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Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake
TECTO-127227; No of Pages 8 Tectonophysics xxx (2016) xxx–xxx
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Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake Anhua He a, Xuefang Fan b,⁎, Gang Zhao a, Yang Liu c, Ramesh P. Singh d, Yuliang Hu b a
Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, CEA, Beijing 100085, PR China Earthquake Administration of Shanxi Province, CEA, Taiyuan 030021, PR China Earthquake Administration of Hainan Province, CEA, Haikou 570203, PR China d School of Life and Environmental Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA b c
a r t i c l e
i n f o
Article history: Received 30 December 2015 Received in revised form 8 August 2016 Accepted 24 August 2016 Available online xxxx Keywords: Co-seismic response Groundwater level The Gorkha earthquake Underground reservoir Precursory waves
a b s t r a c t Changes in co-seismic water levels associated with the Gorkha Nepal earthquake (25 April 2015, Mw 7.8) were recorded in the Jingle well in Shanxi Province China (longitude E112.03°, latitude N38.35°, about 2769 km from epicenter). Based on the observed water levels, we clearly identified signals relating to P, S and surface waves. However, the water temperature recorded at a depth of 350 m shows no co-seismic changes. A spectrum analysis of co-seismic variations of water level shows that the oscillation frequency and amplitude of water level in the borehole are determined by the natural frequency of the borehole, which is not associated with the propagation of seismic waves. The borehole-aquifer system shows a large amplification associated with ground vibrations generated by earthquakes. Considering the local hydro-geological map and the temperature gradient of the Jingle well, a large volume “groundwater reservoir” model can be used to explain these processes. Due to seismic wave propagation, the volume of a well-confined aquifer expands and contracts forming fractures that change the water flow. In the well-confined aquifer, water levels oscillate simultaneously with high amplitude ground shaking during earthquakes. However, the water in the center of the “underground reservoir” remains relatively stationary, without any changes in the water temperature. In addition, a possible precursor wave is recorded in the water level at the Jingle well prior to the Gorkha earthquake. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Changes in ground water level and water temperature in boreholes in and around earthquake epicenters have been studied for several decades (Cooper et al., 1965). Water is known to be a rigid body and is incompressible (Agarwal et al., 2011). The internal pressure of a wellconfined aquifer fluctuates due to expansion and contraction associated with the stress and propagation of seismic waves (Liu et al., 1989). If the borehole penetrates through a well-confined aquifer, the water level in the borehole fluctuates due to the internal pressure of the aquifer, known as the co-seismic response of water levels (Ferreira et al., 1995; Brodsky et al., 2003). During the stress build-up process, water in different layers is mixed; as a result the temperature may vary depending upon the water temperature in different layers. Changes in water temperature also depend on the subsurface geology. As a result, co-seismic changes in water temperature can be observed (Wang et al., 2001). The co-seismic changes in water level/temperature associated with earthquakes have been reported by many studies (Roeloffs,
⁎ Corresponding author. E-mail address: [email protected] (X. Fan).
1998; Roeloffs et al., 2003; Huang et al., 2004; Ingebritsen and Manga, 2014). Wakita (1975) considered co-seismic changes in water wells as a possible indicator of changes in tectonic strain associated with earthquakes. Shi et al. (2007, 2015) suggested that permeability, rather than static strain, is a more plausible factor to explain most of the co-seismic changes associated with earthquakes. King et al. (2000) suggested that the high sensitivity of water level to an earthquake occurrence can be attributed to the hydrological conditions as well as to the relatively high permeability of the tapped aquifer (Elkhoury et al., 2006). Kano and Yanagidani (2006) monitored pore pressure changes from hydroseismograms and examined the performance of the closed wells over a wide frequency range, and found a relationship (a zero-order system) between the radial ground velocity and pore pressure. In China, various parameters are being monitored in water wells, including water level, water temperature and water radon concentrations associated with earthquakes (Ye et al., 2015). Recently, co-seismic changes in water level and water temperature associated with many earthquakes were observed (Chen et al., 2007; Shi et al., 2007; Liu et al., 2015; He et al., 2016). The study of co-seismic changes in groundwater has emerged as an important research area, which can provide an improved understanding of earthquake processes and corresponding changes in surface and subsurface parameters.
http://dx.doi.org/10.1016/j.tecto.2016.08.019 0040-1951/© 2016 Elsevier B.V. All rights reserved.
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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A. He et al. / Tectonophysics xxx (2016) xxx–xxx
Co-seismic change of water level up to a maximum variation of 1.75 m was observed at the Jingle well associated with the 25 April 2015 Gorkha Nepal (Mw7.8) earthquake. However, water temperature measured by a sensor deployed at the depth of 365 m show no appreciable change. In this paper, we invoke an “underground reservoir” model to explain the water level change in the context of no appreciable change in water temperature. We take into consideration the local hydro-geological information, borehole lithology, distribution of aquifers and temperature gradient in the Jingle well. 2. Jingle well The Jingle well (longitude E112.03°, latitude N38.35°, elevation 1295 m) is located in Jingle County, Shanxi Province, China, at the south section of Ningwu-Jingle multiple syncline, which is mainly a monoclinic structure (340°∠ 30°) (Fig. 1). The well is located about 100 m from the DongNian River, which runs east to west and feeds into the Fen River. The depth of the Jingle well is 362.29 m, and the observed layer is the pressure-bearing karst water of Ordovician (O2) Majiagou limestone, siliceous limestone and upper Cambrian argillaceous limestone, and a Quaternary alluvial sand and gravel layer 0– 46.30 m thick (Fig. 2). Fault fracture zones are found at depth intervals 229.81–245.95 m and 258.28–288.76 m. The Cambrian and Ordovician karst aquifer lies in the fracture zone at a depth of 229.81–288.76 m (Fig. 2). The water level and water temperature (at a depth of 350 m) have been recorded in the Jingle well since 2007. The water level is measured using a SWY-II water-level meter, which is a differential pressure sensor with a resolution of 0.001 m and a sampling rate of 1 per second. The water temperature is monitored using a SZW-1A digital thermometer containing a quartz crystal temperature sensor (Shimamura, 1980), which has a resolution of 0.0001 °C and sampling rate of 1 per minute. Water level (m) (red line) and water temperature (°C) (red line) measured during 2007–2016 are shown in Fig. 3. The monthly cumulative rainfall (mm) in the surrounding area is shown with the blue bar (Fig. 3) from July 2007 to August 2014. Representative short-term (January 1–2, 2016) fluctuations of water level and water temperature
are shown in the insets of Fig. 3. The perennial variation of water level is about 2 m, with an annual variation about 1 m, while the daily variation was found to be less than 0.02 m, associated with earth tidal response. In addition, a weak correlation between water level and rainfall is found, where the maximum value of water level is observed in the month of October (the peak rainfall occurs in the month of July/ August every year). In the initial 3-year measurement period, the yearly water temperature varied up to about 0.05 °C/a (the black dotted line in panel b of Fig. 3), which may be caused by the aging of the sensor (Shimamura et al., 1984) or borehole cable. After the initial three year measurement period, the annual variation of water temperature is about 0.3 °C and the daily variation is only about 0.001 °C. The water level and water temperature in the Jingle well are not substantially affected by changes in external conditions. The temperature gradient in the Jingle well was measured two times in the years 2007 and 2014 (Fig. 2, blue line 2007, red line 2014), with measurements carried out at depth interval of 50 m in the year 2007 and 10 m in the year 2014. We measured for about 30 min at each point, and considered an average value of the last 5 min of water temperature. The water temperature gradient was almost close to 0 °C per 100 m to a depth 229.81 m, which is very low compared to an average geothermal gradient (about 2.5 °C per 100 m). Such a low geothermal gradient could be associated with the large permeability coefficient (84.5 m per day to the depth of 229.81 m) that may promote mixing in the borehole. However, the water temperature gradient becomes unstable below 229.81 m in the Jingle well. From a local hydrogeological investigation, we found that the development of karst fissures and karst caves in the Jingle well region, where the karst to caves ratio is found to be 1.37%. The fissures and caves could attribute to the fast movement of water in horizontal layers, causing the temperature gradient to rapidly decline. Here, we consider karst fissures and karst caves to be well-confined and constitute a large “underground reservoir”. 3. 25 April 2015 Gorkha Nepal earthquake The Gorkha earthquake occurred at 06:11:26 on 25 April 2015 (UTC), with a moment magnitude of 7.8 and a maximum Mercalli
