Journal of Marine Science and Engineering

Article Impact of Sea Level Rise on Tourism Carrying Capacity in

Pattrakorn Nidhinarangkoon 1,*, Sompratana Ritphring 1 and Keiko Udo 2

1 Department of Water Resources Engineering, Kasetsart University, 10900, Thailand; [email protected] 2 International Research Institute of Disaster Science, Tohoku University, Sendai 9808572, Japan; [email protected] * Correspondence: [email protected]

 Received: 26 December 2019; Accepted: 4 February 2020; Published: 10 February 2020 

Abstract: Sea level rise due to climate change affects beaches, which are a source of high recreational value in the economy. The tourism carrying capacity (TCC) assessment is one of the tools to determine the management capacity of a beach. beach represents the character of well-known beaches in Thailand, while Chalatat beach represents the character of beaches that are the focus of domestic tourism. To evaluate beach area this study detected the shoreline position using Google Earth images with tidal correction. The Bruun rule was used for shoreline projection. TCC was calculated by using the beach area, correction factors, and management capacity. The results find that the current effective carrying capacity is approximately 200,000 for Pattaya beach and 49,000 for Chalatat beach. Although the Chalatat beach areas are larger than Pattaya, the effective carrying capacity of Pattaya beach is larger than the effective carrying capacity of Chalatat beach for all situations because TCC is affected by beach areas, correction factors, and management capacity. Because beach areas experience the effects of sea-level rise, protection against future beach loss should be considered for coastal management.

Keywords: climate change; sea level rise; tidal correction; Bruun rule; tourism carrying capacity; Pattaya beach; Chalatat beach

1. Introduction The beach is an important ecosystem that has many benefits, including recreation, fisheries, and a buffer near the ocean. Recreation opportunities on the beach affect economic growth in many coastal areas. In this study, Pattaya beach and Chalatat beach were chosen to be the study areas because they represent the character of well-known beaches for tourists who travel to Thailand and the character of recreational use for local people in those areas, respectively. Approximately 14 million tourists visit Pattaya annually, while 7 million tourists visit (located at Chalatat beach), according to statistical data from the Ministry of Tourism and Sports. Due to climate change, the global sea level is rising and will increase during the early twenty-first century because of increasing temperatures [1]. The data from the tidal gauge near the study area reveals that the sea level has risen approximately 14.2 mm per year from 1992 to 2006 at Pattaya beach and 7.4 mm per year from 1987 to 2011 at Chalatat beach [2]. From a previous study, the national beach loss rate projections using the Bruun rule for 2081–2100 are 45.8% for the RCP2.6 scenario and 71.8% for RCP8.5. Also, 23 of 64 beach zones in Thailand will be completely lost [3]. To address these concerns, beach area loss from sea-level rise will be an essential issue for beach tourism. The Bruun rule is the widely applied method for projecting shoreline retreat from sea level rise [4]. Tourism carrying capacity (TCC) is a tool to measure and determine the development of the beach when combining it with other management tools [5]. TCC is defined as the physical and social

J. Mar. Sci. Eng. 2020, 8, 104; doi:10.3390/jmse8020104 www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, 104 2 of 10 capacity of the environment related to tourist activity and beach development. Carrying capacity is “the maximum number of people that may visit a tourist destination at the same time, without destroying the physical, economic, socio-cultural environment and an unacceptable decrease in the quality of visitors’ satisfaction” [6]. A TCC assessment consists of physical carrying capacity (PCC), real carrying capacity (RCC), and effective carrying capacity (ECC) [7]. Beach area loss from sea-level rise decreases the carrying capacity of the beach, especially in physical terms. Moreover, the different forms of management at each beach affects that beach’s ECC. Several studies have used the Bruun rule to examine the impacts of sea-level rise on shoreline retreat that affect TCC, such as at Catalan beaches where PCC will decrease in proportion to the sea level rise [8]. In Thailand, the TCC has been analysed at (Southern part) in province. The PCC can support the tourists but the inefficient management of Jomtien beach decreases the facility carrying capacity [9]. Furthermore, the study of TCC at Jomtien beach examined present-day scenarios, which do not account for the sea level rise from climate change in future scenarios. The purpose of this study is to evaluate the change in the area of the locations under study expected to be caused by sea-level rise and the TCC of the beaches in future scenarios. The shoreline recession from sea level rise was analysed using the Bruun rule and the detection of shoreline position from satellite images using the tidal correction method. The shoreline retreat was used to calculate the changes in beach area. The areas required per-user data; the average visit time was obtained using a survey. The correction factor (a rainy day) was measured by the Thailand Meteorological Department. Then, data on beach management were collected by field observation of the two beaches. These findings should be considered in the planning of near-future coastal zone management to protect the tourism carrying capacity and beach areas from future sea level rise.

