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BY-NC-ND 3.0 license Open Access Published by De Gruyter Open Access November 6, 2016

NEHRP Site Classification and Preliminary Soil Amplification Maps of Lamphun City, Northern Thailand

  • Thanop Thitimakorn EMAIL logo and Thanabodi Raenak
From the journal Open Geosciences


The primary goal of this study is to generate the NEHRP soil classification map for Lamphun City using the average shear wave velocity values (Vs(30)) derived from the multi-channel analysis of surface wave (MASW) data. The secondary goal is to use the Vs(30) data to create the preliminary site amplification map of the city. For this work, multi-channel surface wave seismic data were acquired at 48 preselected sites in the Lamphun City area, northern Thailand. After generating the NEHRP map, soil class D is found to be present mostly in the northern part of the area, while soil class C is found mostly in the southern part. A major part of the Lamphun City is located on soil class D. The soil amplification map indicates higher amplification in the east, north and west of the city, where the soils consisted of mostly soft sediments from the alluvial plain and river terrace. The central and south eastern parts of Lamphun City had a relatively low amplification, perhaps because the sediment in this part is relatively thin or the bedrock is shallow. The results of study imply that the major part of Lamphun city may experience earthquake ground shaking due to amplification of the soft soils.

1 Introduction

Most unconsolidated materials amplify earthquake ground motions, and this can affect the stability of structures far from the epicenter of the earthquake. Mapping the areas where soil amplification is likely to occur is very important. Geophysical methods have been used to determine the shear-wave velocity (SWV) for earthquake hazard mapping for many years. In this study, we use the multi-channel analysis of surface wave (MASW) approach that was developed by the Kansas Geological Survey to determine the average SWVs of soils [1]. The technique is similar to the single-channel analysis of surface wave (SASW) method used in the engineering community, except that the MASW method employs several receivers to detect the Rayleigh waves (ground roll).

The MASW data were acquired at 48 representative sites in Lamphun City in northern Thailand (Figure 1). The primary goal of this study was to use the SWV derived from the acquired MASW data to generate the NEHRP (National Earthquake Hazards Reduction Program) site classification map of the Lamphun City area. The NEHRP is a national agency of the United State of America who provide the recommended provision for seismic regulations for new buildings and other structure. The resulting map will help the city assess its earthquake shaking vulnerability and mitigation. The secondary goal is to use the Vs(30) data for creating the preliminary site amplification map of the city using the [2] relation.

Figure 1 Location of Lamphun City, Northern Thailand.
Figure 1

Location of Lamphun City, Northern Thailand.

2 Geologic setting

Lamphun City is located in the northern part of Thailand, approximately 670 km north-northeast from Bangkok and 20 km south of Chiang Mai. The city is situated on the Quaternary sediments of the Kuang and Mae Ping River basins at an average elevation of 580 m above mean sea level. The study area was 120 km2 and covered almost the entire city area. The geological map of the study area is shown in Figure 2. Sedimentary rocks such as limestone and classtic rocks are mainly found in the western part of the study area and also exposed on some small hills in the middle of the area.

Figure 2 The geological map of the study area and the MASW test sites (Red dots).
Figure 2

The geological map of the study area and the MASW test sites (Red dots).

Figure 3 Active faults (black lines) in Northern Thailand [12].
Figure 3

Active faults (black lines) in Northern Thailand [12].

The Quaternary sediments found in the area can be divided into two units, as shown in Figure 2. The alluvial plain (Qa) unit is found on or nearby the Kuang River channel and consists mainly of sand and silt with some clay. The Qa unit is also found in the eastern part of the area. The terrace (Qt) unit consists of mostly gravel and sand and is found at the western side of the area. However, the colluvium soil unit can also be found near the foot of the hill and mountain.

In seismic terms, Lamphun City is located in a low to medium seismic hazard area and there have been several historic records of earthquakes in the area [3]. The most recent earthquake was a Mw 6.3 on May 16, 2007 with the epicenter located about 100 km to the east of Lampoon City in the northern part of P.D.R. Laos. This earthquake caused damage to several buildings in Lamphun city. The active faults in northern Thailand and the vicinity are shown in Figure 3. The Mae Chan fault is considered to be the major threat to the city because it can produce an earthquake up to Mw 6 [4], while the soils underneath the city can amplify earthquake ground motion up to three times [5]. Moreover, the unconsolidated sediments in some areas of the city can be subjected to liquefaction by a nearby earthquake up to Mw 5 [6].

