One of the main challenges in the application of coupled or integratedhydrologic models is specifying a catchment's initial conditions in terms ofsoil moisture and depth-to-water table (DTWT) distributions. One approach toreducing uncertainty in model initialization is to run the model recursivelyusing either a single year or multiple years of forcing data until the systemequilibrates with respect to state and diagnostic variables. However, such"spin-up" approaches often require many years of simulations, making themcomputationally intensive. In this study, a new hybrid approach was developedto reduce the computational burden of the spin-up procedure by using acombination of model simulations and an empirical DTWT function. Themethodology is examined across two distinct catchments located in a temperateregion of Denmark and a semi-arid region of Australia. Our results illustratethat the hybrid approach reduced the spin-up period required for anintegrated groundwater–surface water–land surface model (ParFlow.CLM) by upto 50%. To generalize results to different climate and catchmentconditions, we outline a methodology that is applicable to other coupled orintegrated modeling frameworks when initialization from an equilibrium stateis required.
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