1 Integrating outcomes from probabilistic and deterministic seismic
2 hazard analysis in the Tien Shan
3 I. Mosca1, B. Baptie 1, S. Sargeant 1, R. T. Walker 2
4 1 British Geological Survey, the Lyell Centre, Research Avenue South, Edinburgh EH14
5 4AP, United Kingdom
6 2 COMET, Department of Earth Sciences, Oxford University, South Parks Road, Oxford
7 OX1 3AN, United Kingdom
8
9 Abstract
10 In this study, we have evaluated the probabilistic and deterministic seismic hazard for the city
11 of Almaty, the largest city in Kazakhstan, which has a population of nearly 2 million people.
12 Almaty is located in the Tien Shan mountain belt, a low strain rate environment within the
13 interior of the Eurasian plate that is characterized by large, infrequent earthquakes. A robust
14 assessment of seismic hazard for Almaty is challenging because current knowledge about the
15 occurrence of large earthquakes is limited due to the short duration of the earthquake
16 catalogue and only partial information about the geometry, rupture behaviour, slip rate, and
17 the maximum expected earthquake magnitude of the faults in the area. The impact that this
18 incomplete knowledge has on assessing seismic hazard in this area can be overcome by using
19 both probabilistic and deterministic approaches and integrating the results.
20 First, we simulate ground shaking scenarios for three destructive historical earthquakes that
21 occurred in the Northern Tien Shan in 1887, 1889 and 1911, using ground motion prediction
1
22 equations (GMPEs) and realistic fault rupture models based on recent geomorphological
23 studies. We show that the large variability in the GMPEs results in large uncertainty in the
24 ground motion simulations. Then, we estimate the seismic hazard probabilistically using a
25 Monte Carlo-based PSHA and the earthquake catalogue compiled from the databases of the
26 International Seismological Centre and the British Geological Survey. The results show that
27 earthquakes of Mw 7.0 to 7.5 at Joyner-Boore distances of less than 10 km from the city pose
28 a significant hazard to Almaty due to their proximity. These potential future earthquakes are
29 similar to the 1887 Verny earthquake in terms of their magnitude and distance from Almaty.
30 Unfortunately, this is the least well understood of the destructive historical earthquakes that
31 have occurred in the Northern Tien Shan.
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32 Introduction
33 The Tien Shan is situated in a low strain region in the interior of the Eurasian plate (e.g.,
34 Landgraf et al., 2016a). Slip on faults accumulates at rates of less than a few millimeters per
35 year compared with plate boundaries where slip rates reach 10-100 mm/yr (England and
36 Jackson, 2011). In the Tien Shan, there are many segmented faults that form a zone hundreds
37 of kilometers wide. The time required to accumulate the tectonic displacement is from a few
38 hundreds to a few thousands of years due to the low strain rate and the low tectonic loading
39 (e.g., England and Jackson, 2011; Landgraf et al., 2016b). For this reason, earthquakes of
40 moment magnitude (Mw) > 7 are infrequent here and their recurrence intervals are up to
41 thousands of years (e.g., Abdrakhmatov et al., 2016; Landgraf et al., 2016a). Furthermore,
42 most of these faults are poorly understood or unknown until an earthquake occurs along them
43 (e.g., England and Jackson, 2011; Liu and Stein, 2016). Recent studies, based on
44 geomorphological and paleoseismological data, have become available for some areas of the
45 Tien Shan. They can be used to extend the earthquake records back in time (e.g., Landgraf et
46 al., 2016a; Grützner et al., 2017) by mapping and characterizing probable surface ruptures
47 associated with the historical earthquakes that occurred between 1885 and 1911 in the
48 Northern Tien Shan (Arrowsmith et al., 2016; Abdrakhmatov et al., 2016).
49 Seismic hazard assessment for this region is challenging because the available seismological
50 data do not adequately represent the long-term earthquake history in the region (e.g.,
51 Abdrakhmatov et al., 2016; Landgraf et al., 2016a). As a result, the undertaking of either
52 probabilistic seismic hazard analysis (PSHA; e.g., Reiter, 1990; McGuire, 2004) or
53 deterministic seismic hazard analysis independently (DSHA; e.g., Reiter, 1990) may be
54 insufficient for this region. Instead, integrating the outcomes from PSHA and DSHA may
55 produce a more rigorous seismic hazard assessment. The goal of this paper is to combine the
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56 outcomes from both PSHA and DSHA to address the lack of ‘sufficient’ seismological and
57 geological data for this area. First, we evaluate the deterministic scenarios and then compute
58 the hazard using a probabilistic approach in order to estimate the annual frequency of
59 exceedance of the deterministic ground motion value(s). Then, we check the results of the
60 probabilistic analysis with DSHA to determine the credible earthquake scenario for low
61 annual frequencies of exceedance. Using both PSHA and DSHA is recommended for the
62 seismic hazard of highly critical infrastructure, such as nuclear power plants (IAEA, 2010),
63 where the standard practice is to perform PSHA and then to apply DSHA for the scenario of
64 the maximum credible earthquake that is the reasonably largest earthquake. There are also
65 studies that combine the PSHA and the DSHA for region-based seismic hazard analysis (e.g.,
66 Wong et al., 2002).
67 This study focuses on Almaty, the former capital of Kazakhstan and the largest city in the
68 region (Figure 1). It is situated in a topographical depression in the foothills of the Zailisky
69 Alatau mountain ranges that are bounded by poorly understood and sometimes unmapped
70 faults (Pilz et al., 2015; Grützner et al., 2017). The building profile of the city is ever-
71 changing and many new buildings have been constructed in the last 30 years including
72 residential buildings of four to nine stories (King et al., 1999) and buildings of up to 38-
73 stories, such as Almaty Towers and Esentai Tower (Paramzin, 2005). The population of
74 Almaty has increased from a few thousands of people at the beginning of the 20th century to
75 almost two million in 2017 (Silacheva et al., 2017). This rapid growth has increased both the
76 number of people and assets exposed to the earthquake risk. This requires using techniques
77 that allow for a robust estimate of the seismic hazard due to our incomplete understanding of
78 the earthquake environment in this region.
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79 The mapping and characterization of the surface ruptures for the historical earthquakes that
80 occurred between 1887 and 1911 in the Northern Tien Shan from the recent studies of
81 Arrowsmith et al. (2016) and Abdrakhmatov et al. (2016) allows now for such a seismic
82 hazard re-estimation to take place. These mapped faults are the basis for realistic fault rupture
83 models using DSHA. Then, we perform a PSHA to determine the return periods for different
84 levels of the scenario ground shaking for a site in Almaty. The hazard results obtained from
85 the PSHA are disaggregated to show the contribution of future earthquakes similar to the
86 historical earthquakes to the overall hazard of Almaty.
87 Regional setting
88 The Tien Shan is a tectonically and seismically active intraplate mountain belt that is
89 bounded by the Kyzyl-Kum desert to the east and the Gobi Desert to the west, and lies
90 between the Kazakh Platform to the north and the Tarim Basin to the south (Figure 1).
91 The formation of this mountain belt is a consequence of the continental collision between the
92 Indian and Eurasian plates that started 50 Ma ago. This resulted in the reactivation of pre-
93 Cenozoic structures in the last 50 Ma in Central Asia, including the Tien Shan, (e.g.,
94 Tapponnier and Molnar, 1979; Burtman et al., 1996). The present-day crustal shortening
95 across the Tien Shan is 20 mm/yr, corresponding to 40% of the crustal shortening between
96 India and Eurasia, even though the mountain belt is situated more than 1000 km north of the
97 plate boundary (e.g., De Mets et al., 1990; Zubovich et al., 2010). This deformation is
98 accommodated by E-W oriented thrusts, NNW-SSE-trending right-lateral strike-slip faults,
99 and ENE-WSW-trending left-lateral strike-slip faults (e.g., Tapponnier and Molnar, 1979;
100 Thompson et al., 2002; Abdrakhmatov et al., 2016). The E-W-striking faults delineate the E-
101 W-trending mountain ranges and the sub-parallel intra-mountain basins (e.g., Tapponnier and
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102 Molnar, 1979; Thompson et al., 2002). The major strike-slip structure in the Northern Tien
103 Shan is the NNW-SSE-oriented right-lateral strike-slip Talas-Ferghana fault. It
104 accommodates part of the N-S shortening in the Tien Shan with different rates of
105 convergence between the western and eastern Tien Shan (Alinaghi and Krüger, 2014;
106 Campbell et al., 2013).
107 SEISMICITY IN THE NORTHEN TIEN SHAN
108 The seismicity in the Tien Shan mountain belt is characterized by a large number of
109 earthquakes of Mw < 7 and 13 seismic events of Mw ≥ 7 since 1875. Since fault slip is
110 accumulated slowly in a low strain rate environment, the recurrence intervals of large
111 earthquakes on active faults in the Tien Shan are likely to exceed the length of the historical
112 earthquake record and so the seismicity catalogue presents an incomplete picture of the
113 earthquake environment (e.g., Abdrakhmatov et al., 2016; Landgraf et al., 2016a). In similar
114 tectonic settings, the identification of hazardous faults that often remain unmapped (2010
115 Canterbury earthquake in New Zealand; Landgraf et al., 2016b) or for which threat had not
116 been recognized (2003 Bam earthquake; England and Jackson, 2011) further complicates any
117 attempt to assess the seismic hazard. This is because the diffuse network of widespread,
118 highly-segmented faults in low rate environments, is much less well defined than the narrow
119 fault zones found along the plate boundaries (England and Jackson, 2011; Liu and Stein,
120 2016).
121 The seismicity in the Tien Shan is associated with faults bounding the intra-mountain basins
122 (e.g., Lake Issyk-Kul and the Ferghana Basin) and tend not to occur within the basins
123 (Zubovich et al., 2010; Alinaghi and Krüger, 2014) (Figure 1). The largest historical
124 earthquakes in the region occurred along the northern (i.e., 1885 surface wave magnitude
125 [Ms] 6.9 Belovodsk; 1887 Ms 7.3 Verny; 1889 Ms 8.3 Chilik; 1911 Ms 8.0 Chon-Kemin)
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126 and southern margins of the Tien Shan (e.g., 1902 Ms 8.3 Artux). High levels of instrumental
127 seismicity with magnitudes smaller than Mw 7.0 are located along the margin between the
128 Tien Shan and the Tarim Basin and to a lesser extent, along the margin between the Tien
129 Shan and the Kazakh Platform (Alinaghi and Krüger, 2014) (Figure 1). The largest
130 instrumental earthquakes are the 19 August 1992 Ms 7.3 Suusamyr earthquake and the 24
131 March 1978 Mw 6.9 Dzhalanash-Tyup earthquake (Figure 1). The 1992 Suusamyr
132 earthquake sequence is the first well-recorded seismic sequence in the region (Ghose et al.,
133 1997; Mellors et al., 1997).
134 Levels of seismicity of Mw < 6 are associated with the Talas-Ferghana fault and no major
135 earthquakes have occurred along this fault in the last 200 years (Campbell et al., 2013).
136 Ghose et al. (1998) suggest that the lack of large earthquakes on the Talas-Ferghana fault is
137 due to its locked state and present-day activity is accommodated along neighboring
138 compressional structures. The 2 November 1946 Mw 7.6 Chatkal earthquake might have
139 occurred along the Talas-Ferghana fault (e.g., Molnar and Deng, 1984). However, the large
140 uncertainties in the epicentral location and the style of faulting of this earthquake make this
141 hypothesis debatable.
142 The general tectonic regime in the Tien Shan is compressional and the dominant focal
143 mechanisms are reverse faulting with various degrees of strike-slip motion (Alinaghi and
144 Krüger, 2014). The P-axis of focal mechanisms for the earthquakes in the region is oriented
145 N-S, in agreement with the direction of the convergence between India and Eurasia (e.g.,
146 Tapponnier and Molnar, 1979; Alinaghi and Krüger, 2014). There are also a few strike-slip
147 events (e.g., the 12 November 1990 Mw 6.3 earthquake and the 28 January 2013 Mw 6.2
148 earthquake) that occurred along the margin between the Tien Shan and the Tarim Basin and
149 between the Northern Tien Shan and the Ili Basin.
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150 Sloan et al. (2011) use inversion of teleseismic body waves, identification of depth phases
151 and modeling of regional waveforms, to relocate 123 earthquakes with Mw 5.2 in the Tien
152 Shan region. They find that hypocentral depths for earthquakes in the Tien Shan mountain
153 belt are in the upper crust at depths of less than 25 km, whereas the earthquakes in the Tien
154 Shan Foreland, the Kazakh Platform, and the Tarim Basin are of the mid to lower crustal
155 nature (up to 40 km hypocentral depth). This may suggest the presence of remnants of
156 subducting plate or underplating involved in the formation of the Tien Shan (Alinaghi and
157 Krüger, 2014).
158 Deterministic approach
159 DSHA is generally based on discrete, single-valued models to arrive at scenario-like
160 descriptions of seismic hazard (Reiter, 1990). After defining the seismic source(s), in the
161 study area, the controlling earthquake is usually selected as the largest earthquake that the
162 seismic source is capable of generating, i.e., the maximum credible earthquake (Reiter, 1990).
163 How the magnitude of the controlling earthquake is defined will determine the level of
164 conservatism of the assessment (Reiter, 1990). The level of ground shaking at the site caused
165 by the controlling earthquake is estimated using a ground motion prediction equation
166 (GMPE) or a numerical method to simulate the ground motion.