3 NEHRP site classification and soil amplification

Several methods for classifying soils and rock based on their site-dependent amplification properties have been proposed [7-11]. For example, the site amplification can be characterized using the average SWV to a depth equal to one quarter of the wavelength of the dominant frequency of interest [9]. However, this method has not been widely used, probably because it is relatively difficult to apply. In a recent study, [1] simplified the method by demonstrating a correlation between the ground motion amplification and the average SWV of the upper 30 m of sediments and/or rocks, and this has since been incorporated into the NEHRP program. The current NEHRP approach categorizes soils into six classes (A–F) based on their vertical SWV profile, thickness and liquefaction potential.

For the purpose of earthquake hazards investigations, according to the NEHRP guidelines, the SWV of the sub-surface must be measured or estimated to a depth of 30 m. The NEHRP SWV (Vs) assigned to the subsurface at a specific site is calculated using Eq. (1):


where V¯s is the NEHRP SWV, vsi is the SWV of any layer in m/s, and di is the thickness of any layer (between 0 and 30 m).

Table 1 shows the site soil profile classification system used by NEHRP. In (year of study of [13]) [13] evaluated the use of the average SWV in the upper 30 m. According to their work, attenuation affects ground motions as much as the SWV, particularly for deeper geologic deposits. Although attenuation is not directly included in the current NEHRP provisions, it is accounted for in seismic hazard maps.

Table 1

Soil profile type classification for seismic amplification [14].

NEHRP soil typeGeneral descriptionAverage SWV to 30 m (m/s)
AHard rock> 1500
BRock760 < Vs ≥ 1500
CVery dense soil and soft rock360 < Vs ≥ 760
DStiff soil 15 ≥ N ≥ 50 or 50 kPa ≥ Su ≥ 100 kPa180 ≥ Vs ≥ 360
ESoil or any profile with more than 3 m of soft clay defined as soil with PI > 20, w > 40% and Su < 25 kPa.≥ 180
FSoils requiring site-specific evaluations

Note: N: SPT blow count, Su: Undrained shear strength, PI: Plasticity index, w: water content

When planning residential areas, it is very important to determine the possible soil amplifications caused by earthquakes in terms of the need for earthquake-resistant designs. Soft soils increase the earthquake energy during an earthquake and are responsible for a large share of the earthquake damage. In this study, the SWV data obtained by the MASW approach were used to determine the probable soil amplification of the soils in the Lamphun City area, since the SWV is known to be an index property to evaluate the soil amplifications. The SWV and soil amplification (A) relationships [2] are given in Eqs. (2) and (3):

A=68Vs(30)0.6(Vs < 1100m/s)(2)

where A is the soil amplification and Vs(30) is the average SWV in the upper 30 m.

4 MASW technique

The surface wave (Rayleigh wave) has traditionally been viewed as an unwanted signal in conventional seismic surveys, and as such is normally discarded during data processing. Rayleigh waves travel along or near the ground surface and are typically characterized by a low velocity, low frequency and high amplitude [15]. By inverting the fundamental mode of the Rayleigh wave, the Vs profile of the soil column can be determined.

The MASW method was first introduced into the geotechnical and geophysical community in early 1999 [1]. This seismic method generates a one-dimensional (1-D) vertical SWV (Vs) profile by analyzing the Rayleigh surface waves on a multi-channel record. The method utilizes energy commonly considered to be noise on conventional seismic surveys. The acquisition of the 1-D MASW data is similar to conventional seismic data acquisition (Figure 4). Generally, 24 low-frequency vertical-component geophones, placed at X2 intervals, are centered on each test location. The impact source is at X1 and is typically either a sledge hammer (as in this study) or an acceleratedweigh drop. The seismic signal is then detected by the geophones and sent to the seismograph for recording and display.

Figure 4 MASW data acquisition field setup.
Figure 4

MASW data acquisition field setup.

