Versão online: http://www.lneg.pt/iedt/unidades/16/paginas/26/30/185 Comunicações Geológicas (2014) 101, Especial II, 893-896 IX CNG/2º CoGePLiP, Porto 2014 ISSN: 0873-948X; e-ISSN: 1647-581X
Site Effect Studies in the Lower Tagus Region Estudos de Efeitos de Sítio no Vale Inferior do Tejo R. Dias1*, J. Carvalho1, C. Pinto1,2, J. Leote1, S. Vilanova3, J. Narciso3 R. Ghose4
Abstract: The Lower Tagus Valley region of central Portugal mainland is located about 350 Km from the Eurasian-African plate boundary. It is characterized by low slip-rates (<0.4 mm/year) and a moderate seismicity, occasionally shaken by some important historical earthquakes causing significant damages and economical losses. The most well know damaging earthquakes occurred in 1344, 1531, 1755, 1909 and 1969. The seismic hazard evaluation and mitigation is therefore of great importance to this densely populated area. This paper focuses on the evaluation of P-wave and S-wave seismic velocities of the near surface using seismic refraction data interpretation and in-situ lithostratigraphic studies to obtain the first detailed VS30 and soil classification maps based on shear wave velocity. Hundreds of available boreholes drilled for engineering (with SPT data) and water supply were used to confirm layer thicknesses and lithologies at depth. The soil classification is based upon the European Code 8 for civil engineering which was carried out for land use planning and design of critical facilities. Keywords: Lower Tagus Valley, Seismic refraction, SPT, VS30, Soil classification. Resumo: A região do Vale Inferior do Tejo situa-se a cerca de 350 km da fronteira de placas Eurásia-Africana. É caracterizada como uma zona de sismicidade moderada e taxas de deslizamento baixas (<0,4 mm/ano) mas historicamente tem sido afetada por terramotos que causaram importantes perdas materiais e de vidas. Os terramotos mais importantes ocorreram em 1344, 1531, 1755, 1909 e 1969. É pois importante avaliar a perigosidade e risco sísmico desta região, de forma a mitigar os efeitos destes sismos destrutivos. Neste trabalho efetuou-se a caraterização dos solos superficiais na região através da determinação das velocidades das ondas sísmicas longitudinais e de corte obtidas a partir de perfis de sísmica de refração e estudos litostratigráficos de detalhe, que permitiram a elaboração dos primeiros mapas detalhados de classificação de solos e de VS30 baseados na velocidade das ondas de cisalhamento As litologias e espessuras das camadas foram corroboradas através de centenas de sondagens de captação de água e geotecnia (com dados de SPT). A classificação de solos baseou-se no Eurocódigo 8 para a engenharia civil, estabelecida com vista ao ordenamento do território e a construção de estruturas críticas. Palavras-chave: Vale Inferior do Tejo, Refração sísmica, SPT, VS30, Classificação de solos.
1Laboratório Nacional de Energia e Geologia, Amadora, Portugal 2Landmark, Londres, Inglaterra 3Instituto Superior Técnico, Lisboa, Portugal 4Delft University of Technology, Delft, The Netherlands. *Corresponding author / Autor correspondente: [email protected]
1. Introduction
The study area is located in an intraplate region under the influence of the generally E-W trending Eurasian-African plate boundary. Slip rates in the study area are below 0.4 mm/year (Cabral, 2012) but in the last 1000 years the Lower Tagus Valley region has been struck by several destructive earthquakes with estimated magnitudes above 6 (e.g. see Besana-Ostman et al., 2012, Cabral et al., 2011 and references therein).
Several authors have recognized the importance of the thick Cenozoic cover of the region (e.g, Carvalho et al., 2006) and also of local site effects in the fabric of the seismic intensities observed during historical earthquakes (e.g. Teves-Costa & Batló, 2011). Site effect studies require the geodynamical characterization of the shallow layers. Near surface P-wave and S-wave seismic velocities provide valuable information for studies of ground motion behavior, natural frequencies and the liquefaction potential under earthquake (e.g. Bauer et al., 2001; Fumal & Tinsley, 1985).
When macroseismic data or earthquake records are not available, this information is even more relevant. Different methods for estimating shear waves can be used, such as borehole logging, surface wave inversion or seismic refraction profiles. The latter method is an expeditious and economical method capable of providing average values of shear wave velocities, which present a great lateral variability in the shallow layers (Ghose & Goudswaard, 2004).