167 For each fault rupture model and GMPE, we compute a set of values of the selected ground
168 motion parameter (e.g., peak ground acceleration and spectral acceleration) for a single site or
169 grid point. We model the earthquake rupture as planar fault segments, using the fault
170 orientation (i.e., strike, dip and rake), the thickness of the seismogenic zone, rupture aspect
171 ratio and a magnitude-length scaling relationship. We do not consider the direction of the
172 rupture and, therefore, the location of the epicenter does not have any effect on the ground
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173 motion calculations. Only the location, the dimensions of the fault and the style of faulting
174 are important for the deterministic scenarios. The GMPEs used in this study are derived from
175 large worldwide strong motion datasets for active shallow crustal regime and are considered
176 appropriate for the Tien Shan (see “Selection of the ground motion models” for further
177 discussion).
178 For each controlling earthquake, we define a single rupture model, and select one or more
179 GMPEs that are combined in a logic tree. Then, we compute multiple realizations of the
180 ground motion value, each realization sampling the aleatory uncertainty in the GMPEs using
181 Monte Carlo simulations. This procedure allows us to include the aleatory uncertainties in
182 GMPEs by selecting the ground motion values from their probability density functions, as
183 defined by the median prediction within one standard deviation (the aleatory uncertainty in
184 the GMPE), which corresponds to the 84th percentile ground motion (e.g., Abrahamson,
185 2006). This procedure is similar to the scenario-based seismic hazard analysis implemented
186 in the software OpenQuake (e.g., Pagani et al., 2014).
187 DEFINING THE SCENARIO EARTHQUAKES
188 In this study, we use the DSHA to estimate ground motion scenarios for the three largest
189 earthquakes recorded in the Northern Tien Shan region between the end of the 19th century
190 and the beginning of the 20th centuryː the 1887 Ms 7.3 Verny earthquake, the 1889 Ms 8.3
191 Chilik earthquake, and the 1911 Ms 8.0 Chon-Kemin earthquake (Figure 1). All of them
192 caused heavy damage in Almaty. We refer to them not as controlling earthquakes, but as
193 scenario earthquakes because there is no conclusive evidence that they are either the closest
194 or the largest potential earthquakes to Almaty due to the short length of the earthquake
195 catalogue in the region (see Appendix A). We cannot rule out the occurrence of a destructive
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196 earthquake of Mw ≥ 8.0 before 1875, since the earthquake catalogue for Mw 8.0 and greater
197 is complete.
198 For these earthquakes, we determine the rupture geometry based on the available information
199 in the literature, geological observations, and earthquake physics. We use the self-consistent
200 empirical relationships of Leonard (2010) to estimate the dimension of the fault rupture using
201 Mw, and Mw to estimate the seismic moment M0 (Kanamori, 1977; Hanks and Kanamori,
202 1979).
203 The parameters of the rupture models for the three scenario earthquakes are summarized in
204 Table 1, together with their uncertainties if available from published sources or estimated
205 from the error propagation. The location of the epicenters and the mapped fault ruptures are
206 shown in Figure 2.
207 1887 Verny earthquake
208 The 8 June 1887 Verny earthquake was the closest event to Almaty among the earthquakes
209 that occurred between the end of the 19th and the beginning of the 20th century. The epicenter
210 was located 30 km west of the city. One month after the event, an expedition was sent from
211 St. Petersburg into the epicentral area to collect macroseismic information (Mushketov,
212 1890). These macroseismic data were used to infer the surface wave magnitude of MLH 7.3 ±
213 0.5 (Kondorskaya and Shebalin, 1982) (see Appendix A for the definition of MLH). MLH and
214 Ms are almost identical for MLH ≥ 5.4 (Scordilis, 2006; Bormann et al., 2013). Kondorskaya
215 and Shebalin (1982) also use the macroseismic data to estimate isoseismals, a hypocentral
216 depth of 20 km, and an epicentral intensity I0 of IX-X 0.5 for the Verny earthquake (the
217 intensity scale is not indicated in Kondorskaya and Shebalin, 1982). Tatevossian (2007)
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218 estimate a magnitude between MLH 7.3 and 7.5. Using the conversion equation of Scordilis
219 (2006), Ms 7.3 corresponds to Mw 7.3 0.2 (Table 1).
220 No surface rupture has been identified for this earthquake because the event triggered many
221 large landslides that may have covered the fault trace (Abdrakhmatov et al., 2016). For this
222 reason, very little is known about the rupture process of this event. Using the length-
223 magnitude scaling relationships of Leonard (2010), an earthquake of Mw 7.3 0.2 generates
224 a 75 20 km long and 31 8 km wide rupture (Table 1).
225 We assume a reverse faulting mechanism with a small strike-slip component, similar to the
226 mechanism of the 1911 earthquake (see Table 1). However, a pure reverse focal mechanism,
227 in agreement with the focal mechanisms determined for other earthquakes in the Zailisky
228 Alatau range, cannot be ruled out.
229 1889 Chilik earthquake
230 The 11 July 1889 Ms 8.3 Chilik earthquake is one of the largest historical continental events
231 in the world and one of the earliest teleseismically recorded earthquakes (Krüger et al., 2016).
232 Despite its size, relatively little is known about the source of the earthquake because the
233 isoseismals were the result of the sparse intensity observations in Mushketov (1891).
234 Mushketov (1891) do not report any primary surface rupture and assign a MSK-64 intensity
235 of IX-X around the Chilik River and VII-VIII in Almaty (Figure 3). Kondorskaya and
236 Shebalin (1982) estimate MLH 8.3 based on macroseismic observations. Bindi et al. (2014)
237 determine Ms 8.3 using data from the earthquake catalogue of Mikhailova et al. (2015).
238 Krüger et al. (2016) estimate the event to be between Mw 8.0 and 8.3 with a preferred value
239 of Mw 8.0 by analyzing a fragment of an early Rebeur-Paschwitz seismogram, recorded in
240 Wilhelmshaven, Germany, and magnetograph readings for the earthquake. In this study, we
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241 assume the magnitude for this earthquake to be Mw 8.2, which is an average value between
242 the findings of Krüger et al. (2016) and Bindi et al. (2014), with an uncertainty of 0.2
243 magnitude unit, i.e., the standard deviation in the magnitude conversion equations of
244 Scordilis (2006) (Table 1 and Appendix A). The Chilik earthquake was associated with the E-
245 W trending left-lateral Chon-Kemin-Chilik fault zone (e.g., Abdrakhmatov et al., 2002; 2016;
246 Krüger et al., 2016). The epicentral location is not well constrained by the sparse intensity
247 observations of Mushketov (1891) and the epicentral coordinates have an uncertainty of 0.5º
248 (Kondorskaya and Shebalin, 1982; Bindi et al., 2014).
249 Recent field investigations have found evidence of fresh scarps that may be associated with
250 the Chilik earthquake (e.g., Tibaldi et al., 1997; Abdrakhmatov et al, 2016). Abdrakhmatov et
251 al. (2016) identify three segments that potentially ruptured during this event: the 45-km-long
252 right-lateral Beshkaragai segment; the 30-km-long Saty segment with an oblique left-lateral
253 slip; and the 100-km-long right-lateral Kurmentey segment (Figure 2). They sum up to a total
254 of 175 km of complex multi-segmented surface rupture including step-overs (up to 6-7 km)
255 (Abdrakhmatov et al., 2016). Using the rupture length-magnitude scaling relationships of
256 Leonard (2010), an earthquake of Mw 8.2 0.2 would be associated with a 260 71 km long
257 rupture. This is longer than the 180 km surface rupture mapped by Abdrakhmatov et al.
258 (2016). The difference may be explained by: 1) a large hypocentral depth that did not allow
259 the entire fault rupture to reach the surface; or 2) the fact that not all the surface ruptures have
260 been identified (Abdrakhmatov et al., 2016; Krüger et al., 2016).
261 The hypocentral depth of this seismic event cannot be constrained by the available data.
262 Bindi et al. (2014) and Krüger et al. (2016) suggest a hypocentral depth in the mid or lower
263 crust and a depth of 40 km may be consistent with the isoseismals of this earthquake and the
264 lack of local intensity greater than MSK X (Figure 3). The 24 March 1978 Mw 6.9
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265 Dzhalanash-Tyup earthquake occurred in the epicentral area of the 1889 earthquake and had
266 a hypocentral depth of 35 km. This seems to support the possibility of large hypocentral
267 depth for the 1889 event (Krüger et al., 2016; Abdrakhmatov et al, 2016). However, this
268 hypothesis is not supported by any geological evidence and a depth of 20-25 km cannot be
269 ruled out (Krüger et al., 2016; Sloan et al., 2011).
270 Since the hypocentral depth is unconstrained, the down-dip width of the rupture is unknown.
271 However, we fix the vertical extent of the fault plane to 40 km, based on Sloan et al. (2011),
272 who suggest that the seismogenic layer is 40 km thick (see “Seismicity in the Northern Tien
273 Shan”). We did not use the scaling relationship of Leonard (2010) to evaluate the down-dip
274 width of the fault rupture because the thickness of the seismogenic layer limits the rupture
275 width, especially for large strike-slip earthquakes (e.g., Leonard, 2010). The focal mechanism
276 of the 1889 earthquake determined from the geomorphological study of Abdrakhmatov et al.
277 (2016) favors oblique-reverse faulting with a large left-lateral strike-slip component. In the
278 rupture model, we assume a dip of 70° (Table 1).
279 1911 Chon-Kemin earthquake
280 The 3 January 1911 Ms 8.0 Chon-Kemin earthquake caused less than 500 casualties,
281 considering its size (Bogdanovich et al., 1914; Delvaux et al., 2001). This is because the
282 region mainly affected by this event was the Alatau mountain ranges between Lake Issyk-Kul
283 and Almaty (e.g., Delvaux et al., 2001), which was sparsely populated at the beginning of the
284 20th century (e.g., Abdrakhmatov et al., 2002; Kulikova and Krüger, 2015). A field
285 expedition was sent to the epicentral area three months after the event to investigate the
286 damage from the earthquake (Bogdanovich et al., 1914). From their observations,
287 Bogdanovich et al. (1914) assign an MSK-64 intensity of X in the epicentral zone and VIII in
288 Almaty (Figure 3).
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289 The earthquake has been studied by various authors, resulting in a number of different
290 estimates of the epicenter and magnitude. Abdrakhmatov et al. (2002) report Ms 8.2.
291 Arrowsmith et al. (2016) infer Mw 7.9 from geological observations. Kulikova and Krüger
292 (2015) estimate the source parameters of the Chon-Kemin earthquake using digitized data
293 from 23 stations worldwide. They compute Mw 8.0 ± 0.1 that we use in the present work.
294 Bogdanovich et al. (1914) estimate that the epicenter was situated near the junction between
295 the Chon-Kemin, Chilik and Chon-Aksu valleys (Figure 2). Various historical catalogues
296 (e.g., Gutenberg and Richter, 1954; Kondorskaya and Shebalin, 1977) report different
297 epicentral locations whose differences are within 1° in longitude and <1° in latitude
298 (Kulikova and Krüger, 2015).
299 The Chon-Kemin earthquake produced a total of 145 to 195 km surface rupture on six
300 different segments of the Chon-Kemin-Chilik fault (e.g., Molnar and Ghose, 2000;
301 Abdrakhmatov et al., 2002; 2016; Kulikova and Krüger, 2015). Applying the scaling
302 relationships of Leonard (2010), we estimate that an earthquake of Mw 8.0 0.1 generates a
303 rupture of 202 28 km length. We fix the vertical extent of the Chon-Kemin fault plane to 40
304 km following the same reasoning as described for the Chilik earthquake. However, it is worth
305 noting that the hypocentral depth of the Chon-Kemin event is 20 3 km (Kulikova and
306 Krüger, 2015), and not 40 km as for the Chilik event. This means that although the two
307 earthquakes have the same vertical fault extent, the 1911 earthquake hypocenter is shallower.
308 This is supported by the trend of the isoseismals that are broader for the 1889 earthquake than
309 for the 1911 earthquake, indicating that the hypocenter may be deeper in the first case (Figure
310 3).
311 The Chon-Kemin event was identified as a reverse-faulting event by Molnar and Ghose
312 (2000) because the Chon-Kemin-Chilik fault system was initially interpreted to be a reverse
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313 fault system, but other studies have suggested varying amounts of strike-slip movement in
314 addition to the shortening. For example, Kulikova and Krüger (2015) determine a reverse
315 faulting focal mechanism with a minor strike-slip component for the Chon-Kemin
316 earthquake. A significant left-lateral strike-slip component was found by Delvaux et al.
317 (2001) on the Chon-Kemin-Chilik fault segments from field surveys and examination of
318 remote sensing imagery. Arrowsmith et al. (2016) find a complex multi-segmented fault
319 rupture consisting of south-dipping segments in the west and north-dipping segments in the
320 central and eastern part of the fault rupture, with a variable dip angle between 45° and 60°,
321 but with little evidence for strike-slip. In the rupture model of the 1911 earthquake, we use
322 the focal mechanism determined by Kulikova and Krüger (2015), i.e., 264 20° strike, 52
323 10° dip, and 98 10° rake (Table 1).
324 Although the studies of Arrowsmith et al. (2016) for the 1911 earthquake and Abdrakhmatov
325 et al. (2016) for the 1889 earthquake show evidence of multi-segmented ruptures with step-
326 overs, we use simplified rupture models (Figure 2). Using the mapped fault traces by
327 Arrowsmith et al. (2016) for the 1911 earthquake and Abdrakhmatov et al. (2016) for the
328 1889 earthquake would not increase the maximum ground shaking in the earthquake
329 scenarios within one standard deviation. The comparison between our rupture model and the
330 potential mapped segments for the 1889 Chilik earthquake shows some differences (Figures 2
331 and 3). In order to match the observed intensity distribution (Figure 3), our rupture model
332 was extended further NE than the surface ruptures mapped in Abdrakhmatov et al. (2016).
