GST Journal 2010-2011 V.1

วารสารสมาคมธรณีวิทยาแหงประเทศไทย JOURNAL OF THE GEOLOGICAL SOCIETY OF THAILAND

2010 - 2011

ISSN 1513 2587

volume 1

1. Provenance of a Black Sand Deposit in Laem Ngob District, Trat Province, Eastern Thailand_________________________________________________________________________1 2. Understanding of Sulfate-Formation Related Sinkhole Occurrence from an Integrated Geoscientific Study______________________________________________________________7 3. Thailand Earthquake Risk : Geological and Tectonic Model ____________________________15 4. Palaeobiogeographic Analysis of the Early to Middle Jurassic (Toarcian-Aalenian) Bivalves of Western Thailand____________________________________________________22 5. The Late Cimmerian Event in Western Thailand and Central Lao PDR _________________25 6. Application of Rare Event Logistic Regression Model to Landslide Susceptibility Mapping: A Case-Study in the Kitchakut Mountain, Chanthaburi, Thailand_______________30 Co-editors Angsumalin Puntho Niran Chaimanee

Editor Sommai Techawan

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สมาคมธรณีวิทยาแหงประเทศไทย GEOLOGICAL SOCIETY OF THAILAND

12 / 14 1st floor, D1 Building, Lumpini Condo Town Ramintra-Laksi, Bang Khen, Bangkok, 10220, THAILAND

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สมาคมธรณีวิทยาแห งประเทศไทย GEOLOGICAL SOCIETY OF THAILAND

http://www.thaigeology.com e-mail : thaigeology@hotmail.com tel. +66 2 197 9053 fax. +66 2 197 9053 12 / 14 1st floor, D1 Building, Lumpini Condo Town Ramintra-Laksi, Bang Khen, Bangkok, 10220, THAILAND

The Geological Society of Thailand (GST), a non-profit geoscience organization was incorporated in Bangkok in March 1968 with headquarters at the Department of Mineral Resources, Bangkok, Thailand. Its objectives are : to exchange geoscience knowledge and opinion among geoscientists and interested persons; to diffuse technical knowledge and results of investigation by publications and activities; to cooperate with and to assist any local and overseas geoscience societies and organizations; and to promote the advancement of geological sciences.

The GST Executive Committee 2010 – 2012 President Vice-President 1 Vice-President 2 Vice-President 3 Vice-President 4 Vice-President 5 Advisor Secretary Treasurer Registrar Editor Public Relations House-Master Member Association Income Promotion Sport and Recreation

Dr. Songpope Polachan Mr. Surawit Pradidtan Mr. Owas Chinoroje Dr. Tawsaporn Nuchanong Dr. Pol Chaodumrong Dr. Dacha Luangpitakchumpol Mr. Nares Sattayarak Mr. Visit Coothongkul Ms. Keeratikorn Kongjuk Mr. Jittawat Meesuk Dr. Sommai Techawan Dr. Thasinee Charoenthitirat Mr. Bandit Chaisilboon Mr. Monkol Lukmuang Mr. Somkiat Thaeppunkulngam Mr. Noppadon Poomvises

MEMBERSHIP There are five categories of membership, Honorary Member, Ordinary Member, Associate Member, Juristic Person Member and Student Member. The membership is granted for persons at home or abroad on formal application.

PUBLICATIONS 1. The Newsletter of Geological Society of Thailand (GST Newsletter): is distributed to the members free of charge. The Newsletter includes the Society’s activities, news, light articles, notes and short reports.

2. The Journal of the Geological Society of Thailand: is currently published yearly - free to members and available to non-members and libraries by subscription. The subscription price for the Journal within Thailand is 500 Baht per copy, overseas is US$ 25 per copy (mailing cost included). Papers can be written in Both English and Thai.

GST JOURNAL EDITORIAL COMMITTEE 1. Dr.Sommai Techawan 2. Dr.Sampan Singharajwarapana 3. Dr.Panya Charusiri 4. Dr.Wickanet Songtham 5. Dr.Oranuj Lorpensri 6. Dr.Dhiti Tulyatid 7. Mr.Cherdsak Utha-aroon 8. Dr.Phumee Srisuwon 9. Mr. Niran Chaimanee 10. Miss Angsumalin Puntho

Editor-in-chief Geotechnology Geology of Thailand, Tectonics.

Paleontology Groundwater Geophysics Minerals Petroleum Geology Environmental Geology and Geohazards Secretary

Preface One of the Geological Society of Thailand (GST)’s key missions is to disseminate the geoscientific information and knowledge to the public. More technically, results of geoscientific researches and studies for professional and academic communities are disseminated through the GST journal.

The GST journal 2010-2011 volume 1 includes six interesting articles written by our geoscientist colleagues covering various fields of geosciences : a study of a black sand deposit in Eastern Thailand which might be considered as a new type of black sand deposit apart from placer and littoral explosion deposits and might be the only black sand deposit in Thailand; application of integrated geophysical study in understanding of sulfate-formation related sinkhole occurrence in Southern Thailand; Palaeobiogeographic analysis of the Early to Middle Jurassic bivalves of western Thailand by use of the Simpson Coefficient; a study of the Late Cimmerian event in western Thailand and central Lao PDR which points to a period of intense epeirogenic movements in the Late Jurassic – Early Cretaceous times; a case study on use of “rare events” logistic regression model to landslide susceptibility in the Kitchakut Mountain, Chanthaburi, Thailand; and the last but not least, a study of geological and tectonic model of the earthquake risk in Thailand which suggests a modeled tectonic movement of the related tectonic plates and blocks.

We hope that the articles in this GST journal volume provide interesting and useful information to all the readers, and hope that the journal will continue to be a center for all GST’s geoscientist colleagues to express and share geoscientific knowledge and information, especially the researches related to the geology of Thailand and the neighbouring countries.

Editor

“GST promotes understanding and strengthen cooperation in geosciences among members and Thai society”

Provenance of a Black Sand Deposit in Laem Ngob District, Trat Province, Eastern Thailand.

Wickanet Songtham 1, Janjira Sratongyung 2, Sujintana Chompusri 2, Dallas C. Mildenhall 3, Suchada Sriphirojthikul 1, Saowanee Seammai 1, Benjama Khomwongthep 1 and Chongkolnee Khanmanee 1 1

Department of Mineral Resources, Rama VI Road, Ratchathewi, Bangkok 10400 Thailand E-mail : wic.wickanet@gmail.com 2 Major of Geoscience, Kanchanaburi Campus, Mahidol University, Sai Yok, Kanchanaburi 71150 Thailand 3 GNS Science, 1 Fairway Drive, PO Box 30 368, Lower Hutt, New Zealand

ABSTRACT Samples of black sand were collected to study mineral composition by XRD, grainsize analyses by sieving, and shapes and sizes of the sand by SEM. A sample of PermoTriassic chert was examined by thin section and XRF to determine mineral and chemical compositions. Analyses reveal that the black sand is a chemical weathering product of an iron-bearing chert parent rock that formed as ferrihydrite (5Fe2O3.9(H2O)) in the early stages and subsequently transformed into a hydrous iron oxide, a brownish black goethite-coated silica sand. The silica sand was deposited as a thin layer on tidal mud flats and further transported to accumulate as a thick sand deposit in narrow seaside fringes of the mangrove zone by wave actions and daily tidal changes within the intertidal zone. This deposit is considered a new type of black sand deposit apart from placer and littoral explosion deposits and is the only black sand deposit in Thailand.

Key words : Thailand, chert, black sand, iron oxides, goethite, weathering products, chert INTRODUCTION All over the world local inhabitants and tourists are generally attracted to white sand beaches, particularly those beaches along tropical coasts. White sand is made up of either silica or coral sand debris within clear emerald sea water under warm climatic conditions. Black sand beaches are also glamorous destinations for visitors and are found worldwide mainly associated with tectonic volcanism along both convergent and divergent plate boundaries.

In the Pacific region black sand deposits are confined to the Ring of Fire, including volcanic islands and archipelagoes extending from Malaysia to Indonesia, Philippines, New Zealand, Hong Kong, Taiwan, Japan, Korea, Kamchatka Peninsula, Aleutian islands in Alaska, and the east Pacific coasts of North America, Central America, and South America.

Volcanic islands in the Pacific Ocean with extensive black sand deposits are in Hawaii, Galapagos, and Tahiti.

Black sand deposits of the Atlantic Ocean occur along mid-oceanic ridges from Jan Mayen and Svalbard, Iceland, Azores, Madeira, Canary,

and Sao Filipe, extending to the far south to Antarctica, as in Deception Island, as well as in the Caribbean Sea. Black sand also occurs in the Mediterranean Sea as in the Santorini islands of Greece and Sicily of Italy.

Black sand may be derived from weathering and erosion products of dark source materials, normally volcanic rocks such as basalt and andesite. The black sand-sized detritus is carried along streams or rivers to be deposited as sand bars or to flow out from river mouths to be deposited as black sand beaches under the influence of long shore currents (Briggs et al., 2009). Sand-sized particles may be directly produced where hot lava flows into abrupt contact with sea water. Hot lava may cool so rapidly in sea water that steam or littoral explosions occur which shatters lava into sand and rubble giving rise to huge amounts of fragmental volcanic sand debris. Many black sand beaches in Hawaii were created virtually instantaneously by the violent interaction between hot lava and sea water (Clark, 1985; Smellie & Chapman, 2002).

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In many places black sand deposits are mined for iron as the sand has high iron concentrations namely iron oxides and sometimes titanomagnetite sand often with ilmenite and magnetite that is magnetic, with perhaps up to 60 % iron as in New Zealand and the Philippines.

The only known black sand deposit site in Thailand is at Laem Ngob (Sratongyung, 2009).

This deposit fascinates all visitors but its provenance and why it occurs are still unknown.

This study reports on an analysis of the black sand and its presumed source, answering some of the questions on the nature of the Laem Ngob black sand deposit.

STUDY AREA The study area is located in Laem Ngob district about 20 kilometers southwest of Muang Trat township via route no. 3148. The general features of the study area are divided into two parts, a northern inland and a southern sea area with some islands and islets. The northern part is undulating with widely distributed hills ranging in elevation from 50 to 200 meters above mean sea level. The southern area covers a part of the Gulf of Thailand where the largest island is Ko Chang (Chang Island), the second largest island of Thailand, with some islets off its southeastern coast. Ko Kood, a mediumsized island in the region is located off the far southeastern end of the islets of Ko Chang. A shoreline forms a demarcation between the two areas that is mainly characterized by mud with mangrove forests. Minor sand deposits are found especially in the western part such as Tan Khu Bay and Thammachat Bay. Ko Chang is in the south about eight kilometers from the Laem Ngob fishery wharf and the closest portion between the island and the mainland is about 4.5 kilometers from Thammachat Cape to the island.

Ko Chang is mostly composed of PermoTriassic volcanic rocks comprising andesite, rhyolite, agglomerate, tuff, and basaltic andesite.

The rock on the mainland is chert (Tansuwan, 1997) that extends under the sea between the island and the mainland as a seafloor and is sparsely exposed near the shoreline especially during low tide, about 300 meters east of the Laem Ngob fishery wharf and about 500 meters off the coast south of Yai Mom village.

Moreover, the chert seems to extend further north, exposed in an abandoned quarry of highly

weathered chert with some quartz veinlets in the north of route no. 3148, not very far from Laem Ngob municipality. The rock in the north of the study area has been previously mapped as Permo-Triassic well-bedded chert and is widely distributed over most areas of Laem Ngob and Khao Sa Sing districts (Tansuwan, 1997).

The black sand deposit is found along an east-west shoreline about 700 – 800 meters east of the Laem Ngob fishery wharf. It occurs (see topographic map, scale 1: 50,000, sheet 5433 II) from Yai Mom village eastwards along the mangrove shoreline for about 900 meters (Fig. 1). The black sand occurs as a very thin layer on tidal mud flats along the mangrove fringe fading out to sea not very far from the mangrove communities (Fig. 2). However, thick deposits of black sand, about 2 to 4 meters wide, have predominantly accumulated along the outer rim of the mangrove zone, generally under scattered Rhizophora stilt roots (Fig. 3).

