Different hydraulic responses to the 2008 Wenchuan and 2011 Tohoku earthquakes in two adjacent far-field wells: the effect of shales on aquifer lithology
© The Author(s) 2016
Received: 10 June 2016
Accepted: 27 October 2016
Published: 11 November 2016
Zuojiazhuang and Baodi are two adjacent wells (~50 km apart) in northern China. The large 2008 M w 7.9 Wenchuan and 2011 M w 9.1 Tohoku earthquakes induced different co-seismic water-level responses in these far-field (>1000 km) wells. The co-seismic water-level changes in the Zuojiazhuang well exhibited large amplitudes (~2 m), whereas those in the Baodi well were small and unclear (~0.05 m). The mechanism of the different co-seismic hydraulic responses in the two wells needs to be revealed. In this study, we used the barometric responses in different frequency domains and the phase shifts and amplitude ratios of the tidal responses (M2 wave), together with the well logs, to explain this inconformity. Our calculations show that the co-seismic phase shifts of the M2 wave decreased or remained unchanged in the Baodi well, which was quite different from the Zuojiazhuang well and from the commonly accepted phenomena. According to the well logs, the lithology of the Baodi well is characterized by the presence of a significant amount of shale. The low porosity/permeability of shale in the Baodi well could be the cause for the unchanged and decreased phase shifts and tiny co-seismic water-level responses. In addition, shale is one of the causes of positive phase shifts and indicates a vertical water-level flow, which may be due to a semi-confined aquifer or the complex and anisotropic fracturing of shale.
KeywordsTidal response Aquifer lithology Shale Far-field large earthquake
Different kinds of hydrologic responses to earthquakes have been documented (Wang and Manga 2010). Many have occurred at great distances from the ruptured fault and where the associated static stress changes are relatively small (e.g., Kayen et al. 2004; Sil and Freymueller 2006; Chadha et al. 2008). Liu and Manga (2009) reported that significant water-level changes can be driven at great distances by moderate-amplitude dynamic (time-varying) stresses.
Several mechanisms have been proposed to explain these co-seismic changes in water level. Fracture clearing and increased permeability caused by earthquake-induced dynamic stress have been widely used to explain most documented far-field water-level changes (Brodsky et al. 2003; Elkhoury et al. 2006; Wang and Chia 2008; Wang and Manga 2010; Zhang et al. 2015). Overcoming capillary traps in porous channels is hypothesized to be one of the principal pore-scale mechanisms by which natural permeability is enhanced by the passage of elastic waves (Beresnev et al. 2011). Wang et al. (2009) found that groundwater flow associated with S and Love waves may generate shear stresses large enough to break up the flocs in sediment pores, thereby enhancing the permeability of aquifers. Others have theorized that the dynamic strain induced by the passage of seismic waves, most probably long-period surface waves, might be the cause of water-level changes in the far field (West et al. 2005; Sil and Freymueller 2006; Chadha et al. 2008 Π). In addition, the results of several laboratory experiments suggest that dynamic shaking can enhance effective permeability, especially that of fractured systems (Roberts 2005; Elkhoury et al. 2011; Candela et al. 2014). Manga et al. (2012) studied the mechanism of permeability changes using field observations and experiments and concluded that strain amplitudes as small as 10−6 can enhance permeability in natural systems. Other proposed but unverified mechanisms include pore pressure increases caused by a mechanism ‘akin to liquefaction’ (Roeloffs 1998), shaking-induced dilatancy (Bower and Heaton 1978), increased pore pressure through the seismically induced growth of bubbles (Linde et al. 1994), and the fracture of an impermeable fault (King et al. 1999).
Yan et al. (2014) studied groundwater-level changes in mainland China induced by the 2011 M w 9.0 Tohoku earthquake. They found that earthquake-induced temporal variations in permeability might have occurred in 43% of the wells that displayed sustained water-level changes, but occurred in less than 15% of all observed wells overall. Furthermore, they found that the co-seismic phase shifts of the M2 tidal constituent decreased for some wells, and their statistical analysis indicated no obvious significant relation between water-level changes and any other parameter (except tidal admittance). These results indicate that the processes underlying groundwater-level changes induced by distant earthquakes of great magnitude are complex.
