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Helium content in thermal waters in the Caucasus from 1985 to 1991 and correlations with the seismic activity
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Tectonophysics 246 (1995) 263-278
Helium content in thermal waters in the Caucasus from 1985 to 1991 and correlations with the seismic activity F. B e l l a a, P . F . B i a g i b, M . C a p u t o c, E . C o z z i a, G . D e l l a M o n i c a a, A . E r m i n i d, W . P l a s t i n o a, V. S g r i g n a a, D . Z i l p i m i a n i e a Dipartimento di Fisica, III Universitd, 14a C. Segre, 2, 00146 Rome, Italy b Dipartimento di Fisica, Universit~ di Bari, Via Orabona, 4, 70100 Bari, Italy c Dipartimento di Fisica, Universit~ 'La Sapienza" Piazzale Aldo Moro, 2, 00185 Rome, Italy a Dipartimento di Ingegneria Meccanica, Universitd "Tor Vergata', l/'ta 0. Raimondo, 00173 Rome, Italy e Institute of Geophysics of the Academy of Sciences of Georgia, Z. Ruckhadze, L 380093 Tbilisi, Georgia Received 23 February 1994; accepted 5 December 1994
Abstract
A wide data set of groundwater helium content collected in the Caucasus from 1985 to 1991 has been analyzed. The strongest earthquakes that occurred in this area during the helium measurement period were the: Paravani (May 13th, 1986, M = 5.6), Spitak (December 7th, 1988, M = 6.9) and Georgian (April 29th, 1991, M--6.9) earthquakes. The analysis of the helium content data revealed statistically significant increases in this parameter on the occasion of the Paravani and Spitak earthquakes and no increase on the occasion of the Georgian earthquake. These results corroborate those obtained by the analysis of scanty helium content data presented in previous papers. With the exception of the anomalous increases, the helium content data were subjected to randomness tests and spectral analysis and cross correlation with meteorological parameters and areal seismicity were also attempted. The main result obtained is that the destructive Spitak earthquake produced some statistical changes in the groundwater helium content fluctuations some years before and after its occurrence.
1. Introduction
Extensive studies carried out in the last 15 years have shown that soil-gas and groundwater helium changes are often associated with earthquakes (Wakita, 1978; Mamyrin et al., 1979; Barsukov et al., 1979a,b, Barsukov et al., 1982; Chi-Yu King, 1984; Reiner, 1985). As part of an ItalianGeorgian study, the thermal waters of some springs located in the Georgian Caucasus were sampled systematically once a day from 1985 to 1991 for analysis of the helium content. Since the
middle of 1991 this research has been interrupted due to the war situation in the zone. Anomalies in the helium content measured in some sites of the network were revealed on the occasion of the Paravani ( M = 5.6, 1986) and Spitak ( M = 6.9, 1988) earthquakes and have already been reported in a previous paper (Areshidze et al., 1992a). The non-occurrence of the same kind of anomalies on the occasion of the Georgian ( M = 6.9, 1991) earthquake has also been presented and discussed (Areshidze et al., 1992b). The previous results were discussed using
0040-1951/95/$09.50 © 1995 Elsevier Science B.V. All rights reserved SSDI 0040-1951(94)00260-6
264
F. Bella et al. / Tectonophysics 246 (1995) 263-278
a partial data set. Now we have gathered the entire helium content data set from January, 1985, up to June, 1991, and for the same period we have collected meteorologic data from some weather stations located near the springs. In addition, we have at our disposal the data from the Seismological Notes of the Institute of Geophysics of the Academy of Sciences of Georgia (Academy of Sciences of the Georgian SSR, 1986-1991). The results we have obtained using these data sets are presented in this paper.
2. Tectonic setting and seismicity The Caucasus is characterized by a complex evolutionary history. Due to the collision of the Arabian and Eurasian plates in this area it is a mixture of tectonic units belonging to different continental margins. Fig. 1 shows the main fault systems in the Georgian Caucasus area. The Lesser Caucasus consists of a north-verging system of folds which have their origin in the conti-
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nental collision. In contrast, the Greater Caucasus is formed from a south-verging system of folds, related to the intracontinental compression connected with the northward thrust of the Arabian plate. These two, seismogenetically different, tectonic units are separated by the Transcaucasian Massif (Adamia et al., 1991). The active tectonic setting is a compressive one, with evident slip fronts and folded structures. Folds are locally interrupted by continuous structural lineations that suggest a strike-slip movement. The most significant lineament system is parallel to the orogenic belt ( W N W - E S E ) . Other lineaments (N-S, N E - S W and N W - S E ) appear that probably correspond to the same stress field of Central Anatolia. The strongest seismic events in the Caucasus from 1985 to 1991 were: (1) The Paravani main shock ( M = 5.6), which occurred on May 13th, 1986, at a depth of about 10 km. (2) The Spitak main shock (M = 6.9), which occurred on December 7th, 1988, at a depth of about 4 km.
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F. Bella et al. / Tectonophysics 246 (1995) 263-278
(3) The Georgian main shock (M--6.9), which occurred on April 29th, 1991, at a depth of less than 10 km. The first two events occurred in the seismotectonic area of the Lesser Caucasus and the northern border of the Armenian plateau; the latest one on the southern slope of the Greater Caucasus. These earthquakes were followed by aftershock activity; in the case of the Spitak event, aftershocks occurred for 2 years after the main shock. The location of these seismic sequences is shown in Fig. 2. Except for these events, the seismicity from 1985 to 1991 appears with a mean frequency of about 100 earthquakes/yr and is
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characterized by K values (the logarithm of energy in joules) ranging from 8.5 to 12.7. The spatial pattern of the seismicity is shown in Fig. 2.
3. E x p e r i m e n t a l
data and analytical procedures
Fig. 2 shows the location of the measurement sites at springs that were operating in 1991. The helium content of waters was measured using an INGEM-1 instrument (Varshal et al., 1985). The sensor is a miniature magnetic discharge pump supplied with a diffusive quartz membrane which has a high selectivity for helium. The waters flow
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F. Bella et al. / Tectonophysics 246 (1995) 263-278
266 (/~1/1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 (/~1/I 2.5
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Fig. 4. (a) Variations in the groundwater helium content at V A R spring from January 1st, 1985, to June 30th, 1991. ( b - d ) M e a n air temperature, atmospheric pressure and rainfall m e a s u r e d at a local weather station. (e) K values of seismicity in a circle of 300 km radius around the spring.
F. Bella et al. / Tectonophysics 246 (1995) 263-278
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Fig. 5. (a) Variations in the groundwater helium content at QUA spring from January 1st, 1985, to June 30th, 1991. ( b - d ) Mean air temperature, atmospheric pressure and rainfall measured at a local weather station. (e) K values of seismicity in a circle of 300 km radius around the spring.
F. Bella et aL / Tectonophysics 246 (1995) 263-278 (~IA 9
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Fig. 6. (a) and (b) Variations in the groundwater helium content at springs BAK and BOR from January 1st, 1988, to June 30th, 1991. (c-e) Mean air temperature, atmospheric pressure and rainfall measured at a local weather station. (f) K values of seismicity in a circle of 300 km radius around the springs that we considered as located in the same place.
F. Bella et al. / Tectonophysics 246 (1995) 263-278
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F. Bella et al. / Tectonophysics 246 (1995) 263-278
271
Table 1 Time interval when the helium content increases exceed the response level Spring LIS
VAR
QUA
BAK
SAB
May 13, 1986May 16, 1986 Dec. 7, 1988Jan. 2, 1989
May 13, 1986May 19, 1986 Dec. 1, 1988Jan. 10, 1989
-
-
Dec. 5, 1988Jan. 31, 1989
Dec. 1, 1988Jan. 1, 1989
June 15, 1986June 17, 1986 -
naturally from a number of springs and they belong to the fault- and fissure-karst types of waters. These waters are characterized by deep and generally rapid circulation. The main features of the springs indicated in Fig. 2 are reported in Areshidze et al. (1992b). Figs. 3-6 show the variations in the helium content at the LIS, SAB, VAR, QUA, BAK and BOR springs, during the period January 1st, 1985, to June 30th, 1991. The interruptions in the trends indicate when data were not collected. For the BAK and BOR springs, the data were collected starting from 1988. For the SAB spring the sampling was interrupted from November 1988 to allow building construction at that site. Meteorological data collected at local weather stations and the seismicity, represented by the K values of the earthquakes which occurred in a circle of a radius of 300 km from each spring, are shown, together with the helium content data. A radius of 300 km represents the distance at which it seems reasonable to consider some influence of seismic activity on the helium content variations (Barsukov et al., 1979a; Barsukov et al., 1979b; Barsukov et al., 1984/85a,b; Varshal et al., 1985). For rainfall and K values we obtained a regular progression considering the weighted average over 30 days 1, moving in steps of 1 day. We considered the clear relationship between the most obvious helium content increases and the K values in the cases of the Paravani and Spitak seismic sequences. In the first case such a relationship does not appear at the QUA spring, 5 1 If x is the variable we use the relationship: ~ = [(,~_',xn)+ 10 15 20 25 30 2( ,~,x n ) + 4( ,~,x n) + 8 ( ~ n ) + 16(,~_',Xn) + 32(~,xn)]/63 6 11 16 21 26
1
which is the farthest one from the epicentre of the earthquake, probably outside the 'sensitive' zone (Areshidze et al., 1992a). For each helium concentration data set we calculated the standard deviation, tr, over the entire sample. If the 3(r level is chosen as the response level, the helium variations can all be explained as being due to the release of seismic energy connected with the Paravani and Spitak sequences. Fig. 7 shows the helium content trends at the various springs. The 3~ level (horizontal line) is indicated in each case. The occurrence of the Paravani, Spitak and Georgian main shocks is also shown. Raw data show clearly when the helium content increases exceed the response level; these time intervals are listed in Table 1. We then analyzed the helium content data during the periods in which the variations in the trend are below the risk level, in order to uncover some possible physical meaning of such variations. We used for the statistical and mathematical analysis the STATGRAPHICS software package of the Statistical Graphics Corporation. In the beginning we carried out several distribution fittings on the experimental data, in order to test their randomness (Barsukov, 1984/85a,b). The fittings were tested using both X 2 and Kolmogorov-Smirnov tests. The entire data set below the + 3o~ value was tested and randomness did not appear, so we tried to examine these data by splitting them into different time intervals. We met with some randomness choosing the following three time intervals: (1) before the Paravani main shock (January 1, 1985-April 30, 1986); (2) after the Paravani main shock and the following aftershock activity and before the Spitak main shock (July 1, 1986-October 31, 1988);
272
F. Bella et al. / Tectonophysics 246 (1995) 263-278
LIS (/,IA) 0,03 0.025 0.02 0.015 0.01 0.005 0 120
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Fig. 8. Spectral analysis obtained from LIS helium data related to the intervals: (a) January 1st, 1985-April 30th, 1986. (b) July 1st, 1986-October 31st, 1988. (c) March 1st, 1989-June 30th, 1991. The periods indicated at the bottom of each spectrum are the cut-off periods used for the data filtering.
F. Bella et al. / Tectonophysics 246 (1995) 263-278
(3) after the Spitak more intense seismic sequence (March 1, 1989-June 30, 1991). The randomness was obtained in the time intervals 1 and 2 only. In case 1 our goal was a lognormal (LIS) and a normal (VAR and QUA) distribution fitting; in case 2 sufficient success was achieved with a lognormal (LIS and QUA) and a Weibull's distribution (VAR). The results of these tests are listed in Table 2. We then carried out a spectral analysis on the helium content data during the above mentioned time intervals (Mendenhall et al., 1981; Shapiro et al., 1984/85). In general the amplitude of the signals does not appear to be related to particular frequencies but is distributed over a wide range. In the cases in which it was possible to obtain the spectra in all three time intervals some differences seem to appear. Fig. 8 shows the spectra related to the LIS data, using 29 values of a continuous data set of the three intervals and it is clear that, in the time interval from January 1st, 1985, to April 30th, 1986, the amplitude of the signal is mostly associated with the helium variation of high frequencies. We continued to look for the influence of external processes on the helium content in the quoted time intervals (Klusman and Webster, 1981; Shapiro et al., 1984/85). To this purpose, on the basis of the spectra, we applied highfrequency pass filters, band-pass filters and lowfrequency pass filters to the raw trends. Then we compared the raw and filtered trends of the helium content data with the meteorological data
Table 2 Randomness tests Test
Spring US
VAR
QUA
January 1, 1985- April 30, 1986 X2 v a K- S
7.935 9 54% 88%
16.198 9 6% 63%
17.130 8 3% 18%
July 1, 1986-October 31, 1988 X2 v a K-S
9.025 6 17% 45%
15.624 7 3% 5%
13.630 8 9% 7%
273
and the seismicity (K values). Obviously, in the case of correlation with filtered helium content data, we applied the same filters to the meteorological and seismic data. The best values of the cross correlation coefficient, r (in phase-= +, opposite phase -= - ) that we obtained in period 2 are listed in Table 3. The corresponding values of the temporal shift (advance = - , d e l a y - + ) of the helium content trend with respect to the various parameter trends are indicated in parentheses in Table 3. For the cross correlation with meteorological parameters we considered only positive shifts; in any case, we assumed 60 days as the maximum shift (Bella et al., 1993; Barsukov et al., 1984/85a,b). The results of this analysis on the data in the other two time intervals are very similar, except for the low-frequency pass filter, where the cross correlation coefficients are always smaller than 0.5.
4. Discussion
The first analysis we carried out on the helium content data (Fig. 7) revealed statistically significant increases in the helium content on the occasion of the Spitak seismic sequence from all active stations. From the data listed in Table 1 the existence of a precursory phenomenon can be clearly seen at the V A R and Q U A sites. At the LIS site the anomaly does not seem to precede the earthquake. The same circumstance happens on the occasion of the Paravani earthquake (M = 5.6). The duration of the helium content increase was about 30-40 days for the Spitak earthquake and 3-6 days for the Paravani event. Such periods correspond quite well with the periods where the aftershock activity was more energetic (Areshidze et al., 1992a). This seems to indicate that the helium content anomalies are clearly connected with an intensification of the microfracturing processes a n d / o r changes in the existing cracks. The consequent delivery of gases, vapours and pore solutions, which are squeezed out of the rock into the water-bearing strata, could be the possible origin of the helium content increases observed (Shabynin et al., 1983; Varshal et al., 1983; Barsukov et al., 1984/85a,b). The
274
F. Bella et al. / Tectonophysics 246 (1995) 263-278
existence of clear precursory anomalies only before the occurrence of the Spitak ( M = 6.9) earthquake can be explained by the greater amount of energy dissipated in preseismic stressreadjustment processes than in the case of the Paravani ( M = 5.6) earthquake (Areshidze et al.,
1992a). The exception at spring LIS on the occasion of the Spitak earthquake seems to indicate some anisotropic character in the stress readjustment processes. The data listed in Table 1 are in agreement with the results presented in Areshidze et al.
Table 3 Helium content correlation
LIS Raw data High-pass filter T = 30 d Band-pass filter T = 30 d T = 50 d Band-pass filter T = 50 d T = 120 d Low-pass filter T = 120 d VAR Raw data High-pass filter T = 21 d Band-pass filter T = 21 d T = 34 d Band-pass filter T = 34 d T = 50 d Low-pass filter T = 160 d QUA Raw data High-pass filter T = 20 d Band-pass filter T = 20 d T = 35 d Band-pass filter T = 35 d T = 8 0 d Low-pass filter T = 120 d SAB Raw data High-pass filter T = 16 d Band-pass filter T = 16 d T = 33 d Band-pass filter T = 33 d T = 80 d Low-pass filter T = 120 d
Pressure
Temperature
Rainfall
Seismicity
- 0.20 (8) 0.02 (29) 0.18 (35) 0.20 (4) - 0 . 3 8 (8) 0.36 (30) - 0.42 (8) 0.23 (32) - 0.21 (30)
- 0.18 (60) 0.03 (0) 0.28 (43) 0.25 (35) -0.13 (37) 0.25 (56) 0.1 (2) 0.26 (49) - 0.38 (58) 0.11 (2)
- 0.15 (60) 0.25 (43) - 0 . 2 2 (11) 0.18 (l) - 0 . 1 3 (37) 0.25 (56) - 0.30 (60) 0.44 (42) - 0.09 (43) 0.12(6)
0.43 ( - 6)
0.44 (25) 0.12 (42) 0.08 (9) - 0 . 4 0 (47) 0.35 (33) - 0.46 (48) 0.24 (29)
-0.01 (33) 0.29 (58) - 0 . 2 0 (29) 0.27 (4) -0.35 (37) 0.37 (23) - 0.26 (38) 0.29 (60)
0.55 (24)
0.45 (55)
0.41 (8) - 0 . 1 6 (15) 0.13 (20) - 0.47 (53) 0.46 (39) --0.23 (27) 0.24 (6)
- 0.03 (38) 0.26 (0) 0.21 (9) 0.21 (2) - 0.38 (39) 0.41 (54) - 0 . 0 8 (39) 0.09 (23)
0.41 (7)
0.51 (2)
- 0.03 (44) 0.02 (7) - 0 . 1 7 (10) 0.15 (16) -(/.15 (1) 0.14 (12) - 0 . 1 0 (0) 0.32 (60) - 0 . 1 9 (53) 0.09 (4)
- 0.07 (34) 0.20 (0) - 0 . 1 3 (6) 0.14 (11) - 0 . 1 7 (34) 0.14 (23) - 0 . 1 9 (60) 0.26 (8)
-0.20 (53) (1.27 (16) 0.21 (28) 0.23 (0) -0.35 (28) 0.30 (41) - 0.16 (31) 0.39 (12) 0.58 (63) 0.47 (9) - 0.17 (58) 0.05 (26) -0.15 (47) 0.10 (53) - 0.40 (60) 0.31 (48) - 0 . 3 4 (50) 0.43 (26) 0.17 (5)
- 0.04 (60) 0.15 (17) 0.11 (41) 0.13 (20) - 0 . 4 8 (54) 0.45 (44) -0.11 (60) 0.09 (18) - 0 . 0 8 (2) 0.12 (55)
0.14 ( - 4 ) 0.42 ( - 6) 0.45 ( - 7) 0.72 ( - 4)
0.40 ( - 10) 0.21 ( - 4 2 ) 0.28 ( - 16) 0.28 ( - 16) 0.80 ( - 15)
0.42 ( - 16) 0.27 (51) 0.37 (46) 0.60 ( - 16) 0.62 (25)
0.26 ( - 6) 0.20 (53) 0.23 ( - 6) 0.30 ( - 9 ) 0.14 (0)
0.68 (14)
F. Bella et al. / Tectonophysics 246 (1995) 263-278
(1992a). Only for the case of the SAB spring is there a discrepancy: in fact Areshidze et al. presented the signal with an asterisk in their fig. 7 as anomalous. In the present paper this signal is below the + 3 t r level and, instead, an increase over this level appears from June 15th to June 17th, 1986 (Table 1), that is about 1 month after the Paravani main shock. The interpretation of such an anomaly as a post-seismic effect does not appear realistic on the basis of our data. Therefore, we considered this anomaly as the only exception to the correspondence between statistically significant increases in the helium content and the occurrence of the Paravani and Spitak seismic sequences. We shall discuss the behaviour of SAB later. The absence of a helium content anomaly on the occasion of the Georgian earthquake appears dearly from the examination of the complete helium content data set (Fig. 7). Areshidze et al. (1992b) gave a reasonable interpretation for such an absence of anomalies on the basis of differences between the seismogenetic area of the Georgian earthquake with respect to that of the Paravani and Spitak earthquakes (see previous section). The results of the randomness analysis can be summarized as follows: (A) Before the Paravani earthquake the groundwater helium content variations can be considered statistically random according to a (log)normal distribution (Table 2). (B) After this earthquake, and before the Spitak earthquake, the randomness of the helium content variations changes; generally, it is less evident and at site VAR it seems to change according to a Weibull's distribution (Table 2). It must be noted that, in this period, only the tests on SAB data have not given any randomness. This is the second exception for the SAB spring. (C) In the period after the Spitak seismic sequence the randomness tests failed everywhere. A possible explanation of these results is as follows. Let us consider that the usual variations in groundwater helium content happen according to case (A) (i.e., in the time before the Paravani earthquake). The stress readjustment processes following the Paravani earthquake and preceding the Spitak earthquake produce some modifica-
275
tions in the frequency and periodicity of the microcracks over a wide zone so a consequent variation in the delivery of helium into the water-bearing strata occurs. The changes in the randomness of the helium content variations pointed out in (B) could be connected with this phenomenon. It seems reasonable to consider that the modifications connected with the occurrence of the Paravani earthquake, because of the lesser stress, are less influential on the observed phenomena than those connected with the prerupture phase of the Spitak earthquake; if this is correct a long-term (about 2 yr) statistical precursor of the Spitak earthquake appears. Such a hypothesis is corroborated by the fact that a Weibull's distribution can describe (Barsukov et al., 1982) the 'fatigue' of a system and we find randomness, according to such a distribution, only at the VAR site, which is the nearest one to the epicentre of the Spitak earthquake. The statement in (C) above seems to indicate that the occurrence of the Spitak seismic sequence had modified the hydrogeochemical system for a long time. We tried to evaluate the duration of this modification. For this purpose we applied the randomness tests to the final part of our data set and obtained a good result for the LIS spring, where we had the best result for a lognormal distribution, with a X 2 = 8.343 (v = 9, a = 50%) and K - S = 40%, testing the data from October 1st, 1990, to June 30th, 1991. This suggests that an estimation of about 2 yr for the time of the modification is reasonable. The spectra we obtained revealed that, in general, no characteristic frequency stands out and this situation appears whether the data seem random or not. However, the spectral content of the helium data appears to be mostly associated with the helium variations of high frequencies in the time interval from January 1st, 1985, to April 30th, 1986. If we assume such amplitude distribution in helium content variations to be usual it seems reasonable to consider that the subsequent modifications of the spectra are connected, at first, with the phenomenon we described for randomness in the pre-rupture phase of the Spitak earthquake and with the quoted stress readjustment induced by its occurrence (Zhelankina et
276
F. Bella et al. / Tectonophysics 246 (1995) 263-278
al., 1985). In the first case another long term statistical precursor of the Spitak earthquake appears. As regards the cross correlations we have tried, the influence of periodic parameters, such as long-term solar-lunar tides, on the groundwater helium content may exist (Lebedev et al., 1985) but it does not seem relevant on the basis of the previous analyses. We therefore neglected this effect among the external processes that can act on the helium fluctuations in a substantial way. From the data listed in Table 3, which refer to the period July 1st, 1986-October 31th, 1988, a correlation exists between the low-pass filter trend of the helium content and seismicity. An exception is the SAB spring, where, in contrast, a good correspondence with rainfall seems evident. In the previous section it was pointed out that, in the time intervals from January 1st, 1985, to April 30th, 1986, and from March 1st, 1989, to June 30th, 1991, the correspondence between the helium content and any other parameter appears uncertain. If we look at the results from the LIS, VAR and Q U A springs it appears that the seismicity leads the helium content variations in groundwaters only in about the 2 yr preceding the Spitak earthquake. It is thus reasonable to consider this behaviour as another long-term precursor of such an earthquake. In this way the long-period variations in the helium content seem to be modulated in frequency by the seismicity, as an effect of the increasing tectonic stress preceding the Spitak earthquake. Such modulation indicates the occurrence of modifications in the spatial-temporal distribution and in the energy release of the seismic activity in the Caucasus. According to the first statement of this section, when the seismicity becomes a paroxysmal phenomenon (Spitak and Paravani seismic sequences) an amplitude modulation is induced in the helium content variations and so the correspondence between the helium content and the seismicity appears complete. The fact that after the Spitak seismic sequence the correspondence between the helium content and the seismicity does not appear seems to indicate that in these particular circumstances the helium content in the groundwater was more
strongly controlled by the gradual tectonic packing subsequent to the Spitak seismic sequence than by the fracturing associated with its aftershock activity. Finally, if we look at the result at the SAB spring, we can conclude that here the helium content data are disturbed by rainfall in a substantial way. Such a phenomenon had been present for some time so the direct correspondence between helium content and rainfall we pointed out is natural (Klusman and Webster, 1981; Lebedev et al., 1985). In addition, the building construction work mentioned in the previous section produced evident infiltrations. Thus, all the above mentioned exceptions at the SAB spring can be understood. The behaviour of the groundwater helium content concerning randomness, spectral analysis and correlations with the areal seismicity in the time interval after the Spitak seismic sequence has been presented here as directly connected with the stress readjustment related to the earthquake. It did not seem right to interpret this behaviour as a phenomenon connected with the preparation of the Georgian earthquake of April 1991. The absence of anomalous behaviour in the helium content in the network of Fig. 2 on the occasion of this earthquake (Areshidze et al., 1992b) has been confirmed again by the statistical treatment of the data. The possibility that such an absence is due to a decrease in the sensitivity (Barsukov et al., 1984/85a,b) of the hydrothermal system connected with the external effects of the Spitak earthquake exists. We consider it to be more probable that the quoted network for the study of precursors is predominantly 'sensitive' to earthquakes that take place in the seismogenetic zone of the Lesser Caucasus and the Armenian plateau (Areshidze et al., 1992b).
5. Conclusions
The study of the helium content in thermal springs of a network located in Georgia during a long time interval (about 6 yr) has revealed that, when strong earthquakes occurred in the seismogenetic zone to which the network is 'sensitive'
F. Bella et al. / Tectonophysics 246 (1995) 263-278
(Areshidze et al., 1992b), the helium content increases over the 'response level', represented by the +3or value; such an increase also has a preseimic phase if the impending earthquake is a destructive one. In such circumstances the helium content data exhibit term precursors as changes in randomness fittings, differences in spectral content and a good correspondence with the areal seismicity. After the occurrence of the earthquake the helium content variations are affected by the subsequent gradual tectonic packing. If the groundwater helium content is considered as an indicator, all the phenomena quoted can help to understand the complex tectonic processes that take place before and after the occurrence of a destructive earthquake.
References Academy of Sciences of the Georgian SSR, 1986-1991. Seismological Notes of the Institute of Geophysics of the Academy of Sciences of the Georgian SSR. Tbilisi, Georgia. Adamia, S., Chabukiani, A., Kakabadze, M., Koteshvili, E., Lordkipanidze, M. and Tabidze, D., 1991. Geological background of the Caucasus and adjacent area. In: S. Adamia and M. Kakabadze (Editors), Geological Events on Cretaceous-Paleogene Boundary, Int. Syrup. Metsniereba, Tbilisi, pp. 18-51. Areshidze, G., Bella, F., Biagi, P.F., Caputo, M., Chkuaseli, V., Della Monica, G., Ermini, A., Manjgaladze, P., Melikadze, G., Sgrigna, V., Slavina, L. and Zilpimiani, D., 1992a. Anomalies in geophysical and geochemical parameters revealed on the occasion of the Paravani (M = 5.6) and Spitak (M = 6.9) earthquakes (Caucasus). Tectonophysics, 202: 23-41. Areshidze, G., Bella, F., Biagi, P.F., Caputo, M., Della Monica, G., Ermini, A., Manjgaladze, P., Melikadze, G., Sgrigna, V. and Zilpimiani, D., 1992b. No preseismic evidence from hydrogeochemical parameters on the occasion of the April 29, 1991, Georgian earthquake, Caucasus. Tectonophysics, 213: 353-358. Barsukov, V.L., Varshal, G.M., Garanin, A.V. and Serebrennikov, V.S., 1979a. Hydrogeochemical earthquake precursors. Int. Symp. Earthquake Prediction (UNESCO, Paris, April 2-6). Barsukov, V.L., Serebrennikov, V.S., Varshal, G.M. and Garanin, A.V., 1979b. Geochemical methods for earthquake prediction. Geokhimiya, 3: 323-337. Barsukov, V.L., Belyeyev, A.A., Serebrennikov, V.S.,
277
Bakaldin, Yu.A., Urunov, M.Kh. and Arsenyeva, R.V., 1982. Potentialities of using variational estimations of helium content in thermal waters for earthquake prediction. Geokhimiya, 11: 1614-1620. Barsukov, V.L., Serebrennikov, V.S., Belyaev, A.A., Bakaldin, Yu.A. and Arsenyeva, R.V., 1984/85a. Some experience in unraveling geochemical earthquake precursors. Pure Appi. Geophys., 122: 157-163. Barsukov, V.L., Varshai, G.M. and Zamokina, N.S., 1984/1985b. Recent results of hydrogeochemical studies for earthquake prediction in USSR. Pure Appl. Geophys., 122: 143-156. BeUa, F., Biagi, P.F., Caputo, M., Della Monica, G., Ermini, A. and Sgrigna, V., 1993. Ground tilt variations detected in Central Apennines (Italy) in the period 1986-1989 and their correlation with seismicity. Nuovo Cimento, 16C: 303-311. Chi-Yu King (Editor), 1984/85. Earthquake Hydrology and Chemistry. Pure Appl. Geophys. Spec. Issue, 122. Klusman, R.W. and Webster, J.D., 1981. Preliminary analysis of meteorological and seasonal influences on crustal gas emission relevant to earthquake prediction. Bull. Seismol. Soc. Am., 71: 211-222. Lebedev, V.S., Sardarov, S.S. and Mirzaliyev, M.M., 1985. Results in regular observations in Daghestan by use of automatic systems for monitoring gas composition. In: G.A. Sobolev and G.M. Varshal (Editors), Hydrogeochemical earthquake precursors, Nauka, Moscow, 286 pp. Mamyrin, B.A., Tolstikhin, I.N. and Khabarin, L.V., 1979. On the possibility of using the 3He/4He ratio for earthquake prediction. Geokhimiya, 3: 384-386. MendenhaU, M.H., Shapiro, M.H., Melvin, J.D. and Tombrello, T.A., 1981. Preliminary spectral analysis of near-real-time radon data. Geophys. Res. Lett., 8: 449-452. Reiner, G.M., 1985. Prediction of Central California earthquakes from soil gas helium fluctuations. Pure AppL Geophys., 122: 369-375. Shabynin, L.L., Naidich, V.I. and Novikov, V.M., 1983. On the mechanism of formation of hydrogeochemical precursors. All-Union Conf. Hydrogeochemical investigation at precursor study areas (Alma-Ata, Inst. Seismology, Academy of Sciences of Kazakhstan, June), Abstracts, pp. 99-101. Shapiro, M.H., Rice, A., Mendenhall, M.H., Melvin, J.D. and Tombrello, T.A., 1984/85. Recognition of environmentally caused variations in radon time series. Pure Appl. Geophys., 122: 309-326. Varshal, G.M., Sobolev, G.A., Koltsov, A.V., Kostin, B.I., Kudinova, T.F., Tretyakova, S.P., Ponomarenko, V.A., Kalinkina, O.M., Kubrakova, I.V., Galuzinskaya, A.Kh. and Myachkin, V.V., 1983. Separation of volatile components from rocks at mechanical loading as the source of formation of hydrogeochemical anomalies during the period of a forthcoming earthquake. All-Union Conf. Hydrogeochemical investigation at precursor study areas (AlmaAta, Inst. Seismology, Academy of Sciences of Kazakhstan, June), Abstracts, pp. 23-26.
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Varshal, G.M., Zamokina, N.S., Timakova, E.P., Bakaldina, N.A., Dzeheglova, M.L. and Zinger, A.A., 1985. Halogenide and sulfide ions as earthquake precursors and their detection by use of ion-selective electrodes. In: G.A. Sobolev and G.M. Varshal (Editors), Hydrogeochemical Earthquake Precursors. Nauka, Moscow, 286 pp. Wakita, H., 1978. Earthquake prediction and geochemical studies in China. Chin. Geophys., 1: 443-457.
Zhelankina, T.S, Kushnir, A.F., Pisarenko, V.F., Tsvarg, S.L., Zigan, F.G., Latipov, S.U., Sultankhodzhayev, A.N. and Chernov, I.G., 1985. Complex statistical analysis of hydrogeochemical earthquake precursors. In: G.A. Sobolev and G.M. Varshal (Editors), Hydrogeochemical Earthquake Precursors. Nauka, Moscow, 286 pp.
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Tectonophysics 246 (1995) 263-278
Helium content in thermal waters in the Caucasus from 1985 to 1991 and correlations with the seismic activity F. B e l l a a, P . F . B i a g i b, M . C a p u t o c, E . C o z z i a, G . D e l l a M o n i c a a, A . E r m i n i d, W . P l a s t i n o a, V. S g r i g n a a, D . Z i l p i m i a n i e a Dipartimento di Fisica, III Universitd, 14a C. Segre, 2, 00146 Rome, Italy b Dipartimento di Fisica, Universit~ di Bari, Via Orabona, 4, 70100 Bari, Italy c Dipartimento di Fisica, Universit~ 'La Sapienza" Piazzale Aldo Moro, 2, 00185 Rome, Italy a Dipartimento di Ingegneria Meccanica, Universitd "Tor Vergata', l/'ta 0. Raimondo, 00173 Rome, Italy e Institute of Geophysics of the Academy of Sciences of Georgia, Z. Ruckhadze, L 380093 Tbilisi, Georgia Received 23 February 1994; accepted 5 December 1994
Abstract
A wide data set of groundwater helium content collected in the Caucasus from 1985 to 1991 has been analyzed. The strongest earthquakes that occurred in this area during the helium measurement period were the: Paravani (May 13th, 1986, M = 5.6), Spitak (December 7th, 1988, M = 6.9) and Georgian (April 29th, 1991, M--6.9) earthquakes. The analysis of the helium content data revealed statistically significant increases in this parameter on the occasion of the Paravani and Spitak earthquakes and no increase on the occasion of the Georgian earthquake. These results corroborate those obtained by the analysis of scanty helium content data presented in previous papers. With the exception of the anomalous increases, the helium content data were subjected to randomness tests and spectral analysis and cross correlation with meteorological parameters and areal seismicity were also attempted. The main result obtained is that the destructive Spitak earthquake produced some statistical changes in the groundwater helium content fluctuations some years before and after its occurrence.
1. Introduction
Extensive studies carried out in the last 15 years have shown that soil-gas and groundwater helium changes are often associated with earthquakes (Wakita, 1978; Mamyrin et al., 1979; Barsukov et al., 1979a,b, Barsukov et al., 1982; Chi-Yu King, 1984; Reiner, 1985). As part of an ItalianGeorgian study, the thermal waters of some springs located in the Georgian Caucasus were sampled systematically once a day from 1985 to 1991 for analysis of the helium content. Since the
middle of 1991 this research has been interrupted due to the war situation in the zone. Anomalies in the helium content measured in some sites of the network were revealed on the occasion of the Paravani ( M = 5.6, 1986) and Spitak ( M = 6.9, 1988) earthquakes and have already been reported in a previous paper (Areshidze et al., 1992a). The non-occurrence of the same kind of anomalies on the occasion of the Georgian ( M = 6.9, 1991) earthquake has also been presented and discussed (Areshidze et al., 1992b). The previous results were discussed using
0040-1951/95/$09.50 © 1995 Elsevier Science B.V. All rights reserved SSDI 0040-1951(94)00260-6
264
F. Bella et al. / Tectonophysics 246 (1995) 263-278
a partial data set. Now we have gathered the entire helium content data set from January, 1985, up to June, 1991, and for the same period we have collected meteorologic data from some weather stations located near the springs. In addition, we have at our disposal the data from the Seismological Notes of the Institute of Geophysics of the Academy of Sciences of Georgia (Academy of Sciences of the Georgian SSR, 1986-1991). The results we have obtained using these data sets are presented in this paper.
2. Tectonic setting and seismicity The Caucasus is characterized by a complex evolutionary history. Due to the collision of the Arabian and Eurasian plates in this area it is a mixture of tectonic units belonging to different continental margins. Fig. 1 shows the main fault systems in the Georgian Caucasus area. The Lesser Caucasus consists of a north-verging system of folds which have their origin in the conti-
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nental collision. In contrast, the Greater Caucasus is formed from a south-verging system of folds, related to the intracontinental compression connected with the northward thrust of the Arabian plate. These two, seismogenetically different, tectonic units are separated by the Transcaucasian Massif (Adamia et al., 1991). The active tectonic setting is a compressive one, with evident slip fronts and folded structures. Folds are locally interrupted by continuous structural lineations that suggest a strike-slip movement. The most significant lineament system is parallel to the orogenic belt ( W N W - E S E ) . Other lineaments (N-S, N E - S W and N W - S E ) appear that probably correspond to the same stress field of Central Anatolia. The strongest seismic events in the Caucasus from 1985 to 1991 were: (1) The Paravani main shock ( M = 5.6), which occurred on May 13th, 1986, at a depth of about 10 km. (2) The Spitak main shock (M = 6.9), which occurred on December 7th, 1988, at a depth of about 4 km.
A
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Fig. 1. Map showing the main fault systems in the Georgian Caucasus.
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F. Bella et al. / Tectonophysics 246 (1995) 263-278
(3) The Georgian main shock (M--6.9), which occurred on April 29th, 1991, at a depth of less than 10 km. The first two events occurred in the seismotectonic area of the Lesser Caucasus and the northern border of the Armenian plateau; the latest one on the southern slope of the Greater Caucasus. These earthquakes were followed by aftershock activity; in the case of the Spitak event, aftershocks occurred for 2 years after the main shock. The location of these seismic sequences is shown in Fig. 2. Except for these events, the seismicity from 1985 to 1991 appears with a mean frequency of about 100 earthquakes/yr and is
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265
characterized by K values (the logarithm of energy in joules) ranging from 8.5 to 12.7. The spatial pattern of the seismicity is shown in Fig. 2.
3. E x p e r i m e n t a l
data and analytical procedures
Fig. 2 shows the location of the measurement sites at springs that were operating in 1991. The helium content of waters was measured using an INGEM-1 instrument (Varshal et al., 1985). The sensor is a miniature magnetic discharge pump supplied with a diffusive quartz membrane which has a high selectivity for helium. The waters flow
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F. Bella et al. / Tectonophysics 246 (1995) 263-278
266 (/~1/1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 (/~1/I 2.5
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Fig. 4. (a) Variations in the groundwater helium content at V A R spring from January 1st, 1985, to June 30th, 1991. ( b - d ) M e a n air temperature, atmospheric pressure and rainfall m e a s u r e d at a local weather station. (e) K values of seismicity in a circle of 300 km radius around the spring.
F. Bella et al. / Tectonophysics 246 (1995) 263-278
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F. Bella et aL / Tectonophysics 246 (1995) 263-278 (~IA 9
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Fig. 6. (a) and (b) Variations in the groundwater helium content at springs BAK and BOR from January 1st, 1988, to June 30th, 1991. (c-e) Mean air temperature, atmospheric pressure and rainfall measured at a local weather station. (f) K values of seismicity in a circle of 300 km radius around the springs that we considered as located in the same place.
F. Bella et al. / Tectonophysics 246 (1995) 263-278
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F. Bella et al. / Tectonophysics 246 (1995) 263-278
271
Table 1 Time interval when the helium content increases exceed the response level Spring LIS
VAR
QUA
BAK
SAB
May 13, 1986May 16, 1986 Dec. 7, 1988Jan. 2, 1989
May 13, 1986May 19, 1986 Dec. 1, 1988Jan. 10, 1989
-
-
Dec. 5, 1988Jan. 31, 1989
Dec. 1, 1988Jan. 1, 1989
June 15, 1986June 17, 1986 -
naturally from a number of springs and they belong to the fault- and fissure-karst types of waters. These waters are characterized by deep and generally rapid circulation. The main features of the springs indicated in Fig. 2 are reported in Areshidze et al. (1992b). Figs. 3-6 show the variations in the helium content at the LIS, SAB, VAR, QUA, BAK and BOR springs, during the period January 1st, 1985, to June 30th, 1991. The interruptions in the trends indicate when data were not collected. For the BAK and BOR springs, the data were collected starting from 1988. For the SAB spring the sampling was interrupted from November 1988 to allow building construction at that site. Meteorological data collected at local weather stations and the seismicity, represented by the K values of the earthquakes which occurred in a circle of a radius of 300 km from each spring, are shown, together with the helium content data. A radius of 300 km represents the distance at which it seems reasonable to consider some influence of seismic activity on the helium content variations (Barsukov et al., 1979a; Barsukov et al., 1979b; Barsukov et al., 1984/85a,b; Varshal et al., 1985). For rainfall and K values we obtained a regular progression considering the weighted average over 30 days 1, moving in steps of 1 day. We considered the clear relationship between the most obvious helium content increases and the K values in the cases of the Paravani and Spitak seismic sequences. In the first case such a relationship does not appear at the QUA spring, 5 1 If x is the variable we use the relationship: ~ = [(,~_',xn)+ 10 15 20 25 30 2( ,~,x n ) + 4( ,~,x n) + 8 ( ~ n ) + 16(,~_',Xn) + 32(~,xn)]/63 6 11 16 21 26
1
which is the farthest one from the epicentre of the earthquake, probably outside the 'sensitive' zone (Areshidze et al., 1992a). For each helium concentration data set we calculated the standard deviation, tr, over the entire sample. If the 3(r level is chosen as the response level, the helium variations can all be explained as being due to the release of seismic energy connected with the Paravani and Spitak sequences. Fig. 7 shows the helium content trends at the various springs. The 3~ level (horizontal line) is indicated in each case. The occurrence of the Paravani, Spitak and Georgian main shocks is also shown. Raw data show clearly when the helium content increases exceed the response level; these time intervals are listed in Table 1. We then analyzed the helium content data during the periods in which the variations in the trend are below the risk level, in order to uncover some possible physical meaning of such variations. We used for the statistical and mathematical analysis the STATGRAPHICS software package of the Statistical Graphics Corporation. In the beginning we carried out several distribution fittings on the experimental data, in order to test their randomness (Barsukov, 1984/85a,b). The fittings were tested using both X 2 and Kolmogorov-Smirnov tests. The entire data set below the + 3o~ value was tested and randomness did not appear, so we tried to examine these data by splitting them into different time intervals. We met with some randomness choosing the following three time intervals: (1) before the Paravani main shock (January 1, 1985-April 30, 1986); (2) after the Paravani main shock and the following aftershock activity and before the Spitak main shock (July 1, 1986-October 31, 1988);
272
F. Bella et al. / Tectonophysics 246 (1995) 263-278
LIS (/,IA) 0,03 0.025 0.02 0.015 0.01 0.005 0 120
32
T (days)
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Fig. 8. Spectral analysis obtained from LIS helium data related to the intervals: (a) January 1st, 1985-April 30th, 1986. (b) July 1st, 1986-October 31st, 1988. (c) March 1st, 1989-June 30th, 1991. The periods indicated at the bottom of each spectrum are the cut-off periods used for the data filtering.