Fig. 1. Hydrogeological map of the Jingle well region, location of the Jingle well is shown with yellow star. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
A. He et al. / Tectonophysics xxx (2016) xxx–xxx
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conglomerate
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-0.06
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dolomite carbonaceous marl
350
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Fig. 2. Lithology and temperature gradient of the Jingle well. The blue line is the temperature gradient measured in 2007 and the red line is the temperature gradient measured in 2014. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
7
320
9.3 (Jan/01/2016-Jan/02/2016)
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9.31 9.315
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9.32 00 04 08 12 16 20 00 04 08 12 16 20
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11 2007
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Rainfall (mm)
Water Level(m)
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2015
2016
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(a) Water Level and Rainfall 10.2
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9.97 (Jan/01/2016-Jan/02/2016) 9.969
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9.8 2007
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Rainfall (mm)
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(b) Water Temperature and Rainfall Fig. 3. The multi-year observed water temperature and water level in the Jingle well (a. the red line is water level (m) and the blue bar is rainfall (mm), the inset shows the two days' water level on January 01–02, 2016; b. the red line is water temperature (°C) and the blue bar is rainfall (mm), the inset is the two days' water temperature (°C) measured on January 01–02, 2016, the pink arrow is the event that the temperature sensor was repaired in July 2013, and the black dotted line is the trend of water temperature). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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Fig. 4. Co-seismic response of groundwater in the Jingle well associated with the 2015 Mw 7.8 Gorkha, Nepal earthquake.
Intensity scale of IX (violent). Its epicenter (longitude E84.708°, latitude N28.147°) was east of the district of Lamjung, and its hypocenter was at a depth of approximately 15 km (Galetzka et al., 2015). After the 1934 Nepal–Bihar earthquake, the Gorkha earthquake was one of the deadliest earthquakes in the region, resulting in over 8000 fatalities (Ahmad and Singh, 2015; Hayes et al., 2015). The co-seismic water level changes in the Jingle well (located about 2769 km from the epicenter) associated with the Gorkha earthquake are shown in Fig. 4. An important observation is that despite water level changes observed in the borehole, the water temperature remains unaffected. 3.1. The underground reservoir model
3.2. Seismic phases in water level fluctuations Here, we analyze the seismic phases in water level oscillations in the Jingle well associated with the Gorkha earthquake. Within 100 km of the Jingle well, four seismic stations (KEL, LOF, NIW and CHS) (Fig. 6) are selected to analyze the seismic waves. We have considered seismic waveforms measured for the Gorkha earthquake and computed arrival-time, seismic phase, amplitude and oscillation periods, and estimated the seismic arrival-time at the Jingle well from these four stations. The BBVS-60 model seismometer is used; its base time was calibrated with GPS with an absolute accuracy of 0.001 s. Table 1 shows the estimate of the arrival-time of P-wave of the Gorkha earthquake in the Jingle well at 06:16:48 h and S-wave arrival-time at 06:21:22 h on 25 April 2015. The time difference between P and S
The co-seismic response of water level during the Gorkha earthquake shows oscillation with large amplitudes, with a maximum peak-to-peak value of about 1.75 m. The water temperature almost remained constant despite the large-amplitude water level oscillation (Yang et al., 2008). From the local hydrogeological analysis, we consider that a large volume “underground reservoir” model explains this phenomenon. There are many karst caves, underground rivers and fractures in the Jingle well area, which constitute a large volume “underground reservoir” (Fig. 5). Seismic waves propagating across the well region may induce small changes in the volume of the reservoir via expansion and contraction, with simultaneous changes in the internal reservoir pressure. The water in the borehole is connected to the confined cavity, and oscillates with the internal pressure of the cavity; as a result, the water level declines with the decrease in internal pressure, and the water level rises when the internal pressure increases. The volume of water moving in the borehole can be estimated from the following equation: Q ¼ π∙r2 ∙h ¼ π∙0:062 ∙1:75≈0:02m3
ð1Þ
Where Q is the volume of water, r is the borehole radius, and h is the maximum amplitude. The volume of water moving is only 0.02 m3, even though the water level fluctuates up to 1.75 m, which is a very small volume relative to the “underground reservoir” and insufficient to cause water moving in the center of reservoir. Thus, the water temperature in the center of the reservoir (symbolized by the “T” in Fig. 5) remains unaffected when the water level fluctuates. P-waves, with high frequency and small amplitudes propagates through water, causing small fluctuations of water in the borehole. Sand surface waves cannot propagate in water; however, the volume of the confined cavity with compression and expansion may change. The “underground reservoir” (borehole-aquifer system) is likely to deform due to S-waves and surface waves and amplify water level causing large fluctuations in the borehole.
Fig. 5. The “underground reservoir” model (“T” is the position of water temperature sensor).
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
A. He et al. / Tectonophysics xxx (2016) xxx–xxx
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Fig. 6. Map showing locations of seismic stations and Jingle well.
wave is about 273 s. Due to the absence of basic tectonic information of each seismic station, it is difficult to estimate the surface wave parameters. Fig. 7 shows the co-seismic response of water level of the Gorkha earthquake in the context of the arrival of seismic waves. Water level was recorded by a SWY-II water level meter, which adopts the SNTP (Simple Network Time Protocol) (Mills, 1996) to calibrate the time, where the SWY-II water level meter allow the time error was smaller than 5 min. The absolute time between the hydroseismograms and the seismograms cannot be compared since the time error of water level recorder is so large (about 3 min slower than seismometer). We therefore compare the seismic and well records by aligning the first
movement of the hydroseismograms and seismograms (Fig. 7). The P-, S- and surface waves were clearly identified as propagating through the water level. In addition, we find that the start time of S- and surface waves in the hydroseismograms is the same as the seismograms. Therefore, we conclude that the relationship between the hydroseismograms (pore pressure) and seismograms (radial ground velocity) is a zeroorder system, similar to the findings of Kano and Yanagidani (2006). The teleseismic P-wave period was found to be about 1 ~ 10 s, Swave periods about 3 ~ 20 s, and surface wave periods about 8 ~ 60 s. We have used the seismic data of station NIW, which is very close to the Jingle well, to compute the seismic phases and amplitudes simulating the SK seismometer (Bormann et al., 2007). We find that the P-wave
Table 1 The parameters, compute from the seismic waves data, of the Gorkha earthquake in four stations (KEL, LOF, NIW and CHS), and the hydroseismograms of water level of the Jingle well. Origin time
2015-04-25 06:11:11.15
Epicenter Magnitude Focal depth Residual Epicenter accuracy Depth accuracy Azimuth gaps
27°52.60′ 82°58.04′ 8.4(Ms) 20.0 1.306 N/A(km) N/A 358
NO.
