Integrated land surface-groundwater models are valuable tools in simulating the terrestrial hydrologic cycle as a continuous system and in exploring the extent of land surface–subsurface interactions from catchment to regional scales. However, the fidelity of model simulations is impacted not only by the vegetation and subsurface parameterization, but also by the antecedent conditions such as initial soil moisture and ground temperature. In land surface modeling, a given model is often run repeatedly over a single year of forcing data until it reaches an equilibrium state, at which there is minimal artificial drift in the model state or prognostic variables. In this study, multiple criteria analysis was performed to assess the spin up behaviour of an integrated groundwater-surface water-land
surface model (ParFlow.CLM) over a 200 km2 subcatchment of the Ringkobing Fjord catchment in Denmark. Various measures of spin up performance were computed for model state variables such as soil moisture and groundwater storage, and diagnostic variables such as latent and sensible heat fluxes. The impacts of initial conditions on the fidelity of surface water–groundwater interactions were then explored. Our analysis illustrates that improper initialization of the model can generate simulations that lead to a misinterpretation of land surface-subsurface feedback processes, and determination of an equilibrium state depends on the variable and performance measure used. Results highlight the advantage of using a multiple criteria approach in determining the equilibrium state.
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Last updated 31st January 2013