Abstract
The hydrological model assessment and development (hydromad) modeling package is an R-based package that can be applied to simulate hydrological models and optimize parameters. As the hydromad package is incompatible with hydrological models outside the package, the parameters of such models cannot be directly optimized. Hence, we proposed a method of optimizing the hydrological-model parameters by combining the executable (EXE) file of the hydrological model with the shuffled complex evolution (SCE) algorithm provided by the hydromad package. A physically based, spatially distributed, grid-based rainfall–runoff model (GRM) was employed. By calibrating the parameters of the GRM, the performance of the model was found to be reasonable. Thus, the hydromad can be used to optimize the hydrological-model parameters outside the package if the EXE file of the hydrological model is available. The time required to optimize the parameters depends on the type of event, even for the same catchment area.
Highlights
A physically based, distributed hydrological model can be applied to simulate runoffs by extracting the required values of the parameters from the characteristics of a catchment, without requiring parameter calibration
Previous studies have optimized the parameters of a distributed hydrological model using the trial-and-error method in cases where the required optimization algorithms were not included in the modeling package [6,7,8,9,10]
In the cases of the two events in Danseong, as shown in Figure 3a,b, the simulated flow is in very good agreement with the observed flow; the simulated value is slightly lower at the peak flow
Summary
A physically based, distributed hydrological model can be applied to simulate runoffs by extracting the required values of the parameters from the characteristics of a catchment, without requiring parameter calibration. It is difficult to incorporate various optimization algorithms into the modeling package when the number of parameters in the distributed hydrological model to be optimized is considerable. Previous studies have optimized the parameters of a distributed hydrological model using the trial-and-error method in cases where the required optimization algorithms were not included in the modeling package [6,7,8,9,10]. The hydromad package can be used to simulate conceptual hydrological models, optimize parameters, and analyze uncertainties. Because the existing hydromad package is incompatible with hydrological models outside the package, the parameters of such models cannot be automatically
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