St. name
Phase
Date
Time
OTime
t-res
Delta
Ms
0
SX/KEL
26.23°
8.3
11-06.61
0.32 4.04
26.22°
8.4
2
SX/NIW
11-09.96
−0.15 0.62
26.67°
8.5
3
SX/CHS
06:16:46.780 06:21:19.020 06:24:45.9 06:25:1.0 06:16:47.030 06:21:22.880 06:24:40.8 06:25:8.6 06:16:50.700 06:21:26.780 06:25:21.2 06:25:21.2 06:16:50.820 06:21:21.030 06:24:58.5 06:25:26.2 06:20:12 06:24:40 06:28:10
−0.08 −0.09
SX/LOF
2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25
11-11.07
1
P S Surf.-N Surf.-E P S Surf.-N Surf.-E P S Surf.-N Surf.-E P S Surf.-N Surf.-E P S Surf.
11-17.82
−0.09 −5.24
26.68°
8.4
Water Level
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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A. He et al. / Tectonophysics xxx (2016) xxx–xxx
Fig. 7. Comparison of the seismogram (top) and hydroseismogram (bottom) at the Jingle well during the Gorkha earthquake of 25 April 2015.
period is about 3 s with an amplitude of 577 μm, the S-wave period is 12 s with an amplitude 2701 μm, and the surface wave period is 19 s with an amplitude of 13,193 μm. We also carried out spectral analysis of the hydroseismograms in three period intervals, 06:18–06:21 for P-waves, 06:22–06:24 for Swaves, and 06:26–06:28 for surface waves. The results are shown in Fig. 8. The dominant frequency in every period interval is compared with the parameters between hydroseismograms and seismograms in Table 2. Table 2 shows the periods of P-, S- and surface waves in seismograms, as 3, 12 and 19 s, respectively. The periods of P-, S- and
surface waves in the hydroseismograms are 13.85, 14.12 and 12.00 s, respectively. These observations suggest that the same periods of all three types of waves in water level are nearly independent of seismic waves. Based on the spectral analysis of hydroseismograms, especially the Sand surface waves, the bandwidth of hydroseismograms is very narrow and sharply declines in two sides of the dominant frequency. The borehole-aquifer system for seismograms is a band-pass filter with a narrow bandwidth, which indicates that the oscillation period of water level in borehole is determined by the resonant frequency of borehole and independent of the seismic waves. We estimate a resonance frequency of 12 s for the Jingle well from the surface waves, which cause the maximum oscillation in water level.
Fig. 8. The spectral analysis of hydroseismograms.
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
A. He et al. / Tectonophysics xxx (2016) xxx–xxx
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Table 2 Comparison of the parameters of hydroseismograms and seismograms.
Perioda Seismograms Hydroseismograms a
Amplitude (μm) Period (s) Amplitude (m) Period (s)
P-wave
S-wave
Surface wave
06:18–06:21
06:22–06:24
06:26–06:28
577 3 0.0018 1/0.0722 = 13.85
2701 12 0.0198 1/0.0708 = 14.12
13,193 19 0.3449 1/0.0833 = 12.00
Period(s) of seismograms.
The resonance frequency of the borehole is given by the following equation (Cooper et al., 1965): vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u g ωw ≈u u 3 t Hþ d 8
ð2Þ
Here, ωw is the resonance frequency, g is acceleration due to gravity, H is water column height of the casing of well, and d is the length of filter pipe. For the Jingle well, we assumed H = 50m , d = 312 m,and (H + d = depth of well = 362.29 m). Thus, ωw ≈0.213, implying that the oscillation period of 4.7 s has the largest amplification factor. However, we obtained the natural frequency of 12 s for the Jingle well from the spectrum analysis, and there are very large errors associated with calculating the natural frequency using Eq. (2) in the karst borehole. To correct this equation, we need the co-seismic responses of water level with many earthquakes, and the observed water level must use water level recorder with high sampling rate (1 per second). The amplitude ratio of P-, S- and surface waves in seismograms is 577:2701:13,193 ≈ 1:4.7:22.9. However, the same ratio in the hydroseismograms is 0.0018:0.0198:0.3449 ≈ 1:11.0:191.6. We conclude that the borehole-aquifer system magnifies ground vibration, and the amplification factor shows a non-linear relationship, which is larger when the ground vibration is more intense. The magnifying function of the borehole-aquifer system suggests the relationship between hydroseismograms (pore pressure) and seismograms (ground vibration) is a zero-order system, which is characterized by no distortion or time lag, but the seismograms cannot be recorded without distortion. 4. Discussion The 2015 Mw 7.8 Gorkha, earthquake caused 1.75 m of water level oscillation at the Jingle well, at a distance of 2769 from the epicenter. The P, S and surface waves are identified from the co-seismic water level response. Water temperature in the Jingle well remained almost constant in response to the Gorkha earthquake, which is rather surprising given the large-amplitude oscillations of water level observed. The “underground reservoir” model can provide a reasonable explanation for this unexpected observation. This model not only explains the amplification of the borehole-aquifer system by seismic waves, but also shows that no change in the water temperature is required for large amplitude water level oscillations. The oscillation frequency of water level caused by surface waves is about 12 s, but the actual seismic wave frequency is 19 s. The natural frequency of the borehole, when computed using Eq. (2) (Cooper et al., 1965), reveals a disagreement in the theoretical and observed natural frequencies of the borehole. One solution to this problem is to sample co-seismic water levels with a high sampling rate water level recorder. The borehole-aquifer system is a band-pass filter with a narrow bandwidth compared to seismic waves. To more fully investigate this problem, we considered the Menyuan, China earthquake (Mw = 5.9, 2016–01-20 17:13:13), which occurred 914 km from the Jingle well and for which seismic phases can be identified in water levels. We compute the ratio of amplitudes between seismogram and water
level and from Table 3, and conclude that the amplitude ratio between seismograms and water levels shows different values at the Jingle well. The Mw 5.9 Menyuan earthquake did not influence water level fluctuations similarly to the Gorkha earthquake, even though the Menyuan epicenter was much closer (~914 km). The borehole-aquifer system can magnify ground vibrations, and the amplification factor is larger with more intense ground vibration. We find another very interesting wave from water level oscillations in the Jingle well; a small amplitude and short time oscillation with frequency of about 6.5 Hz with duration of about 120 s, peak-to-peak value of about 30 mm observed at 23:57–23:59 h on 24 April 2015 (UTC), 6.5 h prior to the Gorkha mainshock (Fig. 9). A similar observation was also noted earlier by Kanamori and Cipar (1974) for long-period (300–600 s) waves arriving at the P time for a large foreshock, which occurred about 15 min before the great Chilean earthquake of 22 May 1960 (Ms = 8.3). This is likely due to a large-scale deformation associated with the triggering of foreshocks and the main earthquake event. According to Zhou et al. (2009) and Zhang et al. (2011), observations of gravity, ground tilt, strain, ground water and seismographs can show similar phenomenon prior to earthquakes. In addition, Zhou et al. (2009) and Zhang et al. (2011) considered that the precursory waves have clear physical mechanism and suggested they represent short-term precursory information for early indication of an impending earthquake. The water level fluctuations observed at 23:57–23:59 h on 24 April 2015 occur prior to the impending Gorkha earthquake (occurred at 06:11:26 h on 25 April 2015) yet there was no other recognized disturbance recorded in the proximity of Jingle well. We cannot get the precursory crustal deformative processes since experimental data are lacking, but lateral migration of the stress field after dislocation events has been recognized for the generation of impending earthquakes (Whitcomb et al., 1973; Igarashi et al., 1992; Martinelli, 2015; Lupi et al., 2016), we infer such observed water level fluctuations/oscillation in the Jingle well hint at the existence of precursory waves, which is an intriguing possibility that needs to be further investigated. 5. Conclusions The “groundwater reservoir” model can help to explain the unusual co-seismic response observed at the Jingle well in response to the Gorkha earthquake, which includes water oscillating with large amplification and almost constant water temperature. The borehole-aquifer system is a band-pass filter with narrow bandwidth, where the parameters are dependent on the natural frequency of borehole. The boreholeaquifer system can amplify the ground vibration, and the amplification factor will be larger with the intense ground vibration. Potential precursory waves were recorded about 6.5 h prior to the Gorkha earthquake,
Table 3 The ratio of amplitudes between the 2016 Menyuan, China Mw 5.9 seismogram and water level at the Jingle well.
