Journal of Marine Science and Engineering
Article Analysis of Longshore Drift Patterns on the Littoral System of Nusa Dua Beach in Bali, Indonesia
Anthony Harlly Sasono Putro and Jung Lyul Lee *
Graduate School of Water Resources, Sungkyunkwan University, Suwon-si 16319, Korea; [email protected] * Correspondence: [email protected]
Received: 26 August 2020; Accepted: 24 September 2020; Published: 26 September 2020
Abstract: Bali is one of the most popular tourist areas in Indonesia. With its coastline stretching 633 km, Bali has many beautiful beaches that have become world tourism attractions, thus making tourism the economic engine of Bali. The biggest priority of major tourism sites is maintaining sufficient beach width. However, based on a survey from Balai Wilayah Sungai (BWS) Bali Penida, Bali has suffered from a series of erosions along 215 km of its coastline, including Nusa Dua, in 2015. The location of the study area for this report is a 2.8 km stretch of coastline at Nusa Dua Beach. The erosion problem at Nusa Dua Beach was assessed by analyzing the longshore drift patterns. Simulations are required to assess this erosion problem, combined with the erosion rate and the simulated equilibrium shoreline for each sublittoral cell. To estimate the erosion rate, this study employed profile monitoring data of the beach obtained from 2003 to 2016. This advanced study was based on the mass conservation principle as a governing equation used to predict longshore drifts between sublittoral cells. The satellite image for every sublittoral cell was also used to check the equilibrium condition and estimate the predominant wave direction as the shoreline orientation. Nusa Dua Beach was found to suffer from the change of wave direction and the consequent generation of littoral drift after the reclamation project of Serangan Island located north of the Benoa strait. The correlation between the transportation of longshore sediments and the predominant wave direction indicates the effect of longshore drift in the system. The groin system also created a unique longshore transport pattern in the coastal area. The results obtained in this study can help manage the longshore drift system of Nusa Dua Beach and can be used to predict the beach area subject to erosion and deposition after every beach conservation project. Hence, a strategic plan for managing the shore target lines can be formulated.
Keywords: beach erosion; equilibrium shoreline; longshore drift; predominant wave direction; shoreline orientation
1. Introduction Beaches play an essential role in the life of an ecosystem. They participate in water purification, nutrient renewal, coastal defense, recreational activities, etc. Previous studies have stated that the use of beach does not integrate well with the importance of maintaining sustainable resources. These studies considered beach use as a cause of environmental degradation and imbalance in the sedimentary process [1–3]. Fast-growing tourism, coastal development, and global climate change can worsen the degradation impact [4–6]. To better understand their socioeconomic and engineering impacts, these erosion problems need to be assessed via the physical processes of the coastal zone [7]. Some indicators, such as shoreline positions, beach morphology, coral reef condition, hydro-oceanography condition, and coastal structures, can be used to assess erosion problems, and the results of this assessment should be considered for the development of coastal management.
J. Mar. Sci. Eng. 2020, 8, 749; doi:10.3390/jmse8100749 www.mdpi.com/journal/jmse J. Mar. Sci. Eng. 2020, 8, 749 2 of 19
Some cases of beach erosion are due to imbalances in sediment transport, which are caused by the longshore sediment transport. Previous studies have analyzed the impact of longshore sediment transport on the conditions of coastal areas [8–12]. Bergillos et al. [10], analyzed the relationship between the morphology of the conserved beach and longshore sediment transport. These conditions can be affected by some factors, such as the change in bathymetry condition and the predominant wave condition [8]. The changes in sediment volume can also be analyzed by using the longshore sediment transport gradient [8]. Furthermore, Andrade et al. [1], concluded that via the change in beach width and shoreline position, the gradients of longshore drift play an essential role in erosion processes. The main aim of this study is to assess the erosion problems at Nusa Dua Beach of Bali Indonesia, based on the data from the beach monitoring survey. The assessment of the longshore drift process and equilibrium shoreline are the primary tools used for checking the erosion problems. The results of this research will serve as guidance for planning and developing the next strategic approach in coastal management.
2. Characterization of Study Area Bali is one of the most popular tourist sites in Indonesia. In 2017, tourism constituted almost 23% of the gross regional domestic product of Bali [13]. With a coastline stretching 633 km, beaches remain the most popular tourist destination in Bali. The southern part of Bali has a flourishing tourism industry and some of its beaches, such as Nusa Dua, Sanur, Kuta, and Tanah Lot, are particularly popular tourist destinations. Additionally, the beaches are of significant value to the Balinese Hindu population. However, according to the 2015 survey data obtained by the Indonesian Ministry of Public Works and Housing, erosion in Bali has affected 215 km of the coastline. Coastal erosion has recently become a global environmental problem. Most coastlines suffer from erosion owing to the sediment deficit caused by human disturbances such as damming, land reclamation, urbanization, and coastal area development [14–19]. Over 70% of the world’s beaches suffer from erosion [20]. One of the goals of integrated coastal zone management's (ICZM) is to improve beach quality. The European Commission [21] has noted coastal erosion as an issue that must be addressed in ICZM strategies. Coastal erosion may generate several negative impacts on social-economical aspect such as the potential loss of life, damage of property and infrastructure, loss of tourism revenue, and degradation of the ecosystem. The study area for this work is located on Nusa Dua Beach, from groin G12 to the north part of groin GA2, with a total shoreline of approximately 2.8 km (Figure1). Located in the southern part of Bali Island, in front of Benoa Strait, Nusa Dua has been one of the most famous Bali beach resorts for several years. Up to the eastern part of the north coast of Tanjung Benoa, the beach is made of carbonaceous sand and foraminiferan components. The beach slope is slightly steep and steadily levels as it nears the sea. Based on the data obtained after a beach nourishment project, the grain size (D50) at Nusa Dua Beach is 0.606 mm. The beach erosion problem at Nusa Dua was caused by the interruption of the northward littoral drift by a natural tombolo behind the Nusa Kecil and Nusa Besar islands that occurred several decades [22]. The other reason for the erosion problem is a reduction in the reef flat owing to coral mining. The lower reef flat allows waves with high energy to be propagated to the beach. The decreased supply of sand creates an imbalance in the sediment budget. Furthermore, the general stress from the disturbance on the beach area induces localized erosion. From 2001 to 2003, the Indonesian Ministry of Public Works in collaboration with Japan International Cooperation Agency completed the Bali Beach Conservation Project Package II at Nusa Dua by implementing civil works such as beach nourishment, and constructing coastal structures. The coastal conservation and protection efforts essentially propped the tourism at Nusa Dua Beach. The project focused on maintaining the beach from a functional perspective and developing a plan for its utilization as a tourist area and its landscaping while protecting and conserving the beach environment. Furthermore, the project facilitated the construction of several groins to stabilize the J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 3 of 20
shoreline and protect it from longshore drift. Hence, the coastline has the same phase potential line. These artificial headlands divided Nusa Dua Beach into several sublittoral cells. To optimize its effectiveness, the beach nourishment project needs to be adjusted with the coastline morphology, J.sediment Mar. Sci. Eng. grain2020 size,, 8, 749 and input volume [11]. 3 of 19 The wave direction is predominantly south and south east. This oblique wave is reflected by the shoreline generating a northerly longshore current. Its motion is one of the external forces responsible shorelinefor either erosion and protect or sedimentation it from longshore in the area. drift. The Hence, tidal thecharacteristic coastline hasin the the Nusa same Dua phase area potential is mixed line.semidiurnal. These artificial Based on headlands the tidal elevation divided Nusadesign Dua for Beachthe beach into conservation several sublittoral project, cells. the highest To optimize water itslevel eff ectiveness,obtained was the 2.6 beach m higher nourishment than the projectlowest water needs level to be (LWL). adjusted Hence, with the mean coastline sea morphology,level was 1.3 sedimentm above the grain LWL. size, and input volume [11].