The main goal of this work is to provide information about the geomechanical properties of the subsurface, using P and S wave velocities from refraction studies and geotechnical information. For each profile location careful geological and lithological studies were carried out and all available wells were analyzed, assuring a good control of the litho-stratigraphic column. VS30 and a soil classification based on the Eurocode 8 (Penelis, 1997) were estimated from shear wave velocity, layer thickness and standard penetration tests (SPT) information. The preliminary results allowed producing maps that can be used in the design of critical facilities, land use planning and estimated losses under the effect of an earthquake.
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2. Seismic refraction data acquisition and interpretation
The location of the refraction profiles was selected according to logistics and the location of existing geotechnical soundings. All Neogene and Quaternary formations were sampled at least once. A total of 35 locations was selected (Fig. 1).
To reach an investigation depth of about 30 m required for VS30 estimation, a profile length of 84 m was used with 24 vertical and 24 horizontal receivers spaced 3.5 m. Offset shots and shots inside the receiver layout were carried out to achieve a good control of the uppermost low velocity layer. The sources used were a 5 kg hammer and (1) a plate, for P-wave surveys, and (2) a 3 m wide wooden beam coupled under the wheels of a jeep, for S-wave.
In the S-wave records, strikes from the opposite side of the beam are usually summed with polarity reversal of one of the strikes, in order to eliminate P-wave contamination (Hasbrouck, 1991). For first arrival picking, strikes from both sides of the wooden beam were used and compared.
Interpretation of P and S wave refraction data was done with commercial software using the Generalized Reciprocal Method (GRM, Palmer, 1981) combined with the intercept-slope method. In the interpretation we used available nearby (< 1 km) wells and a detailed geological survey was carried out at all sites, ensuring an adequate lithological control. In this task were used hundreds of wells drilled in the study area for water supply and geotechnical studies, covering almost all the geological formations of the study area (Hydrogeology Department of LNEG). Information of water table depth was also gathered.
All this information was collected, georeferenced and integrated in a GIS together with geological data. SPT values were used (tests were performed every 1 or 2 m) when available to correlate with estimated seismic refraction velocities and geological data or to estimate bedrock thickness, when the basement was not detected with refraction data.
Each profile was interpreted considering the limitations of the refraction method such as velocity inversions or the hidden layer problem (e.g. Palmer, 1981). Using this methodology we were able to derive an appropriate relation between seismic velocities and geological formation, lithology, age and depth of burial.
The measured seismic velocities for P-waves varied from 150 m/s to 740 m/s and 490 m/s to 2280 m/s respectively for the first and second layers. The S-wave velocities observed in the transverse receiver component ranges were 84 m/s-690 m/s and 140-1160 m/s respectively for the shallowest and second layers. For the first layer VP/VS ratios ranged from 0.60 to 6.07. We attribute this unrealistic VP/VS values for the first layer to the presence of air, organic matter among other materials. Velocity errors estimations also possibly contributed at a smaller scale to these incorrect values. In the second layer, velocity ratios range from 1.51 to 7.32. The determined values of VP/VS ratios are compatible with those found in the literature for similar shallow sediments (e.g. Salem, 2000; Lankston, 1989).
For some of the profiles the layers interface depths for the P and S models differ greatly. The presence of a shallow water table is, in some cases, the explanation for the observed differences. When the water table is very shallow, the profiles present the highest VP/VS ratios. Profiles VFX5, PAN46 and PSE49 e.g. (Table 1), acquired over alluvium sediments with a very shallow (1 m) water table, present, for the second layer, very high VP/VS ratios (up to 9), similar to those found for totally saturated shallow unconsolidated or clayish sediments (Salem, 2000; Lankston, 1989). For other profiles, the interfaces depth discrepancy can be attributed to the different properties that P-waves and S-waves respond to.
3. Application to VS30 and soil classification maps
For the calculation of VS30 values the formula of Borcherdt (1994) was used. Figure 1 shows the obtained VS30 color coded data points overlaid to a geological map. This figure clearly demonstrates the complex task and extensive resources demand for producing a VS30 map based only in geological maps. Due to lithological and thickness lateral variations it became impossible to correctly generalize a VS30 velocity for a particular lithology.
Therefore, a great number of velocity measurements should be used to produce a detailed VS30 map of the study region. For the moment we choose to plot data points with correspondent color coded value and not a gridded map that would lead to erroneous information. However, a careful geological characterization and wells data analysis (to address lateral, thickness and lithological changes) would help to reduce the problem.
The central area of the study region that surrounds the Tagus River presents the lowest VS30 values and corresponds to Holocene alluvial sediments. Several cities are located in this region stressing the need to apply strict engineering rules. Other villages and cities located on Miocene sediments, such as the district capital Santarém present some areas with relatively low VS30 values and should also be areas of concern.