Zuojiazhuang and Baodi are two adjacent wells (~50 km apart) in northern China. The two large far-field (>1000 km) earthquakes—the 2008 M w 7.9 Wenchuan and 2011 M w 9.1 Tohoku earthquakes—induced distinct co-seismic water-level responses in these two adjacent wells. The co-seismic water-level changes in the Zuojiazhuang well exhibited large amplitudes (~2 m), whereas those of the Baodi well were small (~0.05 m) and unclear. The mechanism of the different co-seismic hydraulic responses in the two wells needs to be revealed. In this study, we used the barometric responses in different frequency domains and the phase shifts and amplitude ratios of the tidal responses (M2 wave), together with the well logs, to explain this inconformity. Our calculations show that the co-seismic phase shifts of the M2 wave decreased or remained unchanged in the Baodi well, which was quite different from the Zuojiazhuang well and from what is commonly accepted. According to the well logs, the lithology of the Baodi well is characterized by the presence of a significant amount of shale. Due to the compact grain structure of shale, its permeability is low (approximately 10−4–10−3 mD) (Li et al. 2013; Chen et al. 2013). With this low permeability (transmissivity), phase shifts decrease or remain unchanged even when the permeability (transmissivity) increases (Doan et al. 2006). Moreover, clogging is unlikely to be flushed out by the effect of teleseismic waves because of the compact grain structure in shale. It is therefore more difficult to enhance the permeability in the Baodi well, which has shale in its aquifer lithology, and this leads to very small co-seismic water-level changes. Meanwhile, positive phase shifts in the Baodi well indicate a vertical movement of the water level, caused either by a semi-confined aquifer or by the anisotropy and complex fracturing of shale. This needs to be clarified in the future.
Selection principles and observations
The water-level data in both wells were not influenced by pumping or other disturbances. The data were recorded over a sufficiently long time period to obtain relatively stable phase-shift information. Furthermore, although oceanic tides are known to exert an influence tens of kilometers away from the seashore (Beaumont and Berger 1975), the two wells we selected are located at distances greater than 100 km from the ocean.
Basic information about the Zuojiazhuang and Baodi wells
2008 M w 7.9
2011 M w 9.1
Co-seismic water-level change/m
Co-seismic water-level change/m
Next to the ‘Shunyi-Qianmen-Liangxiang’ fracture
Intersection of Yanshan mountain alluvial plain and Jizhong hollow
Amplitude and phase responses of the Zuojiazhuang and Baodi wells
Pre-earthquake water-level amplitude response to M2 wave/mm/nanostrain
Post-earthquake water-level amplitude response to M2 wave/mm/nanostrain
Co-seismic change of water-level amplitude response to M2 wave/mm/nanostrain
Background variability of water-level amplitude response to M2 wave/mm/nanostrain
Pre-earthquake phase shift/°
Post-earthquake phase shift/°
Co-seismic phase-shift change/°
Background phase-shift variability/°
2008 M W 7.9 Wenchuan
2011 M W 9.1 Tohoku
Barometric and tidal response analysis
The well-aquifer system is composed of a well and an aquifer. The Earth tide and barometric pressure cause loading on this system by different mechanisms, contributing two input signals that are dependent on each other at certain frequencies.
Ordinary coherence functions
Barometric response analysis in the frequency domain
During the analysis of the transfer functions, we used a similar data-processing method to Lai et al. (2013b). In the intermediate-frequency band, we calculated the transfer functions of the water-level response to barometric pressure and Earth tide from Eqs. (3) and (4), respectively. In the low- and high-frequency bands, the influence from the Earth tide is small, so we only calculated the transfer functions of the water-level response to barometric pressure, from Eq. (3). For the calculation, we also used the data from December 1, 2010, to March 10, 2011, which is continuous, stable, and not influenced by earthquakes or rainfall (Fig. 2).
As shown in Fig. 5, the barometric efficiencies of the Baodi and Zuojiazhuang wells decrease with increasing frequency from the intermediate- to the high-frequency band, which may be due to the wellbore storage effect (Rojstaczer 1988a). We can therefore suppose that the wellbore storage effect exists in the two wells. The phases at low frequencies are stable and close to zero and decrease with increasing frequency from the low- to the intermediate-frequency band, which also indicates that the wellbore storage effect might exist. In the intermediate-frequency band (0.5–8 cpd), the influence from the Earth tide is remarkable, and the barometric responses are therefore unstable. In the relatively high-frequency band (f > 6 cpd), the signal-to-noise ratio in the water level may be low and the barometric signals are relatively weak, and so the phases in the high-frequency range vary in a disorderly manner. As is commonly acknowledged, the phases may change much more quickly and obviously than the amplitude ratios (barometric efficiencies) after being influenced by noises or disturbances, so we neglect the phase analysis in the frequency band f > 6 cpd in these two wells.
