A synthetic method for earthquake prediction by multidisciplinary data
Yongxian Zhang (),
Fuwang Gao,
Jianjun Ping () and
Xiaotao Zhang
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2013, vol. 69, issue 2, 1199-1209
Abstract:
China Metropolitan area around Beijing is one of the earthquake test sites in Continental China. Through more than 20 years of hard work, abundant seismic, geological, geophysical and geochemical data have been obtained, and the variation of seismic, geophysical and geochemical parameters was recorded before several strong earthquakes and some moderate earthquakes in this area. In this paper, we chose 19 high qualified observatory parameters in this area to establish a multidisciplinary system for earthquake forecast, including apparent resistivity, ground water level, ground-level, tilt, radon content in groundwater, volumetric strain, Hg content in groundwater, low frequency electric signal. We calculate the synthetic information by a simple algorithm. The procedure is: firstly, we detect the abnormal intervals of the observatory data by some data analysis methods such as filtering, differencing, etc.; secondly, we endow the value of 1 to the abnormal intervals and 0 to other intervals and produce a new time series of data set of the ith parameter; thirdly, we compose the value of the new time series of 19 observatory parameters and obtain the normalized value as called synthetic information. The result shows that there are high correlations between the high synthetic information and the earthquakes with M ≥ 5.0 in this area. The earthquakes almost occurred several days to several months after the peak value of the synthetic information. This synthetic method might be taken for a short-term prediction method for M ≥ 5.0 earthquakes in this area. Copyright Springer Science+Business Media B.V. 2013
Keywords: Earthquake prediction test site; Synthetic information; Multidisciplinary data; China Metropolitan area around Beijing (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s11069-011-9961-y
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