Groundwater flow drives partitioning: Soil evaporation and plant transpiration together contribute a substantial proportion of terrestrial freshwater fluxes. Land surface models are used to understand the partitioning of these fluxes on a continental scale; however, model outputs are often inconsistent with stable isotope observations. Maxwell and Condon incorporated dynamic groundwater flow into an integrated hydrologic model simulation for the entire United States. The model showed that water table depth and lateral flow strongly affect transpiration partitioning, thus explaining the inconsistencies between observations and models. Science , this issue p. 377
A warmer climate increases evaporative demand. However, response to warming depends on water availability. Existing earth system models represent soil moisture but simplify groundwater connections, a primary control on soil moisture. Here we apply an integrated surface-groundwater hydrologic model to evaluate the sensitivity of shallow groundwater to warming across the majority of the US. We show that as warming shifts the balance between water supply and demand, shallow groundwater storage can buffer plant water stress; but only where shallow groundwater connections are present, and not indefinitely. As warming persists, storage can be depleted and connections lost. Similarly, in the arid western US warming does not result in significant groundwater changes because this area is already largely water limited. The direct response of shallow groundwater storage to warming demonstrates the strong and early effect that low to moderate warming may have on groundwater storage and evapotranspiration.
There are a growing number of large-scale, complex hydrologic models that are capable of simulating integrated surface and subsurface flow. Many are coupled to land-surface energy balance models, biogeochemical and ecological process models, and atmospheric models. Although they are being increasingly applied for hydrologic prediction and environmental understanding, very little formal verification and/or benchmarking of these models has been performed. Here we present the results of an intercomparison study of seven coupled surface-subsurface models based on a series of benchmark problems. All the models simultaneously solve adapted forms of the Richards and shallow water equations, based on fully 3-D or mixed (1-D vadose zone and 2-D groundwater) formulations for subsurface flow and 1-D (rill flow) or 2-D (sheet flow) conceptualizations for surface routing. A range of approaches is used for the solution of the coupled equations, including global implicit, sequential iterative, and asynchronous linking, and various strategies are used to enforce flux and pressure continuity at the surface-subsurface interface. The simulation results show good agreement for the simpler test cases, while the more complicated test cases bring out some of the differences in physical process representations and numerical solution approaches between the models. Benchmarks with more traditional runoff generating mechanisms, such as excess infiltration and saturation, demonstrate more agreement between models, while benchmarks with heterogeneity and complex water table dynamics highlight differences in model formulation. In general, all the models demonstrate the same qualitative behavior, thus building confidence in their use for hydrologic applications.
Interactions between surface and groundwater systems are well-established theoretically and observationally. While numerical models that solve both surface and subsurface flow equations in a single framework (matrix) are increasingly being applied, computational limitations have restricted their use to local and regional studies. Regional or watershed-scale simulations have been effective tools for understanding hydrologic processes; however, there are still many questions, such as the adaptation of water resources to anthropogenic stressors and climate variability, that can only be answered across large spatial extents at high resolution. In response to this grand challenge in hydrology, we present the results of a parallel, integrated hydrologic model simulating surface and subsurface flow at high spatial resolution (1 km) over much of continental North America (~ 6.3 M km2). These simulations provide integrated predictions of hydrologic states and fluxes, namely, water table depth and streamflow, at very large scale and high resolution. The physics-based modeling approach used here requires limited parameterizations and relies only on more fundamental inputs such as topography, hydrogeologic properties and climate forcing. Results are compared to observations and provide mechanistic insight into hydrologic process interaction. This study demonstrates both the feasibility of continental-scale integrated models and their utility for improving our understanding of large-scale hydrologic systems; the combination of high resolution and large spatial extent facilitates analysis of scaling relationships using model outputs.
Surface flow and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs are dynamically evolving with improvements in technology, and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves the Richards equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite-difference scheme and a conservative finite-volume method for subsurface flow and transport, respectively. ParFlow uses multigrid-preconditioned Krylov and Newton–Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g., the Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective.