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Abstract Integrated hydrological modeling is an effective method for understanding interactions between parts of the hydrologic cycle, quantifying water resources, and furthering knowledge of hydrologic processes. However, these models are dependent on robust and accurate datasets that physically represent spatial characteristics as model inputs. This study evaluates multiple data‐driven approaches for estimating hydraulic conductivity and subsurface properties at the continental‐scale, constructed from existing subsurface dataset components. Each subsurface configuration represents upper (unconfined) hydrogeology, lower (confined) hydrogeology, and the presence of a vertical flow barrier. Configurations are tested in two large‐scale U.S. watersheds using an integrated model. Model results are compared to observed streamflow and steady state water table depth (WTD). We provide model results for a range of configurations and show that both WTD and surface water partitioning are important indicators of performance. We also show that geology data source, total subsurface depth, anisotropy, and inclusion of a vertical flow barrier are the most important considerations for subsurface configurations. While a range of configurations proved viable, we provide a recommended Selected National Configuration 1 km resolution subsurface dataset for use in distributed large‐and continental‐scale hydrologic modeling. 

Mitochondrial cristae are dynamic invaginations of the inner membrane and play a key role in its metabolic capacity to produce ATP. Structural alterations caused by either genetic abnormalities or detrimental environmental factors impede mitochondrial metabolic fluxes and lead to a decrease in their ability to meet metabolic energy requirements. While some of the key proteins associated with mitochondrial cristae are known, very little is known about how the inner membrane dynamics are involved in energy metabolism. In this study, we present a computational strategy to understand how cristae are formed using a phase-based separation approach of both the inner membrane space and matrix space, which are explicitly modeled using the Cahn–Hilliard equation. We show that cristae are formed as a consequence of minimizing an energy function associated with phase interactions which are subject to geometric boundary constraints. We then extended the model to explore how the presence of calcium phosphate granules, entities that form in calcium overload conditions, exert a devastating inner membrane remodeling response that reduces the capacity for mitochondria to produce ATP. This modeling approach can be extended to include arbitrary geometrical constraints, the spatial heterogeneity of enzymes, and electrostatic effects to mechanize the impact of ultrastructural changes on energy metabolism.