Earthquake
Magnitude
Distance(km)
Seis. amp. (μm)
WL amp. (m)
ratio
Nepal Menyuan
Mw7.8 Mw5.9
2769 914
13,193 493
1.757 0.046
7508.822 10,717.39
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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Fig. 9. Potential precursory waves recorded by variations in water level of the Jingle well.
but a causal mechanism of these water level fluctuations has not been identified. Acknowledgments The present study is supported financially by the Central Level, Scientific Research Institute for Basic R and D Special Fund Business (ZDJ2014-04), the National Natural Science Foundation of China (41104051) and Special Key Tasks of Earthquake Monitoring and Forecasting of China (86#). The authors thank the China Earthquake Network Center for providing the water level data and the seismic data. The authors are grateful to the two anonymous Referees, Guest Editor of the special issue and Editor of the Journal for their valuable Comments/suggestions that helped us to improve an earlier version of the manuscript. References Agarwal, M., Alam, M.P., Chakravarty, C., 2011. Thermodynamic, diffusional, and structural anomalies in rigid-body water models. J. Phys. Chem. B 115 (21), 6935–6945. Ahmad, R., Singh, R.P., 2015. Attenuation relation predicted observed ground motion of Gorkha Nepal earthquake of April 25, 2015. Nat. Hazards http://dx.doi.org/10.1007/ s11069-015-1969-2 (EISSN: 1573-0840 ISSN: 0921-030X). Bormann, P., Liu, R., Ren, X., Gutdeutsch, R., Kaiser, D., Castellaro, S., 2007. Chinese national network magnitudes, their relation to NEIC magnitudes, and recommendations for new IASPEI magnitude standards. Bull. Seismol. Soc. Am. 97 (1B), 114–127. Brodsky, E.E., Roeloffs, E., Woodcock, D., Gall, I., Manga, M., 2003. A mechanism for sustained groundwater pressure changes induced by distant earthquakes. J. Geophys. Res. Solid Earth 108 (B8) 1978–2012. Chen, D., Liu, Y., Yang, X., Liu, Y., 2007. Co-seismic water level, temperature responses of some wells to far-field strong earthquakes and their mechanisms (in Chinese). Seismol. Geol. 29 (1), 122–132. Cooper, H.H., Bredehoeft, J.D., Papadopulos, I.S., Bennett, R.R., 1965. The response of wellaquifer systems to seismic waves. J. Geophys. Res. 70 (16), 3915–3926. Elkhoury, J.E., Brodsky, E.E., Agnew, D.C., 2006. Seismic waves increase permeability. Nature 441 (7097), 1135–1138. Ferreira, J.M., De Oliveira, R.T., Assumpção, M., Moreira, J.A., Pearce, R.G., Takeya, M.K., 1995. Correlation of seismicity and water level in the Açu reservoir—an example from Northeast Brazil. Bull. Seismol. Soc. Am. 85 (5), 1483–1489. Galetzka, J., Melgar, D., Genrich, J.F., Geng, J., Owen, S., Lindsey, E.O., Upreti, B.N., 2015. Slip pulse and resonance of the Kathmandu basin during the 2015 Gorkha earthquake, Nepal. Science 349 (6252), 1091–1095. Hayes, G.P., Briggs, R.W., Barnhart, W.D., Yeck, W.L., McNamara, D.E., Wald, D.J., Marano, K., 2015. Rapid characterization of the 2015 Mw 7.8 Gorkha, Nepal, earthquake sequence and its seismotectonic context. Seismol. Res. Lett. 86 (6), 1557–1567. He, A., Singh, R.P., Sun, Z., Ye, Q., Zhao, G., 2016. Comparison of regression methods to compute atmospheric pressure and earth tidal coefficients in water level associated with Wenchuan earthquake of 12 may 2008. Pure Appl. Geophys. http://dx.doi.org/ 10.1007/s00024-016-1310-3. Huang, F., Jian, C., Tang, Y., Xu, G., Deng, Z., Chi, G., 2004. Response changes of some wells in the mainland subsurface fluid monitoring network of China, due to the September 21, 1999 Ms 7.6 Chi Chi earthquake. Tectonophysics 390, 217–234.