333 Although no surface ruptures have been reported, the NE extension does follow a Quaternary
334 fault scarp. The potential existence of a rupture on the NE scarps means that either the
335 surface effects have been eroded, or the rupture did not reach the earth's surface.
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336 SELECTION OF THE GROUND MOTION MODELS
337 The choice of an appropriate GMPE for predicting strong ground motion as a function of
338 magnitude and distance is one of the most difficult aspects of probabilistic and deterministic
339 seismic hazard studies. This is because the hazard estimates are strongly affected by the
340 selected GMPEs, both in terms of expected median prediction and aleatory uncertainty. It is
341 generally considered good practice in seismic hazard assessment to try to account for
342 epistemic uncertainty (i.e., the lack of knowledge about which model is best to adopt) by
343 combining different GMPEs in a weighted logic tree (e.g., Frankel et al., 2002; IAEA, 2010).
344 We adopt the GMPE exclusion criteria of Bommer et al. (2010) to select the most appropriate
345 GMPEs for our study. The first criterion excludes GMPEs that are not relevant to this
346 tectonic regime. The rest relate to the ground motion parameters, the magnitude-distance
347 range covered by the GMPE, and its functional form. By identifying a set of appropriate
348 GMPEs, we can take into account the epistemic uncertainties in the ground motion models.
349 The Northern Tien Shan is considered an active shallow continental regime (ASCR). We use
350 three GMPEs that have been developed for crustal earthquakes in other ASCRs using a
351 worldwide dataset of ground motion recordings. These models are Boore et al. (2014), Chiou
352 and Youngs (2014), and Akkar et al. (2014). The models of Boore et al. (2014) and Chiou
353 and Youngs (2014) are two GMPEs from the ‘Next Generation Attenuation - West2’ project
354 (Bozorgnia et al., 2014), whose GMPEs were derived from a large database of strong motion
355 recordings of earthquakes worldwide. The model of Akkar et al. (2014) is derived from the
356 ground motion recording dataset of Europe and the Middle East. The chosen GMPEs are
357 combined in a logic tree and the weights assigned are 0.35 for Boore et al. (2014), 0.35 for
358 Chiou and Youngs (2014), and 0.30 Akkar et al. (2014). Earlier versions of these GMPEs
359 have been compared with the unpublished dataset of the ground motion recordings of the
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360 Institute of Seismology in Almaty (N. Silacheva, personal comm., 2015) and found to have
361 an acceptable agreement with the local ground motion recordings within one standard
362 deviation. In this work, we selected the updated GMPE for Akkar and Bommer (2010), Boore
363 and Atkinson (2008), and Chiou and Youngs (2008) because one of the exclusion criteria of
364 Bommer et al. (2010) proposes to exclude the models that have been superseded by more
365 recent publications.
366 We also estimate the earthquake scenario in terms of intensity, using two intensity prediction
367 equations (IPE): Bindi et al. (2011), as modified by Ullah et al. (2015); and Allen et al.
368 (2012). The IPE of Bindi et al. (2011) was derived from 66 earthquakes in Central Asia with
369 magnitudes between Ms 4.6 and 8.3 and it is expressed in terms of the MSK-64 scale. The
370 primary distance metric is epicentral distance and therefore it does not account for the finite
371 extent of the fault rupture. The intensity model of Allen et al. (2012) is derived from a large
372 worldwide dataset of > 13,000 crustal earthquakes from Mw 5.0 to 7.9. This uses the closest
373 distance to rupture, therefore accounting for the finite dimensions of the fault rupture. We
374 assigned a weight of 0.5 to each IPE.
375 We assume a rock site condition and, therefore, the time-averaged shear wave velocity of the
376 top 30 m of material (vs30) is 760 m/s for the hazard calculations.
377 HAZARD CALCULATIONS
378 Using a DSHA approach and the rupture models described above, we generated 1000 ground
379 motion scenarios for each scenario earthquake to account for the aleatory uncertainties in the
380 GMPEs. Then, we calculated the mean and the standard deviation of the 1000 deterministic
381 ground motion values. We found that this number of iterations provides a clear convergence
382 towards stable average and standard deviation. In the simulations of the earthquake scenarios,
383 we did not account for the uncertainty in the parameters of the fault rupture models and
17
384 therefore the fault rupture model is the same for all scenarios. We perform a sensitivity
385 analysis to test the influence of the parameters of the fault rupture models on the
386 deterministic scenarios.
387 In this section, we show the ground motion scenarios for peak ground acceleration (PGA)
388 (Figure 4) and MSK-64 intensity (Figure 5) on a regular 0.05X0.05° grid for the 1887 Verny,
389 1889 Chilik, and 1911 Chon-Kemin earthquakes. The distributions of the 0.2 s and 1.0 s
390 spectral acceleration (SA) for the three scenario earthquakes are displayed in Appendix C.
391 The largest PGA values in Almaty are determined for the 1887 earthquake because the city is
392 situated in the surface projection of the fault plane and therefore the Joyner-Boore distance
393 (Rjb) is 0.0 km. The distance between Almaty and the epicenter of the Verny earthquake is
394 21 km, whereas the distance between Almaty and the epicenter of the Chilik and Chon-
395 Kemin earthquakes was 134 and 63 km, respectively (Table 2).
396 The distribution of the standard deviation for the MSK-64 intensity is uniform within the grid
397 area and is up to MSK I. The intensities in the epicentral area and in Almaty (Figure 5) agree
398 well with the isoseismals in Figure 3. For the 1911 earthquake, we estimated an intensity of
399 IX ± I in the epicentral area and VIII ± I in Almaty; whereas, the isoseismals of Bogdanovich
400 et al. (1914) report an intensity of X in the epicentral area and VIII in Almaty. For the 1889
401 earthquake, Mushketov (1891) estimate an intensity of IX-X around the Chilik River and VII-
402 VIII in Almaty; and our calculations show an intensity of IX ± I around the epicenter and
403 VIII ± I in Almaty.
404 Table 3 shows the mean values of PGA, 0.2 s SA, 1.0 s SA, and MSK-64 intensity for the
405 three scenario earthquakes for a central location in Almaty situated at 43.28°N and 76.90°E.
406 The PGA value for the 1911 Chon-Kemin event is 0.23 ± 0.08 g, the 0.2 s SA is 0.48 ± 0.17
407 g, the 1.0 s SA is 0.17 ± 0.07 g, and the MSK-64 intensity is VIII ± I. Clearly, these estimates
18
408 are associated with large uncertainties and the standard deviations are relatively high, due to
409 the large uncertainty in the GMPEs. The values of the MSK-64 intensity for the three
410 earthquakes are identical because the intensity is rounded to the nearest integer.
411 To check which input parameters have the strongest influence on the earthquake scenarios,
412 we made a sensitivity analysis at the site in Almaty, using the 1911 Chon-Kemin earthquake.
413 We performed seven tests for the sensitivity analysis. In each test, we changed one parameter
414 from the rupture model in Table 1, referred as to reference model, and kept the other
415 parameters constant. The parameters tested include moment magnitude, fault dimensions, site
416 condition, GMPEs, and fault plane orientation. For each test, we generated 1000 ground
417 motion scenarios and computed their mean and standard deviation (Table 4). Most of the tests
418 produce similar results within one standard deviation. When we use only one GMPE (Tests 2,
419 3, and 4), the deterministic ground motion values are relatively consistent with each other.
420 The dip angle in the fault rupture model of the scenario earthquake has a strong influence on
421 the deterministic scenarios, as shown by the deterministic values for Tests 5 and 6. It is
422 worth noting that Test 7 considers a multi-segmented fault rupture. It consists of four
423 segments: from west to east, a 45° south-dipping segment, two 60° north-dipping segments,
424 and a 45° north-dipping segment. The ground motion parameters obtained for Test 7 are
425 smaller than the values computed for the reference model, but still within the uncertainty.
426 This is because the fault segment closer to the site has a larger dip angle (dip=60°) in Test 7
427 than in the reference model (dip=52°) and therefore the surface projection of the fault plane is
428 further from Almaty than in the reference model. For this reason, the ground shaking felt in
429 Almaty is lower.
19
430 Probabilistic approach
431 In this section, we take the results from the Hazard Calculations section for DSHA and
432 determine the exceedance frequencies for the ground motions computed for the scenario
433 earthquakes, using PSHA. A probabilistic approach to seismic hazard assessment combines
434 seismological, geological and geophysical data to produce a probabilistic description of the
435 distribution of future shaking that may occur at a site (e.g., Reiter, 1990; McGuire, 2004).
436 We perform a PSHA using the Monte Carlo-based simulations developed by Musson (2000).
437 The site for which the hazard is calculated is the same as in the scenario modeling. The
438 source zone model used in the computation is based on the earthquake catalogue (see
439 Appendix A), tectonics, geology, and kinematic constraints in the Northern Tien Shan. Using
440 this model and Monte Carlo simulations, we generate 100,000 synthetic earthquake
441 catalogues, each 100 years long. This gives a total of 10,000,000 years of simulated data that
442 is sufficient to resolve the hazard accurately for long return periods (Musson, 2000). Each
443 simulated catalogue represents a version of what could occur based on observed seismicity.
444 The ground motion is computed for each earthquake in the simulated catalogues. Then, by
445 sorting the ground motion results in order of decreasing severity, it is possible to identify
446 ground motions associated with different frequencies of exceedance (Musson, 2000).
447 The second stage of the probabilistic hazard analysis involves disaggregating the hazard
448 results in terms of magnitude, distance, and epsilon (, the number of standard deviations
449 above or below the median prediction). We do this in order to determine whether earthquakes
450 similar to the scenario earthquakes considered in the DSHA dominate the ground motion
451 hazard at the site. In our approach, this simply means searching the synthetic catalogues
20
452 derived from the source model for ground motions that are greater than or equal to the
453 deterministic ground motion values within the standard deviation (Musson, 2000).
454 SEISMIC SOURCE ZONE MODEL
455 The study area is divided into a series of seismic sources. Seismic activity in each seismic
456 source is considered to be uniform, and earthquakes have an equal chance of occurring at any
457 point in the zone.
458 The source model for this work includes the Northern Tien Shan and the South Kazakh
459 Platform because other tectonic structures, such as the Tarim Basin, are at distances more
460 than 400 km from Almaty to be considered relevant to the hazard at the site. The model is
461 based on seismological, tectonic and geological analysis of the region and consists of 16
462 zones and two faults (Figure 6). All zones are terminated arbitrarily at the edge of a 400-km
463 radius circle centered in Almaty. We grouped the source zones into larger units where similar
464 tectonic constraints can be applied. The tectonic units are the Western Tien Shan, which is
465 separated by the Northern Tien Shan by the Talas-Ferghana fault; the upper Northern Tien
466 Shan and the lower Northern Tien Shan; the Tien Shan Foreland; the Eastern Tien Shan; and
467 the Kazakh Platform. The Northern Tien Shan is divided into two tectonic groups because the
468 upper Northern Tien Shan has higher seismic activity than the lower Northern Tien Shan in
469 terms of magnitude and frequency.
470 The faults included in the source model are the Chon-Kemin-Chilik fault system (fault source
471 CKCF) and the Talas-Ferghana fault (fault source TFF). We did not include any other fault
472 systems (e.g., Fore-Terskey fault to the south of Lake Issyl-Kul, and the Atushi-Keping fault
473 between the Tien Shan and the Tarim Basin) because the information on their geometry, the
474 rupture behavior, and the maximum magnitude they are capable of generating is incomplete
21
475 or unknown. Furthermore, although the overall deformation rate of the Tien Shan mountain
476 belt is known, it is difficult to partition it among the active tectonic structures in the region
477 and thus estimate the activity rate of the individual faults. This is because earthquakes are
478 distributed over fault zones of hundreds of kilometers in width, on complex networks of
479 many, highly segmented faults, each accumulating slip at a few tenths to a few millimeters
480 per year (England and Jackson, 2011; Liu and Stein, 2016). In the approach we used for
481 PSHA, each simulated earthquake in the source zones is located at the center of a finite fault
482 rupture. The size of the rupture is computed using the magnitude of the synthetic event, the
483 magnitude-length scaling relationship of Leonard (2010), the fault orientation, and the
484 faulting style. Using this procedure, faults are taken into account in general. One of the
485 advantages of this approach is to reduce the likelihood of neglecting important but unknown
486 tectonic structures.
487 We modeled the Chon-Kemin-Chilik fault system as an individual fault in the source model
488 because the 1889 and 1911 earthquakes were generated along it. Its slip rate was estimated
489 using both the seismic moment tensors of the major earthquakes in the 20th century (Molnar
490 and Deng, 1984; Molnar and Ghose, 2000) and GPS data (e.g., Abdrakhmatov et al., 1996;
491 Zubovich et al., 2010). Furthermore, its geometry is known from the recent geomorphological
492 studies (Delvaux et al., 2001; Arrowsmith et al., 2016; Abdrakhmatov et al., 2016). Since no
493 earthquakes of Mw 7.0 have occurred along TFF in the last 200 years, it is not
494 straightforward to quantify the maximum magnitude it can generate. However, we decided to
495 model it as an individual fault in the source model because it is a major tectonic structure in
496 the Northern Tien Shan. Zubovich et al. (2010) estimate an annual slip rate of less than 2
497 mm/yr based on geodetic data from a dense, regional GPS network (see “Recurrence
498 statistics” for further discussion).
