Engineering Geology 107 (2009) 140–153 Contents lists available at ScienceDirect Engineering Geology j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e n g g e o Use of microtremor in liquefaction hazard mapping M.A.A. Beroya a, A. Aydin b,⁎, R. Tiglao c, M. Lasala c a b c Mines and Geosciences Bureau, Quezon City, Manila, Philippines Department of Geology and Geological Engineering, The University of Mississippi, University, MS 38677, USA Philippine Institute of Volcanology and Seismology, C.P. Garcia Avenue, UP Campus, Diliman, Quezon City, Philippines a r t i c l e i n f o Article history: Received 10 April 2009 Accepted 22 May 2009 Available online 30 May 2009 Keywords: Integrated liquefaction hazard map Liquefaction Liquefaction susceptibility Microtremor a b s t r a c t This study shows how microtremor measurements can be used as an aid to liquefaction hazard mapping and zonation, as demonstrated in Laoag City, Northern Philippines. From microtremor measurements, qualitative information on subsoil conditions was obtained and a site classification map was generated. The map was combined with the geomorphology-based liquefaction susceptibility map to produce an integrated liquefaction hazard zonation map. This integrated map is deemed to be more accurate in depicting relative liquefaction susceptibility since it combines information on the distribution of potentially liquefiable soils in terms of geology and grain characteristics with information on the stiffness and thickness of these soils. With information about the thickness of the deposits, an idea of the severity of liquefaction-related damage can also be gathered since thicker deposits relate to more serious damage. Plots of historical liquefaction cases, as well as borehole data and resistivity profiles in the study area, support the validity of the integrated map. The use of microtremor, therefore, constitutes an effective and inexpensive approach to liquefaction hazard zonation, and as such is very useful in less-developed countries like the Philippines and other areas where funds for more rigorous investigations are not always available. © 2009 Elsevier B.V. All rights reserved. 1. Introduction Ambient seismic noise or microtremors are feeble ground motions with displacement amplitudes of about 0.1–1 μm and period range of 1/10 of a second to 10 s (Kanai and Tanaka, 1961; AIJ, 1993). They can be classified into two types: short-period (b1 s) and long-period (also known as microseisms) (N1 s). However, the 1 s limit value separating the two domains may be shifted to longer periods, as for instance in urban areas that are characterized by low frequency and high impedance contrast subsoils. In this case, artificial microtremors may be more energetic than natural microseisms even at intermediate periods of up to a few seconds (Seo, 1997). Kanai and Tanaka (1954) originally introduced a theoretical interpretation and practical engineering application of microtremor. Today, microtremor is used in the characterization of soil layers, prediction of shear-wave velocity of the ground and evaluation of the predominant period of the soil during earthquake events, among others. In recent years, its use as a tool for site effect estimation has gained increased popularity, particularly since measurements can be conducted quickly and easily at a low cost and data analysis is simple. Moreover, it can be applied in areas of low seismicity. ⁎ Corresponding author. E-mail address: [email protected] (A. Aydin). 0013-7952/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.enggeo.2009.05.009 In this study, microtremor was used to obtain qualitative information on subsoil conditions, particularly the density and thickness of soil deposits, from which a site classification map was subsequently generated. When this map was combined with the geomorphologybased liquefaction susceptibility map, a more accurate liquefaction hazard zonation map was shown to be obtained. The basic idea behind the approach is that while the geomorphology-based liquefaction susceptibility map identifies those deposits that are potentially liquefiable by virtue of geology and grain characteristics (e.g., size, sorting, etc.), the site classification map confirms the state of density of these deposits and provides some idea on their thickness. As thicker deposits relate to more serious damage, the potential severity of liquefaction-related damage can therefore also be inferred. It should also be noted that a thick, soft soil deposit may amplify ground shaking and prolong the duration of motion, both of which