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Updated: Jan 20, 2026
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Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
Published on: June 27, 2025
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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
1Department of Physics University of Azad Jammu and Kashmir, Muzaffarbad, 13100, Azad Kashmir, Pakistan.
Summary
This study introduces a novel method for earthquake prediction using soil radon gas (SRG) time series data and boxplots. Analysis reveals patterns in radon levels linked to seismic activity, potentially enabling earlier earthquake forecasting.
Area of Science:
- Geophysics
- Environmental Science
- Seismology
Background:
- Studies have linked radon anomalies to meteorological factors and earthquakes.
- Soil radon gas (SRG) monitoring is a potential precursor for seismic events.
Purpose of the Study:
- To analyze soil radon time series data for earthquake prediction.
- To investigate the utility of boxplots for interpreting radon patterns related to seismic activity.
Main Methods:
- Descriptive statistical analysis of soil radon gas (SRG) time series data collected over a fault line.
- Utilized RTM 1688-2 radiometric instrument for SRG measurements.
- Applied boxplot analysis to identify patterns in SRG concentrations and meteorological parameters.
Main Results:
- SRG data followed a normal distribution, with consistent measurements indicated by coefficient of variation (CV).
- Boxplot analysis revealed specific patterns in radon concentrations (outliers, IQR variations) associated with pre-earthquake seismic activities.
- No significant patterns were found in the dispersion of meteorological factors.
Conclusions:
- Boxplot interpretation of SRG time series offers a potential method for early earthquake prediction.
- This approach may provide an alternative to complex predictive systems.
- This study represents a novel attempt to predict earthquakes using boxplot analysis of radon data.
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