore the implications of these interactions in the context of Earth system dynamics.
