Robust Estimator for Annual Rainfall Erosivity in Korea

Tuesday, 16 December 2014
Joon-Hak Lee1, Hyun-Keun Song2, Hongjoon Shin2 and Jun-Haeng Heo2, (1)Korea Military Academy, Seoul, South Korea, (2)Yonsei University, Seoul, South Korea
This study performed to identify appropriate parameters for estimating annual rainfall erosivity in Korea. Nine types of rainfall parameters for 28 weather stations over 20 years were used in this study. Correlation analysis between calculated rainfall erosivities and nine parameters in 28 stations were conducted to find the proper estimator of annual rainfall erosivity. The results showed a significant positive relationships between "sum of monthly precipitation for 2~5 months (called Modified IAS index)" and annual rainfall erosivity in all 28 stations with a 99% confidence. The second most strongly correlated parameter was annual precipitation; 27 of 28 stations had a siginificant relationship with 99% confidence level. The study found out "Modified IAS index" was the best robust estimator for annual rainfall erosivity more than annual precipitation in Korea.