10As the world's largest distributed store of freshwater, groundwater plays a central role in 11 sustaining ecosystems and enabling human adaptation to climate variability and change. 12The strategic importance of groundwater to global water and food security will intensify 13 under climate change as more frequent and intense climate extremes (droughts, floods) 14 increase variability in soil moisture and surface water. Here we critically review recent 15 research assessing climate impacts on groundwater through natural and human-induced 16 processes as well as groundwater-driven feedbacks on the climate system.

Interactions between surface and ground water are a key component of the hydrologic budget on the watershed scale. Models that honor these interactions are commonly based on the conductance concept that presumes a distinct interface at the land surface, separating the surface from the subsurface domain. These types of models link the subsurface and surface domains via an exchange flux that depends upon the magnitude and direction of the hydraulic gradient across the interface and a proportionality constant (a measure of the hydraulic connectivity). Because experimental evidence of such a distinct interface is often lacking in field systems, there is a need for a more general coupled modeling approach.A more general coupled model is presented that incorporates a new two-dimensional overland flow simulator into the parallel three-dimensional variable saturated subsurface flow code ParFlow. In ParFlow, the overland flow simulator takes the form of an upper boundary condition and is, thus, fully integrated without relying on the conductance concept. Another important advantage of this approach is the efficient parallelism incorporated into ParFlow, which is efficiently exploited by the overland flow simulator.Several verification and simulation examples are presented that focus on the two main processes of runoff production : excess infiltration and saturation. The model is shown to reproduce an analytical solution for overland flow and compares favorably to other commonly used hydrologic models. The influence of heterogeneity of the shallow subsurface on overland flow is also examined. The results show the uncertainty in overland flow predictions due to subsurface heterogeneity and demonstrate the usefulness of our approach. Both the overland flow component and the coupled model are evaluated in a parallel scaling study and show to be efficient.

[1] The influence of groundwater dynamics on the energy balance at the land surface is studied using an integrated, distributed watershed modeling platform. This model includes the mass and energy balance at the land surface; three-dimensional variably saturated subsurface flow; explicit representation of the water table; and overland flow. The model is applied to the Little Washita watershed in Central Oklahoma, USA and compared to runoff, soil moisture and energy flux observations. The connection between groundwater dynamics and the land surface energy balance is studied using a variety of conventional and spatial statistical measures. For a number of energy variables a strong interconnection is demonstrated with water table depth. This connection varies seasonally and spatially depending on the spatial composition of water table depth. A theoretical critical water table depth range is presented where a strong sensitivity between groundwater and land-surface processes may be observed. For this particular watershed, a critical depth range is established between 1 and 5 m in which the land surface energy budget is most sensitive to groundwater storage. Finally, concrete recommendations are put forth to characterize this interconnection in the field.Citation: Kollet, S. J., and R. M. Maxwell (2008), Capturing the influence of groundwater dynamics on land surface processes using an integrated, distributed watershed model, Water Resour. Res., 44, W02402,

Management of surface water quality is often complicated by interactions between surface water and groundwater. Traditional Land-Surface Models (LSM) used for numerical weather prediction, climate projection, and as inputs to water management decision support systems, do not treat the LSM lower boundary in a fully process-based fashion. LSMs have evolved from a leaky bucket to more sophisticated land surface water and energy budget models that typically have a so-called basement term to depict the bottom model layer exchange with deeper aquifers. Nevertheless, the LSM lower boundary is often assumed zero flux or the soil moisture content is set to a constant value; an approach that while mass conservative, ignores processes that can alter surface fluxes, runoff, and water quantity and quality. Conversely, groundwater models (GWM) for saturated and unsaturated water flow, while addressing important features such as subsurface heterogeneity and three-dimensional flow, often have overly simplified upper boundary conditions that ignore soil heating, runoff, snow and root-zone uptake. In the present study, a state-of-the-art LSM (CLM) and a variably-saturated GWM (ParFlow) have been coupled as a single column model. This study demonstrates the affect of aquifer storage and a dynamic water table on predicted watershed 2 flow. The model's ability to capture certain cold processes such as frozen soil and freeze/thaw processes are discussed. Comparisons of the uncoupled and coupled modes are presented and the differences in simulations of soil moisture and shallow and deeper ground processes are highlighted.A distributed version of the coupled model will ultimately be used to assist in the development of Total Maximum Daily Loads (TMDLs) -a surface water quality standard --for a number of pollutants in an urban watershed in Southern California in the United States.3

Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.