Short-Impending Earthquake Prediction Method Based on High-Order Magnetic Anomaly Derivative and High-Order Statistic
Liu Huan
Zhao Runzhuo
Dong Haobin
Abstract：In recent years,moderate-strong earthquakes have brought indelible disasters to the safety of people's lives and properties.Hence,exploring the connection between geomagnetic fields and earthquakes,obtaining precursor information,and then realizing the prediction of moderate-strong earthquakes are vital issues that need to be solved urgently.For now,the vertical component Z of the geomagnetic field has been widely used for moderate-strong earthquake early warning.However,it still has numerous problems such as long prediction periods,difficulty in determining the threshold,and low prediction accuracy.To solve the above problems,a short-impending earthquake prediction method based on high-order magnetic anomaly derivative and high-order statistic,dubbed HMAD-HS,is proposed,which can effectively reduce the influence of Gaussian noise on the precursor geomagnetic field,shorten the prediction period,and then improve the prediction accuracy.To verify the feasibility of this method,taking the moderate-strong earthquakes of Kashgar,Xinjiang in 2017 as an example,the HMAD-HS was compared with two commonly used methods,i.e.,load-unload response ratio and geomagnetic daily ratio.The experimental results show that the precursor signals of moderate-strong earthquakes obtained by HMAD-HS are obvious,and the missing report rate and false report rate are reduced by more than 30%,which greatly improves the forecast credibility.Further,the applications of HMAD-HS for the short-term prediction of moderate-strong earthquakes in many regions of our country prove that the proposed method is universal and has a good effect on predicting moderate-strong earthquakes.
Keywords：short-impending earthquakeprecursor informationhigh-order magnetic anomaly derivativehigh-order statisticgeophysics
Publication Date：2024-08-15
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 2952-2960 )