During low tide, a line of uncharted chert, about 500 meters off the south coast of Yai Mom village, emerges above sea level and is probably related to the chert outcrops on the sea shore near Kung Luang restaurant (Fig. 4). The real characteristics of the undersea outcrops are unknown and need detailed bathymetric investigation. Sea waves from the southwest break into surf against the uncharted chert breaking the rock into fragments which are subsequently weathered into material looking like a yellowish brown lateritic residue dispersing from the rock outcrops towards the shore. Black sand is deposited as a very thin layer on the mud floor between this lateritic residue and the mangrove shoreline.

Fig.1 Map of Laem Ngob district showing some important routes and geographic locations near the black sand beach and showing the pattern of sedimentary deposits between the chert outcrops and seashore.

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MATERIALS AND METHODS

Fig.2 Thin layer of black silica sand deposit on the tidal mud flat.

A bag of brownish black sand was collected to determine surface characteristics under light and scanning electron microscopes and test for the type of material by X-ray diffractometer (XRD). Sixteen samples of the black sand and one rock sample of chert from an outcrop at the seashore were collected for analyses. A rock sample was prepared for thin section to study the mineral composition of the rock under a light microscope and X-ray fluorescence (XRF) for chemical composition.

The sixteen samples of sand were analyzed to determine the relationship between the grain sizes and the distances of dispersal from source.

The laboratory analyses were run at the Department of Mineral Resources in Bangkok, Mahidol University at Kanchanaburi Campus in Kanchanaburi, and National Metal and Materials Technology Center (MTEC) in Pathumthani provinces.

RESULTS

Fig.3 Thick accumulation of black silica sand deposit along the seaside rim of the mangrove forest zone parallel to the seashore about 900 meters in distance and about 2 to 4 meters wide.

Fig.4 A chert outcrop at seashore near Kung Luang restaurant. Construction far beyond the outcrop in the picture is Laem Ngob fishery wharf.

In general, the sedimentary deposits between the chert outcrops and the seashore are divided into four successive zones, namely rock fragment zone, yellowish brown ferricrete residue zone, black sand on tidal mud zone, and black sand in mangrove forest zone. The zones are characterized by their distinctive features based on the nature of material compositions, grain sizes, colors, and locations. This division provides a systematic profile describing processes of weathering and erosion of rock, transportation, and deposition of the rock fragments and weathering products. All zones are more or less parallel to each other and are at a 60ยบ angle to the shoreline in a NW-SE direction due to the effects of the northeasterly sea waves (Fig. 1).

The chert outcrops on both the seashore and off the coast under the sea are regarded as the probable source of the four sedimentary deposition zones. The rock is dense, brownish pink in color, with abundant white colored veinlets. Its weathering surface is yellowish brown in color. XRF analysis of the Laem Ngob chert shows a special chert type with normal to slightly high Fe content (Table 1). This is confirmed by a thin section observation under the light microscope showing it to be mainly composed of microcrystalline quartz with abundant quartz veinlets. Secondary red-brown

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and black colored iron oxides are also present.

Quartz crystals on the wall of cavities and/or veinlets are relatively finer compared to the inner parts of the chert. This quart is considered a secondary deposit. Iron would be dissolved during weathering generating significant amounts of hydrous iron oxides as ferrihydrite (5Fe2O3.9(H2O)) or wustite (FeO), converting to goethite, eventually producing the brownish black goethite-coated silica sand.

Table 1 Chemical composition of whole rock (wt%) SiO2 TiO2 Al2O3 Fe2O3 FeO MnO MgO CaO Na2O K2O P2O5 H2O(-)

96.00 0.02 0.78 1.93 Nil 0.03 0.08 0.05 <0.10 0.01 0.01 0.20

The closest zone to the chert outcrops is dominated by angular rock fragments of chert in various shapes and sizes observable around the chert outcrops at the seashore. The next zone towards the coast has smaller rounded to subrounded granules to pebbles with some gravel, yellowish brown in color, and negligible amounts of brownish black sand. The sediment in this zone is thought to be chert fragments coated by percolating solutions containing iron salts. The sediment of this zone is well exposed during low tide as two small tongues of yellowish brown ferricrete sediment protruding out into the sea where villagers from nearby villages go to dig for several kinds of edible mollusk.

When weathering of the ferricrete residue zone further progresses, more iron oxide materials are transformed into brownish black goethite, FeO(OH), as tiny rounded particles of fine iron-coated silica sand. The iron sand is then transported toward the coast to be deposited thinly on the tidal mud flat. However, under wave actions and daily tidal changes along the littoral zone the brownish black iron sand accumulates further into the mangrove forest as a thick deposit of sand parallel to the mangrove shoreline over a distance of about 900 meters and 2 to 4 meters wide.

The zone further towards the coast is composed of a thin layer of black sand on mud flat and the most inland zone is a thicker black sand deposit, about 60 centimeters thick, in the mangrove forest. An XRD analysis for the black sand identified a hydrated iron oxide of goethite, FeO(OH), and quartz, SiO2. Goethite forms under oxidizing conditions as a weathering product of ferriferous minerals as a principal component of ferricretes, formed where rock decay has progressed without interruption for a long time (Gaines et al., 1997). The brownish black sand is a goethite-coated silica sand a chemical weathering product from the parent chert. The processes of weathering are probably equivalent to that described by Yokoyama & Nakashima (2005) where in the early stages of the iron-bearing chert weathering ferrihydrite is produced subsequently transformed into goethite.

SEM observations on the brownish black iron sand shows that they have a more or less smooth surface and are spheroidal ranging in size from 150 to 230 microns approximately (fine sand), suggesting that they were formed by a coating reaction of silica sand with goethite as chemical weathering products rather than detritus directly broken down from the parent rocks (Fig. 5).

Fig.5 Grains of black silica sand under SEM and LM showing smooth surfaced spheroid to egg shaped grains of hydrous iron sand, goethite. Figs. 5A to 5C are taken under SEM and figs. 5D to 5F are taken under LM.

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Grain-size analyses of the brownish black goethite-coated silica sand play no role in relation to the sand dispersal as the sand is regular in size falling only into the range of fine sand. However, since the sediments are deposited within a small area with the farthest sand deposit less than one kilometer from the parent rock no distinctive grain-size differences are formed.

CONCLUSIONS AND DISCUSSION The black sand deposit from the Yai Mom village area has formed by erosion and weathering from chert outcrops along the seashore and under the sea that periodically emerged above sea level during low tides.

Detailed processes are explained by experiments run by Schwertmann & Murad (1983), Yokoyama & Nakashima (2005), and Cudennec & Lecerf (2006) who indicated that iron must firstly be dissolved from the parent rocks to form the iron-bearing weathering products.

After dissolution of iron, Fe2+ is oxidized to Fe3+ which is subsequently precipitated as ferrihydrite (5Fe2O3.9(H2O)). They further explain that it is widely believed that ferrihydrite transforms to goethite and/or hematite because ferrihydrite is thermodynamically less stable than goethite and/or hematite depending upon pH and temperature conditions within a set period of time. Experimental storage of ferrihydrite in aqueous suspension at 24째C and pHs between 2.5 and 12 for three years resulted in the formation of goethite and hematite. The proportion and crystallinity of these products varied widely with the pH. Maximum hematite was formed at neutral pH or between pH 7 and 8 whereas goethite at around pH 2-5 and at around pH 10-14. This experiment implies that conditions favorable for the formation of goethite are unfavorable for that of hematite and vice versa. In addition, goethite crystals form in solution from dissolved Fe3+ ions produced by the dissolution of ferrihydrite, whereas hematite forms through an internal dehydration and rearrangement within the ferrihydrite aggregates (Fischer & Schwertmann, 1975; Schwertmann & Murad, 1983).Goethite transformation in the Laem Ngob area is hard to imagine in sea water with either high acidity or high alkalinity unlike the normal sea water with pH values between 7.5 and 8.4.

For goethite-coated silica sand, Scheidegger et al. (1993) experimented on the pH dependence of the coating reaction of silica sand with goethite. This showed that the amount of adsorbed goethite increased with increasing pH and abruptly decreased at pH values above the point of zero charge (PZC) of goethite (pHPZC = 7.9). The coating reaction can be explained by a simple electrostatic model where the charge of the adsorbed goethite particles neutralizes the charge of the silica surface.

Scheidegger and others demonstrated that the peak coating reaction took place at around neutral pH or at a pH less than 7.9. The coating process from the experiment gave rise to a strong chemical binding force between the goethite particle and the silica surface enabling the formation of a natural coating. This experiment explains the coating reaction of goethite to the surface of silica sand in normal sea water of the Yai Mom village seashore area.

Goethite-coated silica sand surfaces have higher specific surface areas and more mesopores than uncoated sand. This knowledge has led to its application in controlling toxic environments such as the adsorption of both cadmium and humic acid which are highly pHdependent: cadmium adsorption increased with pH, but humic acid adsorption decreased as pH increased (Lai et al., 2002). Arsenic in drinking water can be removed by using iron oxidecoated sand (Thirunavukkarasu et al., 2003) and so on.

The property of the goethite-coated silica sand in removing toxic elements from the environment might have been active in the area of the goethite-coated silica sand deposition but its impacts upon this environment was not part of this study. We so far have no information on the effects of the iron sand on the seashore environment and mangrove forests in this locality. We strongly recommend further research on the beneficial effects of iron oxide sand on the natural environs and human communities.

ACKNOWLEDGEMENTS We sincerely thank the Department of Mineral Resources for financial and logistical support for this research especially the Mineral Resources Analyses and Identification Division who prepared and analyzed some rock and sand samples. We thank GNS Science, New Zealand, for providing scientific references on the black

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sand deposits that guided us to find out about the nature of the Thai black sand deposit, and Dr. David Skinner on reviewing a draft of this paper. We thank the Major of Geosciences, Mahidol University, Kanchanaburi Campas, who collected the samples and ran grain-size analyses for the black sand.

REFERENCES Briggs, R.M., Laurent, J.C., Hume, T.M. and Swales, A. (2009) Provenance of black sands on the west coast, North Island, New Zealand. AusIMM New Zealand Branch Annual Conference 2009, 41-50.

Clark, J.R.K. (1985) Beaches of the Big Island. University of Hawaii Press, 186 pp.

Cudennec, Y. and Lecerf, A. (2006) The transformation of ferrihydrite into goethite or hematite, revisited.

Journal of Solid State Chemistry, 179(3), 716722.

Fischer, W.R. and Schwertmann, U. (1975) The formation of hematite from amorphous iron (III) hydroxide.

Clays and Clay Minerals, 23, 33-37.

Gaines, R.V., Mason, B. and Rosenzweig, A. (1997) Danaâ&#x20AC;&#x2122;s new mineralogy. 8th edn, John Wiley and Sons, Inc. Lai, C-H., Chen, C-Y., Wei, B-L. and Yeh, S-H. (2002) Cadmium adsorption on goethite-coated sand in

the presence of humic acid. Water Research, 36(20), 4943-4950.

Sratongyung, J. (2009) Sedimentological and geochemical analyses to determining the provenance and depositional processes of Laem Ngob Black Sand Beach, Trat province. Senior Research Project of Major of Geosciences, Mahidol University.

Scheidegger, A., Borkovec, M. and Sticher, H. (1993) Coating of silica sand with goethite: preparation and analytical identification. Geoderma, 58(1-2), 43-65.

Schwertmann, U. and Murad, E. (1983) Effect of pH on the transformation of goethite and hematite from ferrihydrite. Clays and Clay Minerals, 31(4), 277-284.

Smellie, J.L. and Chapman, M.G. (2002) Volcano-ice interaction on Earth and Mars. Geological Society of London, Special Publication No. 202.

Tansuwan, V. (1997) Geological map of Changwat Trat, scale 1: 250,000. Department of Mineral Resources, Geological Survey Division, Bangkok, Thailand.

