This paper proposed a new method for estimating missing values in time series rainfall data. The proposed method integrated the two most widely used estimation methods, general linear model(GLM) and ordinary kriging(OK), by taking a weighted average of covariance matrices derived from each of the two methods. The proposed method was cross-validated using daily rainfall data at thirteen rain gauges in the Hyeong-san River basin. The goodness-of-fit of the proposed method was higher than those of GLM and OK, which can be attributed to the weighting algorithm that was designed to minimize errors caused by violations of assumptions of the two existing methods. This result suggests that the proposed method is more accurate in missing values in time series rainfall data, especially in a region where the assumptions of existing methods are not met, i.e., rainfall varies by season and topography is heterogeneous.

Abstract
 1. 서 론
 2. 재료 및 방법
  2.1. Ordinary Kriging을 수정한 새로운 결측강수량추정기법
  2.2. 추정기법 신뢰도 검증
 3. 결과 및 고찰
 4. 결 론
 참 고 문 헌

• 성찬용(계명대학교 환경대학 환경계획학과) | Chan Yong Sung (Department of Environmental Planning, Keimyung University) Corresponding author