Figure 1.1. Study area location—Nusalocation—Nusa Dua Beach.
TheFrom wave 2003 direction to 2016, a is beach predominantly profile survey south was and conducted south east. in Thissome oblique sections wave of Nusa is reflected Dua Beach by the by shorelinethe Indonesian generating Ministry a northerly of Public longshore Works current. and Housing. Its motion This is activity one of the provided external useful forces information responsible fornecessary either erosionfor understanding or sedimentation the beach in the erosion area. Thephenomena. tidal characteristic After the beach in the conservation Nusa Dua area project is mixed was semidiurnal.completed, the Based change on thein shoreline tidal elevation was evident design in for a thetime beach series conservation of satellite images project, from the highestGoogle waterEarth level(Figure obtained 2). was 2.6 m higher than the lowest water level (LWL). Hence, the mean sea level was 1.3 m above the LWL. From 2003 to 2016, a beach profile survey was conducted in some sections of Nusa Dua Beach by the Indonesian Ministry of Public Works and Housing. This activity provided useful information necessary for understanding the beach erosion phenomena. After the beach conservation project was completed, the change in shoreline was evident in a time series of satellite images from Google Earth (Figure2). Owing to this condition, the coastal system was divided into 17 sublittoral cells in this study (Table1 and Figure3). Because the dominant wave comes from the south, the numbering of the sublittoral cells started from the south and then moved northward. Most of the groins at the Nusa Dua Beach were constructed during the beach conservation project. At that time, one system served as the sublittoral cell between GA8 and GA3; this was also true, for the segment between GA3 and GA2. However, after several years, private and government projects constructed four groins between these two systems: GN 5 and GN 6 in 2009, GTB in 2010, and GN4 in 2011. Therefore, the sublittoral cell between GA8 and GA3 is divided into three control volumes, as is the segment between GA3 and GA2.
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10
9
8
7
FigureFigure 2. 2.Shoreline Shoreline changechange at Nusa Dua Dua Beach Beach (2009 (2009–2019).–2019).
Table 1. The characteristics of the sublittoral cell system. Owing to this condition, the coastal system was divided into 17 sublittoral cells in this study (Table 1 and FigureSublittoral 3). Because Cell the dominant Number wave of Section comes from Length the south, (m) the numbering Groin Segments of the sublittoral cells started from the south and then moved northward. 1 8 257 G12–GN2 2 6 184 GN2–UG1 Table 1. The characteristics of the sublittoral cell system. 3 5 149 UG1–G10 Sublittoral4 Cell Number 6 of Section Length 233 (m) Groin Segments G10–G9 51 78 224257 G12 G9–GN1– GN2 62 66 192184 GN2 GN1–G5– UG1 7 6 181 G5–G4 3 5 149 UG1 – G10 8 5 169 G4–G1 4 6 233 G10 – G9 9 4 100 G1–G0 105 67 209224 G9 – G0–GA8 GN1 11A6 36 78192 GN1 GA8–GTB – G5 11B7 46 119181 G5 GTB–GN4 – G4 11C8 65 201169 G4 GN4–GA3 – G1 12A9 44 120100 G1 GA3–GN6 – G0 12B10 46 121209 G0 GN6–GN5– GA8 12C 4 119 GN5–GA2 11A 3 78 GA8 – GTB 13 5 163 GA2–GA1 11B 4 119 GTB – GN4 Total 89 2,819 J. Mar. Sci. Eng. 2020, 8, x FOR11C PEER REVIEW 6 201 GN4 – GA3 5 of 20 12A 4 120 GA3 – GN6 12B 4 121 GN6 – GN5 12C 4 119 GN5 – GA2 13 5 163 GA2 – GA1 Total 89 2,819
FigureFigure 3. 3.Sections Sections ofof the sublittoral cell cell system. system.
Most of the groins at the Nusa Dua Beach were constructed during the beach conservation project. At that time, one system served as the sublittoral cell between GA8 and GA3; this was also true, for the segment between GA3 and GA2. However, after several years, private and government projects constructed four groins between these two systems: GN 5 and GN 6 in 2009, GTB in 2010, and GN4 in 2011. Therefore, the sublittoral cell between GA8 and GA3 is divided into three control volumes, as is the segment between GA3 and GA2.
3. Theoretical Background
3.1. Sediment Budgets A sediment budget analysis is a fundamental element of the framework used for understanding erosion and accretion processes in a coastal zone. This analysis play an essential role in evaluating the impacts of engineering activities, such as providing an understanding of sediment transport magnitudes and pathways in the selected coastal region and within a specified time [23]. Sediment budgets represent an analysis of sediment balance (gains and losses) in a determined control volume (or sublittoral cell) or an adjacent sublittoral cell system, over a specified time [24]. The formulation of a sediment budget is derived from the mass conservation equation. In a coastal cell, the difference between sediment budgets over a specified period time must equal the sediment volume change, which occurs in that region. To calculate the sediment budget, the sublittoral cell should be defined as the system’s boundary. The cell is usually defined by geologic controls, coastal structures, available data resolutions, and isolating known quantities or a quantity of interest. The record of sediment volume data in a sublittoral cell is used to formulate a sediment budget. Rosati [24] introduced the general equation for analyzing sediment budgets (Equation (1)).
ΣQsource − ΣQsink – ΔV + P – R = Residual (1) All of the terms in Equation (1) are represented by a volumetric rate. ΔV is the net accumulated change in sediment volume, Qsource and Qsink are the source and sink for the specified system, respectively, P and R are the volumes of sediment placed in or removed from the control volume, respectively, and the residual serves as means for balancing the cell. The residual is zero for a balanced cell.
3.2. Equilibrium Shoreline The predominant wave direction and coastal structures have a potential impact on the coastline [25]. The shoreline responds to such processes until an equilibrium is established, which is the balance
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3. Theoretical Background
3.1. Sediment Budgets A sediment budget analysis is a fundamental element of the framework used for understanding erosion and accretion processes in a coastal zone. This analysis play an essential role in evaluating the impacts of engineering activities, such as providing an understanding of sediment transport magnitudes and pathways in the selected coastal region and within a specified time [23]. Sediment budgets represent an analysis of sediment balance (gains and losses) in a determined control volume (or sublittoral cell) or an adjacent sublittoral cell system, over a specified time [24]. The formulation of a sediment budget is derived from the mass conservation equation. In a coastal cell, the difference between sediment budgets over a specified period time must equal the sediment volume change, which occurs in that region. To calculate the sediment budget, the sublittoral cell should be defined as the system’s boundary. The cell is usually defined by geologic controls, coastal structures, available data resolutions, and isolating known quantities or a quantity of interest. The record of sediment volume data in a sublittoral cell is used to formulate a sediment budget. Rosati [24] introduced the general equation for analyzing sediment budgets (Equation (1)).