Thirunavukkarasu, O.S., Viraraghavan, T. and Subramanian, K.S. (2003) Arsenic removal from drinking water using iron oxide-coated sand.

Water, Air, & Pollution, 142(1-4), 95-111.

Yokoyama, T. and Nakashima, S. (2005) Color development of iron oxides during rhyolite weathering over 52,000 years. Chemical Geology, 219, 309-320.

Understanding of Sulfate-Formation Related Sinkhole Occurrence from an Integrated Geoscientific Study.

Aksara Mayamae and Helmut DĂźrrast Geophysics Group, Department of Physics, Faculty of Science, Prince of Songkla University, 90112 Hatyai, Thailand.

Eâ&#x20AC;&#x201C;mail: aksara_mym@hotmail.com, helmut.j@psu.ac.th

ABSTRACT In January 2005 and August 2009, large sinkholes (5-15 m in diameter, 10-19 m depth) were discovered in Nakhon Si Thammarat Province, in an area close to a gypsum mine. An integrated geophysical and hydrogeological study was carried out in order to understand the sinkhole occurrence. Vertical sounding measurements revealed a weathered anhydrite/gypsum layer (80 ohm-m) in about 15 to 25 m depth above a very high resistivity layer, likely to be solid, non-weathered sulfate rocks in the area between the sinkholes and the mine. The depth increases to about 70 m further away from the sinkholes with the location of the sinkholes at the slope of the depth change. Weathering of the sulfate is mainly at the top and along open joints in the rock mass. Seismic refraction and reflection surveys indicated several layers in the overlying clay and sandy clay and in the weathered gypsum/anhydrite layer. Following scenario can be drawn: as the depth increases the weathered sulfate layer is in larger contact with the adjacent groundwater layer resulting in an increased dissolution of the sulfates leading to caverns in the subsurface. Groundwater pumping at the mine probably lowered the water in the dissolution caverns. Subsequently, parts of the overlying sediments felt into the empty caverns. However, the collapse of the cavern's roof and formation of the sinkhole itself can be correlated to strong earthquakes in the Andaman Sea prior to that.

Key words : sinkhole, geophysics, VES, seismic, SP, sulfate, geological hazard INTRODUCTION Sinkholes are one type of geological natural hazards, and their occurrence is directly related to the occurrence of soluble subsurface formations, like limestone, rock salt, and other evaporates, like gypsum and anhydrite (e.g.

Appelo and Postma, 2005). The development of a sinkhole in an urban area is a direct threat to people, housing, and infrastructure, because the area above a subsurface hole stays intact until suddenly the sinkhole develops. The size of a sinkhole can vary from less than a meter to tenths of meters in diameter and depth.

However, it is also know that land use practices, with groundwater pumping and construction, can trigger or even cause the development of sinkholes (e.g. Kresic, 2006). In Thailand sinkholes are common features in many part of the country, as limestone formations can be found in all part of the country, a rock salt formation in the northeastern part, and gypsum and anhydrite formations in the southern part, the focus of this ongoing study.

In the Tayang Sub-district, Tungyai District, Nakhon Si Tammarat Province, unexpected two larger sinkholes occurred. The first one, with 15 meters in diameter and 10 meters depth, occurred in January 2005, and the second had formed in August 2009, with 5 meters in diameter and 19 meters depth (Fig. 1).

Both sinkholes were about 100 m apart from each other, and about half a kilometer away from an active gypsum mine (Fig. 2). As local people claimed that sinkholes were not a common feature in their village area until early 2005, besides the existence of the subsurface evaporate formation, this study aims to investigate the development of these sinkholes, by mainly applying geophysical and hydrogeological methods.

Various geophysical studies have been carried out to investigate the sinkhole occurrence. High-resolution seismic reflections have been used to characteristic sinkholes formed from the dissolution of a bedded salt (Miller et al., 2009). Seismic refraction was used to delineate the salt layer that is an

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essential condition for sinkhole occurrence (Ezersky, 2006). An electrical resistivity tomography (ERT) study was carried out to understand the subsurface geoelectric structure at the sinkhole development site (Ezersky, 2008). A high-resolution seismic survey and 2D electrical imaging were used to map the hydrogeological system in karst area

environments (Sumanovac and Weisser, 2001).

In hydrogeological investigations, self-potential measurement is a useful technique, which has been used to study groundwater movement and flow path (Fournier, 1989) and by this to map sinkholes and evaluate the risk of potential collapses in karst areas (Wanfang et al., 1997).

Fig.1 Sinkhole occurred in January 2005 (left) and sinkhole discovered in August 2009 (right), both in Nakhon Si Tammarat Province.

Fig.2 Gypsum mining in Nakhon Si Tammarat Province. View to North.

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GEOLOGY The general geology around the study area, where the sinkholes occurred, is mostly unconsolidated sediment. There are sedimentary rock at hills in the north and south. The Department of Mineral Resources (DMR), Thailand, classified the rock units in this area as following (Rattanajaruruk, 1994): SilurianCarboniferous, SDC, in mountains along NorthSouth; it is classified in Tanaosi Group, Kanchanaburi Formation. It composes of shale, sandstone, quartzite, mudstone and slate, well bedded and with abundant drag folds.

Carboniferous-Permian, CP, is found at small mountains along northâ&#x20AC;&#x201C;south direction. It is classified into Ratburi Group that composed of limestone, which is light to dark gray, thinbedded to massive; with shales, sandstones, mudstones and interbedded cherts. Mesozoic, MZ, is found in mountain and hill geographies.

It is classified into Korat Group that composed of sandstone, siltstone, shale, and reddish brown to brown conglomeratic sandstone, conglomerate, dolomitic limestone, with crossbedding and ripple marks, and basal conglomerate. Quaternary is composed of unconsolidated sediments and divided into two groups, alluvial deposits composing of gravel, sand, silt and clay, and terrace deposits

composed of gravel, sand, silt and lateritic soil (Fig. 3a). Gypsum ore in Southern Thailand is primary gypsum, which is deposited along a north to south direction at the west edge of Khao Luong to Khao Yai Mountain in Surat Thani and Nakhon Si Tammarat Province. Its layering is related to Khao Hun Formation and Ratburi Group, indicating a deposition in the Lower Permian age (Rattanajaruruk, 1994).

The general geology of Ban Tarang-Khao To, where the gypsum mine and the study area are, are sedimentary rocks of the Late Paleozoic, which can classified as following: Khao Hun Formation is in lower Permian age composed of sandstone, reddish brown shale. It was found as Khao To Hill located in the center of the study area. Ratburi Group is of Permian age composed of gray limestone inserted and shuffled with shale layers and conglomeratic limestone layers.

Limestone is often forming the hills. Sediments of Quaternary age composed of unconsolidated gravel and sand. Gypsum source potential areas are parallels to the mountains with SDC Formation along north-south direction (Fig. 3a).

Its average wide is about 50 meters and approximately 25 meters thick with a dip of 4570 degrees; sometimes the gypsum layer can be found in anticline structures (Fig. 3b) (Rattanajaruruk, 1994).

Fig.3 Geology around study area show classified rocks (a) and discovered gypsum trend boundary in potential area (b). Modified from Kheunkhong (2001), Vimuktanandana (1985), and Rattanajaruruk (1994).

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Fig.4 Geological cross section at the gypsum mine. View from VES point R4 (bottom right) to the opposite side of the mine (bottom left).

GEOPHYSICAL INVESTISATIONS In the present, in the mining is down to a depth of about 40 to 45 meters (Fig. 2 and 4 top), and it appears to be no groundwater at the base of the mine (Fig. 2 and 4, top). In the contrary, the water level around the study area, which is close to the mine, can be considered in the second sinkhole, which was found at about 9 meters from the surface (Fig. 1, right).

Therefore, the flow direction of groundwater can be assumed a gradient of the groundwater as flowing down from the sinkhole to the base of mine in west to east direction.

The subsurface layering close to the study area can be clearly seen at the walls of the mine at the side of the resistivity measurement point R4. It was found 12 to 14 meters thick of unconsolidated clay cover on 24 to 30 meter thick anhydrite layer (Fig. 4, bottom right) which correlated to the opposite R4 point that reveal two layer of clay with 12 meters thick overlay on the anhydrite (Fig. 4, bottom left).

The integrated geophysical survey comprised of several methods, mainly seismic and electric methods. A seismic reflection survey was conducted on flat plain near the sinkholes in order to establish the top of the evaporate formation (Fig. 5). A SmartseisTM S24 seismograph for data recording was used with a sampling rate of 125 ms and a 10 kilograms sledge hammer as energy source.

Two seismic reflection survey lines at the first and second sinkhole used 12-channels of 14-Hz geophones with 2 meters spacing of single geophone at the first sinkhole and 1 meter at the second sinkhole site. The source was 30 meter off-end. This geometry were fixed and rolled with source and receivers along each survey line for 24 shots with 1-meter and 2-meters increments at the second and the first sinkhole site, respectively. The GLOBE claritas program was used to process the data. Common-depth-

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point reflection technique was employed to interpret the data.

Two seismic refraction survey lines also have been performed on flat plain and parallel near to the sinkholes in N-S direction (Fig. 5).

The acquisition was using the same equipment than used for the seismic reflection survey, however here with 24 14-Hz-geophones in north-south direction with one meter geophone spacing at both the first and the second sinkhole site. The sledge hammer was also used as the energy source. Seven records were done per spread at each site, one record at the center, two records at the end of the line, two records at 12 meters and two last records at 24 meters from the line end. For the interpretation of the seismic refraction data, SIP version1 software from Rimrock Geophysics was used. Results were analyzed with delay-time method to produce a depth section along the survey line with the Pwave velocities and depth for each layer, except the last one.

Fig.5 Location of the two sinkholes and the gypsum mining area. Seismic lines (S) and resistivity (R) survey points are indicated with number which also the direction of the measurement and selfpotential survey (SP).

Four vertical electrical sounding points were measured in an E-W line from the mine to the sinkhole area in order to establish the subsurface geo-electric structure over this distance (Fig. 5). Schlumberger configurations with AB/2 maximum of 250 m (R4) and 350 m (R1-R3) were applied (Fig. 5). The forward modeling program IPI2WIN version 3.0.1a was used to compute the resistivity models.

All 134 measurement points of selfpotential survey composed of one loop around the first sinkhole, one long line parallel to seismic lines and four cross lines between first

and second sinkhole. The ABEM SAS 300 equipment and two non-polarizing electrodes containing of a saturated Cu/CuSO4 solution were used for SP measurements with a fixedbase configuration (Fig. 5), and 62 elevation leveling points were also measured along SP lines for the elevation correction of the SP values.

RESULTS The resistivity data analysis provided five layers at each of the four points. The two uppermost layers have a resistivity of about 1,000 and 1,900 ohm-m with 1.5 and 4 meters thickness, which is clay and sandy clay layer, respectively. The third layer has about 240-700 ohm-m with 15-50 meters thickness. The fourth layer has about 76-154 ohm-m with 80 meter thickness representing a weathered gypsum/anhydrite layer. The last layer has a very high resistivity with about 31,000 ohm-m, likely to be solid anhydrite bedrock (Fig. 6)

Fig.6 Resistivity (in ohm-m) and depth (in m) values of five different layers from east (R4) to west (R1). Firstâ&#x20AC;&#x201C;layer resistivity not shown here.

The refraction analysis provides information down to a depth of about 10 m. The refraction survey line at the first sinkhole site reveals near surface velocity values ranging from 384 to 699 m/s likely to be, clay, clay mixed with sand layer, which can seen inside the first sinkhole. Below at about 8 m depth the velocity is 1,665 m/s (Fig. 7, left); it can be assumed to be the groundwater layer. The subsurface stratigraphic from refraction survey line at first sinkhole site can be correlated with the refraction survey line at the second sinkhole

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site that reveals a velocity of 360 m/s for the top 8 meters, which is likely to be clay or sandy clay and the layer below 8 meters depth has a velocity of 1,493 m/s (Fig. 7, right) assumed to be the groundwater layer, which can seen from the insight of the second sinkhole (Fig. 1, right).