Tidal response analysis: phase shift and amplitude ratio calculation
As analyzed by Lai et al. (2013b), the tidal responses are stable at semi-diurnal frequencies, but scatter at diurnal frequencies, which may be due to the diurnal tides being disturbed by resonances induced by the free core nutation and thermal effect (Doan et al. 2006). The tidal constituents O1 and M2 have large amplitudes and are less affected by the barometric effect, and are the constituents most commonly used in the interpretation of tidal analysis. However, the accuracy of the O1 phase is less than that of the M2 phase, and so the most commonly analyzed phase is M2 (Hsieh et al. 1987; Rojstaczer and Agnew 1989; Doan et al. 2006). For the tidal response analysis, we therefore focused on the M2 phase (period = 745.2 min).
The amplitude and phase responses of water level to Earth tides have been used to monitor aquifer storativity and permeability, respectively (Hsieh et al. 1987; Elkhoury et al. 2006; Doan et al. 2006; Xue et al. 2013). In a confined system, small phase lags result from high permeability, whereas large phase lags result from low permeability. The amplitude response is primarily a measure of specific storage.
According to Hsieh et al. (1987), for a homogeneous, isotropic, laterally extensive, and confined aquifer, the phase shifts between Earth tides and water level are assumed to be caused by the time required for the water to flow into and out of the well. In such a case, the water-table drainage effect is ignored, and the resulting phase shift should always be negative. An increase in phase shift (e.g., from −5° to −1°) therefore implies an increase in transmissivity or permeability (Hsieh et al. 1987; Elkhoury et al. 2006). However, positive phase shifts were observed in the Baodi well, as shown in Figs. 6 and 7, indicating that Hsieh’s model is not generally applicable for describing the water-level response to Earth tides. Roeloffs (1996) presented a model in which vertical drainage to the water table can cause positive phase shifts. Figures 6 and 7 shows that the phase response values varied between positive and negative over time in the Baodi well. These phase shifts were a combination of the phase lag caused by the borehole storage effect (already proved by the barometric responses in different frequency domains) and the phase lead caused by water-table drainage.
Lai et al. (2013a) reported that the observed phase responses can be considered a measure of permeability in both the horizontal fluid flow model (Hsieh et al. 1987) and the vertical pore-pressure diffusion model (Roeloffs 1996). Therefore, a phase-shift increase (e.g., from −10° to −5°, −5° to 5°, or 5° to 10°) implies an increase in permeability. As shown in Figs. 6, 7 and Table 2, the phase shift (permeability) in the Baodi well remained unchanged (Fig. 6) or decreased (Fig. 7) after shaking by teleseismic waves, but in the Zuojiazhuang well it increased obviously. It is necessary to compare the two wells to determine the exact mechanism of their different responses.
Transmissivity (permeability) calculations
Transmissivity calculation for the Zuojiazhuang well (without shale)
Permeability estimation for the Baodi well (with shale)
Given that positive phase shifts were observed in the Baodi well (which has shale in its aquifer lithology), Hsieh’s model (Hsieh et al. 1987) may not be generally applicable to describe the water-level response to Earth tides for this well, and the permeability (transmissivity) should not therefore be directly calculated on the basis of Hsieh’s model.
Alternatively, we could estimate the permeability (transmissivity) range for the Baodi well. The pore sizes of shaly sediments are often well below the micron scale, and most of the pores in shale are smaller than 50 nm (Josh et al. 2012). Thus, the permeability of shale is extremely low (approximately 10−4–10−3 mD) (Li et al. 2013; Chen et al. 2013). The compact structure of the grains in shale leads to low porosity and permeability. In exploration seismology, shales are always deemed as traps (closed reservoirs). Within this low permeability (transmissivity 10−9–10−6 m2/s) range, phase shifts at the frequency of the M2 wave will continue to decrease or remain unchanged rather than increase, even when the permeability (transmissivity) increases (Appendix Fig. 11; Doan et al. 2006).
Considering that the co-seismic water level changed with a very low amplitude in the Baodi well, the permeability might be harder to enhance in this well than in the Zuojiazhuang well, because of the compact structure of the shale.
