RESEARCH PROGRESS AND PROSPECT OF SEISMIC FLUID GEOCHEMISTRY IN SHORT-IMMINENT EARTHQUAKE PREDICTION

doi:10.3969/j.issn.0253-4967.2023.03.001

SEISMOLOGY AND GEOLOGY ›› 2023, Vol. 45 ›› Issue (3): 593-621.DOI: 10.3969/j.issn.0253-4967.2023.03.001

• Review • Previous Articles Next Articles

RESEARCH PROGRESS AND PROSPECT OF SEISMIC FLUID GEOCHEMISTRY IN SHORT-IMMINENT EARTHQUAKE PREDICTION

LI Ying¹⁾(), FANG Zhen²^,³^,⁴⁾, ZHANG Chen-lei⁵⁾, LI Ji-ye⁶⁾, BAO Zhi-cheng⁷⁾, ZHANG Xiang⁸⁾, LIU Zhao-fei¹⁾, ZHOU Xiao-cheng¹⁾, CHEN Zhi¹⁾, DU Jian-guo¹⁾

¹⁾ Key Laboratory of Earthquake Prediction, Institute of Earthquake Forecasting, China Earthquake Administration, Beijing 100036, China
²⁾ Anhui Earthquake Agency, Hefei 230031, China
³⁾ Mengcheng National Geophysical Observatory, Mengcheng 233500, China
⁴⁾ Anhui Key Laboratory of Subsurface Exploration and Earthquake Hazard Risk Prevention(in prep.), Hefei 230031, China
⁵⁾ Shaanxi Earthquake Agency, Xi'an 710068, China
⁶⁾ Heilongjiang Earthquake Agency, Harbin 150090, China
⁷⁾ Jiangxi Earthquake Agency, Nanchang 330026, China
⁸⁾ Yunnan Earthquake Agency, Kunming 650224, China

Received:2023-01-30 Revised:2023-03-14 Online:2023-07-18 Published:2023-07-18

地震流体地球化学短临预测研究进展与展望

李营¹⁾(), 方震²^,³^,⁴⁾, 张晨蕾⁵⁾, 李继业⁶⁾, 鲍志诚⁷⁾, 张翔⁸⁾, 刘兆飞¹⁾, 周晓成¹⁾, 陈志¹⁾, 杜建国¹⁾

¹⁾ 中国地震局地震预测研究所, 中国地震局地震预测重点实验室, 北京 100036
²⁾ 安徽省地震局, 合肥 230031
³⁾ 蒙城地球物理国家野外科学观测研究站, 蒙城 233500
⁴⁾ 地下结构探测与震灾风险防范安徽省重点实验室(筹), 合肥 230031
⁵⁾ 陕西省地震局, 西安 710068
⁶⁾ 黑龙江省地震局, 哈尔滨 150090
⁷⁾ 江西省地震局, 南昌 330026
⁸⁾ 云南省地震局, 昆明 650224

作者简介:
李营, 男, 1978年生, 2007年于中国科学院地球化学研究所获流体地球化学专业博士学位, 研究员, 主要从事活动构造带流体地球化学特征及地球深部流体成因研究, E-mail: liying@ief.ac.cn。
基金资助:
国家自然科学基金(42073063); 联合国教科文组织国际地球科学计划(IGCP-724); 安徽蒙城地球物理国家野外科学观测研究站联合开放基金项目(MENGO-202013); 安徽蒙城地球物理国家野外科学观测研究站联合开放基金项目(MENGO-202305)

Abstract

Abstract:

Establishing the method of short-imminent earthquake prediction is the most effective way to reduce losses caused by earthquakes and is also an important scientific issue. In the 1960s and 1970s, research on earthquake prediction was carried out successively in China and other countries in the world, and after over 50 years of development, abundant precursor observation data and earthquake cases have been accumulated, and significant progress has been made in the research of formation mechanisms of precursor anomalies and prediction methods.
Fluid is the most active component in the earth’s interior, and the fluids in various layers of the earth often carry characteristic geochemical information. The composition and variation of seismic fluid geochemistry are sensitive to changes of underground physical and chemical conditions, making them powerful indicators of seismic and tectonic activities. The formation mechanisms of fluid geochemical precursor anomalies mainly include liquid mixing, water-rock reaction, deep magma upwelling, seismic wave vibration, pore compression and pressure solubility mechanism. The fluid chemical anomalies associated with earthquakes can be attributed to the migration process of liquid mixing and the water-rock reaction mechanism caused by crustal stress changes.
This paper systematically summarizes the empirical formulas on the duration of anomaly, earthquake magnitude and epicentral distance, as well as the seismic fluid geochemical models and methods for short-imminent prediction established both domestically and internationally. In addition, four types of seismic fluid geochemical techniques and methods currently used in earthquake situation consultation in China are described. Nine of the most widely used prediction methods are selected to inspect the twenty-seven cases of earthquakes containing water radon or gas radon anomalies in the Earthquake Cases of China from 1997 to 2020. Generally, these methods all show strong applicability. However, empirical formulas based on different regions of the world selected to inspect the above cases generally show weak applicability. It indicates that current earthquake prediction models or methods are only representative to a certain extent, and there are still great difficulties in practical application, which also directly affects the prediction efficiency of the fluid geochemical models applied to the judgment of earthquake three elements.
Combined with our previous results, the paper puts forward the applicable theory for the precursor mechanism-based short-imminent prediction by seismic fluid geochemistry, that is, acquiring the dynamic change characteristics of the geochemical field based on the spatio-temporal dense and multi-item observation network, establishing a deep-shallow coupling anomaly genetic model based on the material cyclic reaction, and determining the temporal and spatial relationship between the evolution of regional fluid geochemical field and fluid geochemical changes at each measuring point in the fault zone. The construction of the geochemical subsystem of China Seismic Experimental Site provides a platform for capturing the short-imminent earthquake anomalies and constructing effective fluid geochemical anomaly mechanisms and models. The causes and abnormal mechanism of fluid geochemistry can be revealed and the seismic fluid geochemical short-imminent prediction method can be established in the light of the principle of seeking the source by field and combining the field and source.

Key words: earthquake, fluid geochemistry, short-imminent prediction

摘要：

建立地震短临预测方法是减轻地震灾害损失的最有效手段, 也是科学难题。流体是地球内部最为主动、活跃的组分, 携带了地球各圈层的地球化学信息。地震流体地球化学的组成和变化对地下物理化学条件的改变响应灵敏, 是指示地震和构造活动的有效指标。文中综述了国内外流体地球化学短临预测机理的研究进展, 介绍了国内外已经建立的流体地球化学地震短临预测模型和方法, 利用《中国震例》数据对主要预测模型和方法进行了检验分析, 评述了各方法的适用性和效能。结合团队已有的工作基础, 提出了基于前兆机理进行地震流体地球化学短临预测的思路, 并对中国地震科学实验场地球化学子系统的地震短临预测研究和应用进行了展望。

关键词: 地震, 流体地球化学, 短临预测

LI Ying, FANG Zhen, ZHANG Chen-lei, LI Ji-ye, BAO Zhi-cheng, ZHANG Xiang, LIU Zhao-fei, ZHOU Xiao-cheng, CHEN Zhi, DU Jian-guo. RESEARCH PROGRESS AND PROSPECT OF SEISMIC FLUID GEOCHEMISTRY IN SHORT-IMMINENT EARTHQUAKE PREDICTION[J]. SEISMOLOGY AND GEOLOGY, 2023, 45(3): 593-621.