The seismic reflection section near the second sinkhole is shown in Fig. 8 (right). The reflectors between depths of 35-65 meters are interpreted as the anhydrite/weathered gypsum layer with a velocity of 1,850 m/s, which correspond with the velocity of 1,800 m/s of the main reflector between depths 25-55 meters of the survey line near the first sinkhole (Fig. 8 left). This depth of the weathered

anhydrite/gypsum layer correlates with the depth of the interface from resistivity measurements of around 18â&#x20AC;&#x201C;30 meters for R2 to R4 (see Fig. 6).

A self potential contour showed groundwater flow directions through the first and the second sinkhole site with negative values down to -25 mV. A value of -5 mV at the 541020-541050E, 922020-922040N (upper right corner) is assumed to be a developing void in the subsurface with the potential of becoming a sinkhole in the future (Fig. 9). The lower and negative values of self-potential survey were observed parallel to the dip of the weathered sulfate layer according to the resistivity data.

Fig.7 Subsurface models from the interpretation of seismic refraction data of survey line at 1st sinkhole site (left) and at 2nd sinkhole site (right).

Fig.8 The subsurface structure of seismic reflection interpretation. The main reflector at the 1st sinkhole site (left) is at 25-45 m and at the 2nd sinkhole site (right) the main reflectors are at 25 m, 35 m and 42 m depth.

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Fig.9 Self-potential contour map reveals ground water flow into the sinkholes. Dark solid line is elevation in meter, white solid line is self-potential value contour, white bigger dots are measurement point and white smaller cycle dots are sinkholes.

Fig.10 Scenario of sinkhole development: From the resistivity data the anhydrite/ gypsum layer is at about 15 m depth in the E, with increasing depth to the West. The excavation of the mine resulted in a drawdown of the groundwater table (L). The groundwater flow leads to an accelerated dissolution at the slope of the anhydrite/gypsum layer with subsequent subsidence and sinkhole development. The groundwater can flow though the anhydrite/gypsum layer due to the existence of open fractures. The locations of the geophysical survey points are indicated.

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DISCUSSION AND CONCLUSIONS From the geophysical data following scenario of the sinkhole development can be drawn (Fig. 10). From the resistivity data four main layers can be identified: surface layers, sandy clay to clayey sand, weathered anhydrite/gypsum layer, and solid anhydrite bedrock layer. The layers show an increase in the depth from E to W, so that a slope appears in the area of the sinkholes.

Further, it can be assumed that at the mine the groundwater level should be below the mine base.

In the area of the sinkholes the groundwater is probably at around 10-15 m depth, as seen from the second sinkhole. Also a private well nearby provided such depth (not shown here). Therefore a gradient of the groundwater table from the sinkhole area to the mine, at about 45-50 m below surface, can be assumed as shown in Fig. 10. The groundwater can flow through the anhydrite /gypsum layer due to existence of fractures, which can be also seen in the mining area.

There is a change of the slope of the anhydrite/gypsum later from East to West with increasing depth, especially in the area at R1 and R2 sounding points. In this area the groundwater is in larger contact with the anhydrite/gypsum layer due to the slope. This geometry accelerates the dissolution of the gypsums and anhydrite in this area leading to the development of larger voids in the subsurface. The beginning of the sinkhole formation is shown with the development of subsidence at the surface. This has been seen for the second sinkhole. Subsidence was seen in June 2009, and the sinkhole occurred in August of the same year.

The actual collapse of the sinkhole can be related to big earthquakes in the Andaman Sea. For the first sinkhole the Mw 9.3 Sumatra– Andaman Earthquake on 26 December 2004 can be seen as the trigger. The larger sinkhole was then observed some days after. For the second sinkhole the Mw 7.6 earthquake near the Andaman Islands on 10 August 2009 can be related to the sinkhole development. Finally, the sinkhole development in the study area can be related to natural processes as the data of the study have shown. However, it is likely that human activities accelerated the sinkhole development.

ACKNOWLEDGEMENTS The authors thank the Graduate School of Prince of Songkla University for supporting

research funds. Thanks also to the International Program in the Physical Science of Uppsala University, Sweden, for supporting research equipment. The authors thank S. Yordkhayhun for his suggestions and valuable discussions regarding the processing of seismic reflection data.

REFERENCES Appelo, C.A.J. and Postma, D. 2005. Geochemistry, groundwater and pollution, 2nd Ed., A.A. Balkema publishers, Amsterdam, the Netherlands, pp131 Ezersky, M. 2006. The seismic velocities of Dead Sea salt applied to the sinkhole problem.

Journal of Applied Geophysics. 58, 45-58.

Ezersky, M. 2008. Geoelectric structure of the Ein Gedi sinkhole occurrence site at the Dead Sea shore in Israel. Journal of Applied Geophysics. l64, 56–69 Fournier, C. 1989. Spontaneous potentials and resistivity surveys applied to hydrogeology in a volcanic area: case history of the Chaîne des Puys (Puy-de-Dôme, France). Geophysics Prospecting. 37(6), 647-668.

Kheunkhong P. 2001, Mineralogy Map of Nakhon Si Thammarat Province 1:250000, Economic Geology Division, Department of Mineral Resource Kresic, N. 2006. Hydrogeology and groundwater modeling, CRC Press, Taylor & Francis Group, Boga Raton, Florida, U.S.A., pp350.

Miller, R.D., Xia, J. and Steeples, D.W. 2009.

Seismic reflection characteristics of naturallyinduced subsidence affecting transportation.

Journal of Earth Science. 20(3), 496–512 Rattanajaruruk, P. 1994. The reserved gypsum ore quantity in border of Surat Thani to Nakhon Sri Tammarat Province, Economic geology report, NO.13/1994, Economic geology division, Department of mineral resources, p.28-30 Sumanovac, F. and Weisser M. 2001. Evaluation of resistivity and seismic methods for hydrogeological mapping in karst terrains.

Journal of Applied Geophysics. l47, 13-28 Vimuktanandana, S. 1985, Geological map of Nakhon Si Thammarat province 1:250000, Geological Survey Division, Department of Mineral Resource Wanfang, Z., Beck, B.F. and Stephenson, J.B. 1997.

Investigation of groundwater flow in karst areas using component separation of natural potential measurements.

Environmental Geology. 37(1-2), 19-25.

Woodward, D.J. 1991. Inversion of seismic refraction data.

Geophysics Division Technical Report No 114. DSIR Geology and geophysics, Lower Hutt, New Zealand

Thailand Earthquake Risk : Geological and Tectonic Model.

Prinya Putthapiban Geoscience, Mahidol University Kanchanaburi Campus, Sai Yok, Kanchanaburi 71150 E-mail : kappt@mahidol.ac.th

ABSTRACT Thailand is located at the northern end of the relatively stable Sundaland block.

Geological and tectonic setting of the country in a broad sense is under compressional stress. GPS measurements on the regional crustal motion and block behavior suggest that the Australian plate, Indian plate and the South China block are rotating clockwise about a large area of Thailand and the Indochina countries, and that the residual vectors are forcing the Sundaland block to move southeastward slowly. Shear stress is mainly confined to the edges of the Sundaland blocks reflecting as a few regional strike slip faults such as the right-lateral Sagiang Fault between Indian plate and the Sunda block in Myanmar and the right lateral Red River Fault between South China block and Vietnam.

Northern and Southern Thailand show higher rate of motion, ~ 2-4 mm/yr. than that of the central and western Thailand which show the least motion, ~ 1 mm/yr. This indicates that the prior areas are at higher risk in terms of earthquake activities. The higher surface water temperatures of the hot springs in northern Thailand, 80 – 100 ºC and those of southern Thailand, 60 – 80 ºC compared to those of western Thailand, 39 – 59 ºC are in good agreement with the above observations. Furthermore, the Northeast Ranong Fault that apparently offset by the Northwest Three Pagodas Fault also supports the above view.

Key words : Sundaland block, GPS measurements, crustal motion, Hot springs, Three Pagodas Fault, Ranong Fault INTRODUCTION Earthquake hazards are perhaps one of the most terrifying natural calamities and a major threat for mankind. In recent years, the number of such natural phenomena are apparently increasing, although statistically, that may not be the case, particularly the relatively big ones.

The main shakes from earthquakes themselves hardly kill people directly, however their consequences such as building collapse, fires, landslide and avalanches, soil liquefaction, tsunami and flood are capable of destroying both human lives and properties. Information to date suggests that the Sundaland block is a relatively stable block and Thailand is located in a low to moderate earthquakes prone area. The high and moderate risk zones of the country are in northern parts, western parts, the Chao Phya plain and most of the peninsular region. The eastern half of the country is more stable in term of seismic risk. Since the Great Sumatra Earthquake in December 26th, 2004, geoscientists and the public have become more

aware and studies to understand the nature of active faults in the region have increased.

Whenever big earthquakes occurred elsewhere in the world, many Thai media and academics have raised awareness as well as built up more panic to the public. However, comparison between the damaged areas of the foreign countries and Thailand, which are often made, do not consider the differences in their geologic settings.

In this paper, information related to geologic settings, earthquake hazard risk and heat flow features in Thailand and GPS measurements within and around the Sundaland block and adjacent areas are presented. Thailand earthquake risk in term of the geological setting and tectonic model are discussed and interpreted.

GEOLOGICAL SETTING AND SEISMIC INTENSITY Thailand is located in the northern part of the Sundaland block. The block is surrounded by the Eurasian plate in the north, South China

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block in the northeast, Philippine plate in the east, Indian plate and Australian plate in the west and southwest respectively. It covers main part of the present-day Southeast Asia that includes Cambodia, Laos, Vietnam, Thailand, Malaysia, Sumatra, Borneo, Java, and the shallow seas (Sunda shelf) located in between (Fig. 1). It is clearly seen that the majority of the active faults and the seismic-prone areas in Thailand are located in the north, northwest, west and southern peninsular Thailand. The seismic risk map published by the Royal Thai Department of Mineral Resources is shown in Fig.2. Probabilistic seismic hazard analysis for Thailand and adjacent areas using regional seismic source zone by Pailoplee, et al., 2008 suggested that ground motion of 0.4 to 1 g may occur in northern and western Thailand and of 0 – 0.4 g in other parts of the area with a 2 % probability of recurrence with periods of 10 to 100 years (Fig. 3)

Fig.2 Thailand earthquake risk map showing in the Modified-Mercalli Intensity Scale (Modified after DMR,2005).

Fig.1 Geologic setting of Thailand and the Sundaland block shows topography, seismicity, main active faults, and the approximate (absolute/ITRF2000) motions of the Eurasian, Indian, Australian, Philippine plates and the South China block, near and in SE Asia (After Simons, W.J.F., et. al., 2007).

HEAT FLOW DATA More than 90 hot springs of medium to low enthalpy have been found scattering around Thailand especially in the northern, southern and western parts of the country. These hot springs have long been known to be closely related to active fault zones (Takashima and Jarach, 1981; Thienprasert and Ranksaskulwong, 1984 ; Takashima et al. 1989 and Ranksaskulwong and Thienprasert, 1995).

Fig. 4 shows their distributions and surface temperatures which are clustered into 3 areas.

The water temperatures of northern, southern and western groups are 80 – 100 ºC, 60 – 80 ºC and 39 – 59 ºC respectively. One good correlation on the alignment of the hot springs and their related Three Pagoda fault zone can be observed (Putthapiban et al., 2010). A brief explanation is given below.