Igarashi, G., Wakita, H., Sato, T., 1992. Precursory and co-seismic anomalies in well water levels observed for the February 2, 1992 Tokyo Bay earthquake. Geophys. Res. Lett. 19 (15), 1583–1586. Ingebritsen, S.E., Manga, M., 2014. Earthquakes: hydrogeochemical precursors. Nat. Geosci. 7 (10), 697–698. Kanamori, H., Cipar, J.J., 1974. Focal process of the great Chilean earthquake May 22, 1960. Phys. Earth Planet. Inter. 9 (2), 128–136. Kano, Y., Yanagidani, T., 2006. Broadband hydroseismograms observed by closed borehole wells in the Kamioka mine, Central Japan: response of pore pressure to seismic waves from 0.05 to 2 Hz. J. Geophys. Res. 111 (B3), B03410. http://dx.doi.org/10.1029/ 2005JB003656. King, C.Y., Azuma, S., Ohno, M., Asai, Y., He, P., Kitagawa, Y., Wakita, H., 2000. In search of earthquake precursors in the water-level data of 16 closely clustered wells at Tono, Japan. Geophys. J. Int. 143 (2), 469–477. Liu, L.B., Roeloffs, E., Zheng, X.Y., 1989. Seismically induced water level fluctuations in the Wali well, Beijing, China. J. Geophys. Res. Solid Earth 94 (B7), 9453–9462 1978–2012. Liu, Y., Ren, H., Zhang, L., Fu, H., Sun, X., He, D., Yu, H., Zhou, Z., Zhang, G., 2015. Underground fluid anomalies and the precursor mechanisms of the Ludian Ms6.5 earthquake (in Chinese). Seismol. Geol. 37 (1), 307–318. Lupi, M., Ricci, B.S., Kenkel, J., Ricci, T., Fuchs, F., Miller, S.A., Kemna, A., 2016. Subsurface fluid distribution and possible seismic precursory signal at the Salse di Nirano mud volcanic field, Italy. Geophys. J. Int. 204 (2), 907–917. Martinelli, G., 2015. Hydrogeologic and geochemical precursors of earthquakes: an assessment for possible applications. Boll. Geofis. Teor. Appl. 56, 83–94. Mills, D., 1996. Simple network time protocol (sntp) version 4 for ipv4, ipv6 and osi. Network 31 (4), 133–135. Roeloffs, E.A., 1998. Persistent water level changes in a well near Parkfield, California, due to local and distant earthquakes. J. Geophys. Res. All Series 103, 869–889. Roeloffs, E., Sneed, M., Galloway, D.L., Sorey, M.L., Farrar, C.D., Howle, J.F., Hughes, J., 2003. Water-level changes induced by local and distant earthquakes at Long Valley caldera, California. J. Volcanol. Geotherm. Res. 127 (3), 269–303. Shi, Y., Cao, J., Ma, L., Yin, B., 2007. Tele-seismic coseismic well temperature changes and their interpretation. Acta Seismol. Sin. 29 (3), 265–273. Shi, Z., Wang, G., Manga, M., Wang, C.Y., 2015. Mechanism of co-seismic water level change following four great earthquakes–insights from co-seismic responses throughout the Chinese mainland. Earth Planet. Sci. Lett. 430, 66–74. Shimamura, H., 1980. Precision quartz thermometers for borehole observations. J. Phys. Earth 28 (3), 243–260. Shimamura, H., Ino, M., Hikawa, H., Iwasaki, T., 1984. Groundwater microtemperature in earthquake regions. Pure Appl. Geophys. 122 (6), 933–946. Wakita, H., 1975. Water wells as possible indicators of tectonic strain. Science 189 (4202), 553–555. Wang, C.Y., Cheng, L.H., Chin, C.V., Yu, S.B., 2001. Coseismic hydrologic response of an alluvial fan to the 1999 Chi-Chi earthquake, Taiwan. Geology 29 (9), 831–834. Whitcomb, J.H., Garmany, J.D., Anderson, D.L., 1973. Earthquake prediction: variation of seismic velocities before the San Francisco earthquake. Science 180 (4086), 632–635. Yang, Z., Deng, Z., Liu, C., Wang, G., Zu, H., Tao, J., Song, J., 2008. Coseismic changes of water level and water temperature caused by Ms8.0 Wenchuan earthquake (in Chinese). Seismology and Geology 30 (4), 895–905. Ye, Q., Singh, R.P., He, A., Ji, S., Liu, C., 2015. Characteristic behavior of water radon associated with Wenchuan and Lushan earthquakes along Longmenshan fault. Radiat. Meas. 76, 44–53. Zhang, S., Lv, F., Li, B., 2011. Discussion about the general problems existing in the precursory wave of well water level (in Chinese). Earthq. Res. China 27 (4), 348–362. Zhou, L., Qiu, Z., Tang, L., 2009. Statistical test of precursory waves before Wenchuan Ms8.0 earthquake. J. Of. Geod. Geodyn. 29 (2), 24–28.
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake Anhua He a, Xuefang Fan b,⁎, Gang Zhao a, Yang Liu c, Ramesh P. Singh d, Yuliang Hu b a
Key Laboratory of Crustal Dynamics, Institute of Crustal Dynamics, CEA, Beijing 100085, PR China Earthquake Administration of Shanxi Province, CEA, Taiyuan 030021, PR China Earthquake Administration of Hainan Province, CEA, Haikou 570203, PR China d School of Life and Environmental Sciences, Schmid College of Science and Technology, Chapman University, Orange, CA 92866, USA b c
a r t i c l e
i n f o
Article history: Received 30 December 2015 Received in revised form 8 August 2016 Accepted 24 August 2016 Available online xxxx Keywords: Co-seismic response Groundwater level The Gorkha earthquake Underground reservoir Precursory waves
a b s t r a c t Changes in co-seismic water levels associated with the Gorkha Nepal earthquake (25 April 2015, Mw 7.8) were recorded in the Jingle well in Shanxi Province China (longitude E112.03°, latitude N38.35°, about 2769 km from epicenter). Based on the observed water levels, we clearly identified signals relating to P, S and surface waves. However, the water temperature recorded at a depth of 350 m shows no co-seismic changes. A spectrum analysis of co-seismic variations of water level shows that the oscillation frequency and amplitude of water level in the borehole are determined by the natural frequency of the borehole, which is not associated with the propagation of seismic waves. The borehole-aquifer system shows a large amplification associated with ground vibrations generated by earthquakes. Considering the local hydro-geological map and the temperature gradient of the Jingle well, a large volume “groundwater reservoir” model can be used to explain these processes. Due to seismic wave propagation, the volume of a well-confined aquifer expands and contracts forming fractures that change the water flow. In the well-confined aquifer, water levels oscillate simultaneously with high amplitude ground shaking during earthquakes. However, the water in the center of the “underground reservoir” remains relatively stationary, without any changes in the water temperature. In addition, a possible precursor wave is recorded in the water level at the Jingle well prior to the Gorkha earthquake. © 2016 Elsevier B.V. All rights reserved.
1. Introduction Changes in ground water level and water temperature in boreholes in and around earthquake epicenters have been studied for several decades (Cooper et al., 1965). Water is known to be a rigid body and is incompressible (Agarwal et al., 2011). The internal pressure of a wellconfined aquifer fluctuates due to expansion and contraction associated with the stress and propagation of seismic waves (Liu et al., 1989). If the borehole penetrates through a well-confined aquifer, the water level in the borehole fluctuates due to the internal pressure of the aquifer, known as the co-seismic response of water levels (Ferreira et al., 1995; Brodsky et al., 2003). During the stress build-up process, water in different layers is mixed; as a result the temperature may vary depending upon the water temperature in different layers. Changes in water temperature also depend on the subsurface geology. As a result, co-seismic changes in water temperature can be observed (Wang et al., 2001). The co-seismic changes in water level/temperature associated with earthquakes have been reported by many studies (Roeloffs,
⁎ Corresponding author. E-mail address: [email protected] (X. Fan).
