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http://dx.doi.org/10.3741/JKWRA.2019.52.1.21

Evaluation of GPM satellite and S-band radar rain data for flood simulation using conditional merging method and KIMSTORM2 distributed model  

Kim, Se Hoon (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Jung, Chung Gil (Texas A&M AgriLife Research Center at El Paso)
Jang, Won Jin (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Kim, Seong Joon (Department of Civil, Environmental and Plant Engineering, Konkuk University)
Publication Information
Journal of Korea Water Resources Association / v.52, no.1, 2019 , pp. 21-33 More about this Journal
Abstract
This study performed to simulate the watershed storm runoff using data of S-band dual-polarization radar rain, GPM (Global Precipitation Mission) satellite rain, and observed rainfall at 21 ground stations operated by KMA (Korea Meteorological Administration) respectively. For the 3 water level gauge stations (Sancheong, Changchon, and Namgang) of NamgangDam watershed ($2,293km^2$), the KIMSTORM2 (KIneMatic wave STOrm Runoff Model2) was applied and calibrated with parameters of initial soil moisture contents, Manning's roughness of overland and stream to the event of typhoon CHABA (82 mm in watershed aveprage) in $5^{th}$ October 2016. The radar and GPM data was corrected with CM (Conditional Merging) method such as CM-corrected Radar and CM-corrected GPM. The CM has been used for accurate rainfall estimation in water resources and meteorological field and the method combined measured ground rainfall and spatial data such as radar and satellite images by the kriging interpolation technique. For the CM-corrected Radar and CM-corrected GPM data application, the determination coefficient ($R^2$) was 0.96 respectively. The Nash-Sutcliffe efficiency (NSE) was 0.96 and the Volume Conservation Index (VCI) was 1.03 respectively. The CM-corrected data of Radar and GPM showed good results for the CHABA peak runoff and runoff volume simulation and improved all of $R^2$, NSE, and VCI comparing with the original data application. Thus, we need to use and apply the radar and satellite data to monitor the flood within the watershed.
Keywords
Radar; GPM; Kriging; KIMSTORM2; Conditional merging; Distributed rainfall-runoff model;
Citations & Related Records
Times Cited By KSCI : 12  (Citation Analysis)
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