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a) 2% POE in 10 years

b) 10% POE in 10 years N

N

India

India

25

25

China Myanmar

Vietnam

Laos

3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Nicobar Islands

Cambodia

5

Su

m atr

250 km

Malaysia aI

0 90

95

sla n

d

100

Laos

g

Thailand

10

Vietnam

20

105

10

Su

m atr

250 km

Malaysia aI

0 90

c) 2% POE in 50 years

95

sla n

d

100

105

N

India

India

25

25

China Myanmar

Nicobar Islands 250 km

Malaysia aI

0 90

95

sla n

d

100

105

10

Su

m atr

250 km

Malaysia aI

0 90

e) 2% POE in 100 years

95

sla n

d

100

105

N

India

India

25

25

China Myanmar

Nicobar Islands 250 km

0 90

95

Malaysia aI

sla n

100

d

105

110

g 3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Thailand

15

Nicobar Islands

3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Cambodia

m atr

Laos

g

Thailand

Su

Vietnam

20

Laos

5

China Myanmar

Vietnam

20

10

110

f) 10% POE in 100 years N

15

3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Cambodia

5

110

g

Thailand

15

Nicobar Islands

3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Cambodia

m atr

Laos

g

Thailand

Su

Vietnam

20

Laos

5

China Myanmar

Vietnam

20

10

110

d) 10% POE in 50 years N

15

3 2.8 2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Cambodia

5

110

g

Thailand

15

Nicobar Islands

20

15

China Myanmar

10

Cambodia

5

Su 250 km

0 90

95

m atr

Malaysia aI

sla n

100

d

105

110

Fig.3 Probabilistic seismic hazard maps of Thailand and adjacent areas showing the probabilities (%) that ground shaking will be equal to or greater than level IV, V, VI, and VII (Modified Mercalli Intensity) for return periods of 10, 50 and 100 years (after Pailoplee, et.al., 2008).

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Fig.4 Distribution of hotsprings in Thailand.

The surface water temperatures of northern, southern and western groups are 80 - 100 ºC, 60 - 79 ºC and 37 - 59 ºC respectively.

The alignment of 4 hot springs on land and one submarine high heat flow spot obtained from the heat flow map of Southeast Asia, scale 1:5,000,000 (GSJ and CCOP, 1997), GT1, offshore forming a straight line which runs at N44°W. The line is most likely indicates the main Three Pagodas Fault path in the region.

The other four submarine high heat flow spots which formed another perfect straight line subparallel to the first one and has a trace of N20°W. This trace is considered to be the most southeastern continuation of the Three Pagodas Fault Zone. The above two lines was off-set by the northeastward extension of the Ranong Fault Zone which runs at N25°E. The sense of movement clearly indicate right lateral feature for the Ranong Strike Slip Fault Zone (Fig. 5).

The evidence from two seismic profiles along the upper Gulf of Thailand (Putthapiban et al., 2010) confirmed that the main path of the Three Pagodas Fault Path did not run through Bangkok Metropolis as previously thought.

Fig.5 The map showing four hot springs on land and one high heat flow spot, GT1, offshore forming a straight line which runs at N44°W suggesting the main Three Pagodas Fault Path in the region. The other four submarine high heat flow spots which form another perfect straight line sub-parallel to the first one and have a trace of N20°W. The apparent offset is possible the northeastward continuation of the Ranong lateral Fault Zone which runs at N25°E (background is from Geological Map of Thailand, Scale 1: 2,500,000, Department of Mineral Resources, 1999) CRUSTAL MOTION FROM GPS MEASUREMENTS Sundaland block motion using global positioning system (GPS) measurements have been carried out and reported by many researchers including; Michel et al., Simons et al., 2007, and Socquet et al. 2006. These studies indicate that Sundaland constitutes a relatively stable tectonic block moving approximately east with respect to Eurasia at a velocity of 12 ± 3 mm/yr (Michel et al., 2001). With respect to India and Australia this block moves due south.

GPS measurements also confirm that the current motion of India is approximately 50 mm/year with right lateral motion between India and Sundaland in the Andaman-Burma region.

Thailand as a whole is generally under compressive stress. Surrounding plates motions

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are in opposing directions; Indian Plate and Australian Plate to the northeast, South China Block to the south and southeast and the Phillipines Plate and Pacific Plate to the west which make Thailand a relatively stable landmass (Fig. 6). Shear stress is mainly confined to the north, northwest, west and southern peninsular where relative movement and active faults are located. The Red River fault in South China and Vietnam is still active and accommodates a strike-slip motion of appx.

2 mm/yr. Sundalands internal deformation (Fig. 7) is generally very small (less than 7 nanostrain/yr), with an important accumulation of elastic deformation occurring along its boundaries with fast-moving neighboring plates (Simons et al., 2007).

The GPS measurements from 8 stations along both sides of the Three Pagodas Fault and Sri Sawat Fault zones during 2007 â&#x20AC;&#x201C; 2010 show no sign of displacement (Emaruchi and Putthapiban, 2011). This confirms the slow movement, appx. 1 mm/yr, as shown in Fig. 6.

Fig.7 SEAMERGES GPS velocities with regard to Sundaland. The integer numbers near the vector heads are the norm of the velocity vector in mm/yr. Thick and thin solid black lines depict the primary and secondary fault systems in the region, and the annotated lines represents the trace of the trenches associated with active subduction. The boxes denote the four investigated Sundaland boundary zones that exhibit clear deformation patterns (after Simons, et.al., 2007).

DISCUSSION AND CONCLUSIONS

Fig.6 Geologic setting of Thailand and the Sundaland block shows topography, seismicity, main active faults, and the approximate (absolute/ITRF2000) motions of the Eurasian, Indian, Australian, Philippine plates and the South China block, near and in SE Asia (After Simons, W.J.F., et. al., 2007).

1. Geological setting and tectonic framework of the Sundaland block including a large part of Thailand at its the northern end is relatively stable. Thailand as a whole is generally under compressional stress.

Surrounding plates motions are in opposite direction; Indian Plate and Australian Plate to the northeast, South China Block to the south and southeast and the Phillipines Plate and Pacific Plate to the west which make Thailand a relatively stable area.

2. GPS measurements on the regional crustal motion and block behavior suggests that the Australian plate, Indian plate and the South China block are rotating clockwise about a large area of Thailand and the Indochina countries with the residue vectors forcing the Sundaland block to move southeastward slowly at a rate of

20

approximately 12 ± 3 mm/yr (Michel et al., 2001).

3. Shear stress is mainly confined to the edges of the Sundaland block reflecting a few major regional strike slip faults such as the right lateral Great Sumatra Fault, the Sagiang Fault between Indian plate and the Sunda block in Myanmar with approximately 18 mm/yr of right lateral slip (Socquet et al., 2005) and the Red River Fault between South China block and Vietnam with approximately 5 mm/yr of right lateral slip (Michel et al., 2001).

4. Northern and Southern Thailand show higher rate of motion, ~ 2-4 mm/yr. than that of central and western Thailand which show the least motion ~ 1 mm/yr indicating that the former areas are higher risk in term of earthquake activities.

5. The higher surface water temperatures of the hot springs in northern Thailand, 80 – 100 ºC and those of southern Thailand, 60 – 80 ºC when compared to those of western Thailand, 39 – 59 ºC suggests that the active faults in the former two areas are relatively more sensitive.

The region is always triggered by seismic waves. In contrast, the much lower surface water temperatures of hot springs in western and central Thailand indicate the relatively more stable or lower seismic risk zone of the region.

6. The Northeast Ranong Fault that apparently offsets the Northwest Three Pagodas Fault indicating that the Three Pagoda Fault is moving only at a very sluggish rate or almost inactive.

7. These observations on the geological and tectonic model indicate that the lower part of southern peninsular Thailand has a higher seismic risk than that of the western Thailand which has a lower seismic risk as was proposed

by Pailoplee et al., 2028.

ACKNOWLEDGEMENTS Mahidol University is grateful for kindly provided research grant for active fault studies in Kanchanaburi and adjacent area. Asst. Prof.

Chernchok Soankwan, the Acting Vice President of Mahidol University, Kanchanaburi Campus is thanked for his full support. Dr. Santi Pailoplee, Mr. Preecha Saithong and Mr. Manop Raksaskulwong for valuable comments and discussions. Mr. Pramote Nontarak help organizing the figures. Dr. Robert B.Stokes offered valuable comments and kindly reviewed the manuscript.

REFERENCRS Department of Mineral Resources, 1999, Geological Map of Thailand, Scale 1:2,500,000.

Department of Mineral Resources, 2005, Thailand Earthquake Risk Map. Emaruchi, B. and Putthapiban, P., in prep., GPS Observations on the Slip Rate on Three Pagodas and Sri Sawat Strike Slip Faults, Western Thailand.

Geological Survey of Japan and Coordinating Committee for Coastal and Offshore Geoscience Programmes in East and Southeast Asia, 1997, Heat Flow Map of East and Southeast Asia, Miscellaneous Map Series 36.

Michel, Gero. W., Yu Q. Y., Zhu Y. S., Reigber, C., Becker, M., Reinhart, E., Simons, W., Ambrosius, B., Yigny, C., Chamot-Rooke, N., Le Pichon, X., Morgan, P., and Matheussen, S., 2001, Crustal motion and block behaviour in SE-Asia from GPS measurements, Earth and Planetary Science Letters 187, 239-244.

Pailoplee, S., Sugiyama, Y., and Charusiri, 2008, Probabilistic Seismic Hazard Analysis in Thailand and Adjacent Areas by Using Regional Seismic Source Zone, Proceeding of the International Symposium on Geoscience Resources and Environments of Asian Terrane (GREAT 2008), 4th IGCP 516 and 5th APSEG, November 24-26, 2008, Bangkok, Thailand.

Peltzer, G. and Tapponnier, P. 1988. Formation and evaluation of strike-slip faults, rifts and basins during the India-Asia collision: An experimental approach. Geophysics Resource 93(B12), 15085-15117.

Putthapiban, P., Chantong, W., Srisuwon, P., Praipiban, C. and Pananont, P., (in press), Geothermal and Seismic Evidence for a Southeastern Continuation of the Three Pagodas Fault Zone in the Gulf of Thailand, the paper presented at the 5th International Conference on Applied Geophysics in Phuket, Thailand, November 2010, Journal of Science and Technology, Sonklanakarin.

Raksaskulwong, M. and Thienprasert, A. 1995. Heat Flow Studies and Geothermal Energy Development in Thailand. In Terrestrial Heat Flow and Geothermal Energy in Asia, M. L. Gupta and M. Yamano, editors. Oxford & IBH Publishing Co. PVT. LTD. New Delhi, India, pp 129-143.

Simons, W.J.F., Socquet, A., Vigny,C., Ambrosius, B.A.C., Haji Abu, S., Promthong, C., Subarya, C., Sarsito, D.A., Matheussen, S., Morgan, Pl, and spakman, W., 2007, A decade of GPS in Southeast Asia: Resolving Sundaland motion and boundaries, Journal of .Geophysics Resource,12, B0640,

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doi:10.1029/2005 JB003868, 20p.

Takashima, I. and Jarach, W. 1981. Geothermal resources of Thailand. Shishitsu News. 325, 33-39.Takashima, I., Honda, S. and Raksaskulwong, M. 1989. Heat source and hydrothermal systems of non-volcanic geothermal resources in northern Thailand. In

Origin and Rservior Characteristics of Nonvolcanic Geothermal Resources of Northern Thailand, editor. S. Honda. Akita Univ., Japan. pp. 31-49.

Thienprasert, A. and Raksaskulwong, M. 1984. Heat flow in northern Thailand. Tectonophysics.

103, 217-233.

Palaeobiogeographic Analysis of the Early to Middle Jurassic (Toarcian-Aalenian) Bivalves of Western Thailand.

Robert B. Stokes Geoscience, Mahidol University, Kanchanaburi Campus, Sai Yok, Kanchanaburi 71150, Thailand E-mail : surbitongs@gmail.com

ABSTRACT Data on the distribution of Early to Middle Jurassic bivalve species present in western Thailand and other countries in Asia are analyzed by use of the Simpson Coefficient. The results show that the Thai fauna had a strong similarity to that of Japan, much less to that of southern Vietnam, and less still to that of the Shan Plateau. Such counter-intuitive and anomalous results probably result from an inadequate taxonomy of Jurassic bivalves in SE Asia, and, with regard to the Shan Plateau at least, a comparison of faunas of significantly differing ages.