are contributing factors to liquefaction occurrence. The study was conducted in Laoag City, Northern Philippines (Fig. 1) for several reasons: the city is densely populated with critical buildings and infrastructures; it is undergoing rapid growth and expansion as it is being developed as an international commercial/ tourism center; it is built upon the Recent, loose, and therefore, generally liquefaction-prone sediments of the Laoag River; several geological structures capable of triggering significant seismicity surround the area; and cases of liquefaction are known to have occurred in certain areas of the city, mostly in that part where urban expansion is going on. Thus, from both economic and scientific viewpoints, the study is relevant and warranted. M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 2. Review of related studies As pointed out by Bard (1999), the earliest application of microtremor is, in fact, as an indicator of ground conditions. Japanese scientists have repeatedly noted the gross correlation between the spectral features of microtremors and site geological conditions. In general, they observed that a short predominant period of microtremor (b0.2 s) indicates a stiff rock, while a longer period indicates softer and thicker deposits. Such an increase in period length with decreasing soil stiffness is often accompanied by an amplitude increase. The combination of predominant period and amplitude therefore provides a qualitative “index” on soil characteristics. Kanai and Tanaka (1954, 1961) were the first to propose a method to classify ground conditions based on the characteristics of the noise 141 spectra. They suggested that the period distribution curve of microtremors shows a definite form for each subsoil type. For instance, in the case of simple, stratified soil, a relatively sharp peak appears around 0.1–0.6 s. On the other hand, when the formation of soil is complex, more than two peaks may appear: a smaller one near 0.2 s and a larger one near 1 s. On a mountain, a sharp peak appears between 0.1–0.2 s, while on firm diluvial soil this peak appears between 0.2– 0.4 s. On soft, alluvial soils, the curve is usually irregular in shape and a number of peaks appear between 0.4–0.8 s. Finally, on especially soft soils the curve is usually flat, with peaks that vary from 0.05 s, 0.1 to 1 s, and 2 s. Kanai and Tanaka's classification scheme uses a main discrimination diagram (average period vs. maximum period) and an auxillary one (predominant period vs. maximum amplitude), and follows the soil categories used in the Japan Building Code. Fig. 1. Location and geology of Laoag City. 142 M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 Since the pioneering work of Kanai and Tanaka (1954), various authors have proposed several means to obtain information related with site conditions using the absolute spectra. Some of these works are discussed in Bard (1999). Later on, other techniques were proposed and applied in the analysis of microtremor records (i.e., site-toreference spectral ratio, horizontal-to-vertical spectral ratio or the Nakamura technique, velocity structure inversion), which proved in many cases to be successful in providing insights to subsoil conditions. Applying the horizontal-to-vertical spectral ratio (HVSR), for instance, Lermo and Chávez-García (1994) obtained an increasing predominant frequency (decreasing predominant period) from the soft lake bed zone, to the harder transition zone, then to the hilly zone (reference site) in Mexico City and Oaxaca. The predominant periods obtained by Navarro et al. (2001) in the city of Almeria, Southern Spain varied from 0.06 s on hard rock, to 0.4 s on medium soil sites, and to 1.4 s on very soft Holocene material and coastal sands. Bour et al. (1998) used microtremor for microzonation of a sector of Rhone Delta, South of France and found an increase in fundamental frequency and amplification with the thickening of alluvial deposits. Teves-Costa et al. (1996) and Nguyen et al. (2003) obtained similar findings for Lisbon, Portugal and Northern Belgium, respectively. In the Philippines, results of microtremor observation conducted in Metropolitan Manila showed that in areas underlain by coastal and fluvial materials, long-period waves tend to predominate and amplification factors are high, while in areas underlain by welded tuff and competent materials, short-period waves are dominant and amplification factors are low (Abeki and Punongbayan, 1999; Narag et al., 2000). So far as known, only one study, that of Huang and Tseng (2002) directly relates microtremor data with liquefaction. Microtremor measurements were conducted in Yuen–Lin area, central Taiwan, where liquefaction was clearly observed during the Chi-chi earthquake. Results showed that in the liquefied areas, predominant frequencies are about 0.8–0.9 Hz, with higher amplification factors relative to other areas. Ground vulnerability index, Kg, was also computed and found to be likewise higher in the liquefied areas. The applicability of these findings in Laoag City was investigated in this study. 