李营, 方震, 张晨蕾, 李继业, 鲍志诚, 张翔, 刘兆飞, 周晓成, 陈志, 杜建国. 地震流体地球化学短临预测研究进展与展望[J]. 地震地质, 2023, 45(3): 593-621.

Figures/Tables 10

Table 1 Empirical formulas for seismic geochemical precursors abroad

序号	经验公式	参数含义	适用范围	参考文献
1	ρ=10^0.43M	ρ为有效前兆异常区的半径,M为震级	是大量地球化学地震预测方法的理论基础,适用性较广泛	Dobrovolsky et al., 1979
2	logT=0.76M-1.83	T为氡地震前兆异常的持续时间,M为震级		Rikitake,1988
3	M_L=2logD-0.07	D为氡地震前兆异常的持续时间,M_L为震级	适用于美国南卡罗莱纳西北部约卡西湖2.0≤M_L≤2.6的地震预测,该模型成功验证了1977年2月23日2.3级地震事件	Talwani,1979
4	t(天)=10^M/143	M为震级,t为氡异常变化的天数	适用于美国蓝山湖地区的地震预测	Fleischer et al., 1985
5	M=2log(λΔR/KT)-15.3	M为震级,λ为氡的衰变常数,ΔR为氡浓度的相对变化,K为常数,给定值为3.96×10^-¹⁷,T为氡异常变化的时间	选取世界各地震级M>5、震中距>100km的17次主震验证了模型的有效性,表明该模型具有较为广泛的应用范围	Ramola etal., 1988
6	logT_long= $0.79 m - 1.88 0.685 m - 1.57 0.80 m - 1.92 0.76 m - 1.83$	T为氡异常变化的时间, m为震级	适用于南极洲地区的地震预测模型	Ilić et al., 2005
7	M=1.93log₁₀3.58D	M为震级,D为震中距	适用于各种氡浓度检测方法	Elmaghraby etal., 2009
	log₁₀DT_P=0.63M-0.483	M为震级,D为震中距,T_P为地震引起的氡浓度最高值出现的时间	适用于地下水和温泉中的氡浓度检测方法
	log₁₀D $T r i s e 1 / 3$ =0.0347M²+0.802	M为震级,D为震中距,T_rise为氡浓度开始出现异常值到升至最高值的时间	适用于土壤气和降雨中的氡浓度检测方法
	log₁₀(DT_P-V/T_P)=0.508M-1.58	M为震级,D为震中距,T_P-V为氡浓度从最高值变化到最低值的时间,T_P为地震引起的氡浓度最高值出现的时间	适用于空气中放射性氡浓度检测以及地下水和土壤气中的氡浓度检测方法

Table 1 Empirical formulas for seismic geochemical precursors abroad

序号	经验公式	参数含义	适用范围	参考文献
1	ρ=10^0.43M	ρ为有效前兆异常区的半径,M为震级	是大量地球化学地震预测方法的理论基础,适用性较广泛	Dobrovolsky et al., 1979
2	logT=0.76M-1.83	T为氡地震前兆异常的持续时间,M为震级		Rikitake,1988
3	M_L=2logD-0.07	D为氡地震前兆异常的持续时间,M_L为震级	适用于美国南卡罗莱纳西北部约卡西湖2.0≤M_L≤2.6的地震预测,该模型成功验证了1977年2月23日2.3级地震事件	Talwani,1979
4	t(天)=10^M/143	M为震级,t为氡异常变化的天数	适用于美国蓝山湖地区的地震预测	Fleischer et al., 1985
5	M=2log(λΔR/KT)-15.3	M为震级,λ为氡的衰变常数,ΔR为氡浓度的相对变化,K为常数,给定值为3.96×10^-¹⁷,T为氡异常变化的时间	选取世界各地震级M>5、震中距>100km的17次主震验证了模型的有效性,表明该模型具有较为广泛的应用范围	Ramola etal., 1988
6	logT_long= $0.79 m - 1.88 0.685 m - 1.57 0.80 m - 1.92 0.76 m - 1.83$	T为氡异常变化的时间, m为震级	适用于南极洲地区的地震预测模型	Ilić et al., 2005
7	M=1.93log₁₀3.58D	M为震级,D为震中距	适用于各种氡浓度检测方法	Elmaghraby etal., 2009
	log₁₀DT_P=0.63M-0.483	M为震级,D为震中距,T_P为地震引起的氡浓度最高值出现的时间	适用于地下水和温泉中的氡浓度检测方法
	log₁₀D $T r i s e 1 / 3$ =0.0347M²+0.802	M为震级,D为震中距,T_rise为氡浓度开始出现异常值到升至最高值的时间	适用于土壤气和降雨中的氡浓度检测方法
	log₁₀(DT_P-V/T_P)=0.508M-1.58	M为震级,D为震中距,T_P-V为氡浓度从最高值变化到最低值的时间,T_P为地震引起的氡浓度最高值出现的时间	适用于空气中放射性氡浓度检测以及地下水和土壤气中的氡浓度检测方法

Table 2 Geochemical short-imminent earthquake prediction and analysis methods abroad

序号	方法	应用实例	参考文献
1	分层神经网络(LNN)	能够区分环境条件改变和地震活动引起的氡浓度变化	Negarestani etal.,2002
2	模型树方法(MT)	在无地震活动时期,计算得到较为真实的氡浓度测值,但在地震活动时期,计算出的氡浓度值与实测值相差较大,可根据该模型计算的结果与实测值之间的差异预测地震活动	Zmazek et al.,2003
3	箱线图分析方法	分析了巴基斯坦的穆扎法拉巴德地区监测点的氡特定模式浓度,可以识别氡浓度的异常变化,预测地震活动的发生	Aleem et al.,2019
4	主成分分析(PCA) 和变化点检测(CP)	根据冰岛北部地下水中微量元素浓度的监测数据,分析与地震活动有关的水文地球化学前兆,为预测地震活动提供研究指标	Barbieri et al.,2021
5	人工神经网络模型方法 (ANNs)	建立人工神经网络模型预测东安纳托利亚断裂带的地震,对发生的147次地震进行验证,准确度较高,误差只有2.3%	Fatih et al.,2009
		对斯洛文尼亚东南部断层土壤气中氡的浓度进行分析,在12次地震中识别出10次异常	Zmazek et al.,2010
		基于斯洛文尼亚地区的环境参数和氡浓度的监测数据预测地震,可成功预测13例地震事件中的10例	Torkar et al.,2010
6	人工神经网络模型(ANN)、多元线性回归(MLR)和决策树(DT)方法	使用不同方法识别巴勒斯坦北部地区构造活动引起的氡异常,从而预测地震的发生	Haider et al.,2021
7	变点分析及检测算法(DA算法)、贝叶斯CP算法	使用DA算法、贝叶斯CP算法对连续监测的气氡数据进行处理能够预测地震的发生,使用该方法成功预测了意大利中部地区地震	Soldati et al.,2020
8	基于异常点画圆,根据氡监测网预测地震位置和震级	可成功验证1988年伊朗Kerman地区发生的地震	Hashemi et al.,2013