The depth ranges of the two wells (shown in Fig. 8) are different; the depth of Baodi well is much shallower than that of Zuojiazhuang well. When the aquifer is confined and Hsieh’s model is completely applicable, as described by Hsieh et al. (1987) and Doan et al. (2006), the depth of the well is not related to the water-level changes. Yet when the reservoir is not confined, the flow in the confining formation is purely vertical, and the phase shifts are all positive, the water-level change is related to the depth of screening interval (Doan et al. 2006). In this study, however, there are both positive and negative phase shifts in the Baodi well, and both horizontal and vertical flow occur, and we may assume that the aquifer is semi-confined; so we may neglect the influence of the well depth on the water-level change.
Shale possesses a unique lithology with low porosity/permeability, anisotropy, and fragility. It may also contain complex fractures. Well aquifers containing shale may thus be characterized by anisotropy, and the aquifer medium may even be fractured. Therefore, homogeneity, isotropy, lateral extensivity, and aquifer confinement should not be ideally assumed in wells that feature shale in their lithology, and Hsieh’s model is not necessarily applicable to wells with shale in the aquifer lithology of the screened section. The precise mechanism requires further clarification, perhaps using numerical modeling methodologies.
We hoped to elucidate the mechanism by including other large earthquakes, such as the 2012 M w 8.6 Sumatra earthquake and the 2015 M w 7.9 Nepal earthquake, in this study. However, because there are many disturbances and data missing from the water-level observations in the Baodi well, we had to abandon these further studies.
The permeability of wells may be relatively more difficult to enhance where shale features in their aquifer lithology, because of the compact structure of shale. This might be the reason why the co-seismic water-level changes in the Baodi well are always smaller than those of the Zuojiazhuang well. In addition, the pre-earthquake heterogeneity of the pore pressure near the well should arguably be considered. However, because the two wells are only a small distance apart, we could neglect this factor.
Shale has a unique lithology with low porosity/permeability, as well as anisotropy, fragility, and possibly complex fractures. It can be found in some well aquifers with specific geologic conditions. In this study, we examined the mechanism behind the different co-seismic water-level responses of two adjacent wells in the far field (>1000 km) of two large earthquakes. We used the barometric responses in different frequency domains and the phase shifts and amplitude ratios of the tidal responses (M2 wave) to explain the uncommon co-seismic change phenomena in the Baodi well, which contains shale in the aquifer lithology of the screened section. We found that the phase shifts either continued to decrease or remained unchanged, even when the co-seismic permeability increased, perhaps due to shale’s low permeability (approximately 10−4–10−3 mD) (Li et al. 2013; Chen et al. 2013). The permeability of wells with shale in the aquifer lithology might be relatively harder to enhance because of the compact structure of shales, and this might be the reason why the co-seismic water-level changes in Baodi well are always small and unclear.
YZ and YM carried out most of the geologic investigation, data collection, and data pre-treatment. YZ finished the calculation and analysis of the phase shifts and amplitude ratios of the tidal responses and calculated the transmissivities. JH finished the co-seismic strain analysis. YZ and LYF conceived and coordinated the study and drafted the manuscript. All authors have read and approved the final manuscript.
We thank the China Earthquake Administration for providing the data used in this study. The authors are deeply grateful to Professor Chi-yuen Wang, Xuezhong Chen, and Friedemann Wenzel for their encouragement and suggestions. We sincerely acknowledge Rui Yan, Xin Liao, Wenhui Zhang, and Guijuan Lai for their discussions on this paper. This research was supported by the Strategic Leading Science and Technology Programme (Class B) of the Chinese Academy of Sciences (Grant No. XDB10010400), the National Natural Science Foundation of China (Grant No. 41604035), and the China Postdoctoral Science Foundation (Grant Nos. 2015M570142 and 2016T90129). We gratefully appreciate the valuable suggestions proposed by the anonymous reviewers.
The authors declare that they have no competing interests.
