Groundwater radon concentrations can reflect the changes of crustal stress and strain. Scholars and scientific institutions have also recorded groundwater radon precursor anomalies before earthquakes. Therefore, groundwater radon monitoring is an effective means of predicting seismic activities. However, the variation of radon concentrations within groundwater is not only affected by structural factors, but also by environmental factors, such as air pressure, temperature, and rainfall. This causes difficulty in identifying the possible precursor anomalies. Therefore, the EMD-LSTM model is proposed to identify the radon anomalies. This study investigated the time series data of groundwater radon from well #32 located in Sichuan province. Three models (including the LSTM (Long Short-Term Memory) model with auxiliary data, the EMD-LSTM (Empirical Mode Decomposition Long Short-Term Memory) model with auxiliary data, and the EMD-LSTM model without auxiliary data) were developed in order to predict groundwater radon variations. The results indicated that the prediction accuracy of the EMD-LSTM model was much higher than that of the LSTM model, and the EMD-LSTM model without auxiliary data also can obtain an ideal prediction result. Furthermore, the different durations of seismic activities T (T = ±10, ±30, ±50, and ±100) were also investigated by comparing the identification results. The identification rate of the precursor anomalies was the highest when T = ±30. The EMD-LSTM model identified five possible radon anomalies among the seven selected earthquakes. Taking well #32 as an example, we provided a promising method, that was the EMD-LSTM model, to detect the groundwater radon anomalies. It also suggested that the EMD-LSTM model can be used to identify the possible precursor anomalies within future studies.

Analyzing the hydrochemical composition in thermal springs is an advantageous method for studying the coupling mechanism of the deep and shallow fluids in active fault zones. Here we conducted sampling in 30 thermal springs near fault zones in Fujian Province, and the major elements, trace elements, silica, stable isotopes (δD and δ¹⁸O) and strontium isotopes were tested in the laboratory. The results show that (1) the thermal springs in the study area can be divided into six types according to the content of the major elements: HCO₃-Na, HCO₃·SO₄-Na, Cl·HCO₃-Na, Cl-Na, Cl-Na·Ca and HCO₃·SO₄-Ca; (2) hydrogen and oxygen isotopes indicate that precipitation is the main source of recharge for thermal springs in the study area, and the recharge height is between 258 m and 1859 m; (3) the content of SiO₂ in the thermal spring varies from 18.1 mg/L to 59.3 mg/L. The geothermal reservoir temperature calculated is 90~226 °C, and the circulation depth is 2.9~5.4 km, except for the W10 thermal spring, whose circulation depth is 8.4 km; and (4) the ⁸⁷Sr/⁸⁶Sr of the thermal springs in southwestern Fujian and eastern Fujian has obviously different characteristics, indicating the influence of different rock formations on the groundwater cycle process. Additionally, a continuous measurement of the main anions and cations was performed in five thermal springs every three days since January 2020. There were obvious abnormal changes in the hydrochemical compositions, chlorine in four of the five springs, sodium at three springs, and four ions at one spring, which all showed abnormal high-value changes by 15% to 80%, and which occurred 85~168 days prior to the M6.1 earthquake in Hualien, Taiwan. An inspiration could be provided for obtaining effective earthquake precursor anomalies by monitoring the change in ion concentration in thermal springs.

Due to frequent large earthquakes in the Lanping-Simao fault basin—located in China’s Yunnan Province—the Simao observation well has observed groundwater discharge, as well as Ca²⁺, Mg²⁺, and HCO₃⁻ concentrations every day between 2001–2018. Over 18 years of observations, M ≥ 5.6 earthquakes within a radius of 380 km from the well were seen to cause hydrochemical variations. In this study, we investigated CO₂ release and groundwater mixing as possible causes of regional earthquake precursors, which were caused by the characteristics of the regional structure, lithology, water-rock reactions, and a GPS velocity field. Precursory signals due to CO₂ injection are normally short-term changes that take two months. However, groundwater mixing linked to earthquakes was found to take, at the earliest, 15 months. The proportion of shallow water that contributes to mixing was found to significantly increase gradually with the stronger regional strain. These finding delineate the two mechanisms of earthquake-induced hydrochemical variations in an observation well, and would contribute to a better understanding of chemical changes before events in the Simao basin.

Springs offer insight into the sources and mechanisms of groundwater recharge and can be used to characterize fluid migration during earthquakes. However, few reports provide sufficient annual hydrochemical and isotopic data to compare the variation characteristics and mechanisms with both atmospheric temperature and seismic effects. In this study, we used continuous δ²H, δ¹⁸O, and major ion data from four springs over 1 year to understand the groundwater origin, recharge sources, circulation characteristics, and coupling relationships with atmospheric temperature and earthquakes. We found that (1) atmospheric temperatures above and below 0 °C can cause significant changes in ion concentrations and water circulation depth, resulting in the mixing of fresh and old water in the aquifer, but it cannot cause changes in δ²H and δ¹⁸O. (2) Earthquakes of magnitude ≥ 4.8 within a 66 km epicentral distance can alter fault zone characteristics (e.g., permeability) and aggravate water–rock reactions, resulting in significant changes in δ²H, δ¹⁸O, and hydrochemical ion concentrations. (3) Hydrogen and oxygen isotopes are the most sensitive precursory seismic indicators. The results of this study offer a reference for the establishment of long-term hydrochemical and isotopic monitoring, with the potential for use in earthquake forecasting.

Groundwater level, permeability and chemical components can be affected by earthquakes, however there are few comprehensive investigations on the combination of long-term continuous monitoring data and multiple strong earthquakes. In this study, continuous two-year dataset of groundwater levels and chemical compositions of groundwater (Ca2+, Mg2+ and HCO3-) in well #32 were collected to analyze the groundwater dynamic changes induced by earthquakes in the aquifer-aquitard system. The groundwater level appeared co-seismic rise change induced by Yangbi MW 6.1 earthquake and Luding MW 6.6 earthquake. The vertical permeability, estimated by the tidal response model, exhibited decrease changes during the period of Yangbi MW 6.1 earthquake and Luding MW 6.6 earthquake. Meanwhile, the continuous two-year chemical compositions showed that Ca2+ and HCO3- concentrations decreased, and Mg2+ concentrations increased during the two earthquakes period. The correlation between the vertical permeability and chemical compositions showed that there was a significant negative correlation between the vertical permeability and Mg2+, and a significant positive between the vertical permeability and Ca2+, HCO3-. A possible mechanism for observed fluctuations in some chemical compositions during earthquakes periods was that the reduction of mixing effect of different groundwater caused by permeability decreased. The flow of groundwater richened in Ca2+ and HCO3- from the overlying aquifer to the observation aquifer has been reduced. Meanwhile, due to the weakening of dilution effect, the Mg2+ concentration of the observation aquifer increased. This study can enhance understanding of the groundwater dynamic changes induced by earthquakes.