3. Geomorphology-based liquefaction susceptibility evaluation of Laoag City Situated in a fluvio-deltaic environment (Fig. 1), Laoag City is shaped both by river and marine processes. Two major geomorphic features can be identified in the study area: the wave-dominated Laoag River Delta and the meandering Laoag River. Landforms associated with these features are well-developed (e.g. floodplains, point bars, beach ridges). A minor creek independent of the Laoag River system, the Darao–Tupec Creek, drains the northern part of Laoag City. Although only a minor stream, it drains about 36% of the study area. As expected, the associated landforms are not as developed, although it has a fairly developed floodplain that covers the city's northwestern part. Together, the deposits of these three geological systems cover about 90% of Laoag City. Underlying these alluvial deposits is the Laoag Formation, which forms the hills and slopes that bound the study area to the north–northeast and southeast. Fig. 2. Micro-geomorphological map. M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 The abovementioned geomorphic units can further be divided into sub-units. Distinct micro-units identified in the study area are shown in Fig. 2. By using the criteria set forth by several authors (i.e., Youd and Perkins, 1978; Iwasaki et al., 1982; Wakamatsu, 1992), as well as the Philippine experience during the 1990 Luzon earthquake, the liquefaction susceptibility of each microgeomorphological unit was categorized as either high, moderate, low or non-liquefiable, as shown in Fig. 3. Included in the high category were those where loose granular deposits are most likely to be found, like the active river channels and active point bars, recently abandoned channels, and the delta-associated floodplain, active sand dunes, channel bars and backswamp. The susceptibility of the abandoned beach ridges/inactive sand dunes, as well as the old meanders, point bars and natural levees was considered moderate. Although deposits in these units were expected to have similar grain characteristics as those in high category, they were likely to have undergone some degree of compaction, and therefore gained increased resistance against liquefaction. The floodplain beyond the northern bank of Laoag River and that associated with the Darao–Tupec Creek were also considered moderately susceptible to liquefaction. Being typical floodplains, these areas were expected to be underlain mainly by clays and silts derived from the vertical accretion of suspended sediments during flooding. In contrast, thick sand deposits resulting from delta front progradation could likely be found underneath the southwestern floodplains. As these deposits are constantly reworked due to active switching and 143 migration of distributary channels, they were inferred to be in a loose state. Thus, these floodplains were ranked as highly susceptible to liquefaction. The susceptibility of valley in-fills and talus deposits composed mainly of fine-grained sediments was ranked as low, while the lowlying hills and slopes were considered non-liquefiable. A complete discussion of this work can be found in Beroya and Aydin (2007). 4. Microtremor measurements, data analysis and checking Among the various approaches to microtremor study, the HVSR technique introduced by Nakamura (1989) was chosen for this investigation due to ease of application. This technique has been described in a number of papers (e.g., Lermo and Chávez-García, 1993, 1994; Teves-Costa et al., 1996; Bour et al., 1998) and is therefore no longer discussed here. Microtremor recordings were carried out in a total of 168 points, covering the entire study area except where access is limited or not at all possible (e.g., rice field, difficult terrain, etc.). To test the stability of recorded microtremors, 24-h continuous measurements at 1 h interval were conducted at 2 sites: Laoag City Elementary School (LCES) and Barangay Zamboanga Hall (ZAMB) (Fig. 1). Measurements were performed using a Midorikawa instrument, which consists of a single