2. Study Areas and Data

2.1. Study Areas In this study, Pattaya beach represents the characteristics of a well-known beach, while Chalatat beach represents the domestic tourism of the local area in Thailand (Figure1). Thailand is a ffected by northeastern monsoons from the middle of October to the middle of February and southwestern monsoons that cause heavy rain and high waves. Pattaya beach is located in on the eastern side of the . Pattaya beach is 3 km long and divided into three areas: North Pattaya, Central Pattaya, and South Pattaya. There are many hotels and shops along the streets in front of the beach. The diverse activities at Pattaya beach include sunbathing, swimming, banana boats, jet skis, and parachuting. Moreover, snorkelling and scuba diving tours to Koh Lan are provided by tour services at Pattaya beach. Chalatat beach is 4.8 km long and located in in the southern part of Thailand. It is crowded with people on the weekend and during special festivals in Thailand. J. Mar. Sci. Eng. 2020, 8, 104 3 of 10 J. Mar. Sci. Eng. 2020, 8, 104 3 of 10

Figure 1. Study areas map. Figure 1. Study areas map. 2.2. Data 2.2. Data The data used in this study contains satellite images from Google Earth, sea level rise data, wave data, slope andThe sedimentdata used size, in this the study average contains visit time satellite and areaimages required from perGoogle user, Earth, and management sea level rise capacity. data, wave data, slope and sediment size, the average visit time and area required per user, and management 2.2.1.capacity. Satellite Images from Google Earth In this study, satellite images from Google Earth were used to detect the shoreline positions for Pattaya2.2.1. Satellite and Chalatat Images beaches from Google for the Earth periods listed in Table1. In this study, satellite images from Google Earth were used to detect the shoreline positions for Pattaya and Chalatat beachesTable 1. forTime the series periods of satellite listed imagesin Table from 1. Google Earth. Study Areas Past Present Table 1. Time series of satellite images from Google Earth. Pattaya beach 30 December 2017 16 February 2019 ChalatatStudy Areas beach 9 July Past 2017 6 AugustPresent 2018 Pattaya beach 30 December 2017 16 February 2019 2.2.2. Sea Level Rise DataChalatat beach 9 July 2017 6 August 2018 This study used sea-level rise data from 21CMIP5 models, which are the ensemble-mean regional 2.2.2. Sea Level Rise Data sea-level rise data (1-degree latitude-longitude resolution) for the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenariosThis that study relate used to 1986–2005 sea-level [1rise]. The data ensemble-mean from 21CMIP5 sea models, level rise which data ranges are the are 0.36–0.60ensemble-mean m for Pattayaregional beach sea-level and 0.38–0.62rise data m(1-degree for Chalatat latitude-longitude beach. resolution) for the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios that relate to 1986–2005 [1]. The ensemble-mean sea level rise data ranges are 2.2.3.0.36–0.60 Wave m Data for Pattaya beach and 0.38–0.62 m for Chalatat beach. This study used 3-h significant wave data and 12-h exceeds significant wave height re-analysed 2.2.3. Wave Data data (1-degree latitude-longitude resolution) provided by The European Centre for Medium-Range WeatherThis Forecasts study used (ECMWF; 3-h significant see www.ecmwf.int wave data and), 12 averaged-h exceeds over significant the 30-year wave period height (1980–2010). re-analysed Thedata significant (1-degree wave latitude-longitude height is 0.92 mresolution) for Pattaya prov beachided and by 0.77The mEuropean for Chalatat Centre beach. for TheMedium-Range significant waveWeather period Forecasts is 7.15 s(ECMWF for Pattaya; see beach www.ecmwf.int), and 6.85 s for averaged Chalatat over beach. the 30-year period (1980–2010). The significant wave height is 0.92 m for Pattaya beach and 0.77 m for Chalatat beach. The significant wave period is 7.15 s for Pattaya beach and 6.85 s for Chalatat beach.

