Literature DB >> 31473581

Descriptive analysis and earthquake prediction using boxplot interpretation of soil radon time series data.

Aleem Dad Khan Tareen1, Malik Sajjad Ahmed Nadeem2, Kimberlee Jane Kearfott3, Kamran Abbas4, Muhammad Asim Khawaja5, Muhammad Rafique6.   

Abstract

Correlation of radon anomalies with meteorological parameters and earthquake occurrence has been reported in many studies. This paper reports descriptive statistical analysis and boxplot contingent earthquake prediction based upon soil radon time series data. Data has been collected over a fault line, passing beneath the Muzaffarabad, for the period of one year. Soil radon gas (SRG) was measured using RTM 1688-2 radiometric instrument (made by SARAD GmbH). The range of radon in soil was found to be 14349 Bqm-3, whereas the ranges of temperature, pressure and relative humidity were found as 38.50 C0, 29 mbar and 67% respectively. SRG data shows that time series follows normal distribution. Values of coefficient of variation (CV) indicate the consistency of the recorded values of radon in soil and metrological parameters. Variance inflation factor (VIF) and Durbin Watson test (d) indicate a moderate multicollinearity and autocorrelation between variables. The analysis of radon time series using boxplots and meteorological parameters show specific patterns in radon concentrations (outliers, variant IQRs, first quartile values, and median values) due to pre-earthquake underground seismic activities. On the basis of these patterns earthquake may be more early predicted without using complicated predictive systems. Boxplots also predicted that there is no significant pattern found in dispersion of meteorological factors measured in this study. To the best of our knowledge this is first ever attempt to predict earthquake using boxplot explanation.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Boxplots; Meteorological parameters; Radon anomalies; Soil radon gas

Year:  2019        PMID: 31473581     DOI: 10.1016/j.apradiso.2019.108861

Source DB:  PubMed          Journal:  Appl Radiat Isot        ISSN: 0969-8043            Impact factor:   1.513


  2 in total

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  2 in total

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