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Development of Regional Regression Model for Estimating Mean Low Flow in Ungauged Basins

미계측 유역 평균갈수량 산정을 위한 지역회귀모형의 개발

  • 이태희 (유량조사사업단 낙동강조사실) ;
  • 이민호 (국토교통부 금강홍수통제소 예보통제과) ;
  • 이재응 (아주대학교 건설시스템공학과)
  • Received : 2016.04.01
  • Accepted : 2016.04.25
  • Published : 2016.06.01

Abstract

The purpose of this study is to develop regional regression models to estimate mean low flow for ungauged basins. The unregulated streamflow data observed at 12 multipurpose dams and 4 irrigation dams were analyzed for determining mean low flows. Various types of regression models were developed using the relationship between mean low flows and various sets of watershed characteristics such as drainage area, average slope, drainage density, mean annual precipitation, runoff curve number. The performance of each regression model for estimating mean low flows was assessed by comparison with the results obtained from the observed data. It was found that a regional regression model explained by drainage area, the mean annual precipitation, and runoff curve number showed the best performance. The regression model presented in this study also gives better estimates of mean low flow than the estimates by the drainage-area ratio method and the previous regression model.

본 연구에서는 미계측 유역의 평균갈수량 추정을 위한 지역회귀모형을 개발하고자 하였다. 12개 다목적댐과 4개의 용수댐에서 관측된 조절되지 않은 유입량 자료로부터 평균갈수량을 산정하였고, 이를 유역면적, 유역경사, 유역밀도, 연평균강수량, 유출곡선지수 등의 유역특성인자와의 상관분석을 통해 다양한 형태의 지역회귀모형을 개발하였다. 평균갈수량의 관측값과 추정값의 비교를 통해 각 회귀모형의 성능을 평가하였고, 유역면적, 연평균강수량, 유출곡선지수를 설명변량으로 하는 회귀모형이 가장 우수한 성능을 보였다. 또한 비유량법과 기존에 개발된 기존회귀모형과의 비교를 통해서 본 연구에서 개발한 모형의 적용성이 가장 우수한 것으로 분석되었다.

Keywords

References

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