Evaluation of a Raingauge Network Considering the Spatial Distribution Characteristics and Entropy: A Case Study of Imha Dam Basin

Currently, several government agencies operate the rainfall station for monitoring of severe weather, flood forecasting and warn-ing, and multi-purpose dam operation. The Entropy theory is usually adopted to evaluate rainfall station network (RSN) installed for special purpose. The Entropy theory, however, evaluates the RSN only by the amount of the total hydrological information, which means it considers only the characteristics of the data collected by an individual rainfall station. However, to obtain the area average rainfall properly which is one of the critical reasons to install rainfall stations, the spatial distribution of rainfall stations is also very important. In general, uniformly distributed rainfall stations produce better the area average rainfall than unevenly dis-tributed rainfall stations do. In this study, the total hydrological information and the soundness of the spatial distribution are two different physical parameters, we adopt the Euclidean distance method to consider them simultaneously. An equation obtained by the Euclidean distance method is used as the objective function in the MOGA (Multi Objective Genetic Algorithm) to determine the optimal combination of the rainfall stations for satisfying the both criteria: the maximum total amount of the hydrological information and the soundness of the spatial distribution. The suggested method is applied to the Imha Dam basin in the Nakdong river basin and the optimal RSN obtained by the suggested method shows more spatially dispersed than an RSN obtain by the entropy theory only. This result implies that the optimal RSN by the suggested method can consider both important aspects whic