Water for future (물과 미래)

Korea Water Resources Association (한국수자원학회)
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Rainfall Prediction of Seoul Area by the State-Vector Model

상태벡터 모형에 의한 서울지역의 강우예측

  • 주철 ((주)금호엔지니어링)
  • Published : 1995.10.01
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Abstract

A non-stationary multivariate model is selected in which the mean and variance of rainfall are not temporally or spatially constant. And the rainfall prediction system is constructed which uses the recursive estimation algorithm, Kalman filter, to estimate system states and parameters of rainfall model simulataneously. The on-line, real-time, multivariate short-term, rainfall prediction for multi-stations and lead-times is carried out through the estimation of non-stationary mean and variance by the storm counter method, the normalized residual covariance and rainfall speed. The results of rainfall prediction system model agree with those generated by non-stationary multivariate model. The longer the lead time is, the larger the root mean square error becomes and the further the model efficiency decreases form 1. Thus, the accuracy of the rainfall prediction decreases as the lead time gets longer. Also it shows that the mean obtained by storm counter method constitutes the most significant part of the rainfall structure.

강우의 평균과 분산이 시 공간적으로 변하는 비정상 다변량 모형을 강우모형으로 선정하였다. 그리고 강우모형의 상태 및 매개변수의 추정을 위해 비정상 대변량 모형의 잔차항에 Kalman Filter 순환추정 알고리즘을 적용하여 강우예측모형 시스템을 구성하였다. 그후 반응시간이 짧은 도시지역에 설치된 T/M 강우관측소에 입력되는 매 시간(10분간격) 강우자료를 사용하여 호우개수방법에 의한 비정상(Non-stationary) 평균과 분산의 추정 그리고 호우속도 추정을 통한 정규잔차 공분산을 추정하여 다수의 지점들 및 선행시간들의 실시간 다변량 단기 강우예측 (On-line, Real-time, Multivariate Short-term, Rainfall Prediction)을 하였다. 강우예측시스템 모형에 의한 결과와 비정상 변량 모형에 의한 강우모의 결과가 잘 일치하였다. 그리고 예측정도를 측정하는 방법인 제곱 평균 제곱근 오차(RMSE)와 모형 효율성 계수(ME)를 분석한 결과, 강우 예측시간 즉 선행시간이 갈수록 제곱 평균 제곱근 오차가 커지고 모형 효율성 계수가 1로부터 점차 작아지는 것으로 보아 강우예측 정도가 떨어지는 것을 알 수 있었다. 또한 호우개수방법으로 구한 평균이 호우구조의 많은 부분을 차지하고 있음을 알 수 있었다.

Keywords

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