Key words : Marine bivalves, Shan Plateau, Myanmar, southern Vietnam, Japan INTRODUCTION Kozai et alia (2006) presented a considerable amount of data regarding the bivalve fauna from the Early to Middle Jurassic of the Umphang and Mae Sot areas of western Thailand and contemporary bivalve faunas from elsewhere in SE Asia, Japan, Pakistan (Cutch), Iran, Northern Sinai, and Europe. They concluded that the Jurassic bivalves of Mae Sot and Umphang “characterize a widely endemic SE Asian Province at the edge of Eastern Tethyan Eurasia.” (Kozai et al., 2006:210).

Their data presented me with the possibility of assessing the relative proximity of the SE Asia terranes during the Jurassic, and whether they indicated a separation of ShanThai and Indochina at that time, as has previously been suggested (Stokes et al., 1996).

The results of my quantitative analysis of the data from the paper by Kozai et al., (2006) were un-expected.

METHOD The fauna from Thailand is compared with those from Vietnam, Myanmar, and Japan by the use of a mathematical similarity coefficient based on a simple binary method (i.e. presence or absence of taxa in the faunal lists).

Of a number of coefficients available, the Simpson coefficient (Simpson, 1960) is chosen because it was devised to minimize the effect of unequal size of the two faunas being compared.

It is expressed by the ratio of the common taxa between two areas (C) with the number of taxa present in the smaller, less diverse fauna (n1). A value of 1 indicates that the faunas are identical; a value of 0 indicates that the faunas have nothing in common.

S=

C n1

It was not possible to include Iran, Europe, Sinai or Pakistan in this analysis because the total number of species in these faunas was not stated by Kozai et alia. Equally, it was only possible to make comparisons between Thailand and other countries, because data on the numbers of taxa in common is restricted to those taxa which occur in the Thai fauna.

STRATIGRAPHIC UNCERTAINTY AND CORRELATION Two main sources of error in this type of analysis are 1) inadequately known stratigraphy and 2) comparing populations from different stratigraphic horizons.

The named ‘lithostratigraphic’ units currently used for marine Jurassic rocks in western Thailand lack clear definition and precise boundary locations.

There is considerable confusion regarding the formations from which ammonite faunas were collected.

The bivalve populations from Mae Sot and

23

Umphang, listed by Kozai et alia (2006), are from horizons which lack ammonites making some of the chronostratigraphic ages uncertain.

Whilst the bivalves from western Thailand have been collected from strata ranging in age from Toarcian to Aalenian, the faunas to which they have been compared show a wide rage of ages, not all of which correspond to the Thai faunas. The Vietnamese and Japanese Toarcian material is clearly coeval with much of the Thai bivalve fauna. The bivalves mentioned from the Shan States of Myanmar come from 1) the Napeng ‘Beds’, which are generally regarded as Triassic in age (Rhaetian or possibly Norian – 68 species) and 2) the Namyau ‘Series’ which is Bathonian and Callovian in age (63 species) (Pascoe, 1968:1191-1203; Bender, 1983:82-84).

TAXONOMIC UNCERTAINTY A further source of error in the analysis of faunal affinities comes from problems of uniformity in the taxonomic database.

Of the 35 species listed from Thailand, very few (6 species = 17%) are named species identified with confidence; one (3%) is an unnamed species (indicated by ‘sp.’); five (14%) can be compared to named species (indicated by ‘cf.’); but the great majority (23 species = 66%) have only affinities with named species (indicated by ‘aff.’).

Given the high degree of taxonomic uncertainty present, it may be more accurate to conduct the analysis at generic level when data is available.

ANALYSIS AT SPECIES LEVEL For this analysis all species listed in Table 1 of Kozai et alia (2006) are regarded as accurate determinations and no distinction is made between definite, “cf.” and “aff.” identifications (see section 4 above). The total number of 35 species from Thailand is used without any attempt to subdivide them

stratigraphically (see section 3 above). For Vietnam the 65 Toarcian species from southern Vietnam are used; for Myanmar, the 63 species from the Namyau ‘Series’; and for Japan, the 20 Toarcian species. The results are shown in Table 1.

The analysis reveals results which are counter-intuitive. The Thai bivalves are least similar to those of the Shan Plateau of Myanmar; have only slightly greater affinities with those of southern Vietnam; but have a high degree of similarity to those of Japan.

CONCLUSIONS At face value, these results would indicate that in the Jurassic western Thailand was closer to Japan than any other region under analysis, far removed from southern Vietnam, and even further distant from the Shan Plateau.

Acceptance of such conclusions would suggest that all current theories about palaeotectonic and palaeogeographic reconstructions for southern and eastern Asia in the mid-Mesozoic are gravely inaccurate. Since this is an unacceptable hypothesis given the weight of evidence for western Thailand to be contiguous with the Shan Plateau (forming the Shan-Thai Block or SIBUMASU) and its possible proximity to southern Vietnam (the Indochina Block) in the Jurassic, (an) alternative explanation(s) must be sought.

The most likely cause for the anomalous results is that the taxonomy of Jurassic bivalves in SE Asia is not sufficiently accurate to enable them to be used in a quantitative analysis. The low similarity between bivalve faunas of western Thailand and the Shan Plateau is most probably due to the significantly different ages of the faunas being compared.

Table 1 Total number of species, number of species in common with Thailand, and Simpson Coefficients for marine Jurassic bivalves. See text for further details.

Total no. of species No of species in common Simpson Coefficient

Thailand 35 -

Myanmar 63 6 0.17

Vietnam 65 8 0.22

Japan 20 13 0.66

24

REFERENCES Bender, F., 1983. Geology of Burma. Beitrage zur Regionalen Geologie der Erde, 16.

Borntraeger, Berlin & Stuttgart.

Kozai, T., Hirsch, F., Ishida, K. & Meesook, A., 2006. Faunal affinity of Toarcian-Aalenian (Early Jurassic) bivalves from Mae Sot and Umphang (Tak Province, Northwestern Thailand. Geosciences Journal, 10 (3), 205215, 2 plates, 4 figures, 1 table.

Pascoe, E., 1968. A Manual of the Geology of India and Burma, Vol. 2. 3rd Edition. xxii + 485-

1338, numerous plates, figures and maps.

Geological Survey of India, Calcutta & Delhi.

Simpson, G., 1960. Notes on the measurement of faunal resemblance. American Journal of Science 258-A, 300-311.

Stokes R B, Lovatt Smith P F & Soumphonphakdy K., 1996. Timing of the Shan-Thai Indochina collision : new evidence from the Pak Lay foldbelt of the Lao P.D.R. In Hall, R. & Blundell, D. J. (Editors), Tectonic Evolution of SE Asia, Geological Society Special Publication No. 106, 225-232. London.

The Late Cimmerian Event in Western Thailand and Central Lao PDR. Robert B. Stokes Geoscience, Mahidol University, Kanchanaburi Campus, SAI YOK, Kanchanaburi 71150, Thailand E-mail : surbitongs@gmail.com

ABSTRACT The folding and faulting of marine Jurassic strata in western Thailand is interpreted as a Jurassic-Cretaceous boundary event, pre-dating the unconformable deposition of non-marine Cretaceous conglomerates. Correlations with comparable sequences in the central Lao PDR constrain the upper age limit of the conglomerates to be pre-Khorat.

This suggests a rapid period of folding, uplift and erosion followed by rapid deposition of non-marine conglomeratic sediments transported by high velocity currents in extensive mountainous terranes. This evidence points to a period of intense epeirogenic movements in end-Jurassic â&#x20AC;&#x201C; early-Cretaceous times, corresponding the Late Cimmerian events so widespread elsewhere in Asia and Europe. A consequence of dating the Cretaceous conglomerates as pre-Khorat, is that the base of the Khorat Group is later than currently accepted, and possibly no older than Valanginian.

INTRODUCTION Until recently the consensus on the geological history of Thailand held that there was a major orogenic event in the mid- to late Triassic (the Indosinian Orogeny) which was followed by a period of quiescence whilst the â&#x20AC;&#x2DC;Khorat Groupâ&#x20AC;&#x2122; red-beds were accumulated on a slowly sagging basement from the Late Triassic until the Late Cretaceous or even Tertiary times.

The realization by Racey et alia (1994), that the Jurassic was missing from the Khorat Group, led not only to a revision of Khorat Group stratigraphy (see Racey 2009 for recent review), but also recognized that the thermal sagging of basins of NE Thailand during the Cretaceous could not be the result of Triassic collision. Stokes et alia (1996) sought to resolve the latter problem by having the Indosinian Orogeny at the end of the Jurassic based on evidence from the Pak Lay fold-belt of westcentral Laos.

Evidence for a major period of folding and faulting at the end of the Jurassic has long been noted, but the significance ignored or down-played.

This paper seeks to emphasise the importance of the Late Cimmerian event by starting with a consideration of the evidence from the Mae Sot area and elsewhere in western Thailand, and moving to evidence from central Lao PDR to demonstrate that this event is widespread and that the widespread Cretaceous

conglomerates are pre-Khorat Group in age. A future paper will examine the Late Cimmerian event in the remaining parts of mainland SE Asia.

PREVIOUS WORK IN WESTERN THAILAND Komalarjun & Sato (1964:151) observed that the strike of the Jurassic rocks of the Mae Sot basin is NNW-SSE and nearly constant through the succession. They also pointed out that these rocks form part of an orogenic belt and that a deformation took place at least once after the Aalenian. They further noted that the Tertiary rocks are nearly horizontal except in marginal areas and that their fold axes are randomly oriented in contrast to the Jurassic strata whose fold axes are perfectly concordant with the general trend of the metamorphic axis of the orogenic belt. Komalarjun & Sato (1964:152 Fig. 2) illustrated this distinction by means of a sterographic projection of poles to bedding.

Komalarjun & Sato (1964:151) did not speculate at which period(s) of time the folding occurred. Campbell & Nutalaya (1975:159) state it is post-Jurassic, and, by implication of their listing, before the late Tertiary fracturing and faulting of Tertiary basins.

Baum & Jordan (1976: 17, Fig. 4) established the Mae Moei Group for a conformable sequence of Mesozoic sediments of

26

the Mae Sot Basin ranging in age from Middle Trassic (Anisian) to Late Jurassic (Oxfordian).

This would preclude a Late Triassic (Indosinian) orogenic event and place the main folding as postâ&#x20AC;&#x201C;Jurassic. Baum & Jordan (1976:18) showed that a red Cretaceous conglomerate is unconformable on the Jurassic coralline limestone NW of Mae Ramat.

More recent work by Fontaine & Suteethorn (1988:92-95) has demonstrated that an extensive area of non-marine conglomerates is no older than Cretaceous in age because they contain pebbles of Jurassic limestone up to 200 mm in diameter.

and W (exceptionally 72 o adjacent to a major fault), the strike of the bedding is E-W to NWSE in the Pang Manora Sandstone changing to NNW-SSE and N-S in the Ban Huai Hin Fon Limestones. The rapid changes in strike suggests that end-Jurassic structures have been complicated by later Cenozoic events.

Faults trend N-S to NW-SE and appear to be close to vertical. The age of these faults is obviously post-Jurassic but it is difficult to differentiate between those which might be earliest Cretaceous and those which might be Cenozoic in age.

Fontaine & Suteethorn (1988:86) postulated a fault in the region of the bridge at Ban Huai Hin Fon to explain the absence of Bathonian to Callovian stages in the Jurassic sequence. Such a fault would need to be a normal fault down-throwing to the west. Normal faulting associated with the extensional formation of the Tertiary Mae Sot Basin could be the cause of the possible fault, which would therefore probably aligned N-S (Stokes, 1986).

CRETACEOUS CONGLOMERATES IN WESTERN THAILAND

Fig.1 Map showing localities of Cretaceous conglomerates (black circles) in western Thailand modified from Fontaine & Suteethorn 1988. Jurassic pebbles (J) are found at localities 1, 6, 8 & 10; Permian pebbles (P) are found at localities 6, 7, 10 & 11 .