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2.2.4. Slope and Sediment Size From field observations, the average foreshore beach slope (Figure2, Table2, Figure3 and Table3) is 9.34 degrees for Pattaya beach and 6.43 degrees for Chalatat beach. The average sediment grain size is 0.30 mm for Pattaya beach and 0.27 mm for Chalatat beach. Sediment size (D50) was analysed using the sieve analysis American Society for Testing and Materials (ASTM) D422-63 (2007) standard test method. The foreshore beach slope was measured using beach profiling. The closure depths of Pattaya beach and Chalatat beach are 7.72 m and 7.60 m, respectively. J. Mar. Sci. Eng. 2020, 8, 104 4 of 10 Table 2. Slope, sediment size of Pattaya beach. 2.2.4. Slope and Sediment Size Coordinates Section Foreshore Beach Slope (Degree) Sediment Size (mm) From field observations, the average foreshore beach slope (Figure 2, Table 2, Figure 3 and Table Latitude ◦N Latitude ◦E 3) is 9.34 degrees for Pattaya beach and 6.43 degrees for Chalatat beach. The average sediment grain a-a 12.945473 100.884282 5.9 0.30 size isb-b 0.30 mm12.941012 for Pattaya beach 100.883742 and 0.27 mm for Chalatat10.0 beach. Sediment size (D50) 0.29was analysed usingc-c the sieve12.936839 analysis American 100.882171 Society for Testing and Materials9.6 (ASTM) D422-63 (2007) 0.33 standard test method.d-d The12.933348 foreshore beach 100.879980 slope was measured using9.8 beach profiling. The closure 0.30 depths of Pattayae-e beach and12.929972 Chalatat beach 100.876831 are 7.72 m and 7.60 m, respectively.11.4 0.30

Figure 2. Figure 2. SurveySurvey sectionssections ofof PattayaPattaya beach.beach. Table 3. Slope, sediment size of Chalatat beach. Table 2. Slope, sediment size of Pattaya beach. Coordinates Section Coordinates Foreshore Beach Slope (Degree) Sediment Size (mm) Section Latitude N Latitude E Foreshore Beach Slope (Degree) Sediment Size (mm) Latitude °N◦ Latitude °E◦ a-a 7.182229 100.617478 0.27 a-a 12.945473 100.884282 0.8 5.9 0.30 b-b 7.182993 100.616394 9.5 0.27 b-bc-c 12.941012 7.183756 100.883742 100.615355 14.5 10.0 0.27 0.29 c-cd-d 12.936839 7.186357 100.882171 100.613644 9.8 9.6 0.27 0.33 d-de-e 12.933348 7.188759 100.879980 100.611942 9.2 9.8 0.27 0.30 e-e f-f12.929972 7.190354 100.876831 100.610879 5.9 11.4 0.27 0.30 g-g 7.191895 100.609843 6.5 0.27 h-h 7.193698 100.608989 8.4 0.27 i-i 7.198230 100.605882 2.5 0.27 j-j 7.202470 100.603497 4.7 0.27 k-k 7.203720 100.602813 3.8 0.27 l-l 7.206058 100.601536 4.9 0.27 m-m 7.209899 100.599467 3.2 0.27 n-n 7.212273 100.598171 6.4 0.27

Figure 3. Survey sections of Chalatat beach.

Table 3. Slope, sediment size of Chalatat beach.