Table 2 Geochemical short-imminent earthquake prediction and analysis methods abroad

序号	方法	应用实例	参考文献
1	分层神经网络(LNN)	能够区分环境条件改变和地震活动引起的氡浓度变化	Negarestani etal.,2002
2	模型树方法(MT)	在无地震活动时期,计算得到较为真实的氡浓度测值,但在地震活动时期,计算出的氡浓度值与实测值相差较大,可根据该模型计算的结果与实测值之间的差异预测地震活动	Zmazek et al.,2003
3	箱线图分析方法	分析了巴基斯坦的穆扎法拉巴德地区监测点的氡特定模式浓度,可以识别氡浓度的异常变化,预测地震活动的发生	Aleem et al.,2019
4	主成分分析(PCA) 和变化点检测(CP)	根据冰岛北部地下水中微量元素浓度的监测数据,分析与地震活动有关的水文地球化学前兆,为预测地震活动提供研究指标	Barbieri et al.,2021
5	人工神经网络模型方法 (ANNs)	建立人工神经网络模型预测东安纳托利亚断裂带的地震,对发生的147次地震进行验证,准确度较高,误差只有2.3%	Fatih et al.,2009
		对斯洛文尼亚东南部断层土壤气中氡的浓度进行分析,在12次地震中识别出10次异常	Zmazek et al.,2010
		基于斯洛文尼亚地区的环境参数和氡浓度的监测数据预测地震,可成功预测13例地震事件中的10例	Torkar et al.,2010
6	人工神经网络模型(ANN)、多元线性回归(MLR)和决策树(DT)方法	使用不同方法识别巴勒斯坦北部地区构造活动引起的氡异常,从而预测地震的发生	Haider et al.,2021
7	变点分析及检测算法(DA算法)、贝叶斯CP算法	使用DA算法、贝叶斯CP算法对连续监测的气氡数据进行处理能够预测地震的发生,使用该方法成功预测了意大利中部地区地震	Soldati et al.,2020
8	基于异常点画圆,根据氡监测网预测地震位置和震级	可成功验证1988年伊朗Kerman地区发生的地震	Hashemi et al.,2013

Fig. 1 Predicting the location of earthquake according to radon concentration anomaly of several monitoring stations(after Hashemi et al., 2013).

Table 3 Comprehensive seismo-geochemical method for earthquake prediction

序号	方法名称	适用范围	预测效果	资料来源
1	统计判据预报方法	对M_S≥5地震的预测	对发震时间的判断有较大的不确定性	张炜等,1988
2	水化短临预报整体化方案	对M_S≥5地震的短临预测	地点预测受水化观测台网分布范围的限制	王吉易等,1991
3	多层次跟踪预报方法	大(强)地震的发震时间的预测	方法中包含多个规则、指标和计算式,需不断修正	王吉易等,1991,1994
4	平面图形演化方法	时间和地点的预测	可预测M_S≥6的大地震,震中及附近观测井点需密集	邵永新等,2000

Fig. 2 Contour map of μ values from February to May, 1989(the shadows represent the μ≥0.5).

Table 4 Main indicators of the seismogeochemical method for tprediction of earthquake three elements(after CHE Yong-tai et al., 2004)

地震三要素	震级	发震时间	发震地点
预测标志	异常形态类型	异常形态类型	异常集中区的分布范围
	异常持续时间	异常的开始、转折和结束时间	异常区的时空迁移和扩展方向
	异常数量
	异常分布范围

Fig. 3 The proportion of passing the significance test(R≥R0)of the four methods in each area.

Table 5 Statistics on geochemistry anomalies based on Earthquake Cases in China(1997-2020)

Table 6 Statistics on applicability of foreign prediction formulas based on China Earthquake Cases(1997—2020)

序号	公式	适用震例数量 /个	适用比例 /%	不适用震例数量 /个	不适用比例 /%	参考文献
1	logT=0.76M-1.83	25	92.59	2	7.41	Rikitake,1988
2	ρ=10^0.43^M	26	96.30	1	3.70	Dobrovolsky et al.,1979
3	log₁₀(DT_P)=0.63M-0.483	26	96.30	1	3.70	Elmaghraby et al.,2009
4	M_L=2logD-0.07	4	14.81	23	85.19	Talwani,1979
5	t(天)=10^M/143	0	0.00	27	100.00	Fleischeretal.,1985
6	M=2log(λΔR/KT)-15.30	3	11.11	24	88.89	Ramola et al.,1988
7	logT_long=0.685m-1.57	0	0.00	29	100.00
8	D=10^0.32^M(10<D≤50) D=100.43M(50<D≤100) D=100.56M(100<D≤500) D=100.63M(500<D≤1250)	5	18.52	22	81.48	Virk,1996
9	M_min<M<M_max,M_min=(logR)/0.43, M_max=(logL)/0.43	6	30.00	14	70.00	Hashemi et al.,2013

Fig. 4 The schematic diagram of gas geochemical migration in the northeastern margin of Qinghai-Tibet Plateau(a)and Zhangbo seismic belt(b)(Chen et al., 2022).