tri-component sensor with a natural period of 1 s and a flat response between 1.5 and 8.0 Hz. The sensor was connected to a gain and period-selectable amplifier, the output of Fig. 3. Preliminary liquefaction susceptibility map. 144 M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 which was recorded by a laptop computer with an A/D card interfacing with a data acquisition program. Measurement at each point was conducted in three sets, each for 3–5 min. Sampling rate was 100 Hz. All recordings were examined to identify and cut-off those parts of the traces disturbed by very near-local sources, such as passing cars and operator's footsteps. A time window of 80 s was then selected from each recording. Fourier amplitudes were calculated from the obtained waveform for each of the three components at each site and smoothed using a Parzen Window with a bandwidth of 0.1 Hz band. Because there are no significant differences between the two horizontal spectra in all the recordings, the geometric mean of the two horizontal components was calculated to produce the horizontal spectra (Yamanaka et al., 1994). The averaged horizontal component was then divided by the vertical component to obtain the HVSR. For each site, the amplification factor and predominant period were estimated from the HVSR curves, where the former is taken as the peak value of the HVSR curve while the latter is the period corresponding to this peak. For some sites, determination of predominant period was not always straightforward. The different HVSR curves obtained can be categorized into 5 general types, following the classification of Lebrun et al. (2004): (1) sharp, with a peak that is clearly visible and the predominant period is easy to determine; (2) broad, with peak that is not as distinct and the predominant period is taken as that where amplification is maximum; (3) rough, with some amplification displayed but the predominant period is not clearly defined and is taken as the first amplification; (4) double amplification, with two visible peaks, and predominant period is taken as that of the first amplification; and (5) no amplification is visible (Fig. 4). Three maps were then derived: 1) predominant period distribution map; 2) amplification factor distribution map; and 3) Kg value distribution map. The Kg or vulnerability index was introduced by Nakamura (1996) for use in the estimation of earthquake damage on ground surface. Its distribution should supposedly delineate weak areas on the ground. It is given as: 2 Kg = Ag = Fg ð1Þ where Ag is the amplification factor and Fg is the fundamental frequency (1/Tg, Tg is the predominant period). To validate the HVSR results, both instrumental and numerical checks were performed. The latter was done by applying the Standard Spectral Ratio (SSR) technique on selected earthquake events recorded by the accelerometers (K2 digital recorders from Kinemetrics, Inc.) that were installed on 4 sites (3 on soil sites, LCES, ZAMB and CENRO, and 1 on reference station INWD, Fig. 1). Description of the SSR technique can be found in the papers of Lebrun et al. (2004), Lermo and Chávez-García (1994), Gutierrez and Singh (1992), and Chavez-Garcia et al. (1990). Table 1 shows the earthquake events used in the analysis. The intense S-wave part of each record 20 s in length was selected for the calculation. Signal processing followed the same procedure as that for microtremor data. All the earthquake events satisfy the hypocentral distance-to-array aperture ratio of at least 5 suggested by Lacave et al. (1999). Fig. 4. General types of HSVR curves obtained: (1) sharp; (2) broad; (3) rough; (4) double amplification; and (5) no amplification. Classification adopted from LeBrun et al. (2004). M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 145 Table 1 Earthquake events used for the Standard Spectral Ratio (SSR) technique (PHIVOLCS, 2007). No. Date Time (GMT) La Lo Depth (km) Ms (PIVS) RC⁎ NS EW UD Reported intensities (PEIS) 007 20030713 21:12:50.71 18.166 120.658 26 3.6 20030914 18:45:51.7 18.715 120.838 4 4.4 020 20031210 15:51:38.92 17.814 120.655 11 5.0 029 20040312 03:28:58.63 18.063 120.359 31 3.8 065 20041103 15:42:56 18.312 120.403 15 3.5 087 20041228 07:47:08.13 18.383 119.977 5 4.6 14.74 13.98 8.19 67.96 55.03 28.62 12.40 23.27 19.96 9.33 8.88 8.91 11.32 12.63 14.45 7.63 17.53 20.70 17.82 12.01 12.60 9.96 63.77 41.50 29.48 14.74 31.11 28.95 9.78 11.42 8.40 10.92 10.84 10.38 7.36 12.66 15.91 14.64 13.72 10.76 6.28 28.46 29.68 10.25 12.59 10.64 16.45 5.74 5.30 4.46 5.57 6.40 3.95 2.30 10.37 19.37 10.36 III — Pasuquin, Ilocos