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http://dx.doi.org/10.12652/Ksce.2016.36.3.0407

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

Lee, Tae Hee (Hydrological Survey Center)
Lee, Min Ho (Geum River Flood Control Office)
Yi, Jaeeung (Ajou University)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.36, no.3, 2016 , pp. 407-416 More about this Journal
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.
Keywords
Ungauged basin; Mean low flow; Basin characteristics; Regional regression model;
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Times Cited By KSCI : 2  (Citation Analysis)
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