F. Bella et al. / Tectonophysics 246 (1995) 263-278
(3) after the Spitak more intense seismic sequence (March 1, 1989-June 30, 1991). The randomness was obtained in the time intervals 1 and 2 only. In case 1 our goal was a lognormal (LIS) and a normal (VAR and QUA) distribution fitting; in case 2 sufficient success was achieved with a lognormal (LIS and QUA) and a Weibull's distribution (VAR). The results of these tests are listed in Table 2. We then carried out a spectral analysis on the helium content data during the above mentioned time intervals (Mendenhall et al., 1981; Shapiro et al., 1984/85). In general the amplitude of the signals does not appear to be related to particular frequencies but is distributed over a wide range. In the cases in which it was possible to obtain the spectra in all three time intervals some differences seem to appear. Fig. 8 shows the spectra related to the LIS data, using 29 values of a continuous data set of the three intervals and it is clear that, in the time interval from January 1st, 1985, to April 30th, 1986, the amplitude of the signal is mostly associated with the helium variation of high frequencies. We continued to look for the influence of external processes on the helium content in the quoted time intervals (Klusman and Webster, 1981; Shapiro et al., 1984/85). To this purpose, on the basis of the spectra, we applied highfrequency pass filters, band-pass filters and lowfrequency pass filters to the raw trends. Then we compared the raw and filtered trends of the helium content data with the meteorological data
Table 2 Randomness tests Test
Spring US
VAR
QUA
January 1, 1985- April 30, 1986 X2 v a K- S
7.935 9 54% 88%
16.198 9 6% 63%
17.130 8 3% 18%
July 1, 1986-October 31, 1988 X2 v a K-S
9.025 6 17% 45%
15.624 7 3% 5%
13.630 8 9% 7%
273
and the seismicity (K values). Obviously, in the case of correlation with filtered helium content data, we applied the same filters to the meteorological and seismic data. The best values of the cross correlation coefficient, r (in phase-= +, opposite phase -= - ) that we obtained in period 2 are listed in Table 3. The corresponding values of the temporal shift (advance = - , d e l a y - + ) of the helium content trend with respect to the various parameter trends are indicated in parentheses in Table 3. For the cross correlation with meteorological parameters we considered only positive shifts; in any case, we assumed 60 days as the maximum shift (Bella et al., 1993; Barsukov et al., 1984/85a,b). The results of this analysis on the data in the other two time intervals are very similar, except for the low-frequency pass filter, where the cross correlation coefficients are always smaller than 0.5.
4. Discussion
The first analysis we carried out on the helium content data (Fig. 7) revealed statistically significant increases in the helium content on the occasion of the Spitak seismic sequence from all active stations. From the data listed in Table 1 the existence of a precursory phenomenon can be clearly seen at the V A R and Q U A sites. At the LIS site the anomaly does not seem to precede the earthquake. The same circumstance happens on the occasion of the Paravani earthquake (M = 5.6). The duration of the helium content increase was about 30-40 days for the Spitak earthquake and 3-6 days for the Paravani event. Such periods correspond quite well with the periods where the aftershock activity was more energetic (Areshidze et al., 1992a). This seems to indicate that the helium content anomalies are clearly connected with an intensification of the microfracturing processes a n d / o r changes in the existing cracks. The consequent delivery of gases, vapours and pore solutions, which are squeezed out of the rock into the water-bearing strata, could be the possible origin of the helium content increases observed (Shabynin et al., 1983; Varshal et al., 1983; Barsukov et al., 1984/85a,b). The
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existence of clear precursory anomalies only before the occurrence of the Spitak ( M = 6.9) earthquake can be explained by the greater amount of energy dissipated in preseismic stressreadjustment processes than in the case of the Paravani ( M = 5.6) earthquake (Areshidze et al.,
1992a). The exception at spring LIS on the occasion of the Spitak earthquake seems to indicate some anisotropic character in the stress readjustment processes. The data listed in Table 1 are in agreement with the results presented in Areshidze et al.
Table 3 Helium content correlation
LIS Raw data High-pass filter T = 30 d Band-pass filter T = 30 d T = 50 d Band-pass filter T = 50 d T = 120 d Low-pass filter T = 120 d VAR Raw data High-pass filter T = 21 d Band-pass filter T = 21 d T = 34 d Band-pass filter T = 34 d T = 50 d Low-pass filter T = 160 d QUA Raw data High-pass filter T = 20 d Band-pass filter T = 20 d T = 35 d Band-pass filter T = 35 d T = 8 0 d Low-pass filter T = 120 d SAB Raw data High-pass filter T = 16 d Band-pass filter T = 16 d T = 33 d Band-pass filter T = 33 d T = 80 d Low-pass filter T = 120 d
Pressure
Temperature
Rainfall
Seismicity
- 0.20 (8) 0.02 (29) 0.18 (35) 0.20 (4) - 0 . 3 8 (8) 0.36 (30) - 0.42 (8) 0.23 (32) - 0.21 (30)
- 0.18 (60) 0.03 (0) 0.28 (43) 0.25 (35) -0.13 (37) 0.25 (56) 0.1 (2) 0.26 (49) - 0.38 (58) 0.11 (2)
- 0.15 (60) 0.25 (43) - 0 . 2 2 (11) 0.18 (l) - 0 . 1 3 (37) 0.25 (56) - 0.30 (60) 0.44 (42) - 0.09 (43) 0.12(6)
0.43 ( - 6)
0.44 (25) 0.12 (42) 0.08 (9) - 0 . 4 0 (47) 0.35 (33) - 0.46 (48) 0.24 (29)
-0.01 (33) 0.29 (58) - 0 . 2 0 (29) 0.27 (4) -0.35 (37) 0.37 (23) - 0.26 (38) 0.29 (60)
0.55 (24)
0.45 (55)
0.41 (8) - 0 . 1 6 (15) 0.13 (20) - 0.47 (53) 0.46 (39) --0.23 (27) 0.24 (6)
- 0.03 (38) 0.26 (0) 0.21 (9) 0.21 (2) - 0.38 (39) 0.41 (54) - 0 . 0 8 (39) 0.09 (23)
0.41 (7)
0.51 (2)
- 0.03 (44) 0.02 (7) - 0 . 1 7 (10) 0.15 (16) -(/.15 (1) 0.14 (12) - 0 . 1 0 (0) 0.32 (60) - 0 . 1 9 (53) 0.09 (4)
- 0.07 (34) 0.20 (0) - 0 . 1 3 (6) 0.14 (11) - 0 . 1 7 (34) 0.14 (23) - 0 . 1 9 (60) 0.26 (8)
-0.20 (53) (1.27 (16) 0.21 (28) 0.23 (0) -0.35 (28) 0.30 (41) - 0.16 (31) 0.39 (12) 0.58 (63) 0.47 (9) - 0.17 (58) 0.05 (26) -0.15 (47) 0.10 (53) - 0.40 (60) 0.31 (48) - 0 . 3 4 (50) 0.43 (26) 0.17 (5)
- 0.04 (60) 0.15 (17) 0.11 (41) 0.13 (20) - 0 . 4 8 (54) 0.45 (44) -0.11 (60) 0.09 (18) - 0 . 0 8 (2) 0.12 (55)
0.14 ( - 4 ) 0.42 ( - 6) 0.45 ( - 7) 0.72 ( - 4)
0.40 ( - 10) 0.21 ( - 4 2 ) 0.28 ( - 16) 0.28 ( - 16) 0.80 ( - 15)
0.42 ( - 16) 0.27 (51) 0.37 (46) 0.60 ( - 16) 0.62 (25)
0.26 ( - 6) 0.20 (53) 0.23 ( - 6) 0.30 ( - 9 ) 0.14 (0)
0.68 (14)
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(1992a). Only for the case of the SAB spring is there a discrepancy: in fact Areshidze et al. presented the signal with an asterisk in their fig. 7 as anomalous. In the present paper this signal is below the + 3 t r level and, instead, an increase over this level appears from June 15th to June 17th, 1986 (Table 1), that is about 1 month after the Paravani main shock. The interpretation of such an anomaly as a post-seismic effect does not appear realistic on the basis of our data. Therefore, we considered this anomaly as the only exception to the correspondence between statistically significant increases in the helium content and the occurrence of the Paravani and Spitak seismic sequences. We shall discuss the behaviour of SAB later. The absence of a helium content anomaly on the occasion of the Georgian earthquake appears dearly from the examination of the complete helium content data set (Fig. 7). Areshidze et al. (1992b) gave a reasonable interpretation for such an absence of anomalies on the basis of differences between the seismogenetic area of the Georgian earthquake with respect to that of the Paravani and Spitak earthquakes (see previous section). The results of the randomness analysis can be summarized as follows: (A) Before the Paravani earthquake the groundwater helium content variations can be considered statistically random according to a (log)normal distribution (Table 2). (B) After this earthquake, and before the Spitak earthquake, the randomness of the helium content variations changes; generally, it is less evident and at site VAR it seems to change according to a Weibull's distribution (Table 2). It must be noted that, in this period, only the tests on SAB data have not given any randomness. This is the second exception for the SAB spring. (C) In the period after the Spitak seismic sequence the randomness tests failed everywhere. A possible explanation of these results is as follows. Let us consider that the usual variations in groundwater helium content happen according to case (A) (i.e., in the time before the Paravani earthquake). The stress readjustment processes following the Paravani earthquake and preceding the Spitak earthquake produce some modifica-
