In the long-term observation of geomagnetic field, the levelness of coil vector magnetometer will affect the measurement of magnetic direction. Therefore, we propose an electrical detection method of instrument non-levelness, which realizes the quantitative calculation of non-levelness by measuring the maximum and minimum values of the resultant magnetic field during detection. Then, a horizontal error model of coil vector magnetometer is constructed, and the mapping from instrument non-levelness to declination measurement error can be realized by vector operation. The results show that when the non-levelness of the instrument is less than 10", the measurement of magnetic declination variation deviates from the real value by 3.4%; When the non-levelness of the instrument is less than 20", the measurement of magnetic declination variation deviates from the real value by 13.5%.
Groundwater monitoring is an indispensable approach to earthquake prediction in China. However, there are many different time-scales of nonlinear interferences in the observation data, by restricting the condition of most monitoring well. So, it is necessary to identify and eliminate these interferences by using advanced signal processing method. In this study, we take Wanshan well in Hubei province as an example, present a method of micro-dynamic response signal reconstruction based on EMD and frequency spectrum analysis. The result shows that water level date can be decomposed in 12 IMF components with definite physical significance, including earth tide(IMF1~5), rainfall(IMF6~8), climate(RES), and tectonic activity(IMF9~12). Finally, we reconstruct the water micro-dynamic signal by using IMF9~12, and discuss the relationship between seismic activity and the micro-dynamic signal from Jan.1 2014 to Nov.1 2015. The result indicates that the micro-dynamic of Wanshan well responding to the seismic activity around BeiheXiangfan-Guangji faults synchronously and obviously. The method can be prospective used in precursory anomaly discriminate and earthquake trend predict.
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