22
499 Recurrence statistics
500 We applied the truncated Gutenberg-Richter law (Gutenberg and Richter, 1954) to the
501 individual zones of the source model using the penalized maximum likelihood procedure
502 (Johnston et al., 1994), the earthquake catalogue and its completeness analysis in Appendix
503 A, and the best regional estimate b = 0.96 as a weighted prior for each of the zones (see
504 Appendix B). Below we describe in detail the recurrence statistics for zone NISK (the North
505 Issyk-Kul region) because it contains the three scenario earthquakes used in the DSHA
506 described earlier. The results of the recurrence statistics for all zones of the source model are
507 displayed in Appendix B.
508 The best-fit values of NISK are N (≥ Mw 4.5) = 0.90 ± 0.13 and b = 0.826 ± 0.078 (Figure 7).
509 The error-bars in Figure 7 are inversely proportional to the number of observations above a
510 certain magnitude in the catalogue and describe the uncertainties in the long-term recurrence
511 for that magnitude value. The recurrence parameters suggest an earthquake somewhere in
512 NISK with a magnitude of Mw 8.0 or above every 864 ± 438 yr. The observed rate for
513 earthquakes of Mw ≥ 7.0 seldom matches the predicted seismicity by the Gutenberg-Richter
514 law because a 100-year sample of seismicity may contain by chance an earthquake with a
515 recurrence of 1000 years. This is especially true for intraplate areas, such as the Tien Shan,
516 where the 138-yr long earthquake catalogue is shorter than the potential recurrence interval of
517 the large earthquakes (e.g., Abdrakhmatov et al., 2016; Landgraf et al., 2016a). The
518 occurrence of two earthquakes with magnitudes higher than Mw 8.0 in 20 years (i.e., the
519 Chilik earthquake in 1889 and the Chon-Kemin earthquake in 1911) can be explained by the
520 fact that large intraplate earthquakes occur on faults that remain dormant for a long time and
521 become active for a short period interacting with neighboring tectonic structures (e.g.,
522 Landgraf et al., 2016b). Therefore, the recurrence interval of these seismic events is less
523 regular than the recurrence interval of earthquakes at plate boundaries (e.g., Liu and Stein,
23
524 2016). To model the deficit of predicted seismicity for Mw ≥ 7.0 in Figure 7, we treat the
525 seismicity of NISK as two populations of earthquakes predicted by the truncated Gutenberg-
526 Richter law: a population of “normal” activity represented by the levels of seismicity in the
527 range Mw 4.5 to 6.9, and a second population consisting of earthquakes in the range Mw 7.0
528 to 8.5. This procedure avoids underestimating the seismicity for earthquakes of Mw ≥ 7.0
529 (Figure 7). In PSHA this can be handled by modeling the source zone twice with the same
530 geometry for each earthquake population (Musson and Sargeant, 2007; Musson, 2015). The
531 best-fit values for the population of earthquakes in the range Mw 7.0 to 8.5 are N (≥ Mw 4.5)
532 = 2.58 ± 2.24 and b = 0.793 ± 0.098. This suggests an earthquake of Mw 8.0 and above
533 somewhere in NISK every 231 ± 262 yr.
534 We estimated the activity rate of the fault sources from their annual slip rate, using the
535 relationship of Youngs and Coppersmith (1985) (see Appendix B). For the fault source
536 CKCF, we used an annual slip rate between 0.1 and 3.0 mm/yr (Thompson et al., 2002) and b
537 = 0.826 ± 0.078 of NISK). We computed an activity rate of N (≥ Mw 4.5) = 0.14 ± 0.10 (see
538 Appendix B for further information). This is equivalent to an earthquake of Mw 8.0 and
539 greater every 5557 ± 2148 yr. For the fault source TFF, we used a range between 0.1 and 1.5
540 mm/yr for the annual slip rate (Zubovich et al., 2010) and the b-value of the entire study area,
541 b = 0.959 ± 0.020 that is similar to the b-value of the neighboring source zones. The activity
542 rate for TFF is N (≥ Mw 4.5) = 0.135 ± 0.092 suggesting an earthquake of Mw ≥ 8.0 every
543 16168 ± 16610 yr.
544 The recurrence statistics described in this section highlights the limitations in estimating
545 reliable earthquake rates in regions where the length of the seismic record is shorter than the
546 average recurrence interval of the largest earthquakes (here 231 ± 262 yr. for an earthquake
547 of Mw > 8.0). This explains also why the standard deviation of the recurrence intervals is
24
548 very large, up to the same order of the value itself (i.e., 5557 ± 2148 yr. for CKCF and 16168
549 ± 16610 yr. for TFF).
550 Maximum magnitudes
551 Maximum magnitude (Mmax) is the largest possible earthquake that is considered in the
552 hazard analysis. This is often highly uncertain, although, in a broad sense, the maximum
553 magnitude can be constrained by fault length because any large earthquake requires a
554 sufficiently large structure to host it. However, this approach is challenging in low strain
555 continental interiors, including the Tien Shan, for the following reasons. First, faults in
556 continental interiors are spread over a large region and are usually extensively segmented
557 (e.g., England and Jackson, 2011). Some of these fault segments are unknown or poorly
558 constrained before an earthquake occurs along them (e.g., Landgraf et al., 2016a; Grützner et
559 al., 2017). Second, due to the low strain accumulation on the faults, the recurrence interval of
560 large earthquakes is of the order of thousands of years. Therefore, the instrumental and
561 historical records of seismicity probably do not include the largest possible earthquakes (e.g.,
562 Abdrakhmatov et al., 2016; Landgraf et al., 2016a). This is especially true for the Northern
563 Tien Shan where the earthquake catalogue is 138 years long. For this reason, a realistic
564 assessment of the uncertainty in Mmax should allow for the possibility of significantly larger
565 events in the future. The distribution of Mmax for the source zones and the fault sources of
566 the source model is assigned on the basis of the tectonic groups and is given in Table 5.
567 Ullah et al. (2015) assign a maximum magnitude of Mw 8.3 to their Northern Tien Shan
568 zone, which includes our zone NISK, and therefore contains the Mw 8.0 Chon-Kemin
569 earthquake and the Mw 8.2 Chilik earthquake. A single value for Mmax is inappropriate for
570 NISK considering the short length of the earthquake catalogue in the Tien Shan. We used
25
571 three values of Mmax for NISK (i.e., Mw 8.2, 8.3 and 8.5) with a weight of 0.40, 0.40, and
572 0.20, respectively (Table 5).
573 HAZARD CALCULATIONS
574 Using a Monte Carlo-based PSHA and the source model described above, we simulated
575 100,000 earthquake catalogues, each 100 years long. The ground motion at the site for each
576 simulation was estimated using the logic tree previously discussed. We did not apply any
577 ground motion truncation for the GMPEs in the hazard calculations for PSHA.
578 The results are expressed as hazard curves that show the annual frequency of exceedance as a
579 function of PGA, 0.2 s, and 1.0 s SA and MSK-64 intensity for the site in Almaty situated at
580 43.28°N and 76.90°E (Figure 8). The return periods (i.e., the inverse of the annual frequency
581 of exceedance) corresponding to the ground motion values simulated for DSHA in Table 3
582 are obtained by interpolation from the hazard curves in Figure 8 and shown in Table 6. The
583 return periods are associated with large standard deviation because the large variability of the
584 ground motion values propagates into larger uncertainties in the return period. For the MSK-
585 64 intensity, the standard deviation of the return period is larger than the return period itself.
586 For a return period of 10,000 years, the ground motion values are PGA=1.34 g, 0.2 s
587 SA=2.06 g, 1.0 s SA=1.13 g and MSK-64 =X. In Figure 8, we also show the comparison
588 between the hazard curves estimated for the source model with 16 area zones and two fault
589 sources and the source model with 16 area zones only. This displays clearly that we did not
590 double-count the earthquakes, and therefore over-predict the seismicity in the vicinity of the
591 Chon-Kemin-Chilik fault system, although we estimated the activity rate of area source zones
592 and fault sources independently. It is not surprising that the fault sources, especially CKCF,
593 which is less than 100 km from the site, do not contribute much to the hazard in Almaty. This
26
594 is because the faults closer to Almaty are more hazardous than CKCF, although they are
595 poorly understood and thus their threat has not been recognized (see Discussion).
596 It is useful to compare the hazard curves of this study with previous works. Most hazard
597 studies in Central Asia use the intensity as primary ground motion parameter, which is then
598 often converted into PGA (e.g., Ulomov et al., 1999). We compare our hazard curve for the
599 MSK-64 intensity with two studies developed for two worldwide projects: Ulomov et al.
600 (1999) and Ullah et al. (2015). In the Global Seismic Hazard Assessment Program (Giardini,
601 1999), Ulomov et al. (1999) performed PSHA for Northern Eurasia (30°-90°N and 20°-
602 170°E) and their maps show that the MSK-64 intensity is around IX for 10% probability of
603 exceedance in 50 years in the Northern Tien Shan (Table 7). For the “Earthquake Model for
604 Central Asia” project (Parolai et al., 2015), Ullah et al. (2015) performed PSHA for the whole
605 of Central Asia (i.e., 34°-56°N and 47.5°- 90°E), using the catalogue of Mikhailova et al.
606 (2015) and the GMPE of Bindi et al. (2011). Their maps show an MSK-64 intensity between
607 VII and VIII for a 475-year return period for Almaty (Table 7). We determined an MSK-64
608 intensity between VIII and IX for a return period of 475 (Table 7). We compare our hazard
609 curve for PGA with the work of Silacheva et al. (2017). They performed a Monte Carlo-
610 based PSHA for Kazakhstan and Almaty using a local catalogue and the GMPEs of Akkar
611 and Bommer (2010), Boore and Atkinson (2008), Campbell and Bozorgnia (2008), Chiou
612 and Youngs (2008), and Zhao et al. (2006). Their maps show that the PGA in Almaty is
613 between 0.36 and 0.44 g for a 475 year return period, whereas we estimated a PGA of 0.44 g
614 in Almaty for the same return period (Table 7). The comparison with Ulomov et al. (1999),
615 Ullah et al. (2015), and Silacheva et al. (2017) is reasonable considering that the four studies
616 are based on different earthquake catalogues, different source models, and different ground
617 motion models. It is worth underlining that a seismic hazard map is intended to be indicative
618 only and will not be expected to give exactly the same results as a site-specific study.
27
619 In the second stage of the hazard analysis, we disaggregated the ground motion hazard results
620 for PGA, 0.2 s SA and 1.0s SA in terms of magnitude, Joyner-Boore distance Rjb, and the
621 originating source zone to determine which earthquake(s) is most likely to produce the hazard
622 values in Table 6. We performed the disaggregation analysis for the return periods computed
623 for the three scenario earthquakes, but we only show the results for the 1911 and 1887
624 earthquakes because they seem to influence more the hazard at Almaty. Disaggregating by
625 zone, we see that the largest influence (between 80 and 97%) on the hazard comes from
626 NISK. This is expected because NISK is next to the site and has high levels of seismicity.
627 The overall hazard is dominated by earthquakes at distances less than 30 km from Almaty
628 within the zone NISK because the seismicity is uniformly distributed within the zone and
629 therefore earthquakes have equal chance to occur anywhere in the zone. The disaggregation
630 plots in terms of magnitude, distance and are shown in Figure 9 for the PGA and in
631 Appendix C for 0.2 s SA, 1.0 s SA, and MSK-64 intensity. The disaggregation plot in Figure
632 9a corresponds to return periods of 139 ± 81 yr and shows that the hazard is dominated by
633 earthquakes of Mw 4.8 to 5.0 at distances of Rjb < 10 km. As the return period increases,
634 the dominant contribution is from earthquakes of Mw 7.0 to 7.2 at distances of less than 10
635 km, but earthquakes of Mw 7.2 to 7.8 at distances between 10 and 30 km contribute to the
636 overall hazard (Figure 9b). Figure 9 clearly suggests that future earthquakes similar to the
637 1887 Verny earthquake strongly influence the overall seismic hazard of Almaty. However, it
638 is worth noting that the histograms in Figure 9 are very broad because the values for PGA,
639 0.2 s SA and 1.0 s SA and the corresponding return periods used in the disaggregation
640 analysis are based on the ground motion values, together with their standard deviation,
641 computed by the DSHA.
28
642 The disaggregation analysis for a return period of 10,000 years indicates that the earthquakes
643 that dominate the hazard are given by earthquakes at distances less than 10 km from Almaty
644 with magnitudes of Mw 7.6 to 7.8 for PGA.
645 Discussion
646 The aim of this paper was to gain new insights into the earthquake hazard of the Northern
647 Tien Shan by using the best available science and combining outcomes from the deterministic
648 and probabilistic approaches. This approach helps overcome our limited understanding of
649 most faults in terms of source geometry, rupture behavior, slip rate, and maximum magnitude
650 and the short length of the earthquake catalogue available in the region.
651 The deterministic approach for seismic hazard analysis can be considered a special case of
652 PSHA. Therefore, the scenario earthquakes used in DSHA are included in PSHA because the
653 latter considers all possible earthquake scenarios and ground motion levels that occur on the
654 seismic sources affecting the site. The disaggregation analysis is an excellent tool to integrate
655 the results from the two approaches. First, we applied DSHA for the largest earthquakes
656 recorded in the Northern Tien Shan. Then, we used PSHA to determine the chance of
657 exceeding the deterministic ground motion values (Figure 8). The disaggregation plots in
658 Figure 9 and Appendix C tell us whether the scenario earthquakes dominate the overall
659 ground motion hazard of Almaty. They show that the earthquake(s) similar to the 1887 Verny
660 Mw 7.3 earthquake dominate the hazard for the city. However, these plots are associated with
661 large uncertainties due to the large uncertainties in the input parameters propagating into the
662 deterministic ground motion values (Table 3) and the corresponding return periods (Table 6).