275
tions in the frequency and periodicity of the microcracks over a wide zone so a consequent variation in the delivery of helium into the water-bearing strata occurs. The changes in the randomness of the helium content variations pointed out in (B) could be connected with this phenomenon. It seems reasonable to consider that the modifications connected with the occurrence of the Paravani earthquake, because of the lesser stress, are less influential on the observed phenomena than those connected with the prerupture phase of the Spitak earthquake; if this is correct a long-term (about 2 yr) statistical precursor of the Spitak earthquake appears. Such a hypothesis is corroborated by the fact that a Weibull's distribution can describe (Barsukov et al., 1982) the 'fatigue' of a system and we find randomness, according to such a distribution, only at the VAR site, which is the nearest one to the epicentre of the Spitak earthquake. The statement in (C) above seems to indicate that the occurrence of the Spitak seismic sequence had modified the hydrogeochemical system for a long time. We tried to evaluate the duration of this modification. For this purpose we applied the randomness tests to the final part of our data set and obtained a good result for the LIS spring, where we had the best result for a lognormal distribution, with a X 2 = 8.343 (v = 9, a = 50%) and K - S = 40%, testing the data from October 1st, 1990, to June 30th, 1991. This suggests that an estimation of about 2 yr for the time of the modification is reasonable. The spectra we obtained revealed that, in general, no characteristic frequency stands out and this situation appears whether the data seem random or not. However, the spectral content of the helium data appears to be mostly associated with the helium variations of high frequencies in the time interval from January 1st, 1985, to April 30th, 1986. If we assume such amplitude distribution in helium content variations to be usual it seems reasonable to consider that the subsequent modifications of the spectra are connected, at first, with the phenomenon we described for randomness in the pre-rupture phase of the Spitak earthquake and with the quoted stress readjustment induced by its occurrence (Zhelankina et
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al., 1985). In the first case another long term statistical precursor of the Spitak earthquake appears. As regards the cross correlations we have tried, the influence of periodic parameters, such as long-term solar-lunar tides, on the groundwater helium content may exist (Lebedev et al., 1985) but it does not seem relevant on the basis of the previous analyses. We therefore neglected this effect among the external processes that can act on the helium fluctuations in a substantial way. From the data listed in Table 3, which refer to the period July 1st, 1986-October 31th, 1988, a correlation exists between the low-pass filter trend of the helium content and seismicity. An exception is the SAB spring, where, in contrast, a good correspondence with rainfall seems evident. In the previous section it was pointed out that, in the time intervals from January 1st, 1985, to April 30th, 1986, and from March 1st, 1989, to June 30th, 1991, the correspondence between the helium content and any other parameter appears uncertain. If we look at the results from the LIS, VAR and Q U A springs it appears that the seismicity leads the helium content variations in groundwaters only in about the 2 yr preceding the Spitak earthquake. It is thus reasonable to consider this behaviour as another long-term precursor of such an earthquake. In this way the long-period variations in the helium content seem to be modulated in frequency by the seismicity, as an effect of the increasing tectonic stress preceding the Spitak earthquake. Such modulation indicates the occurrence of modifications in the spatial-temporal distribution and in the energy release of the seismic activity in the Caucasus. According to the first statement of this section, when the seismicity becomes a paroxysmal phenomenon (Spitak and Paravani seismic sequences) an amplitude modulation is induced in the helium content variations and so the correspondence between the helium content and the seismicity appears complete. The fact that after the Spitak seismic sequence the correspondence between the helium content and the seismicity does not appear seems to indicate that in these particular circumstances the helium content in the groundwater was more
strongly controlled by the gradual tectonic packing subsequent to the Spitak seismic sequence than by the fracturing associated with its aftershock activity. Finally, if we look at the result at the SAB spring, we can conclude that here the helium content data are disturbed by rainfall in a substantial way. Such a phenomenon had been present for some time so the direct correspondence between helium content and rainfall we pointed out is natural (Klusman and Webster, 1981; Lebedev et al., 1985). In addition, the building construction work mentioned in the previous section produced evident infiltrations. Thus, all the above mentioned exceptions at the SAB spring can be understood. The behaviour of the groundwater helium content concerning randomness, spectral analysis and correlations with the areal seismicity in the time interval after the Spitak seismic sequence has been presented here as directly connected with the stress readjustment related to the earthquake. It did not seem right to interpret this behaviour as a phenomenon connected with the preparation of the Georgian earthquake of April 1991. The absence of anomalous behaviour in the helium content in the network of Fig. 2 on the occasion of this earthquake (Areshidze et al., 1992b) has been confirmed again by the statistical treatment of the data. The possibility that such an absence is due to a decrease in the sensitivity (Barsukov et al., 1984/85a,b) of the hydrothermal system connected with the external effects of the Spitak earthquake exists. We consider it to be more probable that the quoted network for the study of precursors is predominantly 'sensitive' to earthquakes that take place in the seismogenetic zone of the Lesser Caucasus and the Armenian plateau (Areshidze et al., 1992b).
5. Conclusions
The study of the helium content in thermal springs of a network located in Georgia during a long time interval (about 6 yr) has revealed that, when strong earthquakes occurred in the seismogenetic zone to which the network is 'sensitive'
F. Bella et al. / Tectonophysics 246 (1995) 263-278
(Areshidze et al., 1992b), the helium content increases over the 'response level', represented by the +3or value; such an increase also has a preseimic phase if the impending earthquake is a destructive one. In such circumstances the helium content data exhibit term precursors as changes in randomness fittings, differences in spectral content and a good correspondence with the areal seismicity. After the occurrence of the earthquake the helium content variations are affected by the subsequent gradual tectonic packing. If the groundwater helium content is considered as an indicator, all the phenomena quoted can help to understand the complex tectonic processes that take place before and after the occurrence of a destructive earthquake.
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Zhelankina, T.S, Kushnir, A.F., Pisarenko, V.F., Tsvarg, S.L., Zigan, F.G., Latipov, S.U., Sultankhodzhayev, A.N. and Chernov, I.G., 1985. Complex statistical analysis of hydrogeochemical earthquake precursors. In: G.A. Sobolev and G.M. Varshal (Editors), Hydrogeochemical Earthquake Precursors. Nauka, Moscow, 286 pp.