ΣQsource ΣQ ∆V + P R = Residual (1) − sink − − All of the terms in Equation (1) are represented by a volumetric rate. ∆V is the net accumulated change in sediment volume, Qsource and Qsink are the source and sink for the specified system, respectively,J. Mar. Sci. Eng. P 20 and20, 8 R, xare FOR the PEER volumes REVIEW of sediment placed in or removed from the control volume,6 of 20 respectively, and the residual serves as means for balancing the cell. The residual is zero for a balancedbetween cell. internal and external forces. An equilibrium shoreline represents a condition in which the shoreline has reached a stable condition and has the same phase potential line. The equilibrium 3.2.shoreline Equilibrium analysis Shoreline is essential to evaluate erosion and accretion processes along the coastline. TheBetween predominant two headlands, wave direction the and coastline coastal makes structures a crenulate have a potential-shaped impact bay [26 on] the as coastline equilibrium [25]. is Theestablished. shoreline respondsTo simulate to suchthe plan processes form of until bayed an equilibriumbeaches, three is established,concepts incl whichuding isthe the logarithmic balance betweenspiral [27 internal], parabolic and external shape (Figure forces. 4) An [26], equilibrium and hyperbolic shoreline tangent represents [28] have acondition been developed. in which Among the shorelinethese three has empirical reached aequations, stable condition the implications and has theof only same the phase predominant potential wave line. direction The equilibrium alone and shorelineits diffraction analysis location is essential (control to evaluate point) erosion have been and considered accretion processes in the parabolic along the bay coastline. shape equation (PBSE)Between [26,29 two]. headlands, the coastline makes a crenulate-shaped bay [26] as equilibrium is established.The shape To simulate of the PBSE the plan(Equation forms of (2 bayed) and (3 beaches,)) [26] is threedependent concepts on two including parameters, the logarithmic Ro and β. As spiralthe control [27], parabolic line, Ro is shape obtained (Figure by determining4)[ 26], and the hyperbolic "focus point," tangent which [28 is] the have center been of developed. the distance Amongbetween these the three diffraction empirical point equations, and the the control implications point, ofthe only point the that predominant protrudes wave into the direction sea, which alone is andstill its in di tffheraction same locationlittoral cell. (control The point)variable have β is been the obliquity considered of inthe the wave, parabolic which bay is shapethe angle equation created (PBSE)between [26, 29the]. control line and the wave crest.
Figure 4. Illustration of parabolic bay shape. Figure 4. Illustration of parabolic bay shape.
R/Ro = C0 + C1(β/θ) + C2(β/θ)2 for θ ≥ β (2)
R/Ro = sin (β)/sin (θ) for θ ≤ β (3)
where C0, C1, and C2 are the determined coefficients related to β; R is the radius along the curve at an angle θ, to a specific point; Ro is the radius at an angle β from the wave crest to the control point; θ is an angle from the wave crest to a specific point; and β is the angle determining the parabolic shape. To fit the equilibrium shoreline for a pocket-shaped beach such that the PBSE can be applied to the shoreline curve, this concept must be transformed into polar coordinates [30]. Then, the coordinates for the center of a circle, with a radius of rs that fits the shoreline are set, using the polar coordinate system (r, φ). In this coordinate system, the predominant wave direction can be estimated by the angle from the circle origin to the center of beach position. The PBSE is illustrated in Figure 5 and expressed by the Equations (4) and (5).
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The shape of the PBSE (Equations (2) and (3)) [26] is dependent on two parameters, Ro and β. As the control line, Ro is obtained by determining the "focus point," which is the center of the distance between the diffraction point and the control point, the point that protrudes into the sea, which is still in the same littoral cell. The variable β is the obliquity of the wave, which is the angle created between the control line and the wave crest.
2 R/Ro = C + C (β/θ) + C (β/θ) for θ β (2) 0 1 2 ≥
R/Ro = sin (β)/sin (θ) for θ β (3) ≤ where C0,C1, and C2 are the determined coefficients related to β; R is the radius along the curve at an angle θ, to a specific point; Ro is the radius at an angle β from the wave crest to the control point; θ is an angle from the wave crest to a specific point; and β is the angle determining the parabolic shape. To fit the equilibrium shoreline for a pocket-shaped beach such that the PBSE can be applied to the shoreline curve, this concept must be transformed into polar coordinates [30]. Then, the coordinates for the center of a circle, with a radius of rs that fits the shoreline are set, using the polar coordinate system (r, ϕ). In this coordinate system, the predominant wave direction can be estimated by the angle from the circle origin to the center of beach position. The PBSE is illustrated in Figure5 and expressed by the Equations (4) and (5). r = rf + R sin (θ) (4)
ϕ = R cos (θ) / [rf + R sin (θ)] (5) where rf is the distance from the center of the fitting circle to the focus point. Using MeEPASoL as the graphical user interface (GUI) program, these concepts and equations were used in this study to implementJ. Mar. Sci. Eng. the 2020 equilibrium, 8, x FOR PEER shoreline REVIEW analysis. 7 of 20
Figure 5. Sketch of the polar coordinate. Figure 5. Sketch of the polar coordinate. 4. Materials and Methods
4.1. Erosion Assessment r = rf + R sin (θ)
4.1.1. Beach Profile Area φ = R cos (θ) / [rf + R sin (θ)] (5)
whereAs rf a is response the distance to erosion from the and center accretion, of the the fitting beach circle profile to the changes focus with point. time. Using Temporal MeEPASoL and spatial as the analyticalgraphical user techniques interface were (GUI) employed program, to assess these theconcepts variations and equationsin the profile were data used along in thisthe coastline.study to Theseimplement data werethe equilibrium used to identify shoreline the naturalanalysis. defense of a particular beach profile and determine the
4. Materials and Methods
4.1. Erosion Assessment
4.1.1. Beach Profile Area As a response to erosion and accretion, the beach profile changes with time. Temporal and spatial analytical techniques were employed to assess the variations in the profile data along the coastline. These data were used to identify the natural defense of a particular beach profile and determine the changes along the adjacent shoreline (erosion and accretion). A survey was performed using methods such as triangulation, traversing, and the use of a global positioning system (GPS) [31]. The surveys of the periodic beach profile provided data for the selected area. The arbitrary vertical datum, which is considered as the boundary between the beach and the coral reef, can be chosen for each profile. Then, the sediment area above the baseline, from the baseline to the seaward limit, can be obtained [32]. The beach monitoring dataset was obtained from the field survey. The survey was conducted by the Indonesian Ministry of Public Works and Housing from December 2003 to January 2016. The area of the beach profile in this study was calculated using the trapezoidal method. Figure 6 illustrates the calculation of the beach profile area.