The processing steps of the MASW data are shown in Figure 5. Each set of Rayleigh wave data (24 channels data set for each station location) was transformed from the time domain into the frequency domain using the fast Fourier transform technique. These field-based data were then used to generate site-specific dispersion curves (phase velocity versus frequency) for each station location and then transformed into vertical 1-D SWV profiles (MASW SWV profile) by inversion as reported previously [1].

Figure 5 MASW data processing steps. (a) Surface wave shot gathering, (b) the corresponding dispersion curve and (c) the inverted SWV profile.
Figure 5

MASW data processing steps. (a) Surface wave shot gathering, (b) the corresponding dispersion curve and (c) the inverted SWV profile.

In this study, the MASW data were collected at 48 sites throughout the study area (Figure 2) with a 24-channel geode engineering seismograph using 24 individual 4.5 Hz vertical component geophones spaced at 2 m apart from each other. A 14-lb sledge hammer was used as the source and was struck on the ground plate at 10 m from the first geophone. The acquired Rayleigh wave data were processed using the Kansas Geological Survey software package SURFSEIS. The field-based Rayleigh wave data were used to extract the dispersion curves for each test site that were then transformed into vertical 1D-SWV profiles through an inversion method. Inversion from the dispersion curves was performed in a fully automated mode [1].

At each test location, at least 3 seismic data files were acquired and each of these data was then used to determine the dispersion curve. The seismic data that provided us with the best quality of dispersion curve and frequency ranges was selected for inversion to get the best shear wave velocity profile. In this strategy, at each test location, there was only one Vs profile which came from the best seismic data.

The reliability of the inverted SWV profile can also be demonstrated by observing the final %RMS error. Figure 6 shows the plot between %RMS errors from the final iteration of the inversion process and test site number. It can be seen that the %RMS errors of all test sites are generally below 10%. From the results of the %RMS errors, we can conclude that the SWV profiles derived from the inversion process are acceptable for developing the NEHRP map of the study area. The maximum depth of penetration of each MASW test site is shown in Figure 7. The depth of penetration of all the test sites is greater than 30 m. So, it can be ensured that the averaged values of SWV of each test site are also reliable. As seen on the map, soil class D is present in the northern part of the area, while soil class C in situated mostly in the southern part. However, a major part of the city is situated on soil class D. From the NEHRP recommendation, soils with lower SWV values (i.e. towards class F and away from class A) will experience more earthquake ground shaking than bedrocks due to the wave-amplifying properties of the soil. This means that most part of Lamphun City will more or less experience soil amplification from earthquake ground motion.

Figure 6 The plot of %RMS error from the final iteration against the test site number.
Figure 6

The plot of %RMS error from the final iteration against the test site number.

Figure 7 Plot of maximum depth of pen etration of each MASW test site.
Figure 7

Plot of maximum depth of pen etration of each MASW test site.

5 Vs(30) and NEHRP site classification map

To create the NEHRP map, the Vs(30) of each test site was calculated using Eq. (1) and the obtained Vs(30) values were also used to classify the soil (class A–F) based on the recommendations of the 2003 National Earthquake Hazards Reduction Program (NEHRP), as shown in Table 1. The Vs(30) and soil type of each test sites is shown in Table 2. Finally, the NEHRP site classification map was generated. The Vs(30) map (Figure 8) revealed that there are only two soil classes (class C and D) in the study area (Figure 9).

Table 2

MASW test location, Vs(30), soil type, and NEHRP site class of Lamphun City.