References 105

[1]	车用太, 刘耀炜, 何镧. 2015. 断层带土壤气中H₂观测: 探索地震短临预报的新途径[J]. 地震, 35(4): 1-10.
	CHE Yong-tai, LIU Yao-wei, HE Lan. 2015. Hydrogen monitoring in fault zone soil gas: A new approach to short/immediate earthquake prediction[J]. Earthquake, 35(4): 1-10. (in Chinese)
[2]	车用太, 王吉易, 李一兵, 等. 2004. 首都圈地下流体监测与地震预测[M]. 北京: 气象出版社: 144-150.
	CHE Yong-tai, WANG Ji-yi, LI Yi-bing, et al. 2004. Underground Fluids Monitoring and Earthquake Prediction in Capital Area[M]. China Meteorological Press, Beijing: 144-150. (in Chinese)
[3]	丁香, 王晓青. 2000. 华北水氡异常与地震关系的Bayes判别分析[J]. 华北地震科学, 18(3): 59-65.
	DING Xiang, WANG Xiao-qing. 2000. Bayes discriminant analysis of the relationship between the radon anomalies and earthquakes in North China[J]. North China Earthquake Sciences, 18(3): 59-65. (in Chinese)
[4]	杜建国, 仵柯田, 孙凤霞, 等. 2022. 隐爆角砾岩: 古地震的一种成因标志[J]. 岩石学报, 38(3): 913-922.
	DU Jian-guo, WU Ke-tian, SUN Feng-xia, et al. 2022. Cryptoexplosive breccia: A genetic mark of the paleoearthquakes[J]. Acta Petrologica Sinica, 38(3): 913-922. (in Chinese) DOI URL
[5]	官致君. 1999. 水化学预报方法及效能评价[J]. 四川地震, (1-2): 89-99.
	GUAN Zhi-jun. 1999. Water chemical methods and their efficiency evaluation of earthquake prediction[J]. Earthquake Research in Sichuan, (1-2): 89-99. (in Chinese)
[6]	和宏伟, 和国文, 李永莉, 等. 1999. 云南地区水氡前兆异常动态演化与地震关系研究[J]. 地震研究, 22(4): 365-371.
	HE Hong-wei, HE Guo-wen, LI Yong-li, et al. 1999. Dynamic evolution of precursory anomaly of water radon and its relations with earthquakes in Yunnan region[J]. Journal of Seismological Research, 22(4): 365-371. (in Chinese)
[7]	贺天培. 1989. 四川地区水化方法预报指标的研究[J]. 四川地震, (4): 27-36.
	HE Tian-pei. 1989. Study on prediction index of hydrochemical method in Sichuan area[J]. Earthquake Research in Sichuan, (4): 27-36. (in Chinese)
[8]	蒋凤亮, 李桂如, 王基华, 等. 1989. 地震地球化学[M]. 北京: 地震出版社: 184-185.
	JIANG Feng-liang, LI Gui-ru, WANG Ji-hua, et al. 1989. Seismological Geochemistry[M]. Seismological Press, Beijing: 184-185. (in Chinese)
[9]	蒋海昆, 付虹, 杨马陵. 2018a. 中国震例(2014-2015)[M]. 北京: 地震出版社.
	JIANG Hai-kun, FU Hong, YANG Ma-ling. 2018a. arthquake Cases in China(2014-2015)[M]. Seismological Press, Beijing. (in Chinese)
[10]	蒋海昆, 杨马陵, 付虹. 2018b. 中国震例(2007-2012)[M]. 北京: 地震出版社.
	JIANG Hai-kun, YANG Ma-ling, FU Hong. 2018b. Earthquake Cases in China(2007-2012)[M]. Seismological Press, Beijing. (in Chinese)
[11]	蒋海昆, 杨马陵, 付虹. 2018c. 中国震例(2013)[M]. 北京: 地震出版社.
	JIANG Hai-kun, YANG Ma-ling, FU Hong. 2018c. Earthquake Cases in China(2013)[M]. Seismological Press, Beijing. (in Chinese)
[12]	蒋海昆, 杨马陵, 付虹. 2018d. 中国震例(2016-2017)[M]. 北京: 地震出版社.
	JIANG Hai-kun, YANG Ma-ling, FU Hong. 2018d. Earthquake Cases in China(2016-2017)[M]. Seismological Press, Beijing. (in Chinese)
[13]	康春丽, 杜建国, 李圣强. 1999. 中强地震活动中汞的异常特征[J]. 地震, 19(4): 352-358.
	KANG Chun-li, DU Jian-guo, LI Sheng-qiang. 1999. Anomaly characteristics of mercury associated with moderately strong earthquake[J]. Earthquake, 19(4): 352-358. (in Chinese)
[14]	李君英, 唐仲兴. 1999. 华北强震水化学参量变化的模糊识别及方法评价[J]. 地震, 19(1): 71-80.
	LI Jun-ying, TANG Zhong-xing. 1999. Fuzzy recognition of the hydrochemical component variations before strong earthquakes in North China and the calculation method evaluation[J]. Earthquake, 19(1): 71-80.
[15]	李圣强, 杜建国, 康春丽. 2001. 信息熵在地下流体资料处理中的应用[J]. 华北地震科学, 19(2): 1-7.
	LI Sheng-qiang, DU Jian-guo, KANG Chun-li. 2001. The application of information entropy in subsurface fluid data processing[J]. North China Earthquake Sciences, 19(2): 1-7. (in Chinese)
[16]	李营, 陈志, 胡乐, 等. 2022. 流体地球化学进展及其在地震预测研究中的应用[J]. 科学通报, 67(13): 1404-1420.
	LI Ying, CHEN Zhi, HU Le, et al. 2022. Advances in seismic fluid geochemistry and its application in earthquake forecasting[J]. Chinese Science Bulletin, 67(13): 1404-1420. (in Chinese)
[17]	李志鹏, 赵冬, 袁梅. 2015. 姑咱台气氡测值异常与地震预报探讨[J]. 四川地震, (4): 24-28.
	LI Zhi-peng, ZHAO Dong, YUAN Mei. 2015. Abnormal changes of the gas radon date in Guzan seismic station and the earthquake prediction[J]. Earthquake Research in Sichuan, (4): 24-28. (in Chinese)
[18]	林纪曾. 1981. 观测数据的数学处理[M]. 北京: 地震出版社: 69-72.
	LIN Ji-ceng. 1981. Mathematical Processing of Observational Data [M]. Seismological Press, Beijing: 69-72. (in Chinese)
[19]	刘耀炜, 任宏微, 张磊, 等. 2015. 鲁甸6.5级地震地下流体典型异常与前兆机理分析[J]. 地震地质, 37(1): 307-318.
	LIU Yao-wei, REN Hong-wei, ZHANG Lei, et al. 2015. Underground fluid anomalies and the precursor mechanisms of the Ludian M_S6.5 earthquake[J]. Seismology and Geology, 37(1): 307-318. (in Chinese)
[20]	刘耀炜, 张元生. 1998. 共和7.0级地震前地下流体前兆的动态演化特征[J]. 西北地震学报, 20(1): 59-64.
	LIU Yao-wei, ZHANG Yuan-sheng. 1998. Dynamic evolution characteristics of ground fluid precursors before the Gonghe M_S7.0 earthquake 1990 in Qinghai Province[J]. Northwestern Seismological Journal, 20(1): 59-64. (in Chinese)
[21]	邵俊杰, 李营, 孙凤霞, 等. 2022. 水-岩反应过程中离子浓度变化特征实验研究及其对地震异常成因的启示[J]. 地震研究, 45(2): 187-198.
	SHAO Jun-jie, LI Ying, SUN Feng-xia, et al. 2022. Experimental study of the characteristics of ion concentration changes during water-rock reaction and its implication to the formation of seismic anomalies[J]. Journal of Seismological Research, 45(2): 187-198. (in Chinese)
[22]	邵永新, 李君英, 李一兵, 等. 2000. 唐山7.8级地震前水氡异常演化特征[J]. 西北地震学报, 22(3): 247-250.
	SHAO Yong-xin, LI Jun-ying, LI Yi-bing, et al. 2000. Evolution feature of radon anomaly in groundwater before the Tangshan M_S7.8 earthquake[J]. Northwestern Seismological Journal, 22(3): 247-250. (in Chinese)
[23]	沈照理, 王焰新, 郭华明, 等. 2012. 水-岩相互作用研究的机遇与挑战[J]. 地球科学(中国地质大学学报), 37(2): 207-219.
	SHEN Zhao-li, WANG Yan-xin, GUO Hua-ming, et al. 2012. Opportunities and challenges of water-rock interaction studies[J]. Earth Science(Journal of China University of Geosciences), 37(2): 207-219. (in Chinese)
[24]	司学芸, 孙小龙, 邵志刚, 等. 2013. 南北地震带流体资料趋势性转折与强震的关系[J]. 中国地震, 29(1): 148-156.