J. Mar. Sci. Eng. 2020, 8, 749 7 of 19 changes along the adjacent shoreline (erosion and accretion). A survey was performed using methods such as triangulation, traversing, and the use of a global positioning system (GPS) [31]. The surveys of the periodic beach profile provided data for the selected area. The arbitrary vertical datum, which is considered as the boundary between the beach and the coral reef, can be chosen for each profile. Then, the sediment area above the baseline, from the baseline to the seaward limit, can be obtained [32]. The beach monitoring dataset was obtained from the field survey. The survey was conducted by the Indonesian Ministry of Public Works and Housing from December 2003 to January 2016. The area of the beach profile in this study was calculated using the trapezoidal method. J.Figure Mar. Sci.6 Eng.illustrates 2020, 8, x the FOR calculation PEER REVIEW of the beach profile area. 8 of 20
Figure 6. Beach profile area calculation results using trapezoidal method. Figure 6. Beach profile area calculation results using trapezoidal method. Equation (6) expresses the total area of the beach profile for a specific time. Equation (6) expresses the total area of the beach profile for a specific time. 푛 Xn Et 푡+ Et푡 D푡t D푡 t t 푡 (퐸i푖 + 퐸i푖++1)(퐷푖i++11− 퐷푖 )i A 퐴=푙 = ∑ − (6(6)) l 2 i=푖1=1 where 퐴푡, 퐸푡, and 퐷푡 are the beach profile area for specific cross-section (l) at a particular time (t), where A푙t, E푖t, and Dt푖 are the beach profile area for specific cross-section (l) at a particular time (t), elevation lpositioni datai for the i-point at t-time for each cross-section, and offshore distance data for elevation position data for the i-point at t-time for each cross-section, and offshore distance data for the the i-point at t-time for each cross-section, respectively. i-point at t-time for each cross-section, respectively.
4.1.2.4.1.2. Sublittoral Sublittoral Cell Cell Volume Volume and and Rate Rate TheThe sediment sediment volume volume in in each each monitoring monitoring period period can can be be calculated calculated a afterfter determining determining the the area area for for allall of of the the cross cross-sections-sections in in the the selected selected sublittoral sublittoral cell. cell. The The sediment sediment volume volume above above the the datum datum can can be be calculatedcalculated by by integrating the the areas areas from from the the adjacent adjacent beach beach profile profile data data obtained obtained from from the same the survey same surveyalong thealong coastline. the coastline. The estimated The estimated volume volume for a for certain a certain monitoring monitoring period period can can be usedbe used to checkto check the thetime time when when erosion erosion and and accretion accretion occurred, occurred and, and the the amount amount of of erosion erosion and and accretion. accretion. EquationEquation (7)7 expressesexpresses the the calculation calculation for for beach beach volum volume.e. 푁 (퐴푡 + 퐴푡 ) 푡 N t 푙 t푙+1 푉 =X ∑(A + A ) × (푥푙+1 − 푥푙) (7) t l 2 l+1 V = 푙=1 (x + x ) (7) 2 × l 1 − l 푡 푡 l=1 where 푉 , 퐴푙 , and 푥푙 are the volume for a specified time in each sublittoral cell, beach profile area for a specifict tcross-section (l) at a particular time (t), and longshore position of the cross-section (l), where V , Al, and xl are the volume for a specified time in each sublittoral cell, beach profile area respectively.for a specific Furthermore, cross-section the (l) atrate a particular of beach timevolume (t), change and longshore versus positiontime (ΔV/Δt) of the was cross-section determined (l) , usingrespectively. linear regression Furthermore, from the the rate calculated of beach volume volume dataset. change versus time (∆V/∆t) was determined using linear regression from the calculated volume dataset. 4.2. Predominant Waves Direction and Prediction of Equilibrium Shoreline The estimation used to predict the equilibrium shoreline for each sublittoral cell was done using MeEPASoL software and the satellite images from Google Earth. MeEPASoL (a GUI program) is an application that simulates the equilibrium shoreline based on the result obtained from the empirical PBSEs (Equations (2) and (3)). This application also estimates the predominant angle of the incident waves as the shoreline orientation. For reliable performance, these equations were applied in the GUI tool to the polar coordinates of existing concave shape shorelines. The prediction of shoreline changes can be estimated by processing the satellite image using the PBSE (Figure 7).
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4.2. Predominant Waves Direction and Prediction of Equilibrium Shoreline The estimation used to predict the equilibrium shoreline for each sublittoral cell was done using MeEPASoL software and the satellite images from Google Earth. MeEPASoL (a GUI program) is an application that simulates the equilibrium shoreline based on the result obtained from the empirical PBSEs (Equations (2) and (3)). This application also estimates the predominant angle of the incident waves as the shoreline orientation. For reliable performance, these equations were applied in the GUI tool to the polar coordinates of existing concave shape shorelines. The prediction of shoreline changes can be estimated by processing the satellite image using the PBSE (Figure7). J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 9 of 20
FigureFigure 7.7. MeEPASoL software result. result.
4.3.4.3. Sediment Sediment Budgets Budgets and and Longshore Longshore DriftDrift ToTo quantify quantify the the sediment sediment loss loss or or gaingain inin each sublittoral cell, cell, it it is is necessary necessary to to estimate estimate a sediment a sediment budget.budget. This This analysis analysis is is also also usedused toto checkcheck the correlation of of sediment sediment transport transport from from each each sublittoral sublittoral cellcell to to the the adjacent adjacent area. area. Furthermore, Furthermore, Equation ( (1),1), which which was was derived derived from from mass mass conservation conservation principles,principles, can can be be transformed transformed into into EquationEquation (8).(8).
ΔV/Δt = ΔQ = Qin - Qout (8) ∆V/∆t = ∆Q = Qin Qout (8) where ΔV/Δt, Qin, and Qout are the rate of volume change− during the monitoring period, amount of wheresediment∆V/∆ transportedt, Qin, and into Qout theare cont therol rate volume, of volume and amount change of during sediment the monitoringtransported out period, of the amount control of sedimentvolume, transportedrespectively. into the control volume, and amount of sediment transported out of the control volume,The respectively. difference in the amount of sediment transport (ΔQ) discussed above is caused by cross- shoreThe sediment difference transport in the amount (Qc), which of sediment is calculated transport using (∆Q) the discussed beach profile above ch isange. caused However, by cross-shore we assume that the cross-shore sediment transport is transformed to the longshore sediment transport sediment transport (Qc), which is calculated using the beach profile change. However, we assume that (Ql). Therefore, this study assumes that Qin in a specified sublittoral cell comes from the southern the cross-shore sediment transport is transformed to the longshore sediment transport (Ql). Therefore, sublittoral cell, then Qout moves to the northern sublittoral cell, as represented by Equation (9). this study assumes that Qin in a specified sublittoral cell comes from the southern sublittoral cell, then Qout moves to the northern sublittoral(ΔV/Δt) cell,n = as ΔQ representedn = Qn-1 − Q byn Equation (9). (9)
where Qn-1 represents the Qin from the previous sublittoral cell, and Qn represents the Qout from this (∆V/∆t)n = ∆Qn = Qn 1 Qn (9) sublittoral cell. − − Walton Jr. and Dean [33] have represented the longshore drift rate as Equation (10). where Qn 1 represents the Qin from the previous sublittoral cell, and Qn represents the Qout from this − sublittoral cell. Q = 푄푝 sin [2 (αs − αb)] (10) Walton Jr. and Dean [33] have represented the longshore drift rate as Equation (10). where Qp , αs, and αb are the longshore drift potential indicating the wave climate of the coast, shoreline orientation owing to the predominant wave direction, and azimuth of the angle of the Q = Qp sin [2 (αs αb)] (10) waves breaking on the shoreline, respectively. Figure 8 illustrates− the shoreline orientation due to the incident main wave angle and the azimuth angle owing to the breaking waves on the shoreline in the sublittoral cell of interest.
