Statistical characteristics analysis on the relationship between radon anomalies and earthquakes in Yunnan region
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摘要:
通过梳理1976—2022年震例总结报告中云南地区73组MS≥5.0地震的氡测项异常，对其特征予以统计分析。结果表明：73组地震中有63组震前出现水氡异常，震前6个月内的短期异常占总异常的71%，3个月内的短临异常占总异常的49%，地震前3个月异常数量增加显著；震级越大，异常分布越远离震中，震前1个月新出现的异常大部分集中在震中附近。相对而言，由于测点位置和观测技术方面的原因，气氡积累的震例远远少于水氡，但具有短期异常占比较高的优势。随着气氡观测技术的不断改进和观测经验的不断积累，其捕捉地震异常信息的能力也将会不断提升。
Abstract:This paper is based on the summary report of Yunnan earthquake cases from 1976 to 2022.It sorts out 73 sets of earthquakes with M≥5.0 one by one, and extracts abnormal information of radon measurement items before earthquakes, then explores the characteristics of radon precursory anomalies.The results are as follows:
1） There were 190 water radon anomalies among 63 out of 73 earthquakes. There were a large number of anomalies and a low earthquake missing rate, indicating that water radon observation have good monitoring capability for regional earthquakes. However, the proportion of gas radon anomalies is relatively low by comparison. In our earthquake cases, there were five gas radon anomalies among only four out of 39 earthquakes, showing a higher earthquake missing rate. But as for the measurement sites with good basic conditions, gas radon anomalies have a high repetition rate, and correspond well to earthquakes. Among the five radon anomalies accumulated in historical earthquake cases, three of them were observed by gas radon well Gaoda.
2） The water radon anomalies appeared mainly within six months before earthquakes with M≥5.0, accounting for 71% of the total anomalies. Among them, anomalies within three months account for 49% of the total anomalies. Starting from the year before the M5.0−5.9 earthquakes, the number of water radon anomalies in different stages increased significantly. One month before the earthquake, most of the anomalies showed a turning point and then returned to normal level, with a decrease in the number of anomalies. On the other hand, there are not many earthquake cases with abnormal gas radon concentration, but all anomalies are within six months before earthquakes, of which 80% are within three months.
3） The spatial distribution of water radon anomalies is different before earthquakes with different magnitudes. Before the earthquakes with magnitude 5.0−5.9, the closer to the time of the earthquake occurrence, the more anomalies are concentrated near the epicenter. During the period of more than six months prior to the earthquake, the anomalies are scattered in space. Starting from six months before the quake, the number of anomalies within a 100 km radius of the epicenter gradually increased. Starting from one month before the earthquake, most of the anomalies outside the 100 km radius of the epicenter showed a turning point and then returned to normal level, the anomalies are concentrated near the epicenter, which can provide reference for location tracking. Before earthquakes with magnitude 6.0 or above, more water radon anomalies appeared in the areas far from the epicenter, which were relatively scattered. Such anomalies appearing in a large area may indicate that the stress levels in the entire field were increasing. In this state, potential risk of a major earthquake is likely higher. There are relatively few earthquake cases with gas radon anomalies, and the spatial distribution characteristics are not obvious.
This paper is based on the summary report of earthquake cases, which shows that there are more anomalies in water radon than in gas radon, and the prediction effect is better than that of gas radon. This is consistent with the practical results reflected by the technical personnel after actual use of the data. Several possible main reasons are: Firstly, the observation sites of water radon are more focused on deep circulating hot spring water, which is more likely to reflect deep tectonic activity. Secondly, the observation methods of water radon and gas radon are different. Water radon is observed by manually collecting water samples and detecting, and the technology is relatively stable. However, gas radon is observed automatically, but the stability of the devices for extracting radon gas from water and collecting it has not been fully solved, and the technology from gas collection to automatic detection process is not mature yet. In addition, the efficiency and stability of degassing directly affect the observation quality of data. Thirdly, at some observation sites the escaping gas was extracted from static water level wells to observe the radon concentration, which is difficult to reflect information from deep Earth.