Norte II — Santa, Ilocos Sur 011 174 20051217 04:00:26 18.255 120.768 1 3.6 INWD LCES ZAMB INWD LCES ZAMB INWD LCES ZAMB INWD LCES ZAMB CENRO INWD LCES ZAMB INWD LCES ZAMB CENRO INWD LCEO ZAMB IV — Pasuquin I.N.; Sto Domingo I.S. III — Santa I.S.; Vigan I.S.; Pidigan, Abra; Callao Caves, Tuguegarao IV — Pidigan, Abra; Santa, Ilocos Sur; Sto Domingo, Ilocos Sur III — Laoag City; Pasuquin I.N. III — Santa, Ilocos Sur III — Laoag City II — Pasuquin; Cabugao I.S.; Sinait I.S. III — Pasuquin Ilocos Norte RC⁎: recording stations; La: latitude; Lo: longitude; PIVS: Philippine Institute of Volcanology and Seismology Seismograph Network; PEIS: Philippine Earthquake Intensity Scale. For the numerical check, 1-D ground response analyses using the SHAKE2000 numerical code were performed on boreholes drilled at or near the accelerometer stations (BH-1, 2, 3, 7 and 8, Fig. 1). The same earthquake events listed in Table 1 were used as input motions, with the earthquake records from the accelerometer station that is nearest to the borehole of interest selected for analysis. Input soil parameters were based on the borehole logs and secondary borehole data. The shear-wave velocity values were Fig. 5. HVSR of hourly measurements of microtremor for 24 h at (A) Laoag City Elementary School (LCES) and (B) Barangay Zamboanga Hall (ZAMB). 146 M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 5. Discussion of results Table 2 Comparison of results of HVSR on microtremor data and SSR on earthquake data. Location LCES ZAMB CENRO 5.1. Stability of HVSR Predominant period (s) Amplification factor HVSR SSR HVSR SSR 0.58 1.02 0.3 0.55 1.02 0.3 5 2 5 4 2.3 15 Table 3 Comparison between the predominant periods (A) and amplification factors (B) obtained from numerical simulation and HVSR technique. Borehole No. Earthquake events 007 011 020 029 065 087 1-D analysis (avg.) HVSR .58 .55 .62 1.02 .63 (A) BH-1 BH-2 BH-3 BH-7 BH-8 .57 .57 .62 1.00 .57 .62 .53 .67 1.05 .62 .62 .62 .62 1.14 .62 .57 .57 .62 1.00 .57 .57 .57 .62 1.00 .57 .57 .57 .62 1.00 .57 .59 .57 .63 1.03 .59 (B) BH-1 BH-2 BH-3 BH-7 BH-8 27.29 26.91 22.88 20.35 21.22 16.34 15.71 17.67 21.23 20.88 15.30 16.55 20.67 10.93 14.36 27.08 26.59 22.56 14.23 21.79 28.81 26.16 25.00 16.08 23.13 25.55 27.05 22.04 12.29 20.52 23.40 23.16 21.80 15.85 20.32 5 .3.1 3.7 2.8 6 obtained from the SPT N-values using the correlation of Ohta and Goto (1978). Layer thicknesses were estimated from the borehole data, as well as from a series of resistivity profiles. Fig. 5 shows the results of stability check on HVSR conducted in LCES ZAMB. It can be seen that in both sites, the H/V spectra consistently identify the predominant period and the amplitudes do not vary significantly. 5.2. Experimental checks Table 2 compares the predominant periods and amplification factors obtained from SSR on earthquake data and HVSR on microtremor data. It can be seen that results of the two techniques generally show a good fit, except for the amplification factors in CENRO. On the other hand, Table 3 shows the results of the numerical simulation in comparison with HVSR results. As can be noticed, the predominant periods obtained using the two techniques show a very good correspondence but large discrepancies exist on the obtained amplification factors. 5.3. Site classification The distribution of predominant period, amplification factor and Kg value in the study area are shown respectively in Figs. 6–8. The correlation of predominant period with geology is immediately evident from Fig. 6. In the hilly area, predominant periods are indeterminable (i.e., H/V spectral curve is flat and does not display any peak). Along the slope, or the transition zone from the hilly part to the floodplain, they range mostly from 0.15 to 0.35, while in the lowland or floodplain areas, Fig. 6. Predominant period distribution map. M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 147 Fig. 7. Amplification factor distribution map. where soil deposits are expected to be thicker and softer, predominant periods are longer. On the other hand, a similar correlation was not obtained between geology and site amplification. For instance, in the hilly and slope area, the amplification factor ranges from 4 to 6, larger than that obtained in the southwestern floodplain but in the same range as that obtained in the northeastern floodplain. The above observations are consistent with the results of the experimental checks where the HVSR technique invariably identifies the site predominant period, but not the amplification level. Several theoretical and experimental studies