TY - JOUR
T1 - Evaluation of error indices of radar rain rate targeting rainfall-runoff analysis
AU - Yoo, Chulsang
AU - Ku, Jung Mo
AU - Yoon, Jungsoo
AU - Kim, Jungho
N1 - Funding Information:
This work was supported by the Basic Science Research Program, through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).
Publisher Copyright:
© 2016 American Society of Civil Engineers.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - This study evaluates several error indices of the radar rain rate from the viewpoint of the accuracy of rainfall-runoff analysis. The error indices considered in this study are the mean error (ME), mean absolute error (MAE), normalized standard deviation (NSD), correlation coefficient (CC), bias (BS), and radar rain rate quality criterion (RRQC). These indices were analyzed using the concept of sum of squares (SS) and mean squares (MS) in the analysis of variance (ANOVA), which explains how the bias and random error of the radar rain rate are combined in an error index. Also, these error indices were linked to the errors in the runoff result, such as the total runoff volume, peak flow, and peak time. As an application, two dam basins in Korea were selected, the Chungju Dam basin and the Namgang Dam basin. The radar rain rates from Gwangdeoksan Radar and Gudeoksan Radar were used as input for the rainfall-runoff analysis. Six different rainfall events were applied to secure various rainfall types. As a result, it was found that ME, BS, and RRQC were linearly proportional to the errors in the runoff result. This result indicates that the bias plays a dominant role in the evaluation of the radar rain rate, targeting the rainfall-runoff analysis.
AB - This study evaluates several error indices of the radar rain rate from the viewpoint of the accuracy of rainfall-runoff analysis. The error indices considered in this study are the mean error (ME), mean absolute error (MAE), normalized standard deviation (NSD), correlation coefficient (CC), bias (BS), and radar rain rate quality criterion (RRQC). These indices were analyzed using the concept of sum of squares (SS) and mean squares (MS) in the analysis of variance (ANOVA), which explains how the bias and random error of the radar rain rate are combined in an error index. Also, these error indices were linked to the errors in the runoff result, such as the total runoff volume, peak flow, and peak time. As an application, two dam basins in Korea were selected, the Chungju Dam basin and the Namgang Dam basin. The radar rain rates from Gwangdeoksan Radar and Gudeoksan Radar were used as input for the rainfall-runoff analysis. Six different rainfall events were applied to secure various rainfall types. As a result, it was found that ME, BS, and RRQC were linearly proportional to the errors in the runoff result. This result indicates that the bias plays a dominant role in the evaluation of the radar rain rate, targeting the rainfall-runoff analysis.
KW - Error index
KW - Radar rain rate
KW - Runoff error
UR - http://www.scopus.com/inward/record.url?scp=84983065008&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)HE.1943-5584.0001393
DO - 10.1061/(ASCE)HE.1943-5584.0001393
M3 - Article
AN - SCOPUS:84983065008
SN - 1084-0699
VL - 21
JO - Journal of Hydrologic Engineering - ASCE
JF - Journal of Hydrologic Engineering - ASCE
IS - 9
M1 - 05016021
ER -