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- Beaumont C, Berger J (1975) An analysis of tidal strain observations from the United States of America: I. The laterally homogeneous tide. Bull Seismol Soc Am 65:1613–1629Google Scholar
- Bendat JS, Piersol AG (1986) Random data: analysis and measurement procedures. Wiley, New YorkGoogle Scholar
- Beresnev I, Gaul W, Vigil RD (2011) Direct pore-level observation of permeability increase in two-phase flow by shaking. Geophys Res Lett 38:231–248View ArticleGoogle Scholar
- Bower DR, Heaton KC (1978) Response of an aquifer near Ottawa to tidal forcing and the Alaskan earthquake of 1964. Can J Earth Sci 15:331–340View ArticleGoogle Scholar
- Brodsky EE, Roeloffs E, Woodcock D, Gall I, Manga M (2003) A mechanism for sustained groundwater pressure changes induced by distant earthquake. J Geophys Res 108(B8):503–518View ArticleGoogle Scholar
- Candela T, Brodsky EE, Marone C, Elsworth D (2014) Laboratory evidence for particle mobilization as a mechanism for permeability enhancement via dynamic stressing. Earth Planet Sci Lett 392:279–291View ArticleGoogle Scholar
- Chadha RK, Singh C, Shekar M (2008) Transient changes in well-water level in bore wells in western India due to the 2004 Mw 9.3 Sumatra Earthquake. Bull Seismol Soc Am 98:2553–2558View ArticleGoogle Scholar
- Chen Q, Liu H, Wang S, Wang LS, Liu JQ, Yang B (2013) Experimental study of the fundamental physical properties on shale in Longmaxi formation of lower silurian, Chongqing. Sci Tech Eng 13(15):796–800 (in Chinese) Google Scholar
- Cooper HH, Bredhoeft JD, Papdopulos IS, Bennnett RR (1965) The response of well-aquifer systems to seismic waves. J Geophys Res 70: 3915–3926View ArticleGoogle Scholar
- Deng QD, Zhang PZ, Ran YK (2006) Distribution of active faults in China (1:4000000). Science Press, BeijingGoogle Scholar
- Doan ML, Brodsky EE, Prioul R, Signer C (2006) Tidal analysis of borehole pressure—a tutorial. Schlumberger Research ReportGoogle Scholar
- Elkhoury JE, Brodsky EE, Agnew DC (2006) Seismic waves increase permeability. Nature 411:1135–1138View ArticleGoogle Scholar
- Elkhoury JE, Niemeijer A, Brodsky EE, Marone C (2011) Laboratory observations of permeability enhancement by fluid pressure oscillation of in situ fractured rock. J Geophys Res 116(B2): B02311/1–B02311/15Google Scholar
- Hsieh PA, Bredehoeft JD, Farr JM (1987) Determination of aquifer transmissivity from earth tide analysis. Water Resour Res 23(10):1824–1832View ArticleGoogle Scholar
- Josh M, Esteban L, Piane CD, Sarout J, Dewhurst DN, Clennell MB (2012) Laboratory characterisation of shale properties. J Petrol Sci Eng 88–89(2):107–124View ArticleGoogle Scholar
- Kayen RE, Thompson E, Minasian D, Moss RES, Collins BD, Sitar N, Dreger D, Carver GA (2004) Geotechnical reconnaissance of the 2002 Denali Fault, Alaska, Earthquake. Earthq Spectra 20(3):639–667View ArticleGoogle Scholar
- Kilb D, Gomberg J, Bodin P (2002) Aftershock triggering by complete Coulomb stress changes. J Geophys Res 107(B4):2060. doi:https://doi.org/10.1029/2001JB000202 View ArticleGoogle Scholar
- King CY, Azuma S, Igarashi G, Ohno M, Saito H, Wakita H (1999) Earthquake-related water-level changes at 16 closely clustered wells in Tono, central Japan. J Geophys Res 104(B6):13073–13082View ArticleGoogle Scholar
- Lai GJ, Huang FQ, Ge HK (2011) Apparent permeability variation of underground water aquifer induced by an earthquake: a case of the Zhouzhi well and the 2008 Wenchuan earthquake. Earthq Sci 24:437–445View ArticleGoogle Scholar
- Lai GJ, Ge HK, Xue L, Brodsky EE, Huang FQ, Wang WW (2013a) Tidal response variation and recovery following the Wenchuan earthquake from water level data of multiple wells in the nearfield. Tectonophysics 619–620(5):115–122Google Scholar
- Lai GJ, Ge HK, Wang WW (2013b) Transfer functions of the well-aquifer systems response to atmospheric loading and Earth tide from low to high-frequency band. J Geophys Res 118:1904–1924View ArticleGoogle Scholar