Overall, the differences in the effectiveness of water radon and gas radon data in earthquake prediction are caused by factors such as the location of measurement sites and observation techniques. At present, the observation data of gas radon in Yunnan has not yet achieved the effect of water radon in earthquake prediction. However, gas radon observation has advantages that water radon does not have, such as higher automation, faster transmission, higher data sampling rates. Technology-oriented and intelligentization are the main development tendency of radon observation. With the improvement of observation technology and the accumulation of observation experience, the ability to capture seismic anomaly will also be strengthen.
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Keywords:
- radon /
- seismic anomaly /
- earthquake prediction /
- statistical characteristics
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1 ① 樊文杰，贺素歌，赵小艳，胡小静，刘强，王光明， 张潜，李智蓉， 刘自凤，孙楠，彭关灵， 李永莉。2021。2021年5月21日云南省漾濞6.4级地震。昆明：云南省地震局：1−76。2 ② 贺素歌，赵小艳，钱晓东，刘自凤，李智蓉，张潜，刘强。2021。2021年6月10日双柏MS5.1地震。昆明：云南省地震局：1−69。3 ③ 张潜，赵小艳，贺素歌，樊文杰，刘翔，张翔。2021。2021年6月12日云南省盈江5.0级地震。昆明：云南省地震局：1−47。4 ④ 罗睿洁，李利波，张天宇，王光明，刘自凤，张潜，刘强，樊文杰，付虹。2022。2022年1月2日宁蒗MS5.5地震。昆明：云南省地震局：1−80。5 ⑤ 刘强，樊文杰，高文斐，曾宁。2022。2022年11月19日云南红河5.0级地震。昆明：云南省地震局：1−65。 -
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图 1 云南氡观测点及地震震中分布
Figure 1. Distribution of radon observation points and earthquake epicenters in Yunnan
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图 2 云南氡观测台项时间进程图
Figure 2. Variation of the number of radon observation stations in Yunnan with time
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图 3 水氡异常与地震关系统计分布图
（a） 不同震级档异常数量分布；（b） 地震前不同阶段异常数量占比；（c） 地震前不同震级档、不同时段异常数量分布
Figure 3. Statistical distribution chart of the relationship between water radon anomalies and earthquakes
（a） Distribution of anomalies in different magnitude ranges；（b） The proportion of anomalies in different stages before earthquakes；（c） Distribution of anomalies in different ranges and different time periods before earthquakes
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图 5 气氡异常数量统计分布图
（a） 不同震级档异常数量占比；（b） 地震前不同阶段异常数量占比
Figure 5. Statistical distribution chart of gas radon anomalies
（a） The proportion of anomalies in different magnitude ranges；（b） The proportion of anomalies in different stages before earthquakes
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图 6 出现水氡异常的观测点的震中距与震级关系统计分布图
（a） 所有地震；（b） 震前1年以上；（c） 震前6—12个月；（d） 震前3—6个月；（e） 震前1—3个月；（f） 震前1个月内
Figure 6. Statistical distribution chart of the relationship between the distance from the observation point of water radon anomaly to the epicenter and the magnitude of the earthquake
（a） All earthquakes；（b） More than 1 year before the earthquake；（c） 6—12 months before the earthquake；（d） 3—6 months before the earthquake；（e） 1—3 months before the earthquake； （f） One month before the earthquake
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图 7 出现气氡异常的观测点的震中距与震级关系统计图
Figure 7. Statistical distribution chart of the relationship between the distance from the observation point of gas radon anomaly to the epicenter and the magnitude of the earthquake
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图 8 高大井水体水化学分析
（a） Piper图；（b） Na-K-Mg三角图；（c） 氢氧同位素组成 （胡小静等，2018）
Figure 8. Hydrochemical analysis of groundwater in Gaoda well
（a） Piper diagram；（b） The triangle diagram of Na-K-Mg；（c） Hydrogen and oxygen isotopes （Hu et al，2018）
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