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where Qp, αs, and αb are the longshore drift potential indicating the wave climate of the coast, shoreline orientation owing to the predominant wave direction, and azimuth of the angle of the waves breaking on the shoreline, respectively. Figure8 illustrates the shoreline orientation due to the incident main wave angle and the azimuth angle owing to the breaking waves on the shoreline in the sublittoral J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 10 of 20 cell of interest.
Figure 8. Illustration of the shoreline orientation and azimuth breaking wave angle in the sublittoral Figure 8. Illustration of the shoreline orientation and azimuth breaking wave angle in the sublittoral cell of interest. cell of interest. Therefore, the gradient of longshore drift (∆Q) is represented by the difference between the sedimentTherefore transports, the gradient in the sublittoral of longshore cell of drift interest (ΔQ) and is the represented adjacent area. by the This difference amount isbetween influenced the sediment transports in the sublittoral cell of interest and the adjacent area. This amount is influenced by the shoreline orientation (αs) and the azimuth of the breaking wave angle (αb). by theAfterward, shoreline orientation the gradient (αs of) and longshore the azimuth drift of (∆ theQ), breaking which is wave the rate angle of (α volumeb). change in the Afterward, the gradient of longshore drift (ΔQ), which is the rate of volume change in the sublittoral cell, can be approximated. The shoreline orientation (αs) for every sublittoral cell was sublittoralcalculated usingcell, can the be MeEPASoL approximated. program. The However, shoreline the orientation azimuth (α ofs) the for breaking every sublittoral wave angle cell to was the calculated using the MeEPASoL program. However, the azimuth of the breaking wave angle to the shoreline (αb) is unknown. However, the variation of αb is small (smaller than the difference in shorelineshoreline orientation), (αb) is unknown. as can However, be seen via the the variation following of process. αb is smallThe coral (smaller reef zone, than which the difference is located in in shorelinefront of the orientation), coastline, makesas can thebe seen area via similar the following to shallow process. water zone. The coral Therefore, reef zone, the dominantwhich is located waves infrom front the of deep the coastline, water, which makes have the area the same similar directional to shallow angle, water are zone. reflected Therefore, and break.the dominant Although waves the fromdirection the deep of the water, breaking which wave have is changed,the same thedirectional change inangle, direction are reflected is small. and Therefore, break. Although Equation (10)the directioncan be simplified of the breaking into Equation wave is (11). changed, the change in direction is small. Therefore, Equation (10) can be simplified into Equation (11). ∆Q Qp ∆sin2β (11) ∼ s ΔQ ~ 푄푝 Δsin2βs (11) where β is defined as αs αs providing the positive ∆Q toward to the north. This study used the s − wherecentral β dis ffiserence defined method as α̅̅̅s owing− αs providing to the effect the from positive the otherΔQ to sublittoralward to the cell north to calculate. This study the used gradient the centralof the longshoredifference driftmethod (∆Q) owing and theto the gradient effect from of sin the (2β others). Finally, sublittoral the resultcell to for calculate the longshore the gradient drift ofpotential the longshore (Qp) and drift correlation (ΔQ) and value the represents gradient theof sin characteristics (2βs). Finally, of thethe longshoreresult for driftthe longshore process and drift the potentialrelation between (Qp) and the correlation longshore value drift represent and the shorelines the characteristics orientation. of the longshore drift process and the relation between the longshore drift and the shoreline orientation.
5. Results
5.1. Erosion Rate and Predominant Wave Direction in the Sublittoral Cell As evident from field survey data obtained from December 2003 to January 2016, the change in sediment budget occurred in every sublittoral cell at Nusa Dua Beach. The shoreline also obtained the equilibrium condition as the response of predominant wave direction and the groin system. Figure 9 shows the percentage of sand volume change at sublittoral cell 1 until 9, and Figure 10 shows the percentage at sublittoral cell 10 until 13.
J. Mar. Sci. Eng. 2020, 8, 749 10 of 19
5. Results
5.1. Erosion Rate and Predominant Wave Direction in the Sublittoral Cell As evident from field survey data obtained from December 2003 to January 2016, the change in sediment budget occurred in every sublittoral cell at Nusa Dua Beach. The shoreline also obtained the equilibrium condition as the response of predominant wave direction and the groin system. Figure9 shows the percentage of sand volume change at sublittoral cell 1 until 9, and Figure 10 shows theJ. Mar. percentage Sci. Eng. 20202020 at, 8 sublittoral, x FOR PEER cell REVIEW 10 until 13. 11 of 20
Figure 9.9. Sand volume change in sublittoral cell 1 until 9.9.
.
Figure 10. Sand volume change in sublittoral cell 10 until 13. Figure 10. Sand volume change in sublittoral cell 10 until 13.
Therefore,Therefore, the the rate rate of beachof beach volume volume change change can be can obtained be obtained from the from trend the line trend of every line sublittoral of every cell forTherefore, further analysis. the rate Some of beach considerations volume change were taken can be to obtained determine from the natural the trend rate line of sediment of every sublittoral cell for further analysis. Some considerationsconsiderations were taken to determine the natural rate of volumesediment in volume every sublittoral in every cell.sublittoral Additional cell. Additi beach nourishmentonal beach nourishment from private from entities private was neglectedentities was in thissediment study. volume Table2 shows in every the sublittoral rate of beach cell. volume Additional change beach in every nourishment sublittoral from cell and private its consideration. entities was neglected in this study. Table 2 shows the rate of beach volume change in every sublittoral cell and its consideration.Furthermore, the predominant wave direction as the shoreline orientation in every sublittoral cell wasits consideration. determined using the MeEPASoL software. This simulation (see AppendixA) also checked the Furthermore, the predominant wave direction as the shoreline orientation in every sublittoral equilibriumcell was determined shoreline using owing the to theMeEPASoL interaction software. between This the predominantsimulation (see wave Appendix and headlands 1) also checked in every sublittoralcell was determined cell (the predicted using the equilibrium MeEPASoL shoreline software. is This showed simulation in yellow (see and Appendix blue line). 1) also checked the equilibrium shoreline owing to the interactioninteraction between the predominant wave and headlands in everyFrom sublittoral the simulation cell (the results,predicted the equilibrium shoreline takes shoreline the parabolic is showed shape in yellow as the equilibriumand blue line). condition. Theevery shoreline sublittoral movement cell (the predicted and equilibrium equilibrium condition shoreline represent is showed the in phase yellow potential and blue line line). in every From the simulation results, the shoreline takes the parabolic shape as the equilibrium condition. sublittoralThe shoreline cell. movement The shoreline and moves equilibrium from the conditio high phasen represent potential the line phase to the lowpotential phase line potential in every line. Then,The shoreline the predominant movement wave and direction equilibrium can represent condition the represent shoreline orientationthe phase potential in every sublittoral line in every cell. sublittoral cell. The shoreline moves from the high phase potential line to the low phase potential line. Then, the predominant wave direction can represent the shoreline orientation in every sublittoral cell. The simulation of equilibrium shoreline using MeEPASoL returns a satsatisfactoryisfactory result for Nusa Dua Beach. Furthermore, the results showshow that erosion problems occurred at Nusa Dua Beach. The evidence of this erosion problem can be indicated from the result of sand volume change in every sublittoral cell.