	SI Xue-yun, SUN Xiao-long, SHAO Zhi-gang, et al. 2013. Analysis of the relationship between the trend turnings in groundwater changes and the strong earthquake activities in north-south seismic belt[J]. Earthquake Research in China, 29(1): 148-156. (in Chinese)
[25]	孙小龙, 刘耀炜, 付虹, 等. 2020. 我国地震地下流体学科分析预报研究进展回顾[J]. 地震研究, 43(2): 216-231.
	SUN Xiao-long, LIU Yao-wei, FU Hong, et al. 2020. A review of study in the analysis and prediction of seismic subsurface fluid during past ten years in China[J]. Journal of Seismological Research, 43(2): 216-231. (in Chinese)
[26]	孙小龙, 王俊, 向阳, 等. 2016. 基于《中国震例》的地下流体异常特征统计分析[J]. 地震, 36(4): 120-130.
	SUN Xiao-long, WANG Jun, XIANG Yang, et al. 2016. Statistical characteristics of subsurface fluid precursors based on earthquake cases in China[J]. Earthquake, 36(4): 120-130. (in Chinese)
[27]	孙小龙, 向阳, 杨朋涛. 2018. 云南会泽井水位地震预测效能检验及其机理分析[J]. 地震学报, 40(2): 185-194.
	SUN Xiao-long, XIANG Yang, YANG Peng-tao. 2018. Earthquake prediction efficiency inspection of water level in Huize well and its anomaly mechanism[J]. Acta Seismologica Since, 40(2): 185-194. (in Chinese)
[28]	万迪堃, 汪成民, 李介成, 等. 1993. 地下水动态异常与地震短临预报[M]. 北京: 地震出版社: 6-9.
	WAN Di-kun, WANG Cheng-min, LI Jie-cheng, et al. 1993. Anomalies of Groundwater Behavior and Short and Imminent Term Earthquake Prediction [M]. Seismological Press, Beijing: 6-9. (in Chinese)
[29]	万永革, 吴忠良, 周公威, 等. 2002. 地震应力触发研究[J]. 地震学报, 24(5): 533-551.
	WAN Yong-ge, WU Zhong-liang, ZHOU Gong-wei, et al. 2002. Research on seismic stress triggering[J]. Acta Seismologica Sinica, 24(5): 533-551. (in Chinese)
[30]	王博, 钟骏, 王熠熙, 等. 2018. 南北地震带北段流体资料地震预测效能检验[J]. 地震, 38(1): 147-156.
	WANG Bo, ZHONG Jun, WANG Yi-xi, et al. 2018. Testing the forecast efficiency of underground fluid observation in the north segment of north-south seismic belt[J]. Earthquake, 38(1): 147-156. (in Chinese)
[31]	汪成民, 李宣瑚, 王铁城, 等. 1990. 中国地震地下水动态观测网[M]. 北京: 地震出版社.
	WANG Cheng-min, LI Xuan-hu, WANG Tie-cheng, et al. 1990. The Groundwater Observation Well-network for Earthquake Prediction in China[M]. Seismological Press, Beijing. (in Chinese)
[32]	王基华, 林元武, 高松升. 1998. 怀来断层气CO₂监测及张北-尚义地震的短临预报[J]. 地震地质, 20(2): 113-116.
	WANG Ji-hua, LIN Yuan-wu, GAO Song-sheng. 1998. Monitoring of CO₂ in fault gas at Huailai and short-term prediction of Zhangbei-Shangyi earthquake[J]. Seismology and Geology, 20(2): 113-116. (in Chinese)
[33]	王基华, 孙风民, 张培仁. 1991. H₂异常和地震活动的关系[J]. 华北地震科学, 9(2): 59-64.
	WANG Ji-hua, SUN Feng-min, ZHANG Pei-ren. 1991. Relationship between hydrogen anomaly and seismic activities[J]. North China Earthquake Science, 9(2): 59-64. (in Chinese)
[34]	王吉易, 董守宇, 陈建民, 等. 1997. 地下流体地震预报方法[M]. 北京: 地震出版社: 112-131.
	WANG Ji-yi, DONG Shou-yu, CHEN Jian-min, et al. 1997. Seismic Underground Fluid Prediction Methods [M]. Seismological Press, Beijing: 112-131. (in Chinese)
[35]	王吉易, 张炜. 1991. 水化地震短临预报的整体方案[M]. 北京: 地震出版社.
	WANG Ji-yi, ZHANG Wei. 1991. Overall Scheme of Short-imminent Earthquake Prediction with Hydrochemical Method[M]. Seismological Press, Beijing. (in Chinese)
[36]	王吉易, 郑云贞, 张素欣, 等. 1994. 水化多层次加速前兆图像[J]. 中国地震, 10(S1): 157-165.
	WANG Ji-yi, ZHENG Yun-zhen, ZHANG Su-xin, et al. 1994. Multilevel acceleration precursor pattern of hydrochemistry[J]. Earthquake Research in China, 10(S1): 157-165. (in Chinese)
[37]	王晓青, 石绍先, 丁香. 1998. 前兆异常识别的X²统计检验法及其应用[J]. 地震, 18(3): 257-264.
	WANG Xiao-qing, SHI Shao-xian, DING Xiang. 1998. Statistical precursory identification and application by X²-test[J]. Earthquake, 18(3): 257-264. (in Chinese)
[38]	魏家珍, 申春生. 1994. 首都圈地区汞测量典型震例剖析及其映震效能评价[J]. 地震, (3): 44-49.
	WEI Jia-zhen, SHEN Chun-sheng. 1994. Analysis of typical earthquake cases and evaluation of earthquake-reflection effect in Hg observation in Beijing and its adjacent region[J]. Earthquake, (3): 44-49. (in Chinese)
[39]	邢玉安, 王吉易. 2000. 水氡动态图强震危险区预测的新方法[J]. 地震, 20(4): 1-6.
	XING Yu-an, WANG Ji-yi. 2000. The new method of prediction for the earthquake risk area with evolutionary diagrams of radon in ground water[J]. Earthquake, 20(4): 1-6. (in Chinese)
[40]	许绍燮. 1989. 地震预报能力评分[M]. 北京: 地震出版社: 586-589.
	XU Shao-xie. 1989. Scientific Evaluation of Earthquake Prediction Efficiency[M]. Seismological Press, Beijing: 586-589. (in Chinese)
[41]	晏锐, 黄辅琼, 顾瑾平. 2004. 中国大陆 7 级强震前地下流体前兆时空特征[J]. 地震, 24(1): 126-131.
	YAN Rui, HUANG Fu-qiong, GU Jin-ping. 2004. Spatial-temporal characteristics of precursory anomaly of underground fluid before M_S7.0 strong earthquakes in China’ s continent[J]. Earthquake, 24(1): 126-131. (in Chinese)
[42]	晏锐, 田雷, 王广才, 等. 2018. 2008年汶川8.0级地震前地下流体异常回顾与统计特征分析[J]. 地球物理学报, 61(5): 1907-1921.
	YAN Rui, TIAN Lei, WANG Guang-cai, et al. 2018. Review and statistically characteristic analysis of underground fluid anomalies prior to the 2008 Wenchuan M_S8.0 earthquake[J]. Chinese Journal of Geophysics, 61(5): 1907-1921. (in Chinese)
[43]	岳明生. 2005. 地震预测研究发展战略几点思考[J]. 国际地震动态, (5): 7-21.
	YUE Ming-sheng. 2005. Some thoughts on the development strategy of earthquake prediction research[J]. Recent Developments in World Seismology, (5): 7-21. (in Chinese)
[44]	张培仁, 王基华, 孙凤民. 1993. 氢: 预报地震的灵敏元素[J]. 地震地质, 15(1): 69-77.
	ZHANG Pei-ren, WANG Ji-hua, SUN Feng-min. 1993. Hydrogen: A sensitive element to predictable earthquake[J]. Seismology and Geology, 15(1): 69-77. (in Chinese)
[45]	张素欣, 张子广, 郑云贞. 2001. 水化学参量的中强地震中短期预报方法在河北及邻区的应用检验[J]. 华南地震, 21(3): 8-14.
	ZHANG Su-xin, ZHANG Zi-guang, ZHENG Yun-zhen. 2001. Test on medium and short term prediction methods for medium and strong earthquake with hydrogeochemical parameters[J]. South China Journal of Seismology, 21(3): 8-14. (in Chinese)
[46]	张炜. 1991. 水文地球化学在地震监测预报中的应用[J]. 水文地质工程地质, 18(2): 45-47.
	ZHANG Wei. 1991. Application of hydrogeochemistry in earthquake monitoring and prediction[J]. Hydrogeology and Engineering Geology, 18(2): 45-47. (in Chinese)
[47]	张炜, 王吉易, 鄂秀满, 等. 1988. 水文地球化学预报地震的原理与方法[M]. 北京: 教育科学出版社: 162-170.
	ZHANG Wei, WANG Ji-yi, E Xiu-man, et al. 1988. Hydrogeochemical Principles and Methods in Earthquake Prediction [M]. Educational Science Publishing House, Beijing: 162-170. (in Chinese)
