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http://dx.doi.org/10.15681/KSWE.2016.32.3.310

A Study on Use of Radar Rainfall for Rainfall-Triggered Mud-Debris Flows at an Ungauged Site  

Jun, Hwandon (Department of Civil Engineering, Seoul National University of Science and Technology)
Lee, Jiho (Department of Civil Engineering, Seoul National University of Science and Technology)
Kim, Soojun (Columbia Water Center, Columbia University)
Publication Information
Journal of Korean Society on Water Environment / v.32, no.3, 2016 , pp. 310-317 More about this Journal
Abstract
It has been a big problem to estimate rainfall for the studies of mud-debris flows because the estimated rainfall from the nearest AWS (Automatic Weather Station) can tend to be quite inaccurate at individual sites. This study attempts to improve this problem through accurate rainfall depth estimation by applying an artificial neural network with radar rainfall data. For this, three models were made according to utilizing methodologies of rainfall data. The first model uses the nearest rainfall, observing the site from an ungauged site. The second uses only radar rainfall data and the third model integrates the above two models using both radar and observed rainfall at the sites around the ungauged site. This methodology was applied to the metropolitan area in Korea. It appeared as though the third model improved rainfall estimations by the largest margin. Therefore, the proposed methodology can be applied to forecast mud-debris flows in ungageed sites.
Keywords
Artificial neural network; Automatic weather station; Mud-debris flow; Radar rainfall;
Citations & Related Records
Times Cited By KSCI : 11  (Citation Analysis)
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