1998; Roeloffs et al., 2003; Huang et al., 2004; Ingebritsen and Manga, 2014). Wakita (1975) considered co-seismic changes in water wells as a possible indicator of changes in tectonic strain associated with earthquakes. Shi et al. (2007, 2015) suggested that permeability, rather than static strain, is a more plausible factor to explain most of the co-seismic changes associated with earthquakes. King et al. (2000) suggested that the high sensitivity of water level to an earthquake occurrence can be attributed to the hydrological conditions as well as to the relatively high permeability of the tapped aquifer (Elkhoury et al., 2006). Kano and Yanagidani (2006) monitored pore pressure changes from hydroseismograms and examined the performance of the closed wells over a wide frequency range, and found a relationship (a zero-order system) between the radial ground velocity and pore pressure. In China, various parameters are being monitored in water wells, including water level, water temperature and water radon concentrations associated with earthquakes (Ye et al., 2015). Recently, co-seismic changes in water level and water temperature associated with many earthquakes were observed (Chen et al., 2007; Shi et al., 2007; Liu et al., 2015; He et al., 2016). The study of co-seismic changes in groundwater has emerged as an important research area, which can provide an improved understanding of earthquake processes and corresponding changes in surface and subsurface parameters.
http://dx.doi.org/10.1016/j.tecto.2016.08.019 0040-1951/© 2016 Elsevier B.V. All rights reserved.
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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Co-seismic change of water level up to a maximum variation of 1.75 m was observed at the Jingle well associated with the 25 April 2015 Gorkha Nepal (Mw7.8) earthquake. However, water temperature measured by a sensor deployed at the depth of 365 m show no appreciable change. In this paper, we invoke an “underground reservoir” model to explain the water level change in the context of no appreciable change in water temperature. We take into consideration the local hydro-geological information, borehole lithology, distribution of aquifers and temperature gradient in the Jingle well. 2. Jingle well The Jingle well (longitude E112.03°, latitude N38.35°, elevation 1295 m) is located in Jingle County, Shanxi Province, China, at the south section of Ningwu-Jingle multiple syncline, which is mainly a monoclinic structure (340°∠ 30°) (Fig. 1). The well is located about 100 m from the DongNian River, which runs east to west and feeds into the Fen River. The depth of the Jingle well is 362.29 m, and the observed layer is the pressure-bearing karst water of Ordovician (O2) Majiagou limestone, siliceous limestone and upper Cambrian argillaceous limestone, and a Quaternary alluvial sand and gravel layer 0– 46.30 m thick (Fig. 2). Fault fracture zones are found at depth intervals 229.81–245.95 m and 258.28–288.76 m. The Cambrian and Ordovician karst aquifer lies in the fracture zone at a depth of 229.81–288.76 m (Fig. 2). The water level and water temperature (at a depth of 350 m) have been recorded in the Jingle well since 2007. The water level is measured using a SWY-II water-level meter, which is a differential pressure sensor with a resolution of 0.001 m and a sampling rate of 1 per second. The water temperature is monitored using a SZW-1A digital thermometer containing a quartz crystal temperature sensor (Shimamura, 1980), which has a resolution of 0.0001 °C and sampling rate of 1 per minute. Water level (m) (red line) and water temperature (°C) (red line) measured during 2007–2016 are shown in Fig. 3. The monthly cumulative rainfall (mm) in the surrounding area is shown with the blue bar (Fig. 3) from July 2007 to August 2014. Representative short-term (January 1–2, 2016) fluctuations of water level and water temperature
are shown in the insets of Fig. 3. The perennial variation of water level is about 2 m, with an annual variation about 1 m, while the daily variation was found to be less than 0.02 m, associated with earth tidal response. In addition, a weak correlation between water level and rainfall is found, where the maximum value of water level is observed in the month of October (the peak rainfall occurs in the month of July/ August every year). In the initial 3-year measurement period, the yearly water temperature varied up to about 0.05 °C/a (the black dotted line in panel b of Fig. 3), which may be caused by the aging of the sensor (Shimamura et al., 1984) or borehole cable. After the initial three year measurement period, the annual variation of water temperature is about 0.3 °C and the daily variation is only about 0.001 °C. The water level and water temperature in the Jingle well are not substantially affected by changes in external conditions. The temperature gradient in the Jingle well was measured two times in the years 2007 and 2014 (Fig. 2, blue line 2007, red line 2014), with measurements carried out at depth interval of 50 m in the year 2007 and 10 m in the year 2014. We measured for about 30 min at each point, and considered an average value of the last 5 min of water temperature. The water temperature gradient was almost close to 0 °C per 100 m to a depth 229.81 m, which is very low compared to an average geothermal gradient (about 2.5 °C per 100 m). Such a low geothermal gradient could be associated with the large permeability coefficient (84.5 m per day to the depth of 229.81 m) that may promote mixing in the borehole. However, the water temperature gradient becomes unstable below 229.81 m in the Jingle well. From a local hydrogeological investigation, we found that the development of karst fissures and karst caves in the Jingle well region, where the karst to caves ratio is found to be 1.37%. The fissures and caves could attribute to the fast movement of water in horizontal layers, causing the temperature gradient to rapidly decline. Here, we consider karst fissures and karst caves to be well-confined and constitute a large “underground reservoir”. 3. 25 April 2015 Gorkha Nepal earthquake The Gorkha earthquake occurred at 06:11:26 on 25 April 2015 (UTC), with a moment magnitude of 7.8 and a maximum Mercalli
Fig. 1. Hydrogeological map of the Jingle well region, location of the Jingle well is shown with yellow star. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
A. He et al. / Tectonophysics xxx (2016) xxx–xxx
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conglomerate
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sand gravel stratum
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limestone
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dolomite limestone 26.3m
breccia marl
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dolomitee dolomite limestone
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10.5
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-0.06
-0.04
-0.02
300
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dolomite carbonaceous marl
350
8.0m
20.2m
350
0
Fig. 2. Lithology and temperature gradient of the Jingle well. The blue line is the temperature gradient measured in 2007 and the red line is the temperature gradient measured in 2014. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
7
320
9.3 (Jan/01/2016-Jan/02/2016)
240
9.31 9.315
9
9.32 00 04 08 12 16 20 00 04 08 12 16 20
10
11 2007
160
Rainfall (mm)
Water Level(m)
9.305
8
80
2008
2009
2010
2011
2012
2013
2014
2015
2016
0
(a) Water Level and Rainfall 10.2
320
9.97 (Jan/01/2016-Jan/02/2016) 9.969
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9.968 9.967
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9.966 00 04 08 12 16 20 00 04 08 12 16 20
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9.8 2007
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Rainfall (mm)
10.1
80
2008
2009
2010
2011
2012
2013
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2016
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(b) Water Temperature and Rainfall Fig. 3. The multi-year observed water temperature and water level in the Jingle well (a. the red line is water level (m) and the blue bar is rainfall (mm), the inset shows the two days' water level on January 01–02, 2016; b. the red line is water temperature (°C) and the blue bar is rainfall (mm), the inset is the two days' water temperature (°C) measured on January 01–02, 2016, the pink arrow is the event that the temperature sensor was repaired in July 2013, and the black dotted line is the trend of water temperature). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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Fig. 4. Co-seismic response of groundwater in the Jingle well associated with the 2015 Mw 7.8 Gorkha, Nepal earthquake.