Coordinates Section Foreshore Beach Slope (Degree) Sediment Size (mm) Latitude °N Latitude °E a-a 7.182229 100.617478 0.8 0.27 b-b 7.182993 100.616394 9.5 0.27 c-c 7.183756 100.615355 14.5 0.27 d-d 7.186357 100.613644 9.8 0.27 e-e 7.188759 100.611942 9.2 0.27 f-f 7.190354 100.610879 5.9 0.27

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2.2.4. Slope and Sediment Size From field observations, the average foreshore beach slope (Figure 2, Table 2, Figure 3 and Table 3) is 9.34 degrees for Pattaya beach and 6.43 degrees for Chalatat beach. The average sediment grain size is 0.30 mm for Pattaya beach and 0.27 mm for Chalatat beach. Sediment size (D50) was analysed using the sieve analysis American Society for Testing and Materials (ASTM) D422-63 (2007) standard test method. The foreshore beach slope was measured using beach profiling. The closure depths of Pattaya beach and Chalatat beach are 7.72 m and 7.60 m, respectively.

Figure 2. Survey sections of Pattaya beach.

Table 2. Slope, sediment size of Pattaya beach.

Coordinates Section Foreshore Beach Slope (Degree) Sediment Size (mm) Latitude °N Latitude °E a-a 12.945473 100.884282 5.9 0.30 b-b 12.941012 100.883742 10.0 0.29 c-c 12.936839 100.882171 9.6 0.33 d-d 12.933348 100.879980 9.8 0.30 J. Mar. Sci. Eng. 2020, 8, 104 5 of 10 e-e 12.929972 100.876831 11.4 0.30

Figure 3. SurveySurvey sections sections of Chalatat beach. 2.2.5. Average Visit Time and Area Required per User Table 3. Slope, sediment size of Chalatat beach. From the questionnaire survey, this study collected a sample size with a 99% confidence factor Coordinates andSection 10% precision. The sample included 166Foreshore of the 40,221 Beach tourists Slope (Degree) who visited Sediment Pattaya beach Size each(mm) day Latitude °N Latitude °E and 165 of the 20,919 tourists who visited Songkhla each day. Based on information gathered from a-a 7.182229 100.617478 0.8 0.27 beachgoers, the average visit time at both Pattaya and Chalatat beach was 3 h. Furthermore, the area b-b 7.182993 100.616394 9.5 0.27 required per user was 3 m2 for Pattaya beach and 11 m2 for Chalatat beach. c-c 7.183756 100.615355 14.5 0.27 2.2.6.d-d Management 7.186357 Capacity 100.613644 9.8 0.27 e-e 7.188759 100.611942 9.2 0.27 The management capacity (Table4) was determined by the facilities and infrastructure in the f-f 7.190354 100.610879 5.9 0.27 study areas, where 0 = absent, 1 = little, and 2 = adequate. The maximum possible score was 30.

Table 4. Management capacity.

Score Title Pattaya Beach Chalatat Beach Public bathroom 0 1 Bins 1 1 Parking 0 1 Security 2 1 Accommodation 2 2 Restaurant 2 2 Accessibility 2 1 Street lighting 2 1 Sunbath bed 2 0 Bay watch 2 2 Swimming 2 2 Snorkeling 0 0 Scuba 0 0 Kayak 2 0 Other sports 2 1 Summary score 21 15

3. Methods The method used in this study is depicted in Figure4. The first step was to detect the shoreline position using the tidal correction method. The next step was to determine the shoreline retreat using the Bruun rule. The last step was to analyse TCC. J. Mar. Sci. Eng. Eng. 20202020,, 8,, 104 104 6 of 10 J. Mar. Sci. Eng. 2020, 8, 104 6 of 10