29
663 Generally speaking, the uncertainties in the hazard results reflect the many limitations of our
664 current knowledge on the occurrence of future earthquakes in the Tien Shan. This is because
665 the hazard results are estimated using incomplete, and sometimes potentially misinterpreted
666 data (e.g., earthquake catalogues and fault mapping data) and models (e.g., geodynamic and
667 tectonic models) that are based on an instrumental earthquake history of a few of hundreds of
668 years in the best case, compared to the geological history that is up to millions of years (e.g.,
669 Stein et al., 2012). This issue is particularly important in low strain continental environments
670 where the tectonic loading rates are low. For this reason, we cannot say whether the largest
671 earthquakes in the seismic catalogue are also the controlling earthquakes for Almaty. The
672 impact of a short earthquake catalogue on the seismic hazard analysis is illustrated clearly in
673 Subsection “Recurrence statistics”. In this section, we have shown that the 138 years length
674 of the seismic record is much shorter than the average recurrence interval of the largest
675 earthquakes (from several hundred to thousand years for an earthquake of Mw ≥ 8.0). If we
676 consider the recurrence intervals of individual faults, they are even longer, as shown by our
677 recurrence statistics for CKCF and TFF and confirmed by recent paleoseismological studies
678 (e.g., Abdrakhmatov et al., 2016; Landgraf et al., 2016a). For example, Abdrakhmatov et al.
679 (2016) find evidence that the fresh scarp on the Saty fault segment associated with the 1889
680 Chilik earthquake was the only surface-rupturing event on this fault in the last 5,000 years.
681 Furthermore, the concept of regular recurrence interval may not be applicable to intraplate
682 continental regions where faults are widespread, highly segmented and often poorly mapped,
683 and the tectonic loading of the faults is slow and variable due to the interaction between faults
684 (e.g., Liu and Stein, 2016).
685 In this context, it is understandable why the source zone NISK controls the hazard and the
686 fault source CKCF does not contribute much to the overall hazard in Almaty. In NISK, faults
687 are taken into account in general to reduce the likelihood of neglecting important but
30
688 unknown tectonic structures and therefore the seismicity rate of NISK is higher than the
689 seismicity rate of CKCF. The results of the PSHA show clearly that the threat to the city
690 comes from nearby faults that are little understood in terms of their source geometry, rupture
691 behavior, slip rate and maximum expected earthquake magnitude. Although these faults close
692 to Almaty are not long enough to generate earthquakes of Mw ≥ 7.3, they would pose a
693 significant hazard due to their proximity to Almaty (Grützner et al., 2017). For example,
694 Grützner et al. (2017) report that the irrigation canal that diverts water from the River Chilik
695 to the metropolitan area of the city crosses the faults of the Zailisky Alatau Range Front
696 several times.
697 Integrating the outcomes from DSHA and PSHA may be also a powerful tool for community-
698 based risk reduction activity and earthquake risk management. The development of simple
699 deterministic scenarios for potential future earthquakes, together with their frequency of
700 occurrence, would contribute to translate the effects of earthquakes into real-life impact
701 (ODI, 2016). This is especially important in densely populated areas in continental low strain
702 rate environments, such as Almaty, where the largest recorded earthquakes occurred in
703 historical or prehistorical time and therefore collective memory of those disasters in the
704 population and society reduces with time.
705 Conclusions
706 This work has highlighted the importance of integrating the outcomes from PSHA and DSHA
707 to reduce, and possibly overcome, the limited amount of seismological, geological and
708 geodetic data in the Tien Shan mountain belt.
31
709 The main finding of the paper is that the major contribution to the seismic hazard of Almaty
710 comes from earthquakes of Mw 7.0 to 7.5 with Rjb < 10 km to the city at return periods
711 smaller than 1000 years. Future earthquakes similar to the 1887 Mw 7.3 Verny earthquake
712 strongly influence the overall ground motion hazard of Almaty. It is important to highlight
713 that these estimates are associated with large uncertainties due to the large uncertainties in the
714 input parameters. Furthermore, the Verny earthquake is the least well characterized of the
715 three destructive historical earthquakes recorded in the Northern Tien Shan between the end
716 of the 19th and the beginning of the 20th century because its rupture process is unknown,
717 making the rupture model in the deterministic scenario hypothetical.
718 Future research should focus on reducing the uncertainties in the rupture model by mapping
719 the faults in the region, especially around Almaty, searching for evidence of the occurrence of
720 paleo-earthquakes on them and characterizing the source of the Verny earthquake. The
721 assessment of the seismic hazard for Almaty should also include the effects of local site
722 geology that may result in de-amplifying or amplifying the ground motions. These may have
723 a strong impact in regions where urban areas are situated in valleys and depressions, such as
724 Almaty (Pilz et al., 2015). Any new information should then be used to update the assessment
725 of the seismic hazard for Almaty.
726 Data and Resources
727 The online database of the International Seismological Centre is at http://www.isc.ac.uk (last
728 accessed November 2016). The earthquake catalogue for the “Earthquake Model for Central
729 Asia” (EMCA) project is at http://www.emca-gem.org/general/tasks/seismic-hazard-and-
730 microzonation/ (last accessed November 2016). All the other data used in this paper came
731 from published sources listed in the references. The plots were made using the Generic
32
732 Mapping Tools version 4.5.2 (www.soest.hawaii.edu/gmt; last accessed June 2010; Wessel et
733 al., 2013).
734 Acknowledgments
735 This work was funded by the Natural Environmental Research Council under the grant
736 Earthquake without Frontiers EwF_NE/J02001X/1_1. We are grateful to Richard Luckett,
737 Roger Musson, Margarita Segou, and Natalya Silacheva whose insightful comments were
738 helpful in improving the manuscript. We thank the EMCA project for making their
739 earthquake catalogue freely available. We also thank the reviewers and the Editor Ivan Wong
740 for their constructive comments that contributed significantly to improve the manuscript. This
741 work is published with the permission of the Executive Director of the British Geological
742 Survey.
743 Appendix A
744 The earthquake catalogue of this work contains data from three sources: the International
745 Seismological Centre Bulletin (ISC); the World Seismicity Database (WSD) of the British
746 Geological Survey (Henni et al., 1998); and the earthquake catalogue for the “Earthquake
747 Model for Central Asia” (EMCA) project (Mikhailova et al., 2015). The ISC Bulletin is
748 generally regarded as a definitive record of the Earth's instrumental seismicity and contains
749 data from 1900 to the present. The WSD contains parametric data for earthquakes from 2500
750 BC onwards and has been compiled over a period of thirty years from various catalogues
751 (Henni et al., 1998). The earthquake catalogue for the EMCA project includes information
752 for 33620 earthquakes that occurred in Central Asia in the period from 2000 BC to 2009 AD,
33
753 although most of the entries (i.e., 33378) are for earthquakes that occurred after 1900
754 (Mikhailova et al., 2015).
755 It is standard practice in seismic hazard assessment to use moment magnitude (Mw; Bolt and
756 Abrahamson, 2003). However, these three catalogues contain magnitude estimates in
757 different magnitude scales. Therefore, we converted the magnitude estimates to Mw using the
758 equations of Scordilis (2006), which are based on a large global dataset of earthquakes and
759 includes data from various tectonic regimes. This is one example that illustrates the
760 conversion process we used. The ISC catalogue contains a number of different magnitude
761 estimates for each earthquake determined by different agencies that reported the event (e.g.,
762 surface-wave magnitude Ms, body-wave magnitude mb, Mw). We used the hierarchy in
763 Table A.1 to select one magnitude from the available estimates. The list of agencies is the
764 result of a careful application of a decision-making process, together with the reliability of
765 the agency in the magnitude determination. Similarly, we apply a hierarchical approach to the
766 WSD data because they also contain different magnitude estimates determined by different
767 agencies.
768 The EMCA catalogue merges many sources and magnitude scales. The magnitude of this
769 catalogue is the surface wave magnitude MLH that is widely used in former Soviet countries
770 and based on the Moscow-Prague formula (Karnik, 1962; Bormann et al., 2013). The original
771 magnitude of the earthquakes in the EMCA catalogue is not indicated (Mikhailova et al.,
772 2015; Ullah et al., 2015). We used only events with magnitudes MLH ≥ 5.4 from the EMCA
773 catalogue if they were not included in the ISC and WSD database. The reason for this is that
774 the uncertainty in the magnitude conversion MoriginalMLHMw becomes large for MLH <
775 5.4 and may produce an overestimation in the final Mw value (Scordilis, 2006).
776 DECLUSTERING AND COMPLETENESS
34
777 To decluster the earthquake catalogue and therefore to remove the dependent events
778 (aftershocks and foreshocks) from the catalogue, we use the approach of Musson (2000),
779 which is a modified version of the moving window method of Reasenberg (1985). The
780 procedure for declustering the catalogue shows that the most appropriate window in time and
781 space has a length of 30 days and 30 km, respectively. If an earthquake is identified as a
782 mainshock, all events within 30 km of the epicenter and 30 days before and after that event
783 are considered to be dependent events.
784 To assess the completeness of the catalogue as a function of time, we use the statistical
785 approach of Stepp (1972), modified by Musson (2000). This is based on estimates of the
786 mean seismicity rate of earthquakes for different magnitude ranges and time windows. Our
787 analysis suggests that the catalogue is complete for magnitudes > Mw 4.5since the second
788 half of the twentieth century (Table A.2). This estimate corresponds to the deployment of the
789 World-Wide Standardized Seismographic Network in the early 1960s. The historical record
790 of seismicity in the Tien Shan is relatively short and, even for events of Mw 7, is probably
791 complete only since the 1880s when the construction of Russian fortresses started in the
792 region (Molnar and Deng, 1984; Korjenkov et al., 2003). The magnitude thresholds in Table
793 A.2 agree with the completeness analysis of the EMCA earthquake catalogue for Mw 5.5,
794 but our completeness analysis is more conservative for smaller magnitudes.
795 Appendix B
796 RECURRENCE STATISTICS
797 To determine the frequency of occurrence for the seismicity in the Northern Tien Shan, we
798 use the Gutenberg-Richter recurrence law, i.e., the relationship between the magnitude and
799 number of earthquakes in a given region and time period (Gutenberg and Richter, 1954):
35
800 Log N = a - b M (1B)
801 where N is the number of earthquakes above a given magnitude M. The activity rate, a,
802 describes the total number of earthquakes per year above M 0.0 in the study area, and the b-
803 value gives the proportion of large events to small ones. In general, b-values tend to be close
804 to one (e.g., Reiter, 1990).
805 We determine the recurrence parameters a and b for the earthquake catalogue using a
806 penalized maximum likelihood procedure (Johnston et al., 1994). This procedure uses the
807 truncated Gutenberg-Richter recurrence law where the earthquake magnitudes are bounded
808 by lower and upper bounds:
809 𝑁 𝑀 10 (2B)
810 where β=bxln(10), Mmin = minimum magnitude and Mmax = maximum magnitude. This
811 method considers different time windows of the catalogue for the magnitude completeness
812 thresholds, the correlation between a and b, and a weighted prior constraining the b-value
813 when there are few earthquakes in the source zone for a realistic estimate. The recurrence
814 parameters are computed in terms of pdfs and therefore it is straightforward to estimate their
815 uncertainties. We used a correction factor in the activity rate calculations based on the
816 standard error of individual earthquake magnitudes, as proposed by Rhoades and Dowrick
817 (2000). This is because ignoring uncertainty in the magnitude values results in an
818 overestimation of the activity rate (e.g., Rhoades and Dowrick, 2000; Castellaro et al., 2006).
819 We assume that all magnitude values in the catalogue have an uncertainty of ± 0.2 that
820 corresponds to the standard deviation in the magnitude conversion equations of Scordilis
821 (2006). This uncertainty may be too small for historical events in the Tien Shan, as suggested
822 by Zöller at al. (2017) who use = 0.5 for historical events, = 0.25 for early
36
823 instrumental events and = 0.1 for recent instrumentally recorded events in Central Asia.
824 However, we decided not to use these values since it is not clear from how these have been
825 estimated. Musson (2012) shows that the magnitude uncertainty should be used carefully to
826 avoid over- or under-estimation of the activity rate in the area under investigation, especially
827 when the earthquake catalogue merges many sources and contains more than one original
828 magnitude scale, as the case of the catalogue in this study.
829 Equation (2B) was applied to all the seismicity in the study area, using the maximum
830 likelihood method and the completeness thresholds in Table A.2. The best- fit values for
831 equation (2B) are N (Mw ≥ 4.5) = 28.19 ± 0.72 and b = 0.959 ± 0.020 (Figure B.1). The
832 predicted seismicity from the Gutenberg-Richter relationship fits the observed rates of
833 seismicity well. The error-bars in Figure B.1 are inversely proportional to the number of
834 observations above a certain magnitude in the catalogue and, therefore, describe the
835 uncertainties in the long-term recurrence for that magnitude value.
836 Mikhailova et al. (2015) have found a b-value of 0.805 for the whole of Central Asia (i.e.,
837 34°-56°N, and 47.5°- 90°E), which is smaller than the estimated b-value in this work. The
838 difference between the two values may be explained by three reasons. First, we applied
839 equation (2B) to a smaller region (i.e., 39°-46°N and 70°-81°E) than the whole of Central
840 Asia. Second, the earthquakes in our catalogue are expressed in Mw, and not in MLH as in the
841 earthquake catalogue of Mikhailova et al. (2015). Therefore, different magnitude conversion
842 equations were applied to homogenize the two catalogues. Third, the completeness analysis
843 of the two catalogues is different for Mw < 5.5 (see Appendix A).
