Soil radon (Rn-222) has been continuously monitored at Badargadh station (23.47°N, 70.62°E) in Kutch region of Gujarat to study the pre-seismic anomalies prior to occurrence of local earthquakes. This monitoring site is in close proximity to the South Wagad Fault, a seismically active fault in the study area. The raw data of radon along with meteorological parameters such as temperature, pressure and humidity in soil of this station for the period of January 01 to December 31, 2017 with a sampling interval of 10 min were used in the analysis. The wind speed and rainfall data of the corresponding period were collected from the nearest weather station. From descriptive statistics, we found an average soil radon concentration of 343 Bq.m⁻³. It is observed that radon has a maximum concentration during the rainy season compared to the other two seasons. We found that radon emission rate is less during mid-nights and early morning, whereas, the radon emission is more during afternoon hours when the sun light intensity is more. In order to identify and extract the periodic oscillations in the radon time series, the Empirical Mode Decomposition (EMD) was applied to the soil radon (Rn-222) time series by decomposing it into different oscillatory modes known as the Intrinsic Mode Function (IMF). Several interesting non-linear features emerged from the analysis after applying Hilbert Huang Transform (HHT) on significant IMFs. The temporal variation of the instantaneous energy is well correlated with four local earthquakes during the study period. Most interestingly, intermittencies in the temporal evolution of the instantaneous energy function have been observed prior to these local earthquakes. We present the results of the seismic and aseismic periods as well as a brief discussion of the analysis of radon data which can be used as a precursor of seismic activity. It is now possible to identify anomalies in radon time series using EMD based HHT method even for small-magnitude earthquakes.

在古吉拉特邦库奇地区的Badargadh站（北纬23.47°，东经70.62°）连续监测了土壤ra（Rn-222），以研究地震发生前的地震前异常。该监测站紧邻研究区的地震活动断层南瓦加德断层。分析使用了该站2017年1月1日至2017年12月31日期间of的原始数据以及气象参数，例如温度，压力和湿度，采样间隔为10分钟。从最近的气象站收集了相应时期的风速和降雨数据。根据描述性统计，我们发现平均土壤ra浓度为343 Bq.m ^-3。可以看出，与其他两个季节相比，在雨季中ra的浓度最大。我们发现，在午夜和清晨，ra的排放量较少，而在太阳光强度较大的下午，during的排放量较多。为了识别和提取the时间序列中的周期性振荡，将经验模式分解（EMD）分解为土壤soil（Rn-222）时间序列，方法是将其分解为不同的振荡模式，称为固有模式函数（IMF） ）。在重要的IMF上应用希尔伯特·黄变换（HHT）后，分析得出了一些有趣的非线性特征。在研究期间，瞬时能量的时间变化与四个地方地震有很好的相关性。最有趣的是 在这些局部地震之前，已经观察到瞬时能量函数的时间演化的间歇性。我们介绍了地震和地震周期的结果，并简要讨论了可以用作地震活动前兆的ra数据分析。现在，即使对于小震级地震，也可以使用基于EMD的HHT方法来识别for时间序列中的异常。