Figure 4. Flow chart. Figure 4. Flow chart. 3.1. Detection of the Shoreline Position Using the Tidal Correction Method 3.1. Detection of the Shoreline Positi Positionon Using the Tidal Correction Method The tidal correction method was developed to obtain the shoreline position by detecting the meanThe sea tidaltidallevel correction correctionas the reference method method and was was correcting developed developed for to the obtainto tidalobtain the effect the shoreline [10].shoreline To position detect position bythe detectingshoreline by detecting the position mean the frommeansea level Google sea aslevel the Earth as reference the images reference and using correcting and the correcting tidal for correction the for tidal the method, etidalffect effect [10 ground]. To[10]. detect controlTo detect the points shoreline the shoreline were position taken position in from the imagesfromGoogle Google Earthto rectify Earth images them. images using An using the image-processing tidal the correction tidal correction method,method method, groundwas used ground control to analyse control points the werepoints pixels taken were in in takenthe the images, images in the andimagesto rectify the toshoreline them. rectify An them.position image-processing An was image-processing detected method automaticall meth wasod usedy withwas to MATLABused analyse to analyse the software. pixels the in Inpixels the the images, tidal in the correction images, and the step,andshoreline the the shoreline capture position timeposition was of detected the was images detected automatically was automaticall estimat withed yby MATLAB with measuring MATLAB software. the software. solar In theazimuth In tidal the correctiontidalangle correction from step, the step,shadowthe capture the objectcapture time on oftime the the ofimages. images the images wasAs depicted estimated was estimat in by Figure measuringed by 5, measuring θ is the the solar foreshore the azimuth solar azimuthslope angle of from theangle thebeach. from shadow Thethe shorelineshadowobject on object theposition images. on wasthe As images.corrected depicted As with depicted in Figurea trigonometri in5, Figureθ is thec 5,function foreshore θ is the to foreshore slope become of the theslope beach.shoreline of the The beach.position shoreline The at positionmeanshoreline sea was levelposition corrected as follows: was corrected with a trigonometric with a trigonometri functionc tofunction become to the become shoreline the positionshoreline at position mean sea at meanlevel as sea follows: level as follows: H𝐻 ∆L∆𝐿= = 𝐻 (1) ∆𝐿tan = 𝑡𝑎𝑛θ𝜃 (1) 𝑡𝑎𝑛𝜃

Figure 5. Beach profile profile of tidal correction method. Adapted from [11]. [11]. Figure 5. Beach profile of tidal correction method. Adapted from [11]. 3.2. Shoreline Retreat Base on the Bruun Rule 3.2. Shoreline Retreat Base on the Bruun Rule The Bruun rule [4] [4] was developed by Bruun to estimate estimate future future shoreline shoreline retreat from the changes in seaThe level Bruun with rule a linear [4] was relationship developed basedbased by Bruun onon equilibriumequilibrium to estimate profileprofile future theory,shorelinetheory, asas retreat follows:follows: from the changes in sea level with a linear relationship based on equilibrium profile theory, as follows: ∆y∆𝑦 S𝑆 ∆𝑦== 𝑆 (2) y 𝑦∗ =hℎ∗+𝐵Bh ∗ ∗ (2) 𝑦∗ ℎ∗ 𝐵 where Δy is the shoreline recession, y* is the distance in the horizontal to the depth of closure, S is the where ∆y is the shoreline recession, y* is the distance in the horizontal to the depth of closure, S is the wheresea level Δy rise, is the h* shorelineis the depth recession, of closure, y* is and the Bdistanceh is the bermin the height. horizo ntal to the depth of closure, S is the sea level rise, h* is the depth of closure, and Bh is the berm height. sea levelTo calculate rise, h* is the the depth depth of of closure closure, [12], and we Bh isused the theberm significant height. wave height and significant wave periodTo as calculate follows: the depth of closure [12], we used the significant wave height and significant wave period as follows:

J. Mar. Sci. Eng. 2020, 8, 104 7 of 10

To calculate the depth of closure [12], we used the significant wave height and significant wave period as follows: 2 He,t h = 2.28He,t 68.5( ) (3) ∗ − 2 gTe,t where He,t is the significant wave height, which is exceeded 12 h per t years, g is the gravitational acceleration, and Te,t is the significant wave period with 12-h-per-t-year exceedance. To determine the distance to the depth of the closure point, y*, which depends on grain size [13] and the depth of closure, we used the following:

h = Ay2/3 (4) ∗ ∗ where A is the scaling parameter based on the sediment size (d50) and h* is the depth of closure from Equation (3). To calculate the berm height (Bh) with Equations (5) [14] and (6) [15], the significant wave data and wave period were required:  3/8 = 5/8 2 Bh 0.125Hb gTs (5) where Bh is berm height, Hb is breaking wave height, and Ts is mean significant wave period, and:

H H 0.25 b = (tan α)0.2( s )− (6) Hs Ls where Hs is mean significant wave height, tan α is beach slope, and Ls is significant wave length. The shoreline retreat can be calculated by including all parameters in Equation (2).

3.3. TCC As defined previously, TCC consists of PCC, RCC, and ECC. In this study, PCC was calculated from the beach areas, area required per user (Equation (7)), and rotation factor (Equation (2)) [16], where A is beach areas, Au is area required per user, and Rf is the rotation factor (the daily open period divided by average visit time):

PCC = A/Au Rf (7) × RCC was calculated using Equation (8), and the correction factors were calculated using Equation (9): RCC = PCC (Cf1 Cf2 Cf3 ... Cfn), (8) × × × where Cf is the correction factors, and:

Cf = 1 Lmx/Tmx, (9) − where Lmx is the limiting magnitude of variable x and Tmx is the total magnitude of variable x. The correction factors were determined by considering the factors that limit tourism activities. ECC is the maximum number of tourists that the area can sustain. ECC is calculated by combining the RCC with management capacity (indicates the present condition of tourism management) [17], as follows: ECC = RCC Mc (10) × where Mc is the management capacity. J. Mar. Sci. Eng. 2020, 8, 104 8 of 10

4. Results

4.1. Beach Areas for Each Scenario From the detection of shoreline position using the tidal correction method combined with the J.Bruun Mar. Sci. rule, Eng. the 2020 beach, 8, 104 areas for past, present, and future scenarios are depicted in Figure6 for Pattaya8 of 10 beach and Figure7 for Chalatat beach. The results demonstrate that the present scenario in the study J. Mar. Sci. Eng. 2020, 8, 104 8 of 10 areas is the maximum beach area compared to the other scenarios, due to sea-level rise.

Figure 6. Pattaya beach area. Figure 6. Pattaya beach area. Figure 6. Pattaya beach area.