likewise have similar conclusions (e.g., Latchet and Bard, 1994; Lermo and Chávez-García, 1994; Teves-Costa et al., 1996; Seekins et al., 1996). Because the amplification factor cannot be used to discriminate the different site conditions in the study area, it follows that the Kg value cannot also be used for the purpose since it is simply a derivative of the amplification factor and predominant period. This implies that the findings of Huang and Tseng (2002) are not applicable in Laoag City. Thus, the site classification of the study area and the discussion that follows are based only on predominant period. In the mid-southern portion of the city proper, periods of 0.8–1.0 predominate. Northwards, the predominant periods become shorter. Two boreholes drilled for the construction of a gymnasium/multipurpose center in the northwestern corner of the city proper (BHS-1a and 1b, Fig. 9) confirm this result. At only 2 m from the ground, stiff to hard clay believed to be part of the Laoag Formation is already encountered. West and southwest of the city proper, in the areas corresponding to an old point bar and the delta plain (Figs. 2 and 6), respectively, the predominant periods are mostly greater than 0.8 and even reach values of 1.5 s. Likewise, long periods are obtained in the active sand dune fields. Except in the old point bar, these results are consistent with expectation of loose deposits in these areas, as discussed in Section 3. A possible explanation for the inconsistent results in the old point bar is that the deposits may not have undergone sufficient compaction yet as previously thought. Two shallow boreholes (6 m depth) drilled in the area in relation to the construction of the Central Bus Terminal support this explanation ((BHS-2a and 2b, Fig. 9). As can be seen from the logs, the entire 6 m consist of medium dense sand and therefore still loose enough to be liquefiable. In contrast, the old point bar east of the city proper has shorter predominant period that generally ranges from 0.4 to 0.65 s. This is unexpected since its deposits are inferred to be of the same type and, based on maps and aerial photographs, the same age as that of the western point bar. The resistivity profiles of the study area offer a possible explanation for this unexpected result. From Fig. 10, it can be seen that the Laoag Formation underlying the alluvial deposits can be divided into two layers: (1) the upper weathered clay layer, which varies in thickness from 15 to 40 m; and (2) the lower, more competent sandstone unit, which may be considered as the “engineering bedrock”. Note that the upper weathered layer was interpreted to be part of the Laoag Formation rather than alluvial deposits due to the general absence of intercalating sequence characteristic of fluvial deposits, as displayed by the surface layers. Both the upper and lower layers appear to be differentially weathered. For instance, the upper clay layer grades westward into a less weathered (but more weathered than the sandstone) siltstone unit (VES-14, Resistivity Profile A–A′, Fig. 10). Likewise, the 148 M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 Fig. 8. Kg-value distribution map. sandstone layer appears more weathered in some places and grades into the same siltstone unit. Along section line B–B′, the lower layer is weathered almost entirely into siltstone, except beneath the vicinity of VES-2 where sandstone is found (Fig. 10). This differential weathering depends on the dynamics of the groundwater, which is the main weathering agent underground. Thus, it can be seen that in the city center (VES 11 to VES 12, Resistivity Profile A–A′, Fig. 10), the sandstone layer can be reached at a depth of about 35 m to 40 m. On the other hand, in the zone of active channel migration encompassing the delta plain and the western old point bar (VES-8 to VES-4, Resistivity Profile B–B′, Fig. 10), this layer is not reached at the limit of the sounding depth. Aside from the difference in the stiffness of the deposits, this difference in thickness of soil profile (alluvial plus residual) must have contributed to the difference in the predominant periods obtained in the two areas. In the same manner, the difference in the soil profile thickness may explain the difference in the predominant periods obtained in the western and eastern old point bars. Note that in the VES-2 area (Resistivity Profiles A–A′ and B–B′, Fig. 10) where the eastern old point bar is located, the alluvium deposits directly overlie the sandstone layer. Soil thickness in this area is only about 10 m. In comparison, the