844 The best regional estimate for b of 0.96 was used as a weighted prior for the individual zones
845 of the source model (see the “Recurrence Statistics” Subsection). Using equation (2B) and the
37
846 completeness values in Table A.2 we determined the recurrence parameters a and b for the
847 individual source zones (Figure B.2 and Table B.1).
848 We estimated the activity rate of the fault sources from their annual slip rate, using the
849 relationship of Youngs and Coppersmith (1985):
µ – – 850 𝑁 𝑀 – (3B)
851 where N is the number of earthquakes above a given magnitude M, S is the annual slip rate,
max 852 Mmax is the maximum magnitude, Mo is the seismic moment for Mmax, A=LxW is the
853 area of a W-wide and L-long fault, µ=3.3x1010 N/m2 is the shear modulus for crustal faults
854 (e.g., Stein and Wysession, 2003), d is one of the two magnitude-scaling coefficients in the
855 relationship of Kanamori (1977) and Hanks and Kanamori (1979), b is the b-value and
856 β=b*ln(10). The slip rate of the fault sources is described by a uniform probability
857 distribution within its range (i.e., 0.1 and 3.0 mm/yr for CKCF, and 0.1 and 1.5 mm/yr for
858 TFF). Therefore, also, the activity rate of the two fault sources from equation (3B) is
859 described by a uniform pdf that is parametrized into four values, each associated with a
860 weight of 0.25 and b = 0.826 for CKCF and b = 0.959 for TFF (Table B.2).
861 OTHER PARAMETERS OF THE SOURCE MODEL
862 The depth distribution of the earthquakes in the Tien Shan and in the South Kazakh Platform
863 is characterized by a distribution down to 40 km (see Subsection “Seismicity in the Northern
864 Tien Shan”). The depth distribution of the model adopted here is combined in a logic tree in
865 which each branch is shown in Table B.3.
866 In the Northern Tien Shan, the dominant focal mechanisms are reverse faulting, as explained
867 in “Seismicity in the Northern Tien Shan”. Therefore, we consider reverse focal mechanism
38
868 for the earthquakes simulated in the source zones. The strike of the finite-fault rupture
869 simulated for the synthetic earthquakes depends on the strike of the faults in Figure 1. The
870 fault source TFF is a right-lateral strike-slip fault.
871 We assume that the minimum magnitude (i.e., the smallest earthquake considered to be of
872 engineering significance) is Mw 4.5.
873 Appendix C
874 EARTHQUAKE SCENARIOS FOR THE SPECTRAL ACCELERATIONS
875 We show the distribution of 0.2 s SA (Figure C.1) and 1.0 s SA (Figure C.2) for the 1887
876 Verny, 1889 Chilik, and 1911 Chon-Kemin earthquakes. Short and longer period spectral
877 accelerations relate the ground shaking to building response, albeit in a simple way. Longer
878 period accelerations, which may be generated by a large earthquake, attenuate more slowly.
879 They are likely to be more significant for taller buildings and, therefore, may be very
880 important to assess the seismic hazard in Almaty (see Introduction).
881 DISAGGREGATION PLOTS FOR THE SPECTRAL ACCELERATIONS
882 The disaggregation plots for 0.2 s (i.e., short period acceleration), for 1.0 s (i.e., long period
883 acceleration) are shown in Figures C.3-C.4. The disaggregation plot in Figure C.3a
884 corresponds to return periods of 132 ± 75 yr and shows that the hazard is dominated by
885 earthquakes of Mw 5.2 to 5.6 at distances of less than 10 km. As the return period increases,
886 the dominant contribution is from earthquakes of Mw 7.0 to 7.2 (Figure C.3b). For long-
887 period acceleration and return periods of 167 ± 108 yr, the major contribution to the hazard
888 comes from earthquakes of Mw 7.0 to 7.6 at 20 ≤ Rjb < 30 km (Figure C.4a). For return
889 periods of 500 ± 409 yr and 1.0 s acceleration, the hazard has a strong contribution from
39
890 earthquakes of Mw 7.4 to 7.6 at 10 ≤ Rjb < 20 km (Figure C.4b). For long-period
891 acceleration, the contribution to the hazard of Almaty from far distance sources increases, but
892 it is still smaller than that from NISK.
893 The disaggregation analysis for the MSK-64 intensity shows that earthquakes of Mw 7.0 to
894 7.2 at distances between 10 and 20 km influence the hazard (Figure C.5).
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1109 Conference Summary Report, 32 pp.
1110
1111 Pagani, M., D. Monelli, G. Weatherill, L. Danciu, H. Crowley, V. Silva, P. Henshaw, M. Nastasi, L.
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1113 Global Earthquake Model, Seismol. Res. Lett. 85 692-702.
1114
1115 Paramzin, A.M. (2005). Qualitative characteristic of the selected building objects in Almaty Oblast
1116 and Almaty City (in Russian), in Risk Management on the Local Level in Earthquake Prone Zones of
1117 Kazakhstan, United Nations Development Programme, Almaty, 76-86 (in Russian).
1118
1119 Parolai, S., J. Zschau, and U. Begaliev (2015). Earthquake Model Central Asia: seismic hazard and
1120 risk assessment in Central Asia, Ann. Geophys. 58.
1121
1122 Pilz, M., T. Abakanov, K. Abdrakhmatov, D. Bindi, T. Boxberger, B. Moldobekov, S. Orunbaev, N.
1123 Sylacheva, S. Ullah, S. Usupaev, P. Yasunov, and S. Parolai (2015). An overview on the seismic
1124 microzonation and site effect studies in Central Asia, Ann. Geophys. 58 DOI: 10.4401/ag-6662.
1125
1126 Reasenberg, P.A. (1985). Second-order moment of Central California seismicity, 1969-1982, J.
1127 Geophys. Res. 90 5479-5495.
1128
1129 Reiter, L. (1990). Earthquake Hazard Analysis: Issues and Insights, Columbia University Press, New
1130 York.
1131
1132 Rhoades, D.A. and D.J. Dowrick (2000). Effects of magnitude uncertainties on seismic hazard
1133 estimates, Proc.12th World Conf. Earthquake Eng., Wellington, New Zealand, Paper 1179.
1134
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1135 Scordilis, E.M. (2006). Empirical global relations converting Ms and mb to moment magnitude,
1136 Journal of Seismology 10 225-236.
1137
1138 Silacheva, N.V., U.K. Kulbayeva, and N.A. Kravchenko (2017). Probabilistic seismic hazard
1139 assessment of Kazakhstan and Almaty city in peak ground accelerations. Geodesy Geodynamics.
1140 DOI:10.1016/j.geog.2017.11.002.
1141
1142 Sloan, R.A., J. Jackson, D. McKenzie, and K. Priestley (2011). Earthquake depth distribution in
1143 Central Asia, and their relations with lithosphere thickness, shortening, and extension, Geophys. J. Int.
1144 185 1-29.
1145
1146 Stepp, J.C. (1972). Analysis of completeness of the earthquake sample in the Puget Sound Area and
1147 its effect on statistical estimates of earthquake hazard, First International Conference on
1148 Microzonation, Seattle, 2 897-909.
1149
1150 Stein, S., and M. Wysession (2003). An Introduction to Seismology, Earthquakes, and Earth
1151 Structure, Wiley-Blackwell Publishing, Oxford.
1152
1153 Stein, S., R.J. Geller, and M. Liu (2012). Why earthquake hazard maps often fail and what to do about
1154 it?. Tectonophysics. 562/553 1-25.
1155
1156 Tapponnier, P., and P. Molnar (1979). Active faulting and Cenozoic tectonics of the Tien Shan,
1157 Mongolia and Baykal regions, J. Geophys. Res. 84 3425-3456.
1158
1159 Tatevossian, R.E. (2007). The Verny, 1887, earthquake in Central Asia: Application of the INQUA
1160 scale, based on coseismic environmental effects, Quatern. Int. 173 23-29.
1161
49
1162 Thompson, S.C., R.J. Weldon, C.M. Rubin, and K. Abdrakhmatov (2002). Late Quaternary slip rates
1163 across the central Tien Shan, Kyrgyzstan, Central Asia, J. Geophys. Res. 107 10.1029/2001JB000596.
1164
1165 Tibaldi, A., E. Graziotto, F. Forcella, and V. Gapich (1997). Morphotectonic indicators of Holocene
1166 faulting in central Tien Shan, Kazakhstan, and geodynamic implications, J. Geodyn. 23 23-45.
1167
1168 Ullah, S., D. Bindi, M. Pilz, L. Danciu, G. Weatherill, E. Zuccolo, A. Ischuk, N. Mikhailova, K.
1169 Abdrakhmatov, and S. Parolai (2015). Probabilistic seismic hazard assessment for Central Asia, Ann.
1170 Geophys. 58 DOI:10.4401/ag-6687.
1171
1172 Ulomov, V.I., and the GSHAP Region 7 Working Group (1999). Seismic hazard of Northern Eurasia,
1173 Ann. Geophys. 42(6) 1023-1038.
1174
1175 Youngs, R.R., and K.J. Coppersmith (1985). Implications of fault slip rates and earthquake recurrence
1176 models to probabilistic seismic hazard estimates. Bull. Seismol. Soc. Am.75 (4) 939-964.
1177
1178 Wong, I., W. Silva, S. Olig, P. Thomas, D. Wright, F. Ashland, N. Gregor, J. Pechmann, M. Dober,
1179 G. Christenson, and R. Gerthl (2002). Earthquake Scenario and Probabilistic Ground Shaking Maps
1180 for the Salt Lake City, Utah, Metropolitan Area. Utah Geological Survey Miscellaneous Publication
1181 MP02-05, 55pp.
1182
1183 Wessel, P., W. Smith, R. Scharroo, J. Luis, and F. Wobbe (2013). Generic Mapping Tools: Improved
1184 version released, EOS, Trans. AGU. 94 409-410.
1185
1186 Zhao, J.X., J. Zhang, A. Asano, Y. Ohno, T. Oouchi, T. Takahashi, H. Ogawa, K. Irikura, H.K.
1187 Thio, P.G. Somerville, Y. Fukushima, and Y. Fukushima (2006). Attenuation relations of strong
1188 ground motion in Japan using site classification based on predominant period. Bull. Seismol. Soc. Am.
1189 96(3) 898–913.
50
1190
1191 Zöller, G., S. Ullah, D. Bindi, S. Parolai, and N.N. Mikhailova (2017). The largest expected
1192 earthquake magnitudes in Central Asia: statistical inference from an earthquake catalogue with
1193 uncertain magnitudes. , in Seismicity, Fault rupture and earthquake hazards in slowly deforming
1194 region. Landgraf, A., S. Kuebler, E. Hintersberger, and S. Stein (Editors), Geol. Soc. Spec. Publ. 432
1195 29-32.
1196
1197 Zubovich, A., X. Wang, Y. Scherba, G. Schelochkov, R. Reilinger, C. Reigber, O. Mosienko, P.
1198 Molnar, W. Michajilow, W. Makarov, J. Li, S. Kuzikov, T. Herring, M. Hamberger, B. Hager, Y.
1199 Dang, V. Bragin, and R. Beisenbaev (2010). GPS velocity field for the Tien Shan and surrounding
1200 regions, Tectonics 29 doi:10.1029/2010TC002772.
1201 List of figure captions
1202 Figure 1: (a) Topographic map of Asia from the global model ETOPO1 (Amante and Eakins,
1203 2009). The white lines represent the plate boundaries and the dashed rectangle indicates the
1204 study area. (b) Seismotectonic map of the Northern Tien Shan mountain belt where historical
1205 seismicity (before 1964) is indicated by squares and instrumental seismicity (after 1964), by
1206 circles. Symbol size is proportional to magnitude. Events of unknown depth are white.
1207 Tectonic structures are from 1) the Kyrgyz Institute of Seismology and digitized by the
1208 Active Tectonics Group at Arizona State University; 2) Hager and co-workers at Central
1209 Washington University, and Bogdanovich et al. (1914) and digitized by the Active Tectonics
1210 Group at Arizona State University. CKCF and TFF stand for Chon-Kemin-Chilik fault and
1211 Talas-Ferghana fault, respectively. The Ferghana Basin, Lake Issyk-Kul, and Ili basin are
1212 indicated by FB, LIK, and ILI, respectively.
51
1213 Figure 2: Epicentral location (solid circles) and fault ruptures (solid lines) of the three
1214 scenario earthquakes considered in this study. The dashed lines indicate the fault segments
1215 mapped by Abdrakhmatov et al. (2016) that potentially ruptured during the 1889 Chilik
1216 earthquake. The irregular lines indicate the surface rupture mapped by Arrowsmith et al.
1217 (2016) for the 1911 Chon-Kemin earthquake. See Figure 1 for details on the tectonic
1218 structures.
1219 Figure 3: Isoseismals for the 1889 Chilik (Mushketov, 1891) and 1911 Chon-Kemin
1220 (Bogdanovich et al., 1914) earthquakes are indicated in grey and black, respectively. See
1221 Figure 2 for details on epicenters (solid circles) and fault ruptures (solid and dashed lines) of
1222 the two earthquakes.
1223 Figure 4: Distribution of PGA, together with its standard deviation, for (a) the 1887 Verny
1224 earthquake; (b) the 1889 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake. The
1225 mean ground motions and their standard deviations have been computed from 1000
1226 scenarios. The white star indicates the city of Almaty. The white dot and the white line
1227 describe the epicenter and the fault rupture, respectively.