Figure 7. Chalatat beach area. Figure 7. Chalatat beach area. 4.2. Tourism Carrying Capacity Figure 7. Chalatat beach area. 4.2. Tourism Carrying Capacity The TCCs are depicted in Figure8 for Pattaya beach and Figure9 for Chalatat beach. The present scenario4.2. TourismThe TCCs has Carrying the are maximum depicted Capacity in TCC Figure in both8 for Pattaya of the study beach areas. and Figure The results9 for Chalatat indicate beach. that The beach present area, scenariocorrection has factors, the maximum and management TCC in both affect of the the TCC. study In termsareas. ofThe PCC, results Pattaya indicate beach that areas beach are morearea, The TCCs are depicted in Figure 8 for Pattaya beach and Figure 9 for Chalatat beach. The present correctionsignificant factors, than Chalatat and management beach areas, affect but the TCC. PCC atIn Pattayaterms of beach PCC, isPattaya higher beach than Chalatatareas are beachmore scenario has the maximum TCC in both of the study areas. The results indicate that beach area, significantbecause of than the larger Chalatat area beach required areas, per but user the at PCC Chalatat at Pattaya beach. beach Thus, is the higher PCC dependsthan Chalatat on the beach area correction factors, and management affect the TCC. In terms of PCC, Pattaya beach areas are more becauserequired of per the user larger and area the averagerequired visit per time, user whichat Chalatat affect beach. the physical Thus, characteristicthe PCC depends of tourism on the beach area significant than Chalatat beach areas, but the PCC at Pattaya beach is higher than Chalatat beach requiredcapacity. per The user RCC and at Pattayathe average beach visit is higher time, which than at affect Chalatat the physical beach because characteristic of the largerof tourism number beach of because of the larger area required per user at Chalatat beach. Thus, the PCC depends on the area capacity.correction The factors RCC at at Chalatat Pattaya beach. beach Theis higher correction than factorsat Chalatat depend beach on thebecause rainy of days the thatlarger are number a factor of required per user and the average visit time, which affect the physical characteristic of tourism beach correctionthe climate factors zone of at the Chalatat study areas.beach. ChalatatThe correction beach isfactors located depend on the on east the coast rainy in days the southernthat are a part factor of capacity. The RCC at Pattaya beach is higher than at Chalatat beach because of the larger number of Thailand,of the climate which zone has of a the longer study rainy areas. season Chalatat than Pattayabeach is beach, located located on the in east the coast eastern in region.the southern Moreover, part correction factors at Chalatat beach. The correction factors depend on the rainy days that are a factor ofPattaya Thailand, beach which has a has higher a longer management rainy season capacity than than Pattaya Chalatat beach, beach, located resulting in the in eastern a significantly region. of the climate zone of the study areas. Chalatat beach is located on the east coast in the southern part Moreover,higher ECC Pattaya at Pattaya beach beach. has Ina conclusion,higher management ECC relies capacity on the parametersthan Chalatat of managementbeach, resulting capacity in a of Thailand, which has a longer rainy season than Pattaya beach, located in the eastern region. wheresignificantly Pattaya higher beach isECC a well-known at Pattaya beach beach. for internationalIn conclusion, tourists, ECC butrelies Chalatat on the beach parameters is known asof Moreover, Pattaya beach has a higher management capacity than Chalatat beach, resulting in a management capacity where Pattaya beach is a well-known beach for international tourists, but significantly higher ECC at Pattaya beach. In conclusion, ECC relies on the parameters of Chalatat beach is known as a domestic tourism beach. Pattaya beach contributes great benefits to management capacity where Pattaya beach is a well-known beach for international tourists, but economic development in the tourism sector of Thailand. Consequently, Pattaya beach has more Chalatat beach is known as a domestic tourism beach. Pattaya beach contributes great benefits to efficient management owing to government expenditure on the area. economic development in the tourism sector of Thailand. Consequently, Pattaya beach has more Moreover, the increase in TCC will explicitly affect the beach environment and ecosystem. The efficient management owing to government expenditure on the area. culture and lifestyle of local people in coastal communities are likely to adjust to the tourists. These Moreover, the increase in TCC will explicitly affect the beach environment and ecosystem. The are interesting topics to study further in the future. culture and lifestyle of local people in coastal communities are likely to adjust to the tourists. These are interesting topics to study further in the future.

J. Mar. Sci. Eng. 2020, 8, 104 9 of 10 a domestic tourism beach. Pattaya beach contributes great benefits to economic development in the J. Mar. Sci. Eng. 2020, 8, 104 9 of 10 tourism sector of Thailand. Consequently, Pattaya beach has more efficient management owing to governmentJ. Mar. Sci. Eng. expenditure 2020, 8, 104 on the area. 9 of 10

Figure 8. Tourism carrying capacity (TCC) of Pattaya beach. Figure 8. Tourism carrying capacity (TCC) of Pattaya beach. Figure 8. Tourism carrying capacity (TCC) of Pattaya beach.