sandstone layer was not reached at the limit of the sounding depth in the VES-13 area where the western old point bar is located (Resistivity Profiles A–A′, Fig. 10). The total thickness of the alluvial and residual soil therefore is greater than 50 m. The active point bars in general have much shorter predominant periods than the delta plain and sand dune area, ranging only from 0.55 to 0.65 although they can also reach higher values of 0.8 to 0.9 in some areas. This is also quite unexpected since they are inferred to be also underlain by loose deposits as the latter areas. Boreholes drilled on these bars confirm the variability of the density of the deposits (e.g., BHS 3, 4 and 5, Fig. 9), although they are generally dense to medium dense. These dominantly sand deposits may contain considerable amount of gravel (Figs. 9 and 11), which may account for their relatively higher density. The site classification map shown in Fig. 12 summarizes the above discussion. Note that the terms “stiff” and “soft”, which are technically used to describe the state of density of clay soils, are also used here to describe “dense” and “loose” sand deposits, respectively. 5.4. Integrated liquefaction hazard map Combining the liquefaction susceptibility map with the site classification map produced an integrated liquefaction hazard map of Laoag City shown in Fig. 13. Since each zone may have varying type of soil deposits with varying densities and thicknesses, liquefaction susceptibility was given in range rather than by single qualitative description. The north–northeast portion of the Laoag City proper is now classified as having a lower susceptibility to liquefaction than the south–southwest portion, whereas in the preliminary susceptibility map these areas were considered as one and given a moderate susceptibility rating. Following indications that the western old point bar is underlain by thick soil deposits that may not be sufficiently compacted, its susceptibility was also changed from moderate to highto-very high except the small portion towards its northeastern end. Thick sand dune/abandoned beach ridge deposits can be found 149 Fig. 9. Logs of selected boreholes. M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 150 M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 Fig. 10. Selected resistivity profiles of the study area (refer to the legend of Fig. 1 for the locations of survey lines). M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 151 moderate susceptibility ranking assigned to these point bars. In contrast, the sand deposits of the delta plain (Barangay Zamboanga and Bencag), which were classified as having high to very high susceptibility, repeatedly liquefied both during strong and weak earthquakes. 6. Summary and conclusions Fig. 11. Trial pit on the present point bar. Note the significant gravel content of the dominantly sand deposits. underneath this part of the bar, which apparently are aged and compacted enough and therefore classified as stiff to medium stiff soil. On the other hand, the relative susceptibility ranking of the active point bars is now lower than earlier assumed since it appears that the deposits are generally in a medium dense to dense state due to the significant amount of gravel they contain. The ranking of all other units remain essentially the same. To check the validity of the integrated liquefaction hazard map, the historical seismicity records of Laoag City (SEASEE, 1985; PHIVOLCS, 2003) were reviewed for possible indications of liquefaction occurrences. Also, interviews with local residents were conducted for supplementary data. Records revealed that liquefaction may have been triggered in at least 4 sites in the study area during 5 earthquake events. These liquefaction cases were plotted on the integrated map (Fig. 13). Note that some accounts of liquefaction that could not be plotted due to lack of reference points. Also, the plots only included those cases where the occurrence of liquefaction was clear, as for example when development of sandboils was reported. As can be noted, all the historical liquefaction cases occurred on areas classified as moderately to highly susceptible to liquefaction, thus validating the integrated map. Even when the sites of liquefaction cannot be exactly located, accounts of their occurrence nevertheless support the susceptibility ranking given in the map. For instance, the “differential settlements observed on most building sites” during the 1983 August M = 6.5 event could have only been in the southern portion of the city proper since buildings are present