Test No.LatitudeLongitudeVS(30), m/sSoil TypeNEHRP ClassTest No.LatitudeLongitudeVS(30), m/sSoil TypeNEHRP Class
118.555199.0435329Terrace (Qt)D2518.592699.0365381Alluvium (Qa)C
218.556999.0408471Terrace (Qt)C2618.614999.0286318Alluvium (Qa)D
318.561499.0345348Alluvium (Qa)D2718.662799.0243269Alluvium (Qa)D
418.564499.0303381Alluvium (Qa)C2818.597698.9878200Alluvium (Qa)D
518.566099.0282413Alluvium (Qa)C2918.569598.9632263Alluvium (Qa)D
618.568699.0241362Alluvium (Qa)C3018.531998.9431374Alluvium (Qa)C
718.571499.0176308Alluvium (Qa)D3118.534898.9717293Alluvium (Qa)D
818.572699.0140294Alluvium (Qa)D3218.523099.0259623Terrace (Qt)C
918.573699.0107370Alluvium (Qa)C3318.535699.0148679Alluvium (Qa)C
1018.583898.9928339Alluvium (Qa)D3418.491698.9886346Terrace (Qt)D
1118.587198.9871246Alluvium (Qa)D3518.476098.9758391Alluvium (Qa)C
1218.588298.9849307Alluvium (Qa)D3618.466198.9668367Terrace (Qt)C
1318.590998.9800271Alluvium (Qa)D3718.500398.9531540Alluvium (Qa)C
1418.592498.9775270Alluvium (Qa)D3818.560598.9956259Alluvium (Qa)D
1518.593998.9746241Alluvium (Qa)D3918.576099.0013303Alluvium (Qa)D
1618.597198.9681216Alluvium (Qa)D4018.567899.0046304Alluvium (Qa)D
1718.621398.9784256Alluvium (Qa)D4118.583199.0146260Alluvium (Qa)D
1818.482999.0551230Alluvium (Qa)D4218.643599.0386331Alluvium (Qa)D
1918.528399.0946267Terrace (Qt)D4318.638099.0238264Alluvium (Qa)D
2018.563999.1132272Terrace (Qt)D4418.637999.0142271Alluvium (Qa)D
2118.600299.1215278Terrace (Qt)D4518.626999.0024349Alluvium (Qa)D
2218.611599.0867370Terrace (Qt)C4618.533698.9978313Alluvium (Qa)D
2318.579999.0731308Terrace (Qt)D4718.511498.9778374Alluvium (Qa)D
2418.567699.0646345Terrace (Qt)D4818.527398.9645290Alluvium (Qa)D

Figure 8 Maps of the (a) Vs(30) of Lamphun City.
Figure 8

Maps of the (a) Vs(30) of Lamphun City.

Figure 9 Map of NEHRP site classification of Lamphun City.
Figure 9

Map of NEHRP site classification of Lamphun City.

6 Preliminary site amplification map

The site amplification map was also generated based on Vs(30) using the relationship provided by [2], and is shown in Figure 10. The soil amplification value ranged from 1.4 to 2.8, with a higher amplification in the east, north and west where the soils are mostly soft sediments from the alluvial plain and river terrace. In the central and south eastern part of Lamphun City, the amplification is relatively low, presumably because the sediment thickness in this part is relatively thin or the low impedance contrast between the sediments and the underling bedrock at this part of the city area.

Figure 10 Variation in the soil amplification at Lamphun city.
Figure 10

Variation in the soil amplification at Lamphun city.

7 Conclusion

This study presented the SWV distribution of soils throughout the Lamphun City area. The SWV profiles were determined using the MASW method from data collected at 48 sites selected to cover the city area as much as possible. The SWV profiles of each test site were then used to calculate the Vs(30) values and the NEHRP site classification was assigned for each test site. Based on the site classification map, we conclude that the Lamphun City area that is located on soil class D is under substantial risk of soil amplification.

The SWV obtained by the MASW method were used to determine the probable soil amplification of soils in the Lamphun City area using the SWV and soil amplification (A) relationships [2] given in Eqs. (2) and (3). The study revealed that soil amplification in Lamphun City is high in the east, north and west part of the city but low in the central and south part. This is supported by the geological data, as the sediments in the east, north and west are mostly young sediments from rivers and hills, while in central and south-east the sediment may be thin or the bedrock very shallow.

The NEHRP site class and soil amplification maps presented in this study provide preliminary information on the soil conditions of the city that can be used for city planning. Although the map represents the first of its kind of the area, it has some limitations. The MASW test sites were not distributed uniformly throughout the study area due to budget constraints and the difficulty of acquiring MASW data in highly populated areas. These limitations should be borne in mind when using this map, particularly when dealing with site-specification evaluation in the city area.


This research was supported by the Ratchadaphiseksomphot Endowment Fund 2013 of Chulalongkorn University (CU-56-524-CC). The authors also thank all the students for their help during the field data acquisition.


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Received: 2015-12-1
Accepted: 2016-4-20
Published Online: 2016-11-6
Published in Print: 2016-1-1

© 2016 T. Thitimakorn and T. Raenak, published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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