[48]	张文冕, 田少柏. 1990. 地震前水氡短临异常判别指标及预报三要素的方法探讨[J]. 西北地震学报, 12(1): 30-38.
	ZHANG Wen-mian, TIAN Shao-bai. 1990. On the indices distinguishing short-imminent anomalies of water-radon before an earthquake and the method predicting its time, location and magnitude[J]. Northwestern Seismological Journal, 12(1): 30-38. (in Chinese)
[49]	张晓东, 傅征祥, 张永仙, 等. 2003. 1999-2002年地震预报研究进展[J]. 地震学报, 25(5): 479-491.
	ZHANG Xiao-dong, FU Zheng-xian, ZHANG Yong-xian, et al. 2003. Studies and experiments on earthquake prediction during 1999-2002[J]. Acta Seismologica Sinica, 25(5): 479-491. (in Chinese)
[50]	张新基, 张慧. 1998. 地下流体异常性质定量判别方法探索与地震预报[J]. 西北地震学报, 20(3): 16-21.
	ZHANG Xin-ji, ZHANG Hui. 1998. A study on method of quantitatively judging ground fluid anomaly character and earthquake prediction[J]. Northwestern Seismological Journal, 20(3): 16-21. (in Chinese)
[51]	郑云贞, 王吉易, 张素欣. 1991. 山西大同6.1级地震前河北省水化异常与地震三要素判断[J]. 华北地震科学, 9(4): 78-83.
	ZHENG Yun-zhen, WANG Ji-yi, ZHANG Su-xin. 1991. Hydrochemical anomalies in Hebei Province and determination of three elements of the earthquake before the Datong M6.1 earthquake in Shanxi Province[J]. North China Earthquake Sciences, 9(4): 78-83. (in Chinese)
[52]	钟骏, 王博, 闫玮, 等. 2021. 阿克苏断层氢气浓度动态特征及其映震效能[J]. 地震学报, 43(5): 615-627.
	ZHONG Jun, WANG Bo, YAN Wei, et al. 2021. Dynamic characteristics of fault hydrogen concentration in Aksu and its earthquake reflecting efficiency[J]. Acta Seismologica Sinica, 43(5): 615-627. (in Chinese)
[53]	Aleem D K, Malik S A, Kimberlee J K, et al. 2019. Descriptive analysis and earthquake prediction using boxplot interpretation of soil radon time series data[J]. Applied Radiation and Isotopes, 154:108861. DOI URL
[54]	Barbieri M, Franchini S, Barberio M D, et al. 2021. Changes in groundwater trace element concentrations before seismic and volcanic activities in Iceland during 2010-2018[J]. Science of the Total Environment, 793:148635. DOI URL
[55]	Chen Z, Du J G, Zhou X C, et al. 2014. Hydrochemistry of the hot springs in western Sichuan Province related to the Wenchuan M8.0 earthquake[J]. The Scientific World Journal, 2014: 901432.
[56]	Chen Z, Li Y, Liu Z, et al. 2019. Evidence of multiple sources of soil gas in the Tangshan fault zone, North China[J]. Geofluids, 2019: 1945450.
[57]	Chen Z, Li Y, Liu Z, et al. 2022. Geochemical and geophysical effects of tectonic activity in faulted areas of the North China Craton[J]. Chemical Geology, 609: 121048. DOI URL
[58]	Ciotoli G, Lombardi S, Annunziatellis A. 2007. Geostatistical analysis of soil gas data in a high seismic intermontane basin: Fucino Plain, central Italy[J]. Journal of Geophysical Research, 112(B5): 1-23.
[59]	Dobrovolsky I P, Zubkov S I, Miachkin V I. 1979. Estimation of the size of earthquake preparation zones[J]. Pure and Applied Geophysics, 117(5): 1025-1044. DOI URL
[60]	Du J G, Fu B H, Guo W S, et al. 2010. Significance of prehistoric liquefaction features in the Xilinhot district, Inner Mongolia, northern China[J]. Terrestrial Atmospheric and Oceanic Sciences, 21(5): 767-779. DOI URL
[61]	Du J G, Zhang Y, Li H. 2007. Advances in studies of thermal-fluid geochemistry and hydrothermal resource in China[J]. Geothermal Energy Research Trends, (3): 51-88.
[62]	Elmaghraby E K, Lotfy Y A. 2009. Differentiation between earthquake radon anomalies and those arising from nuclear activities[J]. Applied Radiation and Isotopes, 67(1): 208-211. DOI PMID
[63]	Fatih K, Murat I, Mahmut D, et al. 2009. Artificial neural network model for earthquake prediction with radon monitoring[J]. Applied Radiation and Isotopes, 67(1): 212-219. DOI PMID
[64]	Fleischer R L, Mogro-Campero A. 1985. Association of subsurface radon changes in Alaska and the northeastern United States with earthquakes[J]. Geochimica et Cosmochimica Acta, 49(4): 1061-1071. DOI URL
[65]	Fu C C, Yang T F, Chen C H, et al. 2017. Spatial and temporal anomalies of soil gas in northern Taiwan and its tectonic and seismic implications[J]. Journal of Asian Earth Sciences, 149: 64-77. DOI URL
[66]	Haider T, Barkat A, Hayat U, et al. 2021. Identification of radon anomalies induced by earthquake activity using intelligent systems[J]. Journal of Geochemical Exploration, 222(1): 106709. DOI URL
[67]	Hashemi S M, Negarestani A, Namvaran M, et al. 2013. An analytical algorithm for designing radon monitoring network to predict the location and magnitude of earthquakes[J]. Journal of Radioanalytical and Nuclear Chemistry, 295(3): 2249-2262. DOI URL
[68]	Hosono T, Masaki Y. 2020. Post-seismic hydrochemical changes in regional groundwater flow systems in response to the 2016 M_W7.0 Kumamoto earthquake[J]. Journal of Hydrology, 580: 124340. DOI URL
[69]	Ilić R, Rusov V D, Pavlovych V N, et al. 2005. Radon in Antarctica[J]. Radiation Measurements, 40(2-6): 415-422. DOI URL
[70]	King C Y, Azuma S, Igarashi G, et al. 1999. Earthquake-related water-level changes at 16 closely clustered wells in Tono, central Japan[J]. Journal of Geophysical Research: Solid Earth, 104(B6): 13073-13082.
[71]	King C Y, Evans W C, Presser T, et al. 1981. Anomalous chemical changes in well waters and possible relation to earthquakes[J]. Geophysical Research Letters, 8(5): 425-428. DOI URL
[72]	Li Y, Chen Z, Hu L, et al. 2022. Advances in seismic fluid geochemistry and its application in earthquake forecasting[J]. Chinese Science Bulletin, 67(13): 1404-1420.
[73]	Lillemor C, Alasdair S, Colin G, et al. 2004. Hydrogeochemical changes before and after a major earthquake[J]. Geology, 32(8): 641-644. DOI URL
[74]	Lu G, Liu R. 2015. Aqueous chemistry of typical geothermal springs with deep faults in Xinyi and Fengshun in Guangdong Province, China[J]. Journal of Earth Science, 26(1): 60-72. DOI URL
[75]	Muir-Wood R, King G C. 1993. Hydrological signatures of earthquake strain[J]. Journal of Geophysical Research: Solid Earth, 98(B12): 22035-22068.