FOLDING AND FAULTING OF THE MARINE JURASSIC AT MAE SOT Along the Tak â&#x20AC;&#x201C; Mae Sot highway section, dips vary from 20 o to 50 o to the SW

Fontaine & Suteethorn (1988:95) record the extent of these conglomerates as being from Ban Mae Ramat (Tak Province) in the North to Khao Nong Bua Yai (Kanchanaburi Prtovince) in the South, a distance of 300 kms. In this region their post-Jurassic age is proved by the presence of pebbles of marine Jurassic limestone. Elsewhere, as Fontaine & Suteethorn (1988:95) pointed out, other conglomerates containing Permian and Triassic pebbles are probably Cretaceous in age, but this cannot be confirmed because of the lack of Jurassic pebbles. Examples of the latter include conglomerates at Khao Mae Ramphung, near Bang Saphan (Prachuab Khiri Khan Province) and at Krabi. Should these prove to be Cretaceous, the extent of Cretaceous conglomerates would be increased to around 1,250 Kms. Although the presence of pebbles marine Jurassic limestones indicates that the conglomerates must be post-Jurassic, the latest age is difficult to establish in western Thailand.

Fontaine & Suteethorn (1988:92) suggested that they span a time from the Cretaceous to the beginning of the Tertiary.

27

FOLDING OF THE JURASSIC IN CENTRAL LAO PDR In Laos, Stokes et alia (1996) first recognized a major period of folding, faulting and erosion at the end of the Jurassic, and before the deposition of the Cretaceous Khorat Group, in a region about 17 km WNW of Kenthao in the Pak Lay Fold-Belt. Here thinly-bedded grey to dark grey claystones yielding a Middle to Upper Jurassic playnomorph assemblage dip 50 o E with a strike of 008o and are overlain unconformably by the Khorat Group which shows gentle dips (c. 20 oSW) with a strike between 140 o-160 o. In this region the Cretaceous conglomerates are absent.

triangular-shaped area which is always in fault contact with other rock units (see Stokes et alia 1996: Fig 2) and are clearly only locally developed or preserved. They were inferred to be post-Jurassic and tentatively included as a basal formation of the Khorat Group beneath the Nam Set (=Phu Kradung) Formation and included in this group by Stokes et alia (1996:Fig 2). I would now suggest that this formation should be regarded as separate from the Khorat Group.

2. Ang Nam Gnum reservoir. Locality 6 of Stokes et alia (in press). On the SE shores of this reservoir, the basement of Permian limestone (Nalang Formation) is overlain by a unit conglomerates with subangular to subrounded clasts up to 100mms of sandstones and limestones in a sand matrix. The conglomerates are found only as large loose boulders and were interpreted as a basal conglomerate of a formation of reddish-brown sandstone and siltstone informally called the Phulekphay Formation in unpublished maps of Monument Resources (Overseas) Ltd (1992).

The Phulekphay Formation was interpreted as an equivalent of the Nam Phong Formation of Thailand and rergarded as Triassic in age. I would now regard the conglomerates, and possibly the overlying strata of the Phulekphay Formation as equivalents of the Cretaceous Conglomerates of western Thailand and of the Kenthao Formation further west.

Fig.2 Map indicating locations in west-central Laos of successions which include the earliest Cretaceous. For explanation see text.

CRETACEOUS CONGLOMERATES IN CENTRAL LAO PDR Isolated conglomerates which are most probably of Cretaceous age, have been found in two regions of central Laos : 1. Kenthao town area. In the immediate vicinity of Muang Kenthao are outcrops of redbrown sandstone, claystones and conglomerates (with clasts up to 90 mm diameter) which were informally called the Kenthao Formation in unpublished maps of Monument Resources (Overseas) Ltd (1995). They occur in an isolated

Fig.3 Correlation of some successions in western Thailand and west-central Laos which constrain the age of the Cretaceous conglomerates to the earliest Cretaceous. For explanation see text.

28

CONCLUSIONS The conglomerates contain pebbles/boulders up to 200 mm in diameter.

This size suggests water velocities of approximately 2 m/s. Such velocities are only possible with a considerable gradient and a considerable volume of water. The rounded shape of the pebbles indicates a considerable transport distance. From these facts it is concluded that the Cretaceous conglomerates formed within, or on the margins of a young mountain belt. Other than the belt in western Thailand from Mae Ramat to Khao Nong Bua Yai, I do not see the conglomerates as forming a continuous sheet of sediment across the area; rather, I see them as local pockets of accummulation resulting from contemporaneous crustal movements.

The age of the conglomerates can be fixed as no earlier than Cretaceous from the evidence presented by Fontaine & Suteethorn (1988) from western Thailand, and no later than Early Cretaceous from the evidence presented here from Kenthao in central Laos.

Together, the evidence from western Thailand and west-central Laos indicate the extension of the Late Cimmerian event into SE Asia.

These conclusions indicate that the base of the Khorat Group must be later than currently thought and some time later in the Early Cretaceous. Late Cimmerian movements in the North Sea of NW Europe are at their peak in the Ryazanian (=Berriasian), the earliest stage of the Cretaceous, and fade away in the early part of the succeeding Valanginian stage (Oakman & Partinton1998:Fig.9.6). If this dating is of global application, the base of the Khorat Group would be no older than Valanginian.

In 1996, Stokes et alia argued that the end Jurassic event was an orogenic episode resulting from the collision of Shan-Thai and Indochina.

The lack of associated metamorphism and plutonism may point to intense epeirogenic movements of the crust rather than a true orogeny.

REFERENCES Braun, E. von. and Jordan, R., 1976. The Stratigraphy and Paleontology of the Mesozoic Sequence in the Mae Sot Area in Western Thailand.

Geologisches Jahrbuch, (B) 21, 5-51, 7 figs., 1 tab., 7 pls. Hannover.

Campbell, K.V. and Nutalaya, P., 1975. Structural Elements and Deformational Events. In Stokes, R.B., Tantisukrit, C. & Campbell, K.V. (eds), Proceedings of the Conference on the Geology of Thailand. Department of Geological Sciences Chinag Mai University, Special Publication, 1 (1), 155-164 plus map.

Fontaine, H. and Suteethorn, V., 1988. Late Palaeozoic and Mesozoic Fossils of West Thailand and their environments. CCOP Technical Bulletin, 20, 1-108, 31 figs., 8 pls.

CCOP, Bangkok.

Komalarjun, P. and Sato, T., 1964. Aalenian (Jurassic) ammonites from Mae Sot, Northwest Thailand.

Japanese Journal of Geology and Geography, 35, 149-162, figs. 1-6, 1 plate. Reprinted in: Geology and Palaeontology of Southeast Asia, 1, 237-251, figs. 1-6, pl. 6. Tokyo.

Oakman, C.D. and Partinton, M.A., 1998.

Cretaceous. In Glennie, K.W. (ed) Petroleum Geology of the North Sea: Basic concepts and recent advances. 4th edition. 294-349.

Blackwell Science, Oxford.

Racey, A., 2009. Mesozoic red bed sequences from SE Asia and the significance of the Khorat Group of NE Thailand. In: Buffetaut, E., Cluny, G., Le Loeuf, J. & Sutethorn, V. (eds) Late Palaeozoic and Mesozoic Ecosystems in SE Asia. Geological Society of London, Specdial Publications, 315, 41-67, 14 figs.

Racey, A., Goodall, J.G.S., Love, M.A., Polachan, S., and jones, P.D., 1994. New age data for the Mesozoic Khorat Group of Northeast Thailand.

In: ANgsuwathana, P., Wongwanich, T., Tansathien, W., Wongsomsak, S. & Tulyatid, J. (eds), Proceedings of the International Symposium on Stratigraphic Correlation of Southeast Asia, 15-20 November 1994, Bangkok, Thailand, 245-252, 3 figs., 1 plate. Department of Mineral Resources, Bangkok.

Stokes, R.B., 1986. Structural Control of Neogene sedimentation in the Mae Sot basin (ThaiBurmese border): implications for oil-shale reserves. Proceedings of the First Conference on Geology of Indochina, 3, 1195-1199.

General Department of Geology of Vietnam, Hanoi. Also 1988 in Journal of Petroleum Geology, 11, 341-346, Beaconsfield.

Stokes, R.B., 1988. Correlation of the Permian “Phawa Limestone” of Thailand with the “Kamawkala Limestone” of Burma. Journal of Southeast Asian Earth Sciences, 2, 35-39, figs. 1-2, 1 table. Oxford.

Stokes, R.B., Lovatt Smith, P. and Soumphonphakdy, K., 1996. Timing of the Shan-Thai -Indochina collision : new evidence from the Pak Lay foldbelt of the Lao P.D.R. In Hall, R. & Blundell, D. J. (Editors), Tectonic Evolution

29

of SE Asia, Geological Society Special Publication No. 106, 225-232. London.

Stokes, R.B., Lovatt Smith, P., Racey, A., Brunton, C.H.C., Dawson, O., Swan, A.R.H. and Whitaker, M.F., (in press). Some Upper Palaeozoic fossil localities in the Vientiane Contract Area, Lao PDR, and their geological importance. Proceedings of the 2nd International Conference on Palaeontology of Southeast Asia, November 2010.

Mahasarakham University Journal.

Application of Rare Event Logistic Regression Model to Landslide Susceptibility Mapping: A Case-Study in the Kitchakut Mountain, Chanthaburi, Thailand.

Thanit Intarat* and Watcharaporn Keankeo Faculty of Geoinformatics.

Burapha University, Chon Buri 20131, Thailand.

E-mail : thaniti@buu.ac.th

ABSTRACT The objective of this study is to produce a landslide susceptibility map of the Kitchakut range, Chanthaburi using a combination of rare events logistic regression and geographic information system as analyzing tools. The dependent variable is binary of historical landslide occurrence obtained by visual interpretation of color aerial photograph and field survey. The independent variables are the related factors extracted from digital elevation model and from geology, forest, landuse, and soil maps.

The landslides in the study area can be regarded as “rare events” because the landslide occurrences in the study area are twelve times fewer than non-occurrences.

Rare events logistic regression, different from ordinary logistic regression, incorporates three correction measures: the endogenous stratified sampling of the dataset, the prior correction of the intercept and the correction of probabilities to include the estimation uncertainty.

After excluding non-significant independent variables, the analytical results show that elevation, rock type, aspect, slope and fault are the most important predictive variables to a landslide model in the study area, respectively. Minus twice the log of the likelihood (-2LL) and Pseudo R2 are used to validate the model. Both show a good agreement between the observed and predicted values of the validation dataset. The resulted landslide susceptibility map is classified into four classes: very high, high, moderate and low susceptibility, covering 2%, 19%, 19% and 60% of the total study area, respectively.

INTRODUCTION In the past two decades, there are many landslide events occurring in Thailand. These disasters cause extensive damage to property and occasionally result in loss of life. In 1999, a landslide event in Kitchakut Mountain, Chanthaburi Province, destroyed almost of the agricultural area and properties around there.

Landslide in the Kitchakut mountain is triggered by the heavy rainfall (more than 400 mm.) and the chemical weathering bedrock in the area.

The rapid mass movement such as, debris flow and rock fall brought tree ruins, boulders 1 meter or more in diameter and various size of particles down to the slope and deposit around the Kitchakut mountain. According to the heavy rainfall, the hazardous and urban area was also affected by flash flood. No matter what the landslide event has occurred many years, there

is a possibility of landslide occurrence in the near future that cannot be specified. This uncertainty always gives suspicion to the villagers who live in that area.

The objective of this study is to produce a landslide susceptibility map of the Kitchakut Mountain, Chanthaburi using a combination of rare events logistic regression and geographic information system as analyzing tools. This conceptual model is based on the hypothesis that “the past and the present are the key to the future” (Carrara et al., 1995). The area susceptible to landslide will be selected because of their similarity in environmental characteristics to the landslides already mapped in the study area. Among all the methodologies used to model landslide susceptibility, statistical and physical-based models are the most widely used (Van Den Eckhaut et al., 2005).

