Evaluation of Parameter Characteristics of a Storage Function Model

Abstract

Applying a lumped runoff model in ungauged basins requires the relationships between the parameter characteristics of a model with watershed characteristics. The authors of this study designed various methods to evaluate the parameter characteristics of the storage function model using the kinematic wave model. They applied genetic algorithms to 101 observed events at 17 dam basins in Korea. The results confirmed that there is a limit to developing an empirical equation for parameter estimation on the basis of observed data. As part of the measures taken to overcome the limit, a runoff simulation was implemented that considered 35,000 various conditions by configuring virtual basins, and the parameter of the storage function model was evaluated based on the results. Hence, the authors discovered that a lag time of the storage function method is primarily determined to be closely connected with the characteristics of the longest stream, and the storage coefficient has high relevancy with the basic characteristics.