Significance Hydrophobic effects, which play a crucial role in many chemical and biological processes, originate in the statistics of microscopic density fluctuations in liquid water. Chandler has established the foundation for a simple and unified understanding of these effects, by identifying essential aspects of water’s intermolecular structure while accounting for its proximity to phase coexistence. Here, we show that coarse-grained models based on this perspective, when constructed to include the statistics of capillary waves at interfaces, can achieve remarkable agreement with results of atomistically detailed simulations. Highly efficient and lacking adjustable parameters, such models hold promise as powerful tools for studying multiscale problems in hydrophobic solvation. , Modern theories of the hydrophobic effect highlight its dependence on length scale, emphasizing the importance of interfaces in the vicinity of sizable hydrophobes. We recently showed that a faithful treatment of such nanoscale interfaces requires careful attention to the statistics of capillary waves, with significant quantitative implications for the calculation of solvation thermodynamics. Here, we show that a coarse-grained lattice model like that of Chandler [Chandler D (2005) Nature 437(7059):640–647], when informed by this understanding, can capture a broad range of hydrophobic behaviors with striking accuracy. Specifically, we calculate probability distributions for microscopic density fluctuations that agree very well with results of atomistic simulations, even many SDs from the mean and even for probe volumes in highly heterogeneous environments. This accuracy is achieved without adjustment of free parameters, because the model is fully specified by well-known properties of liquid water. As examples of its utility, we compute the free-energy profile for a solute crossing the air–water interface, as well as the thermodynamic cost of evacuating the space between extended nanoscale surfaces. These calculations suggest that a highly reduced model for aqueous solvation can enable efficient multiscale modeling of spatial organization driven by hydrophobic and interfacial forces.