There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune’s source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

Recent two moderate earthquakes (2016 Mw=5.4 Gyeongju and 2017 Mw=5.5 Pohang) in Korea provided the unique chance of developing a set of relations to estimate instrumental seismic intensity in Korea by augmenting the time-history data from MMI seismic intensity regions above Ⅴ to the insufficient data previously accumulated from the MMI regions limited up to Ⅳ. The MMI intensity regions of Ⅴ and Ⅵ was identified by delineating the epicentral distance from the reference intensity statistics in distance derived by using the integrated MMI data obtained by combining the intensity survey results of KMA (Korea Meteorological Administration) and ‘DYFI (Did You Feel It)’ MMIs of USGS. The time-histories of the seismic stations from the MMI intensity regions above Ⅴ were then preprocessed by applying the previously developed site-correction filters to be converted to a site-equivalent condition in a manner consistent with the previous study. The average values of the ground-motion parameters for the three ground motion parameters of PGA, PGV and BSPGA (Bracketed Summation of PGA per second for 30 seconds) were calculated for the MMI=Ⅴ and Ⅵ and used to generate the dataset of the average values of the ground-motion parameters for the individual MMIs fromⅠ to Ⅵ. Based on this dataset, the linear regression analysis resulted in the following relations with proposed valid ranges of MMI.