On the Development of a Coupled Land Surface and Groundwater Model

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. A set of simulations based on synthetic data and data from the Project for Intercomparison of Landsurface Parameterization Schemes (PILPS), version 2(d), 18-year dataset from Valdai, Russia demonstrate the temporal dynamics of this coupled modeling system. Changes in soil moisture and movement of the water table are used as indicators of mass conservation between the LSM and GWM. This study demonstrates the affect of aquifer storage and a dynamic water table on predicted watershed 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.

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