Table 2. Rate of beabeachch volume change every sublittoral cell at Nusa Dua BeachBeach.. Sublittoral ΔV/Δt Sublittoral ΔV/Δt Remarks 3 −1 Remarks Cell (m3.year−1) 1 −343.50 December 2003–July 2012
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The simulation of equilibrium shoreline using MeEPASoL returns a satisfactory result for Nusa Dua Beach. Furthermore, the results show that erosion problems occurred at Nusa Dua Beach. The evidence of this erosion problem can be indicated from the result of sand volume change in every sublittoral cell.
Table 2. Rate of beach volume change every sublittoral cell at Nusa Dua Beach.
3 1 Sublittoral Cell ∆V/∆t (m year− ) Remarks December 2003–July 2012 1 343.50 (July 2015 to January 2016, Beach Nourishment from − private parties) 2 114.25 December 2003–January 2016 − 3 157.10 December 2003–January 2016 − 4 152.06 December 2003–January 2016 − 5 178.08 December 2003–January 2016 − December 2003–July 2012 6 142.73 (July 2015 to January 2016, Beach Nourishment from − private parties) 7 370.69 December 2003–January 2016 − 8 42.27 December 2003–January 2016 − 9 150.89 December 2003–January 2016 − 10 122.39 December 2003–January 2016 − December 2007–June 2008 11A 131.85 (New Groin GTB in 2010 and unrecorded data of beach − nourishment from private parties) May 2012–January 2016 11B 63.05 − (New Groin GN4 in 2011) May 2012–January 2016 11C 153.16 − (New Groin GN4 in 2011) June 2010–January 2016 12A 37.07 (New Groin GN6 in 2009) June 2010–January 2016 12B 200.06 − (New Groin GN6 and GN5 in 2009) June 2010–January 2016 12C 9.82 (New Groin GN5 in 2009) 13 884.70 December 2003–January 2016 −
5.2. Longshore Drift Patterns Analysis After the analysis of the erosion cases for every sublittoral cell, the longshore sediment transport was calculated in this study, in which Qin and Qout respectively represent the transport into and out of the control volume every sublittoral cell. Equation (9) was used to calculate the longshore sediment transport (Q). Furthermore, the longshore sediment transport was correlated with the predominant wave direction using MeEPASoL simulation. Then, Equation (11) was used to check the pattern of longshore sediment transport as the leading cause of erosion. Table3 shows the calculation results for the longshore sediment transport. The correlation of longshore sediment transport and the predominant wave’s direction in their gradient is shown in Figure 11. This result indicates that the longshore sediment transport in this system has a strong correlation with the shoreline angle, showing a satisfactory correlation coefficient 0.8712. Then, the result shows a nearly constant value for the longshore drift potential (Qp) for this system, i.e., 740.02 m3/year. The longshore drift potential represents the tendency of longshore sediment transport in this system owing to almost the same wave characteristic. However, the fitting curve J. Mar. Sci. Eng. 2020, 8, 749 12 of 19 shown in Figure 11 does not pass through the origin (0,0). The reason for this phenomenon is discussed in the next section.
Table 3. Summary of erosion rate, longshore sediment transport, and predominant waves direction in Nusa Dua Beach. J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 13 of 20 3 1 3 Sublittoral Cell ∆V/∆t (m year ) Q (m year 1) αs (degree) − − 11A1 −343.50131.85 343.501905.81 58.8 79.0 − 2 114.25 457.75 62.3 11B −−63.05 1968.86 87.1 3 157.10 614.84 70.1 11C −−153.16 2122.02 90.5 4 152.06 766.90 62.9 − 12A5 178.0837.07 944.992084.95 83.3 88.6 − 12B6 −142.73200.06 1087.722285.01 85.2 97.2 − 12C7 370.699.82 1458.412275.19 85.4 100.0 − 8 42.27 1500.68 80.3 13 −−884.70 3159.30 79.4 9 150.89 1651.57 83.4 − 10 122.39 1773.95 80.1 − The correlation11A of longshore sediment131.85 transport and 1905.81 the predominant 79.0 wave’s direction in their − gradient is shown 11Bin Figure 11. This63.05 result indicates 1968.86that the longshore 87.1 sediment transport in this − system has a strong11C correlation with the153.16 shoreline angle, 2122.02 showing a satisfactory 90.5 correlation coefficient − 12A 37.07 2084.95 88.6 0.8712. Then, the result shows a nearly constant value for the longshore drift potential (푄푝) for this 12B 200.06 2285.01 97.2 system, i.e., 740.02 m3/year. The longshore− drift potential represents the tendency of longshore 12C 9.82 2275.19 100.0 sediment transport 13in this system owing884.70 to almost the 3159.30same wave characteristic. 79.4 However, the fitting curve shown in Figure 11 does not −pass through the origin (0,0). The reason for this phenomenon is discussed in the next section.
Figure 11. Correlation between longshore sediment transport Q and shoreline orientation sin2βs. Figure 11. Correlation between longshore sediment transport 푄 and shoreline orientation sin2훽푠. 6. Discussion 6. Discussion Although the gradient of sin2βs is zero, Figure 11 indicates that the net flux of longshore sediment drift flowsAlthough along the the shoreline. gradient Such of sin a situation2훽푠 is zero, is possible Figure for 11 two indicates cases; (a)that the the shoreline net flux is linearized of longshore by thesedimen retreatt drift of a controlflows along point the from shoreline the concave. Such a shape, situation and is (b) possible the shoreline for two is cases concaved; a) the from shoreline the is linearlineariz shorelineed by under the retreat a fixed of a control control point. point Thefrom first the concave and second shape cases, and are b) depictedthe shoreline as shown is concav in ed Figurefrom 12 a,b,the linear in which shoreline the subscript under a ‘w’ fixed implies control the point wave. angleThe first at the and breaking second cases point. are The depicted predominant as shown wavein direction Figure 12 isa, consideredb, in which as the normal subscript angle ‘w’of implies equilibrium the wave shoreline. angle at the breaking point. The predominantMany beaches wave have direction a concave is considered shape under asa the static normal equilibrium angle ofstate. equilibriu However,m shoreline. if the shoreline becomes linearized owing to the retreat(a) of control point downstream, the littoral (b) drift can be generated
J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 13 of 18
The correlation of longshore sediment transport and the predominant wave’s direction in their gradient is shown in Figure 11. This result indicates that the longshore sediment transport in this system has a strong correlation with the shoreline angle, showing a satisfactory correlation coefficient
0.8712. Then, the result shows a nearly constant value for the longshore drift potential (𝑄 ) for this system, i.e., 740.02 m3/year. The longshore drift potential represents the tendency of longshore sediment transport in this system owing to almost the same wave characteristic. However, the fitting curve shown in Figure 11 does not pass through the origin (0,0). The reason for this phenomenon is discussed in the next section.