Figure 9. TCC of Chalatat beach. Figure 9. TCC of Chalatat beach. Moreover, the increase in TCC will explicitly affect the beach environment and ecosystem. Figure 9. TCC of Chalatat beach. The5. Conclusions culture and lifestyle of local people in coastal communities are likely to adjust to the tourists. These are interesting topics to study further in the future. 5. ConclusionsThis study presented the TCC of the Pattaya and Chalatat beaches due to sea-level rise under a 5.range ConclusionsThis of different study presented scenarios. the Pattaya TCC of beach the Pattaya repres entedand Chalatat the character beaches of due the towell-known sea-level rise beaches under of a Thailandrange of differentwhile Chalatat scenarios. beach Pattaya represented beach represthe characterented the of characterbeaches thatof the are well-known the focus of beaches domestic of This study presented the TCC of the Pattaya and Chalatat beaches due to sea-level rise under a tourism.Thailand This while study Chalatat detected beach the represented shoreline position the character using Googleof beaches Earth that images are the with focus tidal of correction domestic range of different scenarios. Pattaya beach represented the character of the well-known beaches of totourism. analyse This beach study areas detected and calculate the shoreline the shorelin positione retreat using Googlewith the Earth Bruun images rule. withThen, tidal the correctionTCC was Thailand while Chalatat beach represented the character of beaches that are the focus of domestic assessedto analyse using beach the areas beach and area, calculate correction the factors,shorelin ane dretreat management with the capacity. Bruun rule. The Then,results the suggest TCC thatwas tourism. This study detected the shoreline position using Google Earth images with tidal correction to theassessed ECC ofusing Pattaya the beach beach area, in the correction present isfactors, about an200,000,d management while it iscapacity. 49,000 forTh eChalatat results suggest beach. Ourthat analyse beach areas and calculate the shoreline retreat with the Bruun rule. Then, the TCC was assessed analysisthe ECC showed of Pattaya that beach the ECC in theof Pattaya present beach is about will 200,000, be more while extensive it is than49,000 the for ECC Chalatat of Chalatat beach. beach Our using the beach area, correction factors, and management capacity. The results suggest that the ECC inanalysis all situations, showed thateven the though ECC ofthere Pattaya is more beach abundant will be more beach extensive area at thanChalatat the ECC than of at Chalatat Pattaya. beach The of Pattaya beach in the present is about 200,000, while it is 49,000 for Chalatat beach. Our analysis factorsin all situations, contributing even to thethough TCC thereare the is beach more area abundants, correction beach factors area at and Chalatat management than at capacity. Pattaya. Sea-The showed that the ECC of Pattaya beach will be more extensive than the ECC of Chalatat beach in all levelfactors rise contributing directly affects to the the TCC beach are theareas, beach so thearea possibilitys, correction of factors future andbeach management loss could becapacity. a concern. Sea- situations, even though there is more abundant beach area at Chalatat than at Pattaya. The factors Also,level risethe directlyeffective affects management the beach of areas,facilities so theand possibility infrastructure of future around beach beac lossh areas could will be aaffect concern. the contributing to the TCC are the beach areas, correction factors and management capacity. Sea-level rise developmentAlso, the effective of TCC. management Nevertheless, of facilitiesthe protection and in offrastructure tourism beaches around should beach beareas considered will affect in thethe directly affects the beach areas, so the possibility of future beach loss could be a concern. Also, the future.development of TCC. Nevertheless, the protection of tourism beaches should be considered in the effective management of facilities and infrastructure around beach areas will affect the development of future. TCC.Author Nevertheless, Contributions: the Project protection administration, of tourism S.R.; beaches supervision, should S.R. be and considered K.U.; validation, in the future.S.R.; formal analysis, P.N.; data curation, P.N.; writing—original draft preparation, P.N.; writing—review and editing, S.R. All authors Author Contributions: Project administration, S.R.; supervision, S.R. and K.U.; validation, S.R.; formal analysis, have read and agreed to the published version of the manuscript. P.N.; data curation, P.N.; writing—original draft preparation, P.N.; writing—review and editing, S.R. All authors Funding:have read This and researchagreed to received the pub lishedno external version funding. of the manuscript.

Funding: This research received no external funding.

J. Mar. Sci. Eng. 2020, 8, 104 10 of 10

Author Contributions: Project administration, S.R.; supervision, S.R. and K.U.; validation, S.R.; formal analysis, P.N.; data curation, P.N.; writing—original draft preparation, P.N.; writing—review and editing, S.R. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Acknowledgments: This research was supported by Advancing Co-design of Integrated Strategies with Adaptation to Climate Change on Thailand (ADAP-T) supported by the Science and Technology Research Partnership for Sustainable Development (SATREPS), JST-JICA. Conflicts of Interest: The authors declare no conflict of interest.

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