10.4122/1.1000001290 Katayama, K. Kimijima, K. Yamanaka, O. Nagaiwa, A. Ono, Y. Stormwater inflow prediction using radar rainfall data compressed by principal component analysis DTU Library, Technical University of Denmark (DTU) 2005 principal component analysis radar rainfall stormwater inflow prediction system identification Toshiba Corporation, Social Systems R&D Dept. Toshiba Corporation, Electrical and Control Systems engineering Dept. 2 en Conference full text 10.4122/1.1000001289 application/pdf 1 This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to preprocessing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.