J. Mar. Sci. Eng. 2020, 8, 749 13 of 19 toward the control point as indicated in Figure 12a. However, Nusa Dua Beach has suffered from the change of wave direction and the consequent generation of littoral drift as depicted in Figure 12b Figure 11. Correlation between longshore sediment transport 𝑄and shoreline orientation sin2𝛽 . after the reclamation project of Serangan Island located north of the Benoa strait. Figure 13 shows the6. Discussion equilibrium shoreline estimated by MeEPASoL after reclamation and the rotated direction of dominant wave. In this case, the Benoa strait becomes a sink point of sand losing. Based on this result, Although the gradient of sin 2𝛽 is zero, Figure 11 indicates that the net flux of longshore Nusa Dua Beach is now classified into the topography-induced dynamic state of allowing a uniform sediment drift flows along the shoreline. Such3 a situation1 is possible for two cases; a) the shoreline is stream of sediment of approximately 110 m year− , as shown in Figure 11. If this is true, however, linearized by the retreat of a control point from the concave shape, and b) the shoreline is concaved this dynamic state would not reach the equilibrium state ever due to the presence of Benoa strait to from the linear shoreline under a fixed control point. The first and second cases are depicted as shown play as a sink. Thus the construction of a jetty at the spit end would is recommended to mitigate such in Figure 12a,b, in which the subscript ‘w’ implies the wave angle at the breaking point. The a uniform stream. predominant wave direction is considered as the normal angle of equilibrium shoreline. (a) (b)
FigureFigure 12. 12.Topography-induced Topography-induced dynamic dynamic state; state; ( a(a)) shoreline shoreline linearizing linearizing of of a a concave concave shoreline shoreline due due to to thethe retreat retreat of of a a control control point point from from the the equilibrium equilibrium state; state; and and ( b(b)) shoreline shoreline concaving concaving from from the the linear linear shorelineshoreline under under a a fixed fixed control control point. point.
FigureMany 14beaches shows have the reasonablea concave shape relationship under a between static equilibrium the gradient state. of However, wave-induced if the sediment shoreline 3 1 transportbecomes Qlinearizedw and sin2 βowings after removingto the retreat the dynamic of control transport point component downstream, of 110 them littoralyear− .drift The revisedcan be 3 1 estimationgenerated oftoward the longshore the control drift point potential as indicat is resulteded in in Figure 1167 m 12a.year However,− , which Nusa is the longshoreDua Beach drift has potential representing the level of wave characteristic. The symbol group posed along the zero gradient of Q is taken into account affected by the shoreline rotation owing to groin construction. The groins, which were constructed to control longshore sediment transport, triggered clockwise shoreline rotation from the dominant wave direction. In the present data analysis, we determined that the littoral cell of the study site has unique longshore transport pattern. Thus, it was considered as one littoral cell although it is composed many subcells divided by natural small headlands or groins. The present methodology shows that Nusa Dua Beach is now suffering from a beach erosion problem owing to the dynamic state of littoral drift directed to an inlet after the reclamation, thereby losing sand into an inner bay. Furthermore, based on the interaction of the predominant wave direction and the headland of groins as a coastal structure, the shoreline can take a parabolic shape at the equilibrium condition. The shoreline movement and equilibrium condition represent the phase potential line in every sublittoral cell. The shoreline moves from the high phase potential line to the low phase potential line. Then, the predominant wave direction can represent the shoreline orientation in every sublittoral cell. From the longshore drift patterns analysis, the simulation results show that the longshore sediment transport in this system correlates strongly with the change of predominant wave direction. From this simulation, to reduce the longshore sediment transport, the gradient of the shoreline orientation must also be reduced (smaller gradient of αs gives a smaller gradient of Q). Therefore, all coastal protection activities should be integrated with the coastal zone system. Occasionally, coastal protection strategies aim to protect a few sublittoral cells, and thus coastal structure is designed such that it can reduce the longshore sediment transport in that specific area. Nevertheless, this protection affects the sediment supply system in the adjacent area. v
\
J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 14 of 20
Figure 12. Topography-induced dynamic state; (a) shoreline linearizing of a concave shoreline due to the retreat of a control point from the equilibrium state; and (b) shoreline concaving from the linear shoreline under a fixed control point.
Many beaches have a concave shape under a static equilibrium state. However, if the shoreline becomes linearized owing to the retreat of control point downstream, the littoral drift can be generated toward the control point as indicated in Figure 12a. However, Nusa Dua Beach has suffered from the change of wave direction and the consequent generation of littoral drift as depicted in Figure 12b after the reclamation project of Serangan Island located north of the Benoa strait. Figure 13 shows the equilibrium shoreline estimated by MeEPASoL after reclamation and the rotated direction of dominant wave. In this case, the Benoa strait becomes a sink point of sand losing. Based on this result, Nusa Dua Beach is now classified into the topography-induced dynamic state of allowing a uniform stream of sediment of approximately 110 m3. year−1, as shown in Figure 11. If this is true, however, this dynamic state would not reach the equilibrium state ever due to the presence J. Mar. Sci. Eng. 2020, 8, 749 14 of 19 of Benoa strait to play as a sink. Thus the construction of a jetty at the spit end would is recommended to mitigate such a uniform stream.
J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 15 of 20
the zero gradient of Q is taken into account affected by the shoreline rotation owing to groin construction. The groins, which were constructed to control longshore sediment transport, triggered FigureFigure 13. 13.New New static static shoreline shoreline and and rotation rotation of wave of wave direction direction after after reclamation reclamation project project of Serangan of Serangan Island. clockwise shoreline rotation from the dominant wave direction. Island.
Figure 14 shows the reasonable relationship between the gradient of wave-induced sediment 3 −1 transport 푄푤 and sin 2훽푠 after removing the dynamic transport component of 110 m . year . The revised estimation of the longshore drift potential is resulted in 1167 m3. year−1 , which is the longshore drift potential representing the level of wave characteristic. The symbol group posed along
Figure 14. Correlation between wave-induced longshore sediment transport Q and shoreline Figure 14. Correlation between wave-induced longshore sediment transportw 푄푤 and shoreline orientation sin2β . orientation sin2s 훽푠.
