홍수 빈도 예측을 위한 통계학적 모형

The Statistical Model for Predicting Flood Frequency

본 연구는 한강유역내 수위표지점 중에서 댐에 의한 인위적 유량 조작을 받지 않는 자연하천유역에서의 지점들을 대상으로 홍수빈도예측을 위한 통계학적 모형의 적용성을 비교 검토하였고 그 결과 적용 가능한 것으로 입증하였다. 또한 홍수빈도모형에 의한 홍수추정량으로 부터모형의 통계학적 효용성을 검토한 결과, 단 기간 기록년수의 자료에서 유용한 부분기간치계열 방법에 의한 POT모형이 연최대치계열 방법에 의한 ANNMAX형보다 효과적임이 판명되었다.

This study is to verify the applicability of statistical models for predicting flood frequency at the stage gaging stations selected by considering whether the flow is natural condition in the Han River basin. From the result of verification, this statistical flood frequency models showed that is fairly reasonable to apply in practice, and also were compared with sampling variance to calibrate the statistical dfficiency of the estimate of the T year flood Q(T) by two different flood frequency models. As a result, it was showed that for return periods greater than about T=10 years the annual exceedence series estimate of Q(T) has smaller sampling variance than the annual maximum series estimate. It was showed that for the range of return periods the partial duration series estimate of Q(T) has smaller sampling varianed than the annual maximum series estimate only if the POT model contains at least 2N(N:record length)items or more in order to estimate Q(T) more efficiently than the ANNMAX model.