- Li YJ, Liu H, Zhang LH, Lu ZG, Li QR, Huang YB (2013) Lower limits of evaluation parameters for the lower Paleozoic Longmaxi shale gas in southern Sichuan Province. Sci China Ser D 56(5):710–717View ArticleGoogle Scholar
- Linde AT, Sacks IS, Johnston MJS, Hill DP, Bilham RG (1994) Increased pressure from rising bubbles as a mechanism for remotely triggered seismicity. Nature 371(6496):408–410View ArticleGoogle Scholar
- Liu WQ, Manga M (2009) Changes in permeability caused by dynamic stresses in fractured sandstone. Geophys Res Lett 36:L20307. doi:https://doi.org/10.1029/2009GL039852 View ArticleGoogle Scholar
- Lu YZ, Li SL, Deng ZH, Pan HW, Che S, Li YL (2002) Seismology analysis and prediction system based on GIS (Mapseis Software). Chengdu Map Press, ChengduGoogle Scholar
- Manga M, Beresnev I, Brodsky EE, Elkhoury JE, Elsworth D, Ingebritsen S, Mays DC, Wang CY (2012) Changes in permeability by transient stresses: field observations, experiments and mechanisms. Rev Geophys 50(2):81–88View ArticleGoogle Scholar
- Okada Y (1992) Internal deformation due to shear and tensile faults in a half-space. Bull Seismol Soc Am 82:1018–1040Google Scholar
- Roberts PM (2005) Laboratory observations of altered porous fluid flow behavior in Berea sandstone induced by low-frequency dynamic stress stimulation. Acoust Phys 51(Supplement 1):S140–S148View ArticleGoogle Scholar
- Roeloffs EA (1996) Poroelastic techniques in the study of earthquakes-related hydrologic phenomena. Adv Geophys 37(1):135–195View ArticleGoogle Scholar
- Roeloffs EA (1998) Persistent water level changes in a well near Parkfield, California, due to local and distant earthquakes. J Geophys Res 103:869–889View ArticleGoogle Scholar
- Rojstaczer S (1988a) Determination of fluid flow properties from the response of water levels in wells to atmospheric loading. Water Resour Res 24(11):1927–1938View ArticleGoogle Scholar
- Rojstaczer S (1988b) Intermediate period response of water levels in wells to crustal strain: sensitivity and noise level. J Geophys Res 93(B11):13619–13634View ArticleGoogle Scholar
- Rojstaczer S, Agnew DC (1989) The influence of formation material properties on the response of water levels in wells to earth tides and atmospheric loading. J Geophys Res 941(B9):12403–12411View ArticleGoogle Scholar
- Sil S, Freymueller JT (2006) Well water level changes in Fairbanks, Alaska, due to the great Sumatra-Andaman earthquake. Earth Planets Space 58(2):181–184. doi:https://doi.org/10.1186/BF03353376 View ArticleGoogle Scholar
- Wang CY, Chia Y (2008) Mechanism of water level changes during earthquakes: near field versus intermediate field. Geophys Res Lett 35(35):86–109Google Scholar
- Wang CY, Manga M (eds) (2010) Earthquakes and water, series: lecture notes in earth sciences. Springer Press, BerlinGoogle Scholar
- Wang CY, Chia Y, Wang PL, Dreger D (2009) Role of S waves and Love waves in coseismic permeability enhancement. Geophys Res Lett 36:L09404Google Scholar
- West M, Sanchez J, McNutt S (2005) Periodically triggered seismicity at Mount Wrangell, Alaska, after the Sumatra earthquake. Science 308:1144–1146View ArticleGoogle Scholar
- Xue L, Li HB, Brodsky EE, Xu ZQ, Kano Y, Wang H, Mori JJ, Si JL, Pei JL, Zhang W, Yang G, Sun ZM, Huang Y (2013) Continuous permeability measurements record healing inside the Wenchuan earthquake fault zone. Science 340(6140):1555–1559View ArticleGoogle Scholar
- Yan R, Woith H, Wang RJ (2014) Groundwater level changes induced by the 2011 Tohoku earthquake in China mainland. Geophys J Int 199(1):533–548View ArticleGoogle Scholar
- Zhang Y, Huang FQ (2011) Mechanism of different coseismic water-level changes in wells with similar epicentral distances of intermediate field. Bull Seismol Soc Am 101(4):1531–1541View ArticleGoogle Scholar
- Zhang Y, Fu LY, Huang FQ, Chen XZ (2015) Coseismic water-level changes in a well induced by teleseismic waves from three large earthquakes. Tectonophysics 651–652:232–241View ArticleGoogle Scholar