only in this part of the city. Moreover, apparently referring to the active point bars, riverbanks were reported to have developed “irregular cracks and fissures” during the same earthquake event. However, during less intense shaking, no such observations had been made. This indicates that since the deposits are relatively dense, they need a stronger (and probably longer duration) earthquake to liquefy, validating the Microtremor, a tool commonly used in site effect estimation, was employed in this study to obtain information on the characteristics of subsoils in Laoag City. Measurements were performed on some 168 points and, using the HVSR or Nakamura technique, the predominant period and amplification factor at each point were determined. Kgvalue, a derivative of the two mentioned site effect parameters and supposedly an index of the vulnerability of the ground to earthquake hazards, was also estimated. Of the corresponding distribution maps that were generated, only the predominant period distribution map correlates well with the geology of the study area. This observation is supported by the experimental checks performed, wherein results show that the HVSR technique reliably identifies the site predominant period, but not the level of amplification of the ground. Thus, the site classification map derived in this study was only based on the predominant period distribution map. The site classification map was then combined with the preliminary liquefaction susceptibility map derived using the geomorphological criteria to generate an integrated liquefaction hazard map of Laoag City. This map is deemed more accurate in depicting relative liquefaction susceptibility since it combines information on the distribution of potentially liquefiable soils in terms of geology and grain characteristics with information on the stiffness and thickness of these soils. With information about the thickness of the deposits, an idea of the severity of liquefaction-related damage can also be gathered since thicker deposits relate to more serious damage. Moreover, together with soil stiffness, soil thickness controls the amplification and duration of ground shaking, which are among the important factors controlling liquefaction occurrences. Borehole data and resistivity profiles of the study area support the validity of the integrated liquefaction hazard map. As a further validation, historical earthquake records of the study area were reviewed for indications of past liquefaction occurrences. These historical liquefaction cases plotted on areas that were identified as highly to moderately susceptible to liquefaction. Thus, it can be concluded that with the use of microtremor, the accuracy of liquefaction susceptibility evaluation and zonation is much improved. Note that commonly, improving the accuracy of geologyand geomorphology-based liquefaction susceptibility map is accomplished by supplementing it with subsurface data (e.g., SPT, CPT, shearwave velocity data). With a large set of subsurface data, the extent of liquefiable deposits within each geomorphological unit can further be delineated. This approach, of course, can be expensive and therefore not always possible especially in less-developed countries like the Philippines. Thus, commonly, extrapolations are simply made from limited and scattered subsurface data and similar subsurface conditions are just assumed for the same geologic/geomorphic units. The resulting map is therefore still largely based on geology and geomorphology. However, even a voluminous subsurface data may also not necessarily deliver the level of accuracy expected. This is especially true in a dynamic system like the fluvio-deltaic environment of Laoag City where the subsoils are inherently very heterogeneous spatially. As can be noted from the borehole data, the type and stiffness of soil can change dramatically within only a few meters. Moreover, due to the cost involved, most subsurface exploration do not comprise the entire soil profile, particularly in areas where sediments are thick. Thus, they do not provide information on deeper layers which can potentially amplify and extend the duration of ground motion. 152 M.A.A. Beroya et al. / Engineering Geology 107 (2009) 140–153 Fig. 12. Site classification map. For regional liquefaction hazard mapping, therefore, microtremor data may be more useful than other subsurface data in providing information on subsoil conditions, particularly since measurements can be done in a much denser array due to the low cost involved. 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