31

Fig.1 Landslide occurrence in the study area. (Credit by Watchrakorn Maireang)

Select study area

Construction of intrinsic factors Detection of landslide occurrence Relative factors selection using statistical methods

Application of rare event logistic regression model

Model validation and landslide susceptibility mapping

Fig.2 Flow diagram of the study.

32

STUDY AREA The Kitchakut Mountain is situated in the central of Chanthaburi Province, that covers 600 km2 with 4 districts, geographically it is located at longitude 102 ° 06’ E and latitude 12° 51’ N. and 350 kilometers far from Bangkok (Fig.3) The bedrock geology of the study area consists mainly of the Triassic biotite granite and granodiorite (Fig.4) There were two types of landslides in the study area: debris flow in the western part and rock slide in the eastern part.

A detailed field survey in combination with the visual interpretation of color aerial photograph in the Kitchakut Mountain revealed that the study area had at least 590 landslides mainly occurred in the southern part of the area.

In order to reduce the damage caused by landslide initiations and reactivations, a landslide susceptibility map is needed and would be a useful tool not only the geographer but also for local and regional authorities, decision makers and provincial strategy planners.

Fig.3 The study area location.

(A)

(B)

Fig.4 Chemical weathered Triassic biotite granite (A) and Grano-diorite (B) founded in area.

33

MATERIALS AND METHODS

VIF ( X n ) =

Mapping of landslide and causal factors In this study the landslide occurrence map was created through the combination of the color aerial photography interpretation and field survey in 600 km2 of the study area. There were at least 590 landslides and all of them will be used for rare events logistic regression analysis.

A 10 meters grid cell resolution was chosen in order to create a landslide susceptibility map.

Landslides locations in the inventory map were replaced by the central point of each landslide grid cell unit. Each mapping unit is given a code typically ‘1’ and ‘0’ to indicate the ‘presence’ or ‘absence’ of the landslide, respectively using ArcView 3.1.

The predictor variables used in this study are topographical variables (aspect, elevation, slope, landuse and forest), geological variables (rock type, distance to fault, and distance to approximately fault) and soil (material, texture and drainage). All variables were acquired from Faculty of Geoinformatics, Burapha University.

Statistical selection

method

for

relative

factors

Chi2 was used to test the association between each predictor variable and the occurrence of landslides (Van Den Eckhaut et al., 2005). Then Cramer’s V was derived from Chi2 to test the strength and type of association (Norusis, 2005). Cramer’s V is bounded by 0 and 1 and can attain the maximum of 1for a table of any size. Cramer’s V is shown as equation 1

V=

χ

2

N min( R − 1)(C − 1)

(1)

When N is the sample size, R is the number of the rows in the contingency table, and C is that of the columns.

The model fitting via logistic regression tends to collinearities among the independent variables (Kosaiyanet, 2006). Then the Variation Inflation Factor (VIF) is used to improve the problem using R software (equation 2) with VIF of > 2 would be excluded from the analysis (Van Den Eckhaut et al., 2005).

Where

1 1 − Rn2

Xn

(2)

is the independent variable,

and Rn is relationship from the predicting of variable from all of the other independent variables in the model.

2

Rare events logistic regression Ordinary logistic regression describes the relationship between a dependent variable and a set of independent variables to clarify the chance of the event. The model aims to calculate the probability of presence and absence in the area. The significance in logistic regression is obtained by comparing the maximum likelihood estimation with its estimated standard error (Hosmer and Lemeshow, 2000). The significance level of this study is at a 0.05. The relationship between the occurrence and its dependency on several variables can be shown as equation 3.

P (Y = 1) = pˆ =

1 1+ e

( αˆ + βˆ1 x1 + βˆ 2 x 2 +... + βˆ n x n )

(3)

Where pˆ is probability of occurrence of landslide. The probability varies from 0 to 1 on S-shape curve. αˆ is the intercept of the model, the βˆi are the slope coefficient of the logistic regression model, and the xi are the independent variables estimated by maximum likelihood.

By the way, logistic regression may cause some problems if the total area affected by landslides is much smaller than the total study area (12 times or more). It can be regarded as ‘rare events’. This case can underestimate the probability of occurrence of the event (King and Zeng, 2001). To correct this problem, three corrections are brought to adjust the model.

The first correction is the representative random sampling of the dataset. It deals with the selection of the representative sample, nonlandslides cells have to be selected 1 to 5 times more than the number of landslide cells. In this study, the 590 central cells of the landslide scars were used. As mentioned, 2,950 cells of nonlandslide were constructed by stratified random sampling method.

34

The random sampling may cause the bias on the logistic coefficients. The second correction, called the prior correction of the intercept, is brought to reduce the problem. By using the actual fraction of 1s in the population, τ , and the observed fraction of 1s in the sample data, y . This process can be calculated as equation 4.

α = αˆ − ln

⎡⎛⎜ 1 − τ ⎞⎟⎛ y ⎞⎤ ⎢⎣⎝ τ ⎠⎜⎝ 1 − y ⎟⎠⎥⎦

(4)

However, the result after put the corrected intercept into the logistic regression model is underestimation according to the coefficient

βˆi

is

neglected.

C i to

Adding

the

ˆ

p should deal with the correction factor estimation uncertainty of the coefficients. The corrected values are shown in equation 5.

P (Yi = 1) = ~pi + C i For each observation in equation 6.

Ci

(5)

X

X

Statistical selected Factors Initially, there were 11 factors used in this study. These factors have to be examined before analyzed by logistic regression model. To prevent the error that could be occurred, Cramer’s V and VIF were used for selecting the appropriate factors. The result is shown in table 1.

According to the table 1, there were 5 selected factors, for instance aspect, elevation, slope, rock type, and distance to fault. These factors were brought into the RELOGIT analysis in the next step.

Rare events logistic regression model in the Kitchakut Mt. The selected factors were brought into the statistical analysis using RELOGIT function in R Software (Imai et al., 2007) , and the following relation was found:

(6)

⎛ pˆ ⎞ ⎟⎟ log(Oods) = log⎜⎜ ⎝ 1 − pˆ ⎠ = -10.41 + 0.18(Aspect) + 0.56(Elevation) + 0.18(Rock type) + 0.07(Slope) + 0.03(Distance to fault)

is a 1× (n + 1) vector of value for

each independent variable, of

RESULT

is calculated as shown

C i = (0.5 − ~pi ) ~pi (1 − ~pi )XV ( β ) X ′ Where

In this study, the negative of twice the log likelihood (-2Log L) and Pseudo R2 were used to validate how well the model fit.

X′

is the transpose

and V (β ) the variance-covariance matrix.

Table 1 Selected variables result.

No. 1 2 3 4 5 6 7 8 9 10 11

Factors

χ2

Critical value 15.51 12.59 9.49 5.99 11.07 9.49 7.81 12.59 14.07 3.84 3.84

P-value*

Aspect** 331.3 0.0 Elevation** 658.1 0.0 Slope** 167.9 0.0 Forest 235.9 0.0 Rock type** 400.8 0.0 Landuse 269.2 0.0 Soil drainage 139.0 0.0 Soil material 347.5 0.0 Soil texture 348.5 0.0 Distance to fault** 8.7 0.0 Distance to app.

0.1 0.7 fault * Significance level at 0.05, **Selected independent variable

Cramer’ sV 0.30 0.43 0.22 0.26 0.34 0.28 0.19 0.31 0.31 0.06 -

VIF (<2) 1.22 1.60 1.26 2.44 1.33 2.52 2.43 4.89 5.32 1.06 -

result Select Select Select No Select No No No No Select No

35

Model validation and landslide susceptibility map in the Kitchakut Mt. The decreasing in the minus twice the log likelihood of the intercept only compared with the minus twice the log likelihood of the intercept with covariates and the Pseudo R2

value (0.267) indicate that the model had a good fit as shown in table 2.

The relation was converted into the map and the susceptibility was classified into 4 classes, very high, high, moderately and low, respectively shown in Fig. 5.

Table 2 The statistical validation results Statistics -2 Log Likelihood of the intercept only -2 Log Likelihood of the intercept and covariates

Value 3,190.000 2,518.300 0.267

Pseudo R 2

Khao Sa Ba

Khao Soi Dow Nua

Khao Ang Rab

Khao Soi Dow Tai

Khao Takean Thong

Khao Plong

Khao Pra Bat

Fig.5 Landslide susceptibility map.

DISCUSSION AND CONCLUSION All of the mountains in the Kitchakut range have the susceptibility to landslide occurrence, especially Khao Soidao and Khao Saba that situated in the northern part of the

range. However, the most area of the landslide occurrences are founded in the southern part of the range, because there are joint sets and faults in the area that drive the chemical weathering activate to the bedrock. The quantity of the rainfall also has an influence on the landslide

36

occurrence (Department of Mineral Resources, 2006). If the rainfall is more than 400 millimeters/day, the landslide would be occurred.

Regarding to the present and absent of the landslide were presented by the value of “1” and “0”, the Logistic Regression analysis was suitable to use in the study (Hosmer and Lemeshow, 2000) and provided a good result.

This method was used by many studies and compared to the other statistical methods (Ayalew et al., 2005). Most of the studies revealed that the result analyzed by the Logistic Regression method had more reliable results than the other methods (Lee and Min, 2001 ; Lee, 2004).

There are 5 factors influenced on the landslide susceptibility in the study area for instant, elevation, rock type, aspect, slope, and distance to fault. The resulted landslide susceptibility map was classified into four classes: very high, high, moderate and low susceptibility, covering 2%, 19%, 19% and 60% of the total study area, respectively.

ACKNOWLEDGEMENT I am very appreciate to thank Asst. Prof.

Dr. Watcharaporn Keankeo, Assoc. Prof. Dr. Kaew Nualchawee, and Mr. Kittisuk Rattanadadart for providing the valuable knowledge in this study.

REFERENCE Ayalew, L., Yamagishi, H., Marui, H. and Kanno, T., 2005. Landslides in Sago island of Japan: part 2, GIS based susceptibility mapping with

comparisons of results from two methods and verifications. Engineering Geology, 81: 432445.

Carrara, A., Cardinali, M., Guzzetti, F. and Reichenbach, P., 1995.

Geographical Information Systems in Assessing Natural Hazards. In Carrara, A., & Guzzetti, F. (Eds), GIS technology in mapping landslide hazard.

Dordrecht: Kluwer Academic, 135-175.

Department of Mineral Resources, 2006. Landslide hazard information network, Chanthaburi.

Bangkok: Department of Mineral Resources.

Hosmer, D.W. and Lemeshow, S., 2000. Applied Logistic Regression. New Jersey: John Wiley & Sons.

Imai, K., King, G. and Lau, O., 2007. Zelig: everyone’s statistical software, version 2.8-2, user’s manual [monograph on the Internet]. [cited 2007 May 4]; Available from:URL: http://gking.harvard.edu/zelig/docs/zelig.pdf.

King, G. and Zeng, L.,2001. Logistic regression in rare events data. Political Analysis, 9:137-163.

Kosaiyanet, S.,2006. Multicollinearity: example in binary logistic regression. DMBN, 2 (1):9-17.

Lee, S. and Min, K., 2001. Statistical analysis of landslide susceptibility at Yongin, Korea.

Environmental Geology, 40: 1095-1113.

Lee, S., 2004. Application of likelihood ratio and logistic regression to landslide susceptibility mapping using GIS. Environmental Management, 34(2): 223-232.

Norusis, M.J., 2005. SPSS 13.0 Statistical Procedures Companion. New Jersey: Prentice Hall.

Van Den Eeckhaut, M., Vanwalleghem, T., Poesen, J., Govers, G., Verstraeten, G. and Vandekerckhove, L.,2005. Prediction of landslide susceptibility using rare events logistic regression: a case-study in the Flemish Ardennes(Belgium). Geomorphology, 76:392410.