Sunwoo, W.; Lee, G.; Nguyen, H.H.; Shin, H., and Jun, K.S., 2021. Parameter optimization of a conceptual rainfall-runoff model in the coastal urban region. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 261–265. Coconut Creek (Florida), ISSN 0749-0208.

The rainfall-runoff simulation based on local conditions is crucial for flood monitoring and mitigation. Although numerous rainfall-runoff models were widely used, only few studies have been applied in coastal regions in South Korea. The major reasons are that model parameters are incorrectly determined, and the peak flooding is overestimated due to extreme rainfall events. In this study, a conceptual rainfall-runoff model, the Probability Distributed Model (PDM), was employed to simulate discharge with an incorporation of combined satellite-, model-, and ground-based soil moisture as an input data. The combined soil moisture data was generated using two renormalization strategies. In this study, we aimed to compare the performances of two optimization techniques associated in the PDM model, including a traditional non-linear and a newly metaheuristics algorithms, for the discharge prediction. The simulation was conducted in a coastal urban region, Hongseong, using the optimized parameter sets for flood events. The simulated results from the PDM model revealed that parameters obtained with the metaheuristics algorithm indicated a superior performance when comparing against the observed runoff data. Moreover, parameter sets obtained by the metaheuristics algorithm and non-linear technique showed significant differences. The method of this study can provide more improvements in rainfall-runoff simulation results for flood management.