[76]	Negarestani A, Setayeshi S, Ghannadi-Maragheh M, et al. 2002. Layered neural networks-based analysis of radon concentration and environmental parameters in earthquake prediction[J]. Journal of Environmental Radioactivity, 62(3): 225-233. PMID
[77]	Putnis A, Austrheim H. 2010. Fluid-induced processes: Metasomatism and metamorphism[J]. Frontiers in Geofluids, 10(1-2): 254-269.
[78]	Ramola R C, Singh S, Virk H S. 1988. A model for the correlation between radon anomalies and magnitude of earthquakes[J]. International Journal of Radiation Application and Instrumentation. Part D. Nuclear Tracks and Radiation Measurements, 15(1-4): 689-692. DOI URL
[79]	Rikitake T. 1988. Earthquake prediction: An empirical approach[J]. Tectonophysics, 148(3-4): 195-210. DOI URL
[80]	Roeloffs E A. 1996. Poroelastic techniques in the study of earthquake-related hydrologic phenomena[J]. Advances in Geophysics, 37(1): 135-195.
[81]	Singh M, Ramola R C, Singh B, et al. 1991. Subsurface soil gas radon changes associated with earthquakes[J]. International Journal of Radiation Applications and Instrumentation, 19(1-4): 417-420.
[82]	Skelton A, Liljedahl-Claesson L, Wästeby N, et al. 2019. Hydrochemical changes before and after earthquakes based on long-term measurements of multiple parameter at 2 sites in northern Iceland: A review[J]. Journal of Geophysical Research: Solid Earth, 124(3): 2702-2720. DOI URL
[83]	Snell T, Paola N D, Hunen J V, et al. 2020. Modelling fluid flow in complex natural fault zones: Implications for natural and human-induced earthquake nucleation[J]. Earth and Planetary Science Letters, 530: 115869. DOI URL
[84]	Soldati G, Cannelli V, Piersanti A. 2020. Monitoring soil radon during the 2016-2017 central Italy sequence in light of seismicity[J]. Scientific Reports, 10(1): 1-12. DOI
[85]	Sun X L, Yang P T, Xiang Y, et al. 2018. Across-fault distributions of radon concentrations in soil gas for different tectonic environments[J]. Geosciences Journal, 22(2): 227-239. DOI
[86]	Talwani P. 1979. An empirical earthquake prediction model[J]. Physics of the Earth & Planetary Interiors, 18(4): 288-302.
[87]	Thomas D. 1988. Geochemical precursors to seismic activity[J]. Pure and Applied Geophysics, 126(2): 241-266. DOI URL
[88]	Torkar D, Zmazek B, Vaupoti J, et al. 2010. Application of artificial neural networks in simulating radon levels in soil gas[J]. Chemical Geology, 270(1-4): 1-8. DOI URL
[89]	Toutain J P, Baubron J C. 1999. Gas geochemistry and seismotectonics: A review[J]. Tectonophysics, 304(1): 1-27. DOI URL
[90]	Utkin V I, Yurkov A K. 2010. Radon as a tracer of tectonic movements[J]. Russian Geology and Geophysics, 51(2): 220-227. DOI URL
[91]	Virk H S. 1996. A critique of empirical scaling relationship between earthquake magnitude, epicentral distance and precursor time for interpretation of radon data[J]. Earthquake Prediction Research, (5): 574-583.
[92]	Wästeby N, Skelton A, Tollefsen E, et al. 2015. Hydrochemical monitoring, petrological observation, and geochemical modeling of fault healing after an earthquake[J]. Journal of Geophysical Research: Solid Earth, 119(7): 5727-5740. DOI URL
[93]	Williams A J, Crossey L J, Karlstrom K E, et al. 2013. Hydrogeochemistry of the Middle Rio Grande aquifer system: Fluid mixing and salinization of the Rio Grande due to fault inputs[J]. Chemical Geology, 351(10): 281-298. DOI URL
[94]	Woith H. 2015. Radon earthquake precursor: A short review[J]. European Physical Journal-Special Topics, 224(4): 611-627. DOI URL
[95]	Woith H, Wang R, Maiwald U, et al. 2013. On the origin of geochemical anomalies in groundwaters induced by the Adana 1998 earthquake[J]. Chemical Geology, 339(2): 177-186. DOI URL
[96]	Yang T F, Fu C C, Walia V C, et al. 2006. Seismo-geochemical variations in SW Taiwan: Multi-parameter automatic gas monitoring results[J]. Pure and Applied Geophysics, 163: 693-709. DOI URL
[97]	Yang T F, Walia V, Chyi L L, et al. 2005. Variations of soil radon and thoron concentrations in a fault zone and prospective earthquakes in SW Taiwan[J]. Radiation Measurements, 40(2-6): 496-502. DOI URL
[98]	Yang Y, Li Y, Guan Z J, et al. 2018. Correlations between the radon concentrations in soil gas and the activity of the Anninghe and the Zemuhe Faults in Sichuan, southwestern of China[J]. Applied Geochemistry, 89: 23-33. DOI URL
[99]	Yasuhara H, Polak A, Mitani Y, et al. 2006. Evolution of fracture permeability through fluid-rock reaction under hydrothermal conditions[J]. Earth & Planetary Science Letters, 244(1): 186-200.
[100]	Yasuoka Y, Ishii T, Tokonami S, et al. 2005. Radon anomaly related to the 1995 Kobe earthquake in Japan[J]. International Congress Series, 1276(5): 426-427. DOI URL
[101]	Yuce G, Fu C C, D'Alessandro W, et al. 2017. Geochemical characteristics of soil radon and carbon dioxide within the Dead Sea Fault and Karasu Fault in the Amik Basin(Hatay), Turkey[J]. Chemical Geology, 469: 129-146. DOI URL
[102]	Zhao Y X, Liu Z F, Li Y, et al. 2021. A case study of 10 years groundwater radon monitoring along the eastern margin of the Tibetan plateau and in its adjacent regions: Implications for earthquake surveillance[J]. Applied Geochemistry, 131: 105014. DOI URL
[103]	Zmazek B, Dzeroski S, Torkar D, et al. 2010. Identification of radon anomalies in soil gas using decision trees and neural networks[J]. Nukleonika, 55(4): 501-505.
[104]	Zmazek B, Todorovski L, Dzeroski S, et al. 2003. Application of decision trees to the analysis of soil radon data for earthquake prediction[J]. Applied Radiation & Isotopes: Including Data Instrumentation & Methods for Use in Agriculture Industry & Medicine, 58(6): 697-706.
[105]	Zhou Z H, Zhong J, Zhao J, et al. 2021. Two mechanisms of earthquake-induced hydrochemical variations in an observation well[J]. Water, 13:2385. DOI URL

