Coastal responses to sea level rise (SLR) include inundation of wetlands, increased shoreline erosion, and increased flooding during storm events. Hydrodynamic parameters such as tidal ranges, tidal prisms, tidal asymmetries, increased flooding depths and inundation extents during storm events respond nonadditively to SLR. Coastal morphology continually adapts toward equilibrium as sea levels rise, inducing changes in the landscape. Marshes may struggle to keep pace with SLR and rely on sediment accumulation and the availability of suitable uplands for migration. Whether hydrodynamic, morphologic, or ecologic, the impacts of SLR are interrelated. To plan for changes under future sea levels, coastal managers need information and data regarding the potential effects of SLR to make informed decisions for managing human and natural communities. This review examines previous studies that have accounted for the dynamic, nonlinear responses of hydrodynamics, coastal morphology, and marsh ecology to SLR by implementing more complex approaches rather than the simplistic “bathtub” approach. These studies provide an improved understanding of the dynamic effects of SLR on coastal environments and contribute to an overall paradigm shift in how coastal scientists and engineers approach modeling the effects of SLR, transitioning away from implementing the “bathtub” approach. However, it is recommended that future studies implement a synergetic approach that integrates the dynamic interactions between physical and ecological environments to better predict the impacts of SLR on coastal systems.

Hydrologic models can be categorized as being either Newtonian or Darwinian in nature. The Newtonian approach requires a thorough understanding of the individual physical processes acting in a watershed in order to build a detailed hydrologic model based on the conservation equations. The Darwinian approach seeks to explain the behavior of a hydrologic system as a whole by identifying simple and robust temporal or spatial patterns that capture the relevant processes. Darwinian‐based hydrologic models include the Soil Conservation Service (SCS) curve number model, the “abcd” model, and the Budyko‐type models. However, these models were developed based on widely differing principles and assumptions and applied to distinct time scales. Here, we derive a one‐parameter Budyko‐type model for mean annual water balance which is based on a generalization of the proportionality hypothesis of the SCS model and therefore is independent of temporal scale. Furthermore, we show that the new model is equivalent to the key equation of the “abcd” model. Theoretical lower and upper bounds of the new model are identified and validated based on previous observations. Thus, we illustrate a temporal pattern of water balance amongst Darwinian hydrologic models, which allows for synthesis with the Newtonian approach and offers opportunities for progress in hydrologic modeling.