Comparison of Field Survey-Based Macroseismic Intensity Map and Numerical Macroseismic Intensity Maps Using MARS and Multiple Regression Methods for 6th of February 2023 Kahramanmaraş Earthquakes

Abstract

Earthquakes are natural events that cause damage to built environments by the instant seismic energy release. This energy is measured by instrumental devices to obtain the peak ground motion parameters such as Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV). Additional measurements based on the questionnaires after the earthquakes are required to identify the felt or macro seismic intensity levels. These measurements are crucial to identify the total effects of earthquakes over not only an area but also for the spatial distribution of ground motion parameters. For this purpose, it is important to study the multi-variable criteria correlations between ground motion parameters and Modified Mercalli Intensity (MMI) levels based on linear relationships of predictor variable couples. In this regard, the Multivariate Adaptive Regression Splines (MARS) Method and the Multiple Linear Regression Method are used. The entire dataset is composed of 69 earthquakes between 2005 and 2022 with 2171 ground motion parameters coupled with MMI levels. For MMI-based correlations, the MARS method is used to identify the non-linearities between predictor variables by piecewise linear functions, but for the Multiple Linear Regression Method, the least correlated variables of PGA-Epicentral Distance and PGV-Epicentral Distance are used to obtain the relationship between MMI and PGM parameters. The resulting equations obtained for the entire Türkiye database are performed to identify MMI maps of the 6th of February 2023, Kahramanmaraş Earthquakes, and these maps are used to check the accuracy of the results by the comparison of field survey-based MMI maps. Finally, the numerical MMI maps are found to be consistent with the field survey-based MMI maps. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.