RESEARCH PROGRESS AND PROSPECT OF SEISMIC FLUID GEOCHEMISTRY IN SHORT-IMMINENT EARTHQUAKE PREDICTION

地震流体地球化学短临预测研究进展与展望

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 105

Related Articles 15

Recommended Articles

Metrics

Comments

[1]	LI Ji-ye, YAN Rui, ZHANG Si-meng, HU Lan-bin, MENG Ling-lei, ZHOU Chen. THE RELATIONSHIP BETWEEN TIDAL RESPONSE OF WELL WATER LEVEL AND MODULATION OF SMALL EARTHQUAKES [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(3): 668-688.
[2]	WANG Bo, CUI Feng-zhen, LIU-ZENG Jing, ZHOU Yong-sheng, XU Sheng, SHAO Yan-xiu. FAULT GAS OBSERVATION AND SURFACE RUPTURE FEATURE INTERPRETATION OF THE M_S7.4 MADOI EARTHQUAKE [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(3): 772-794.
[3]	HAN Xiao-fei, SHI Shuang-shuang, DONG Bin, XUE Xiao-dong, FAN Xue-fang. ANALYSIS ON EVOLUTION MECHANISM OF TIANZHUANG FAULT DEFORMATION ZONE [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(3): 795-810.
[4]	LIU Qing, LIU Shao, ZHANG Shi-min. PALEOSEISMOLOGIC STUDY ON THE YUEXI FAULT IN THE MIDSECTION OF THE DALIANGSHAN FAULT ZONE SINCE THE LATE QUATERNARY [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(2): 321-337.
[5]	JIANG Feng-yun, JI Ling-yun, ZHU Liang-yu, LIU Chuan-jin. THE PRESENT CRUSTAL DEFORMATION CHARACTERISTICS OF THE HAIYUAN-LIUPANSHAN FAULT ZONE FROM INSAR AND GPS OBSERVATIONS [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(2): 377-400.
[6]	WANG Liao, XIE Hong, YUAN Dao-yang, LI Zhi-min, XUE Shan-yu, SU Rui-huan, WEN Ya-meng, SU Qi. THE SURFACE RUPTURE CHARACTERISTICS BASED ON THE GF-7 IMAGES INTERPRETATION AND THE FIELD INVESTIGA-TION OF THE 2022 MENYUAN M_S6.9 EARTHQUAKE [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(2): 401-421.
[7]	LIU Bai-yun, ZHAO Li, LIU Yun-yun, WANG Wen-cai, ZHANG Wei-dong. THE RESEARCH ON RELOCATION AND FAULT PLANE SOLUTION AND GEOMETRIC MEANING OF THE MADUO M7.4 EARTHQUAKE ON 22 MAY 2021 [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(2): 500-516.
[8]	WANG Ming-liang, ZHANG Yang, XU Shun-qiang, XU Zhi-ping. DEEP STRUCTURE IN THE MIDDLE AND SOUTH AREA OF NORTH CHINA DEPRESSION AND THE VICINITY BY MAGNETOTELLURICS [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(2): 536-552.
[9]	ZHAO De-zheng, QU Chun-yan, ZHANG Gui-fang, GONG Wen-yu, SHAN Xin-jian, ZHU Chuan-hua, ZHANG Guo-hong, SONG Xiao-gang. APPLICATIONS AND ADVANCES FOR THE COSEISMIC DEFORMA-TION OBSERVATIONS, EARTHQUAKE EMERGENCY RESPONSE AND SEISMOGENIC STRUCTURE INVESTIGATION USING INSAR [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(2): 570-592.
[10]	LI An, WAN Bo, WANG Xiao-xian, JI Hao-min, SUO Rui. NEW EVIDENCE OF THE PALEOEARTHQUAKE RUPTURE IN THE NORTH GAIZHOU-ANSHAN SEGMENT OF THE JINZHOU FAULT [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 111-126.
[11]	ZHENG Hai-gang, YAO Da-quan, ZHAO Peng, YANG Yuan-yuan, HUANG Jin-shui. NEW ACTIVITY CHARACTERISTICS IN THE CHISHAN SECTION OF TAN-LU FAULT ZONE IN HOLOCENE [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 127-138.
[12]	FAN Wen-jie. CHARACTERISTICS OF TECTONIC STRESS FIELD AROUND THE YANGBI M_S6.4 EARTHQUAKE AND ITS SURROUNDING AREAS ON MAY 21, 2021 AND ITS GEODYNAMIC IMPLICATION [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 208-230.
[13]	ZHANG Ke, WANG Xin, YANG Hong-ying, WANG Yue, XU Yan, LI Jing. THE CHARACTERISTICS AND SEISMOGENIC STRUCTURE ANALYSIS OF THE 2021 YANGBI M_S6.4 EARTHQUAKE SEQUENCE, YUNNAN [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 231-251.
[14]	GOU Jia-ning, LIU Zi-wei, JIANG Ying, ZHANG Xiao-tong. GRAVITY PERTURBATION AND CHARACTERISTICS OF TEM-PORAL AND SPATIAL CHANGES OF BACKGROUND NOISE BE-FORE EARTHQUAKE: THE EXAMPLE OF MADUO M_S7.4 AND YANGBI M_S6.4 EARTHQUAKES [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 252-268.
[15]	ZHU Zhi-guo, ZHU Yi-qing, WANG Dong-zhen, HUSAN Irxat. COMPREHENSIVE ANALYSIS OF GRAVITY AND CRUSTAL DEFORMATION OF JIASHI M_S6.4 EARTHQUAKE IN 2020 [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(1): 269-285.