Model spin-up is an adjustment process where its internal stores move from an initial state of unusual conditions to one of equilibrium. Model outputs during this spin-up process are often unrealistic and misleading. This study investigates some primary factors affecting spin-up time using the Xinanjiang model for 22 river basins throughout the United States. A 10-year recursive simulation with three data sets indicates that time required for model equilibrium is not only a function of initial conditions, but also is affected by input data sets (precipitation and evaporation). The model requires less time to be equilibrated under wetter initial conditions (lowest under saturated initial condition). Moreover, model spin-up time shows distinct variations with the dryness of the input data sets. Analysis suggests that wet basins (ratio of evaporation over precipitation <0.9) require less time (55 days) for model equilibrium in comparison to that of dry basins (298 days). The spin-up time displayed an exponential relationship with the basin aridity index (r2
= 0.85). This relationship could provide a way to predict the maximum model spin-up time using the precipitation and evaporation information only. Predicting maximum model spin-up time based on this relationship could be valuable to reduce uncertainty, particularly under data scarce situations.
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