Soil classifications determine the level of reinforcement of engineering structures and are a useful form to mitigate the effects of an earthquake (Penelis, 1997). In these engineering soil classifications, soil conditions are traduced by shear-wave velocity and layer thickness. Here we present a classification based on Eurocode 8. Due to problems in determining the bedrock in a few refraction profiles, SPT values were used, when available, to determine the presence of this unit and also to characterize the soil classes. In opposition to the original classification (Penelis, 1997) we propose the inclusion of SPT values in our subsoil classification.
The criteria used are shown in table 2 and the soil classification is presented in figure 2. Similarly to the VS30 calculations, the soil classification attempted for the region is highly affected by the lithological and thickness changes of the Cenozoic sediments and we also opted to plot color coded data points and not a gridded map until more data is collected.
Nevertheless, the observation of the preliminary soil classification map (Fig. 2) confirms VS30 map analysis and stresses the need of addressing engineering measures in the
Site Effect Studies in the Lower Tagus 895
central region of the study area. Please note that some areas of the Miocene sediments that were expected to have a low risk,
fall under soil class B and due to focusing and defocusing basin effects may present a serious seismic risk.
4. Conclusions
In this work P-wave and S-wave velocities were obtained from seismic refraction profiles that together with geological and SPT data provided the characterization of the geological formations of the area. In the absence of macroseismic data or earthquake records, these techniques are traditional and solid approaches of acquiring information for site effects and microzonation studies. Well’s data and detailed geological surveys at each profile location allowed to overcome refraction data interpretation limitations, such as velocity inversion and hidden layer problems. This characterization was used not only to produce a subsoil classification but to estimate VS30, from which site effects can be evaluated.
We conclude, at this first phase of the study, that the strong lithological variation of the Cenozoic sediments of the study area where thickness and lateral changes occur prevents a simplistic geographical generalization of the velocity and
soil classification data points. The preliminary results presented here strongly advise the acquisition of additional velocity measurements and a careful geological analysis of its results in order to produce detailed VS30 and soil classification maps.
Nevertheless, preliminary VS30 and the soil classification maps presented here highlight a region of great susceptibility to earthquake shaking, where several small towns and villages are located. This region is covered by Holocene alluvial sediments, with liquefaction potential, but other areas located over older geological formations also show a relatively moderate to high risk.
The data presented here, used in conjunction with peak ground accelerations and seismic intensities constitute an important improvement in the seismic risk evaluation and mitigation in the study area and will provide important information in land use planning and civil protection management.
Fig. 1. Location of the 35 shear wave refraction profiles over a simplified 1:1 000 000 geological map (adapted from LNEG, 2010) and plot of VS30 data points calculated with seismic refraction velocities. Fig. 1. Localização dos 35 perfis de refração S sobre um mapa geológico simplificado de 1:1 000 000 (adaptado de LNEG, 2010) e a representação dos pontos com medições de VS30 obtidas a partir das velocidades de refração.
Fig. 2. Plot of soil classification data points based on the classification of Penelis (1997). Data is overlaid to simplified 1:1 000 000 geological map (adapted from LNEG, 2010). Fig. 2. Representação dos pontos com a classificação de solos (Penelis, 1997), sobreposta ao mapa geológico simplificado de 1:1 000 000 (adaptado de LNEG, 2010).
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Table 1. Location of the seismic refraction profiles (UTM, Zone 29N, WGS84).
Tabela 1. Localização dos perfis de sísmica de refração (UTM, Zona 29N,
WGS84).
Table 2. Criteria used in the soil classification.
Tabela 2. Critérios usados na classificação de solos.
SUBSOIL CLASS CRITERIA 1 CRITERIA 2
A Rock or geologic formation characterized by Vs >= 800 m/s.
Compact deposits of sands, gravels or over consolidated clays, several tens of meters thick (Vs >= 400 m/s at 10 m depth).
B
Deep deposits of medium dense sands, gravel or stiff clays with thickness from several tens to hundreds of meters (Vs >= 200 m/s at 10 m depth to Vs >= 350 m/s at 50m depth (SPT N~60).
C
Loose cohesionless deposits with or without soft cohesive layers (Vs < 200 m/s at depths <20m (SPT N<=10).
Deposits with soft-to-medium stiff cohesive soils (Vs < 200 m/s at depths <20m (SPT N<=10).
Acknowledgments
This work was funded by Foundation for Science and Technology trough NEFITAG (PTDC-CTE/GIX/102245/2008) and SCENE (PTDC-CTE/GIX/103032/2008) projects. The authors also acknowledge the field crew: J. Gomes and F. Caneiras. The authors acknowledge the reviewers for their improvements.
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