1228 Figure 5: Distribution of MSK-64 intensity for (a) the 1887 Verny earthquake; (b) the 1889
1229 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake. The white star indicates the city
1230 of Almaty. The white dot and the white line describe the epicenter and the fault rupture,
1231 respectively.
1232 Figure 6: Seismic source model used in this study. The star denotes the site used for PSHA.
1233 Figure 7: Magnitude-frequency recurrence for the source zone NISK. The solid line indicates
1234 the seismicity of the normal population of earthquakes predicted by the Gutenberg-Richter
1235 law in the range Mw 4.5 to 6.9; and the dashed line describes the seismicity of the additional
52
1236 population of earthquakes predicted by the Gutenberg-Richter law in the range Mw 7.0 to
1237 8.5. The grey area describes the region outside the completeness threshold of the earthquake
1238 catalogue for Mw ≥ 4.5.
1239 Figure 8: Seismic hazard curves for the site in Almaty. The solid lines are for the source
1240 model that consists of 16 zones and two faults; and the dashed lines are for the source model
1241 that consists of 16 zones only. The estimated ground motion values, together with their error-
1242 bars, for the scenario earthquakes are indicated by the circles.
1243 Figure 9: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for two
1244 pairs of PGA values and return periods: (a) 0.23 ± 0.08 g and 139 ± 81 yr; and (b) 0.49 ± 0.19
1245 g and 588 ± 514 yr.
1246 Figure B.1: Magnitude-frequency recurrence for the study area. The grey area describes the
1247 region outside the completeness threshold of the earthquake catalogue for Mw ≥ 4.5.
1248 Figure B.2: Activity rates and b-values for the individual zones in the source model. (a) The
1249 earthquake catalogue within the completeness thresholds set out in Table A.2 and the source
1250 zone model. (b) The activity rate and (d) the b-value of each source zone, together with (c, e)
1251 the standard deviation (maps on the right). The white star denotes the site.
1252 Figure C.1: Distribution of 0.2 s SA, together with its standard deviation, for (a) the 1887
1253 Verny earthquake; (b) the 1889 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake.
1254 The mean ground motions and their standard deviations have been computed from 1000
1255 scenarios. The white star indicates the city of Almaty. The white dot and the white line
1256 describe the epicenter and the fault rupture, respectively.
53
1257 Figure C.2: Distribution of 1.0 s SA, together with its standard deviation, for (a) the 1887
1258 Verny earthquake; (b) the 1889 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake.
1259 The mean ground motions and their standard deviations have been computed from 1000
1260 scenarios. The white star indicates the city of Almaty. The white dot and the white line
1261 describe the epicenter and the fault rupture, respectively.
1262 Figure C.3: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for two
1263 pairs of 0.2 s SA values and return periods: (a) 0.48 ± 0.17 g and 132 ± 75 yr; and (b) 1.11 ±
1264 0.44 g and 588 ± 509 yr.
1265 Figure C.4: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for two
1266 pairs of 1.0 s SA values and return periods: (a) 0.17 ± 0.07 g and 167 ± 108 yr; and (b) 0.32 ±
1267 0.14 g and 500 ± 409 yr.
1268 Figure C.5: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for
1269 MSK-64 intensity VIII ± I and the return period of 161 ± 483 yr.
54
1270 Table 1: Rupture model of the scenario earthquakes.
Parameter 1887 Verny 1889 Chilik 1911
Chon-Kemin
Epicenter 43.10°N#, 43.17 0.50§ °N, 42.80 0.28† °N,
# 76.80°E 78.55 0.50§ °E 77.30 0.49† °E
Mw 7.3 0.2‡ 8.2 0.2‡ 8.0 0.1†
Dip [°] 60# 70# 52 10†
Rake [°] 98# 60# 98 10†
Hypocentral depth [km] 20# 40# 20 3†
Rupture length [km] 75 20* 260 71* 202 28*
Down-dip width [km] 31 8* 42# 50 5*
Geometry of the fault trace**: 43.09; 76.39 42.83; 76.78 42.71; 75.85
latitude [°]; longitude [°] 43.13; 76.58 43.00; 77.61 42.82; 76.83
43.15; 76.96 43.01; 78.25 42.82; 78.34
43.29; 77.21 43.80; 79.50
43.31; 77.35
1271 *The standard deviation is estimated from the error propagation.
1272 # The value is hypothetical.
1273 † The standard deviation is from Kulikova and Krüger (2015).
1274 ‡ The standard deviation is from Scordilis (2006).
1275 § The standard deviation is reported in Bindi et al. (2014).
1276 ** Simplified geometry of the ruptured fault trace based on published data and used in
1277 the DSHA.
55
1278
1279 Table 2: Distance metrics for the scenario earthquakes.
Distance 1887 Verny 1889 Chilik 1911
Chon-Kemin
Source-site 21.4 134.4 62.5
distance [km]
Rjb [km] 0.0 32.9 20.6
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
56
1291 Table 3: Mean values for PGA, 0.2 s and 1.0 s SA, and MSK-64 intensity in Almaty for the
1292 scenario earthquakes using vs30=760 m/s.
1293
Ground motion parameter 1887 Verny 1889 Chilik 1911
Chon-Kemin
PGA [g] 0.49 0.19 0.167 0.06 0.23 ± 0.08
0.2 s SA [g] 1.11 0.44 0.34 0.12 0.48 ± 0.17
1.0 s SA [g] 0.32 0.14 0.14 0.06 0.17 ± 0.07
MSK-64 VIII ± I VIII ± I VIII ± I
1294
1295
1296
1297
1298
1299
1300
1301
1302
57
1303 Table 4: Sensitivity analysis of the ground shaking scenario for the 1911 Chon-Kemin
1304 earthquake*.
Number Test Parameter PGA ± 0.2 s SA 1.0 s SA
[g] ± [g] ± [g]
1 Site conditions Soft rock 0.27 ± 0.59 ± 0.25 ±
(360 < Vs30 < 760 0.09 0.20 0.10
m/s)
2 GMPE Boore et al. (2014) 0.23 ± 0.47 ± 0.17 ±
0.07 0.15 0.06
3 GMPE Chiou and Youngs 0.23 ± 0.52 ±0.17 0.15 ±
(2014) 0.07 0.05
4 GMPE Akkar et al. (2014) 0.23 ± 0.45 ± 0.19 ±
0.09 0.18 0.08
5 Focal Dip = 45° 0.32 ± 0.69 ± 0.23 ±
mechanism 0.11 0.25 0.10
6 Focal Rake = 60° , dip = 65° 0.15 ± 0.30 ± 0.12
mechanism 0.05 0.11 ±0.06
7 Multi- Varying dips 0.19 ± 0.39 ± 0.14 ±
segmented 0.06 0.14 0.06
rupture
1305 *The second column indicates the parameter changed in each test; and the third, fourth and
1306 fifth columns show the estimate of ground motion parameter for the site in Almaty.
1307
58
1308
1309
1310
1311
1312 Table 5: Values of maximum magnitude (Mmax) and weights (WGTs) of the source model.
Tectonic Source Mmax1 WGT1 Mmax2 WGT2 Mmax3 WGT3 Mmax4 WGT4
unit
Western Tien ALAI 7.5 0.20 8.0 0.60 8.2 0.20 - -
Shan FERR 7.5 0.20 8.0 0.60 8.2 0.20 - -
Lower ATBA 7.0 0.25 7.5 0.25 8.0 0.25 8.2 0.25
Northern KERS 7.0 0.25 7.5 0.25 8.0 0.25 8.2 0.25
Tien Shan NARY 7.0 0.25 7.5 0.25 8.0 0.25 8.2 0.25
SISK 7.0 0.25 7.5 0.25 8.0 0.25 8.2 0.25
Eastern Tien CTS1 8.2 0.40 8.3 0.40 8.5 0.20 - -
Shan CTS2 8.2 0.40 8.3 0.40 8.5 0.20 - -
ILI 8.2 0.40 8.3 0.40 8.5 0.20 - -
Foreland FTS1 8.2 0.40 8.3 0.40 8.5 0.20 - -
Tien Shan FTS2 8.2 0.40 8.3 0.40 8.5 0.20 - -
FTS3 8.2 0.40 8.3 0.40 8.5 0.20 - -
Kazakh Plat. KZPL 6.5 0.25 7.0 0.25 7.5 0.25 8.0 0.25
Upper KYRG 8.2 0.40 8.3 0.40 8.5 0.20 - -
Northern NISK 8.2 0.40 8.3 0.40 8.5 0.20 - -
Tien Shan SUUS 8.2 0.40 8.3 0.40 8.5 0.20 - -
Fault CKCF 8.2 0.40 8.3 0.40 8.5 0.20 - -
sources TFF 8.2 0.40 8.3 0.40 8.5 0.20 - -
1313
59
1314
1315
1316
1317
1318
1319 Table 6: Return periods of the ground motion values for a site in Almaty for the scenario
1320 earthquakes.
Ground motion 1887 Verny 1889 Chilik 1911
parameter Chon-Kemin
PGA [g] 588 514 81 44 139 ± 81
0.2 s SA [g] 588 509 76 41 132 ± 75
1.0 s SA [g] 500 409 120 80 167 ± 108
MSK-64 161 ± 483 161 ± 483 161 ± 483
1321
1322
1323
1324
1325
1326
1327
60
1328
1329
1330
1331
1332 Table 7: Comparison of the hazard results for 475 –year return period between this study and
1333 previous works.
Study MSK-64 PGA
Ulomov et al. (1999) IX -
Ullah et al. (2015) VII-VIII -
Silacheva et al. (2017) - 0.36-0.44
This study VIII-IX 0.44
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
61
1345
1346
1347
1348 Table A.1: Hierarchy of magnitude selected among the available magnitude estimates in the
1349 ISC database.
Number Magnitude Agency
1 Mw Global Centroid Moment Tensor
2 Mw National Earthquake Information Centre
3 Ms International Seismological Centre
4 mb International Seismological Centre
5 Ms National Earthquake Information Centre
6 mb National Earthquake Information Centre
7 Ms International Data Centre for Comprehensive
Nuclear-Test-Ban Treaty Organization
8 mb International Data Centre for Comprehensive
Nuclear-Test-Ban Treaty Organization
9 Ms European-Mediterranean Seismological Centre
10 mb European-Mediterranean Seismological Centre
11 Ms/mb Agency providing the hypocentral location
1350
1351
1352
62
1353
1354
1355 Table A.2: Completeness periods for the catalogue.
Mw Completeness period
4.5 1970
5.0 1965
5.5 1925
6.0 1875
6.5 1875
7.0 1875
7.5 1875
8.0 1875
1356
1357
1358
1359
1360
1361
1362
1363
1364
63
1365
1366
1367 Table B.1: Number of earthquakes used for the recurrence statistics, activity rate N (≥ Mw
1368 4.5) and b-value of the source model.
Number of Tectonic unit Source N(≥ Mw 4.5) b-value earthquakes
ALAI 59 1.15 ± 0.15 1.004 ± 0.083 Western Tien Shan FERR 28 0.56 ± 0.10 1.03 ± 0.10
ATBA 38 0.75 ± 0.12 1.009 ± 0.095
KERS 23 0.468 ± 0.095 1.11 ± 0.11 Lower Northern Tien Shan NARY 28 0.56 ± 0.10 1.030 ± 0.10
SISK 21 0.415 ± 0.088 1.00 ±0.11
CTS1 49 0.97 ± 0.14 1.037 ± 0.090
Eastern Tien Shan CTS2 53 1.04 ± 0.14 1.009 ± 0.086
ILI 14 0.269 ± 0.070 0.91 ± 0.11
FTS1 38 0.72 ± 0.11 0.894 ± 0.089
Foreland Tien Shan FTS2 248 4.84 ± 0.30 0.994 ± 0.047
FTS3 14 0.273 ± 0.071 0.95 ± 0.11
Kazakh Plat. KZPL 11 0.209 ± 0.061 0.86 ± 0.11
KYRG 22 0.426 ± 0.089 0.95 ± 0.10
Upper Northern Tien Shan NISK 49 0.90 ± 0.13 0.826 ± 0.078
SUUS 28 0.55 ± 0.10 0.97 ± 0.10
1369
1370
64
1371
1372
1373 Table B.2: Values of slip rates and activity rates of the fault sources CKCF and TFF.
CKCF TFF
Slip Activity rate (≥ b- Weight Slip Activity rate (≥ b- Weight
rate Mw4.5) value rate Mw4.5) value
[mm/yr] [mm/yr]
0.1 -2.0192 0.826 0.25 0.1 -1.7579 0.959 0.25
1.0 -1.0192 0.826 0.25 0.5 -1.0590 0.959 0.25
2.0 -0.7181 0.826 0.25 1.0 -0.7579 0.959 0.25
3.0 -0.5421 0.826 0.25 1.5 -0.5819 0.959 0.25
1374
1375
1376
1377
1378
1379
1380
1381
1382
65
1383
1384 Table B.3: Values of hypocentral depths (h, km), in kilometers, and weights (WGTs) of the
1385 source model.