Intensity scale of IX (violent). Its epicenter (longitude E84.708°, latitude N28.147°) was east of the district of Lamjung, and its hypocenter was at a depth of approximately 15 km (Galetzka et al., 2015). After the 1934 Nepal–Bihar earthquake, the Gorkha earthquake was one of the deadliest earthquakes in the region, resulting in over 8000 fatalities (Ahmad and Singh, 2015; Hayes et al., 2015). The co-seismic water level changes in the Jingle well (located about 2769 km from the epicenter) associated with the Gorkha earthquake are shown in Fig. 4. An important observation is that despite water level changes observed in the borehole, the water temperature remains unaffected. 3.1. The underground reservoir model
3.2. Seismic phases in water level fluctuations Here, we analyze the seismic phases in water level oscillations in the Jingle well associated with the Gorkha earthquake. Within 100 km of the Jingle well, four seismic stations (KEL, LOF, NIW and CHS) (Fig. 6) are selected to analyze the seismic waves. We have considered seismic waveforms measured for the Gorkha earthquake and computed arrival-time, seismic phase, amplitude and oscillation periods, and estimated the seismic arrival-time at the Jingle well from these four stations. The BBVS-60 model seismometer is used; its base time was calibrated with GPS with an absolute accuracy of 0.001 s. Table 1 shows the estimate of the arrival-time of P-wave of the Gorkha earthquake in the Jingle well at 06:16:48 h and S-wave arrival-time at 06:21:22 h on 25 April 2015. The time difference between P and S
The co-seismic response of water level during the Gorkha earthquake shows oscillation with large amplitudes, with a maximum peak-to-peak value of about 1.75 m. The water temperature almost remained constant despite the large-amplitude water level oscillation (Yang et al., 2008). From the local hydrogeological analysis, we consider that a large volume “underground reservoir” model explains this phenomenon. There are many karst caves, underground rivers and fractures in the Jingle well area, which constitute a large volume “underground reservoir” (Fig. 5). Seismic waves propagating across the well region may induce small changes in the volume of the reservoir via expansion and contraction, with simultaneous changes in the internal reservoir pressure. The water in the borehole is connected to the confined cavity, and oscillates with the internal pressure of the cavity; as a result, the water level declines with the decrease in internal pressure, and the water level rises when the internal pressure increases. The volume of water moving in the borehole can be estimated from the following equation: Q ¼ π∙r2 ∙h ¼ π∙0:062 ∙1:75≈0:02m3
ð1Þ
Where Q is the volume of water, r is the borehole radius, and h is the maximum amplitude. The volume of water moving is only 0.02 m3, even though the water level fluctuates up to 1.75 m, which is a very small volume relative to the “underground reservoir” and insufficient to cause water moving in the center of reservoir. Thus, the water temperature in the center of the reservoir (symbolized by the “T” in Fig. 5) remains unaffected when the water level fluctuates. P-waves, with high frequency and small amplitudes propagates through water, causing small fluctuations of water in the borehole. Sand surface waves cannot propagate in water; however, the volume of the confined cavity with compression and expansion may change. The “underground reservoir” (borehole-aquifer system) is likely to deform due to S-waves and surface waves and amplify water level causing large fluctuations in the borehole.
Fig. 5. The “underground reservoir” model (“T” is the position of water temperature sensor).
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
A. He et al. / Tectonophysics xxx (2016) xxx–xxx
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Fig. 6. Map showing locations of seismic stations and Jingle well.
wave is about 273 s. Due to the absence of basic tectonic information of each seismic station, it is difficult to estimate the surface wave parameters. Fig. 7 shows the co-seismic response of water level of the Gorkha earthquake in the context of the arrival of seismic waves. Water level was recorded by a SWY-II water level meter, which adopts the SNTP (Simple Network Time Protocol) (Mills, 1996) to calibrate the time, where the SWY-II water level meter allow the time error was smaller than 5 min. The absolute time between the hydroseismograms and the seismograms cannot be compared since the time error of water level recorder is so large (about 3 min slower than seismometer). We therefore compare the seismic and well records by aligning the first
movement of the hydroseismograms and seismograms (Fig. 7). The P-, S- and surface waves were clearly identified as propagating through the water level. In addition, we find that the start time of S- and surface waves in the hydroseismograms is the same as the seismograms. Therefore, we conclude that the relationship between the hydroseismograms (pore pressure) and seismograms (radial ground velocity) is a zeroorder system, similar to the findings of Kano and Yanagidani (2006). The teleseismic P-wave period was found to be about 1 ~ 10 s, Swave periods about 3 ~ 20 s, and surface wave periods about 8 ~ 60 s. We have used the seismic data of station NIW, which is very close to the Jingle well, to compute the seismic phases and amplitudes simulating the SK seismometer (Bormann et al., 2007). We find that the P-wave
Table 1 The parameters, compute from the seismic waves data, of the Gorkha earthquake in four stations (KEL, LOF, NIW and CHS), and the hydroseismograms of water level of the Jingle well. Origin time
2015-04-25 06:11:11.15
Epicenter Magnitude Focal depth Residual Epicenter accuracy Depth accuracy Azimuth gaps
27°52.60′ 82°58.04′ 8.4(Ms) 20.0 1.306 N/A(km) N/A 358
NO.
St. name
Phase
Date
Time
OTime
t-res
Delta
Ms
0
SX/KEL
26.23°
8.3
11-06.61
0.32 4.04
26.22°
8.4
2
SX/NIW
11-09.96
−0.15 0.62
26.67°
8.5
3
SX/CHS
06:16:46.780 06:21:19.020 06:24:45.9 06:25:1.0 06:16:47.030 06:21:22.880 06:24:40.8 06:25:8.6 06:16:50.700 06:21:26.780 06:25:21.2 06:25:21.2 06:16:50.820 06:21:21.030 06:24:58.5 06:25:26.2 06:20:12 06:24:40 06:28:10
−0.08 −0.09
SX/LOF
2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25 2015-04-25
11-11.07
1
P S Surf.-N Surf.-E P S Surf.-N Surf.-E P S Surf.-N Surf.-E P S Surf.-N Surf.-E P S Surf.
11-17.82
−0.09 −5.24
26.68°
8.4
Water Level
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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Fig. 7. Comparison of the seismogram (top) and hydroseismogram (bottom) at the Jingle well during the Gorkha earthquake of 25 April 2015.
period is about 3 s with an amplitude of 577 μm, the S-wave period is 12 s with an amplitude 2701 μm, and the surface wave period is 19 s with an amplitude of 13,193 μm. We also carried out spectral analysis of the hydroseismograms in three period intervals, 06:18–06:21 for P-waves, 06:22–06:24 for Swaves, and 06:26–06:28 for surface waves. The results are shown in Fig. 8. The dominant frequency in every period interval is compared with the parameters between hydroseismograms and seismograms in Table 2. Table 2 shows the periods of P-, S- and surface waves in seismograms, as 3, 12 and 19 s, respectively. The periods of P-, S- and
surface waves in the hydroseismograms are 13.85, 14.12 and 12.00 s, respectively. These observations suggest that the same periods of all three types of waves in water level are nearly independent of seismic waves. Based on the spectral analysis of hydroseismograms, especially the Sand surface waves, the bandwidth of hydroseismograms is very narrow and sharply declines in two sides of the dominant frequency. The borehole-aquifer system for seismograms is a band-pass filter with a narrow bandwidth, which indicates that the oscillation period of water level in borehole is determined by the resonant frequency of borehole and independent of the seismic waves. We estimate a resonance frequency of 12 s for the Jingle well from the surface waves, which cause the maximum oscillation in water level.