Tectonic unit Source h1 WGT1 h2 WGT2 h3 WGT3 h4 WGT4 h5 WGT5 h6 WGT6
Western Tien ALAI 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - -
Shan FERR 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - -
ATBA 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - - Lower KERS 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - - Northern Tien NARY 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - - Shan SISK 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - -
CTS1 10 0.30 20 0.30 30 0.20 40 0.20 - - - - Eastern Tien CTS2 10 0.30 20 0.30 30 0.20 40 0.20 - - - - Shan ILI 10 0.30 20 0.30 30 0.20 40 0.20 - - - -
FTS1 10 0.25 20 0.25 30 0.25 40 0.10 - - - - Foreland Tien FTS2 10 0.25 20 0.25 30 0.25 40 0.10 - - - - Shan FTS3 10 0.25 20 0.25 30 0.25 40 0.10 - - - -
Kazakh Plat. KZPL 10 0.30 20 0.30 30 0.20 40 0.20 - - - -
Upper KYRG 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - -
Northern Tien NISK 10 0.15 15 0.30 20 0.30 25 0.15 30 0.05 40 0.05
Shan SUUS 5 0.10 10 0.20 15 0.25 20 0.25 25 0.20 - -
Fault CKCF 10 0.20 15 0.20 20 0.30 25 0.30 - - - -
Sources TFF 10 0.20 15 0.20 20 0.30 25 0.30 - - - -
66
1386
1387
1388 Figure 1: (a) Topographic map of Asia from the global model ETOPO1 (Amante and Eakins,
1389 2009). The white lines represent the plate boundaries and the dashed rectangle indicates the
1390 study area. (b) Seismotectonic map of the Northern Tien Shan mountain belt where historical
1391 seismicity (before 1964) is indicated by squares and instrumental seismicity (after 1964), by
1392 circles. Symbol size is proportional to magnitude. Events of unknown depth are white.
1393 Tectonic structures are from 1) the Kyrgyz Institute of Seismology and digitized by the
1394 Active Tectonics Group at Arizona State University; 2) Hager and co-workers at Central
1395 Washington University, and Bogdanovich et al. (1914) and digitized by the Active Tectonics
67
1396 Group at Arizona State University. CKCF and TFF stand for Chon-Kemin-Chilik fault and
1397 Talas-Ferghana fault, respectively. The Ferghana Basin, Lake Issyk-Kul, and Ili basin are
1398 indicated by FB, LIK, and ILI, respectively.
1399
4 4.00 0 100 km
43.50 Sat y seg m en t Besh Almaty karagai se gment 1889 Chilik 1887 Verny ent 43.00 egm ilik s Ch Kur men seg tey Ch on -Kem i n Ch on -Aksu ment segment segment 1911 Ch o n -Kem i n 42.50
42.00 1400 75.00 75.50 76.00 76.50 77.00 77.50 78.00 78.50 79.00 79.50 80.00
1401 Figure 2: Epicentral location (solid circles) and fault ruptures (solid lines) of the three
1402 scenario earthquakes considered in this study. The dashed lines indicate the fault segments
1403 mapped by Abdrakhmatov et al. (2016) that potentially ruptured during the 1889 Chilik
1404 earthquake. The irregular lines indicate the surface rupture mapped by Arrowsmith et al.
1405 (2016) for the 1911 Chon-Kemin earthquake. See Figure 1 for details on the tectonic
1406 structures.
1407
68
46˚
45˚ VII
VIII 44˚ IX Almaty VI 1889 Chilik 43˚ VIII VII IX X 1911 Chon-Kemin
42˚
41˚
0 100 200 km 40˚ 1408 72˚ 73˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 82˚
1409 Figure 3: Isoseismals for the 1889 Chilik (Mushketov, 1891) and 1911 Chon-Kemin
1410 (Bogdanovich et al., 1914) earthquakes are indicated in grey and black, respectively. See
1411 Figure 2 for details on epicenters (solid circles) and fault ruptures (solid and dashed lines) of
1412 the two earthquakes.
69
(a) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ (b)45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ (c)45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.0 0.05 0.10 0.15 0.20 0.25 1413 PGA [ g ] Si g m a (PGA) [ g ]
1414 Figure 4: Distribution of PGA, together with its standard deviation, for (a) the 1887 Verny
1415 earthquake; (b) the 1889 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake. The
1416 mean ground motions and their standard deviations have been computed from 1000
1417 scenarios. The white star indicates the city of Almaty. The white dot and the white line
1418 describe the epicenter and the fault rupture, respectively.
70
(a) 45˚
44˚
43˚
42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚
45˚ (b)
44˚
43˚
42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚
45˚ (c)
44˚
43˚
42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚
IV V VI VII VIII XIX X 1419 Intensity (MSK-64)
1420 Figure 5: Distribution of MSK-64 intensity for (a) the 1887 Verny earthquake; (b) the 1889
1421 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake. The white star indicates the city
1422 of Almaty. The white dot and the white line describe the epicenter and the fault rupture,
1423 respectively.
71
46˚
0 100 200 km 45˚ CTS2 KZPL 44˚ ILI NISK 43˚ CKCF KYRG CTS1
SUUS SISK 42˚ TFF KERS NARY FTS3 FERR 41˚ ATBA ALAI FTS2 40˚ FTS1
39˚
1424 70˚ 71˚ 72˚ 73˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 82˚ 83˚
1425 Figure 6: Seismic source model used in this study. The star denotes the site used for PSHA.
72
10 Gutenberg-Richter law for the normal population Gutenberg-Richter law for the additional population Observed seismicity
1
N=10^ [-0.046-0.826*(Mw-4.5)]
0.1 N ( ≥Mw )
0.01 Co m p l et en ess threshold for Mw 4.5
N=10^ [0.412-0.793*(Mw-4.5)]
0.001 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 1426 Mw
1427 Figure 7: Magnitude-frequency recurrence for the source zone NISK. The solid line indicates
1428 the seismicity of the normal population of earthquakes predicted by the Gutenberg-Richter
1429 law in the range Mw 4.5 to 6.9; and the dashed line describes the seismicity of the additional
1430 population of earthquakes predicted by the Gutenberg-Richter law in the range Mw 7.0 to
73
1431 8.5. The grey area describes the region outside the completeness threshold of the earthquake
1432 catalogue for Mw ≥ 4.5.
100 Source zones and fault sources 10-1 Source zones only 10-1 1889 Chillik 1889 Chillik 10-2 1911 Chon-Kemin 10-2 1911 Chon-Kemin
-3 10 10-3 1887 Verny 1887 Verny Annual frequency ofexceedance Annual frequency ofexceedance 10-4 10-4 0.2 0.4 0.6 0.8 1.0 0.51.01.52.0 PGA [ g] 0.2-s SA [g]
100
10-1 10-1 1889 Chillik 1911 Chon-Kemin 10-2 1911 Chon-Kemin 1889 Chillik 10-2 1887 Verny
10-3 1887 Verny 10-3 Annual frequency of exceedance of frequency Annual exceedance of frequency Annual 10-4 10-4 0.2 0.4 0.6 0.8 1.0 567891011 1433 1.0-s SA [g] MSK-64 [g]
1434 Figure 8: Seismic hazard curves for the site in Almaty. The solid lines are for the source
1435 model that consists of 16 zones and two faults; and the dashed lines are for the source model
1436 that consists of 16 zones only. The estimated ground motion values, together with their error-
1437 bars, for the scenario earthquakes are indicated by the circles.
74
4.8 ≤ Mw ≤ 5.0 Rjb < 10 km 0 ≤ ε ≤ 1 (a)
1887 Verny
1911 Ch o n -Kem i n 1889 Chilik Contribution to hazard [%] Contributionhazard to ε -4
m] ce [k -3 istan M ore d w er-Bo Joyn -2
-1 7.0 ≤ Mw ≤ 7.2 1887 Verny Rjb ≤ 10 km 0 (b) -1 ≤ ε ≤ 0 1
2
3
4
1911 Chon-Kemin
1889 ntribution to hazard [%] ntributionhazard to
o Chilik C
m] ce [k istan ore d Mw er-Bo Joyn 1438
1439 Figure 9: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for two
1440 pairs of PGA values and return periods: (a) 0.23 ± 0.08 g and 139 ± 81 yr.; and (b) 0.49 ±
1441 0.19 g and 588 ± 514 yr.
75
100 Truncated Gutenberg-Richter law Observed seismicity
10
1
N (≥ Mw ) 0.1
0.01 Co m p l et en ess threshold for Mw 4.5
N=10^ [1.450-0.959*(Mw-4.5)] 0.001 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 1442 Mw
1443 Figure B.1: Magnitude-frequency recurrence for the study area. The grey area describes the
1444 region outside the completeness threshold of the earthquake catalogue for Mw ≥ 4.5.
76
45˚
44˚
43˚ 4.5≤Mw<6.0 6.0≤Mw<7.0 42˚ 7.0≤Mw<8.0 41˚ Mw≥8.0 40˚ 39˚
70˚ 72˚ 74˚ 76˚ 78˚ 80˚ 82˚
0.20 0.00
45˚ 45˚ n o i at i ev d d ar d an St 0.36 44˚ 44˚ 0.05
0.52 Activity rate 43˚ 43˚ 0.10 0.68 42˚ 42˚ 0.15 0.84 41˚ 41˚ 0.20 40˚ 1.00 40˚ 0.25 39˚ 1.16 39˚
70˚ 72˚ 74˚ 76˚ 78˚ 80˚ 82˚ 1.16 70˚ 72˚ 74˚ 76˚ 78˚ 80˚ 82˚
0.80 0.040 45˚ 0.85 45˚ ta rd via n o i at i ev d d ar d an St 44˚ 44˚ 0.055 0.90
43˚ b-value 43˚ 0.070 0.95 42˚ 42˚ 0.085 1.00 41˚ 41˚ 0.100 40˚ 1.05 40˚ 0.115 39˚ 1.10 39˚ 1445 70˚ 72˚ 74˚ 76˚ 78˚ 80˚ 82˚ 1.15 70˚ 72˚ 74˚ 76˚ 78˚ 80˚ 82˚
1446 Figure B.2: Activity rates and b-values for the individual zones in the source model. (a) The
1447 earthquake catalogue within the completeness thresholds set out in Table A.2 and the source
1448 zone model. (b) The activity rate and (d) the b-value of each source zone, together with (c, e)
1449 the standard deviation (maps on the right). The white star denotes the site.
77
(a) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ (b) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ (c) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 1450 0.2 s SA [g] Sigma (0.2 s SA) [g]
1451 Figure C.1: Distribution of 0.2 s SA, together with its standard deviation, for (a) the 1887
1452 Verny earthquake; (b) the 1889 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake.
1453 The mean ground motions and their standard deviations have been computed from 1000
1454 scenarios. The white star indicates the city of Almaty. The white dot and the white line
1455 describe the epicenter and the fault rupture, respectively.
78
(a) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ (b) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ (c) 45˚ 45˚
44˚ 44˚
43˚ 43˚
42˚ 42˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚ 74˚ 75˚ 76˚ 77˚ 78˚ 79˚ 80˚ 81˚
0.0 0.1 0.2 0.3 0.4 0.5 0.0 0.05 0.10 0.15 0.20 0.25 1456 1.0 s SA [g] Sigma (1.0 s SA) [g]
1457 Figure C.2: Distribution of 1.0 s SA, together with its standard deviation, for (a) the 1887
1458 Verny earthquake; (b) the 1889 Chilik earthquake; and (c) the 1911 Chon-Kemin earthquake.
1459 The mean ground motions and their standard deviations have been computed from 1000
1460 scenarios. The white star indicates the city of Almaty. The white dot and the white line
1461 describe the epicenter and the fault rupture, respectively.
79
5.2 ≤ Mw ≤ 5.6 Rjb ≤ 10 km -1 ≤ ε ≤ 0 (a) 1887 Verny
1911 Ch on -Kem i n Contribution to hazard [%] Contribution hazard to 1889 Chilik ε -4
m] -3 ce [k istan ore d M er-Bo w Joyn -2
7.0 ≤ Mw ≤ 7.2 -1 Rj b ≤ 1 0 k m -1 ≤ ε ≤ 0 0 (b) 1887 Verny 1
2
3
4
1911 Ch on -Kem i n ntribut ion to hazard [%]
o 1889 Chilik C
m] ce [k istan M ore d w er-Bo Joyn 1462
1463 Figure C.3: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for two
1464 pairs of 0.2 s SA values and return periods: (a) 0.48 ± 0.17 g and 132 ± 75 yr.; and (b) 1.11 ±
1465 0.44 g and 588 ± 509 yr.
80
1887 Verny
7.0 ≤ Mw ≤ 7.2 7.4 ≤ Mw ≤ 7.6 (a) 20 ≤ Rjb < 30 km 20 ≤ Rjb < 30 km -1 ≤ ε ≤ 0 -1 ≤ ε ≤ 0
ε -4
-3 1911 Ch on -Kem i n -2 Contribution to hazard [%]
1889 Chilik -1
0
m] 1 ce [k istan ore d Mw er-Bo 2 Joyn
3
4 1887 Verny
(b) 7.4 ≤ Mw ≤ 7.6 10 ≤ Rjb < 20 km
1911 Ch on -Kem i n ontribution to hazard [%] ontributionhazard to C 1889 Chilik
m] ce [k istan ore d Mw er-Bo Joyn 1466
1467 Figure C.4: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for two
1468 pairs of 1.0 s SA values and return periods: (a) 0.17 ± 0.07 g and 167 ± 108 yr.; and (b) 0.32
1469 ± 0.14 g and 500 ± 409 yr.
81
1887 Verny ε 7.0 ≤ Mw ≤ 7.2 -4 10 ≤ Rjb >20 km -1 ≤ ε ≤ 0 -3
-2
-1 1911 Ch on -Kem i n 0 to hazard [%] n 1
ntributio 1889
o 2
C Chilik
3
m] 4 ce [k ist an ore d Mw er-Bo Joyn 1470
1471 Figure C.5: Disaggregation by magnitude Mw, Joyner-Boore distance and epsilon for
1472 MSK-64 intensity VIII ± I and the return period of 161 ± 483 yr.
1473
82