Fig. 8. The spectral analysis of hydroseismograms.
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
A. He et al. / Tectonophysics xxx (2016) xxx–xxx
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Table 2 Comparison of the parameters of hydroseismograms and seismograms.
Perioda Seismograms Hydroseismograms a
Amplitude (μm) Period (s) Amplitude (m) Period (s)
P-wave
S-wave
Surface wave
06:18–06:21
06:22–06:24
06:26–06:28
577 3 0.0018 1/0.0722 = 13.85
2701 12 0.0198 1/0.0708 = 14.12
13,193 19 0.3449 1/0.0833 = 12.00
Period(s) of seismograms.
The resonance frequency of the borehole is given by the following equation (Cooper et al., 1965): vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u g ωw ≈u u 3 t Hþ d 8
ð2Þ
Here, ωw is the resonance frequency, g is acceleration due to gravity, H is water column height of the casing of well, and d is the length of filter pipe. For the Jingle well, we assumed H = 50m , d = 312 m,and (H + d = depth of well = 362.29 m). Thus, ωw ≈0.213, implying that the oscillation period of 4.7 s has the largest amplification factor. However, we obtained the natural frequency of 12 s for the Jingle well from the spectrum analysis, and there are very large errors associated with calculating the natural frequency using Eq. (2) in the karst borehole. To correct this equation, we need the co-seismic responses of water level with many earthquakes, and the observed water level must use water level recorder with high sampling rate (1 per second). The amplitude ratio of P-, S- and surface waves in seismograms is 577:2701:13,193 ≈ 1:4.7:22.9. However, the same ratio in the hydroseismograms is 0.0018:0.0198:0.3449 ≈ 1:11.0:191.6. We conclude that the borehole-aquifer system magnifies ground vibration, and the amplification factor shows a non-linear relationship, which is larger when the ground vibration is more intense. The magnifying function of the borehole-aquifer system suggests the relationship between hydroseismograms (pore pressure) and seismograms (ground vibration) is a zero-order system, which is characterized by no distortion or time lag, but the seismograms cannot be recorded without distortion. 4. Discussion The 2015 Mw 7.8 Gorkha, earthquake caused 1.75 m of water level oscillation at the Jingle well, at a distance of 2769 from the epicenter. The P, S and surface waves are identified from the co-seismic water level response. Water temperature in the Jingle well remained almost constant in response to the Gorkha earthquake, which is rather surprising given the large-amplitude oscillations of water level observed. The “underground reservoir” model can provide a reasonable explanation for this unexpected observation. This model not only explains the amplification of the borehole-aquifer system by seismic waves, but also shows that no change in the water temperature is required for large amplitude water level oscillations. The oscillation frequency of water level caused by surface waves is about 12 s, but the actual seismic wave frequency is 19 s. The natural frequency of the borehole, when computed using Eq. (2) (Cooper et al., 1965), reveals a disagreement in the theoretical and observed natural frequencies of the borehole. One solution to this problem is to sample co-seismic water levels with a high sampling rate water level recorder. The borehole-aquifer system is a band-pass filter with a narrow bandwidth compared to seismic waves. To more fully investigate this problem, we considered the Menyuan, China earthquake (Mw = 5.9, 2016–01-20 17:13:13), which occurred 914 km from the Jingle well and for which seismic phases can be identified in water levels. We compute the ratio of amplitudes between seismogram and water
level and from Table 3, and conclude that the amplitude ratio between seismograms and water levels shows different values at the Jingle well. The Mw 5.9 Menyuan earthquake did not influence water level fluctuations similarly to the Gorkha earthquake, even though the Menyuan epicenter was much closer (~914 km). The borehole-aquifer system can magnify ground vibrations, and the amplification factor is larger with more intense ground vibration. We find another very interesting wave from water level oscillations in the Jingle well; a small amplitude and short time oscillation with frequency of about 6.5 Hz with duration of about 120 s, peak-to-peak value of about 30 mm observed at 23:57–23:59 h on 24 April 2015 (UTC), 6.5 h prior to the Gorkha mainshock (Fig. 9). A similar observation was also noted earlier by Kanamori and Cipar (1974) for long-period (300–600 s) waves arriving at the P time for a large foreshock, which occurred about 15 min before the great Chilean earthquake of 22 May 1960 (Ms = 8.3). This is likely due to a large-scale deformation associated with the triggering of foreshocks and the main earthquake event. According to Zhou et al. (2009) and Zhang et al. (2011), observations of gravity, ground tilt, strain, ground water and seismographs can show similar phenomenon prior to earthquakes. In addition, Zhou et al. (2009) and Zhang et al. (2011) considered that the precursory waves have clear physical mechanism and suggested they represent short-term precursory information for early indication of an impending earthquake. The water level fluctuations observed at 23:57–23:59 h on 24 April 2015 occur prior to the impending Gorkha earthquake (occurred at 06:11:26 h on 25 April 2015) yet there was no other recognized disturbance recorded in the proximity of Jingle well. We cannot get the precursory crustal deformative processes since experimental data are lacking, but lateral migration of the stress field after dislocation events has been recognized for the generation of impending earthquakes (Whitcomb et al., 1973; Igarashi et al., 1992; Martinelli, 2015; Lupi et al., 2016), we infer such observed water level fluctuations/oscillation in the Jingle well hint at the existence of precursory waves, which is an intriguing possibility that needs to be further investigated. 5. Conclusions The “groundwater reservoir” model can help to explain the unusual co-seismic response observed at the Jingle well in response to the Gorkha earthquake, which includes water oscillating with large amplification and almost constant water temperature. The borehole-aquifer system is a band-pass filter with narrow bandwidth, where the parameters are dependent on the natural frequency of borehole. The boreholeaquifer system can amplify the ground vibration, and the amplification factor will be larger with the intense ground vibration. Potential precursory waves were recorded about 6.5 h prior to the Gorkha earthquake,
Table 3 The ratio of amplitudes between the 2016 Menyuan, China Mw 5.9 seismogram and water level at the Jingle well.
Earthquake
Magnitude
Distance(km)
Seis. amp. (μm)
WL amp. (m)
ratio
Nepal Menyuan
Mw7.8 Mw5.9
2769 914
13,193 493
1.757 0.046
7508.822 10,717.39
Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019
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A. He et al. / Tectonophysics xxx (2016) xxx–xxx
Fig. 9. Potential precursory waves recorded by variations in water level of the Jingle well.
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Please cite this article as: He, A., et al., Co-seismic response of water level in the Jingle well (China) associated with the Gorkha Nepal (Mw 7.8) earthquake, Tectonophysics (2016), http://dx.doi.org/10.1016/j.tecto.2016.08.019