Therefore,In the present a strategic data approach analysis, can we be determined developed tothat deal the with littoral the longshorecell of the sedimentstudy site transport. has unique To managelongshore the transport beach erosion pattern. owing Thus, to it thewaslongshore considered drift, as one the littoral design cell of a coastallthough structures it is composed should many considersubcells the divided shoreline’s by natural orientation. small The headlands designs or should groins. consider The present all sublittoral methodology cells inshows the system. that Nusa TheDua position, Beach length, is now width, suffering distance, from a and beach shape erosion of coastal problem structures owing to aff theect dynamic the shoreline state orientationof littoral drift owingdirected to the to predominant an inlet after wavethe reclamation direction,, whichthereby establishes losing sand the into equilibrium an inner bay. shoreline condition. Therefore,Furthermore, the sediment based budget on atthe adjacent interact sublittoralion of the predominant cells can be a ffwaveected. direction The amount and the of sediment headland of supplygroin ands as the a coastal sand bypassing structure, method the shoreline are also can essential take a factor parabolic in managing shape at beachthe equilibrium conservation. condition. The shoreline movement and equilibrium condition represent the phase potential line in every sublittoral cell. The shoreline moves from the high phase potential line to the low phase potential line. Then, the predominant wave direction can represent the shoreline orientation in every sublittoral cell. From the longshore drift patterns analysis, the simulation results show that the longshore sediment transport in this system correlates strongly with the change of predominant wave direction. From this simulation, to reduce the longshore sediment transport, the gradient of the shoreline orientation must also be reduced (smaller gradient of αs gives a smaller gradient of Q). Therefore, all coastal protection activities should be integrated with the coastal zone system. Occasionally, coastal protection strategies aim to protect a few sublittoral cells, and thus coastal structure is designed such that it can reduce the longshore sediment transport in that specific area. Nevertheless, this protection affects the sediment supply system in the adjacent area. Therefore, a strategic approach can be developed to deal with the longshore sediment transport. To manage the beach erosion owing to the longshore drift, the design of coastal structures should consider the shoreline’s orientation. The designs should consider all sublittoral cells in the system. The position, length, width, distance, and shape of coastal structures affect the shoreline orientation owing to the predominant wave direction, which establishes the equilibrium shoreline condition. Therefore, the sediment budget at adjacent sublittoral cells can be affected. The amount of sediment supply and the sand bypassing method are also essential factor in managing beach conservation.
7. Conclusion
J. Mar. Sci. Eng. 2020, 8, 749 15 of 19
7. Conclusions This study aimed to assess beach erosion at Nusa Dua Beach in Bali. To achieve a better understanding of coastal erosion, it was necessary to conduct longshore drift pattern analysis. The results of this study can be useful for future strategic beach management program. Based on the results of this study, almost all sublittoral cells at Nusa Dua Beach suffered from erosion after the beach conservation project. The longshore sediment transport or littoral drift generated beach erosion in this area. Some groin systems were built to stabilize the longshore sediment transport. Owing to the interaction of predominant waves and the headland of the groin, the beach exhibit the equilibrium shoreline condition. The shoreline moves from the area with a higher phase potential line to that with a lower phase potential line. The simulation of equilibrium shoreline using MeEPASoL gives a satisfactory result for Nusa Dua Beach, and the predicted equilibrium shoreline fits with the satellite image. In this study, although some sublittoral cells were eroded just a few were deposited, like sublittoral cells 12A and 12C. The simulation result shows a strong correlation between longshore sediment transport and predominant wave direction or shoreline orientation, with the correlation value of 0.8712. This simulation result can be used as the pattern for longshore sediment transport at Nusa Dua Beach. 3 -1 The longshore drift potential (Qp) at Nusa Dua Beach was 740.02 m year . This longshore drift · coefficient represents the tendency of longshore sediment transport based on the shoreline orientation. Sublittoral cell 13 had the highest Qout, therefore, it is neccesary to construct a groin near groin GA2 to cut the phase potential line. Nusa Dua Beach is classified into the topography-induced dynamic state, allowing uniform 3 1 stream of sediments of about 110 m year− . Furthermore, the revised estimation of the longshore drift 3 1 potential resulted in 1167 m year− which is the longshore drift potential representing the level of wave characteristic. This was taken into account to be mainly caused by the change of wave direction after the reclamation project of Serangan Island located north of the Benoa strait. MeEPASoL showed that the equilibrium shoreline was clockwise rotated after reclamation and the rotated direction of dominant wave, thus the longshore sediment can be generated toward the Benoa strait. The design of coastal protection activities should be based on the patterns determined in this study because there is a correlation with the beach morphology condition, especially with the predominant wave direction as the shoreline orientation. The groins, which were constructed to control longshore sediment transport, induced a clockwise shoreline rotation from the dominant wave direction. The littoral cell of the study site has unique longshore transport patterns and is thus considered as one littoral cell, although it is composed of many subcells divided by natural small headlands or groins. The present methodology shows that Nusa Dua Beach is now suffering the beach erosion problem owing to the dynamic state of littoral drift directed to an inlet, thus losing sand into an inner bay. Furthermore, it is necessary to simulate the effect of the design of coastal protection activities according to the beach morphology and the sediment budget. The balance of longshore sediment transport needs to be considered a reduction in erosion. The shoreline orientation in every sublittoral cell owing to the impact of the coastal structure, should be managed, such that it exhibits an insignificant difference with the adjacent sublittoral cell. Then, the erosion problem can be reduced. Therefore, for the strategic beach management program, the design of coastal structures (length, shape, and width) should consider the impact on all systems, not just in the selected sublittoral cell. The sediment balance in one sublittoral cell will affect the condition of the other area. This study elucidated the importance of monitoring data in the long term for beach erosion analysis and assessment. Satellite images also provide essential information for conducting shoreline analysis and determining equilibrium shoreline conditions. Furthermore, this study also provided further ideas and research topics in coastal science and engineering. Such ideas can also be generated for improving technology and calculating sediment transport. Moreover, the findings of this study J. Mar. Sci. Eng. 2020, 8, 749 16 of 19
J. Mar. Sci. Eng. 2020, 8, x FOR PEER REVIEW 17 of 20 indicate that the plan or design of beach conservation management activities can be simulated to obtain theAuthor most eContributions:ffective and eSupervision,fficient strategies. J.L.L.; writing-original draft, A.H.S.P; writing—review and editing, J.L.L. All authors have read and agreed to the published version of the manuscript. Author Contributions: Supervision, J.L.L.; writing-original draft, A.H.S.P.; writing—review and editing, J.L.L. AllFunding: authors haveThis research read and was agreed funded to the by publishedthe Ministry version of Oceans of the and manuscript. Fisheries, grant number 20180404, Korea. Funding: This research was funded by the Ministry of Oceans and Fisheries, grant number 20180404, Korea. Acknowledgments: The first author is thankful to KOICA for the opportunity to study at Graduate School of Acknowledgments:Water Resources SungkyunkwanThe first author University. is thankful Also to thanks KOICA to forGovernment the opportunity of Indonesia to study for data at Graduate and information School of Water Resources Sungkyunkwan University. Also thanks to Government of Indonesia for data and information for this study. for this study.
ConflictsConflicts of of Interest: Interest:The The authors authors declare declare no no conflict conflicts of of interest. interest.
AppendixAppendix A. 1. Predominant Predominant WavesWaves Direction and and Prediction Prediction of ofEquilibrium Equilibrium Shoreline Shoreline for Every for Every Sublittoral Cell in Nusa Dua Beach Sublittoral Cell in Nusa Dua Beach
αs = 58.8° αs = 62.3° Sublittoral Cell 1 Sublittoral Cell 2
αs = 70.1° αs = 62.9° Sublittoral Cell 3 Sublittoral Cell 4
αs = 83.3° αs = 85.2° Sublittoral Cell 5 Sublittoral Cell 6
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αs = 85.4° αs = 80.3° Sublittoral Cell 7 Sublittoral Cell 8
αs = 83.4° αs = 80.1° Sublittoral Cell 9 Sublittoral Cell 10
αs = 79° αs = 87.1° Sublittoral Cell 11A Sublittoral Cell 11B
αs = 90.5° αs = 88.6° Sublittoral Cell 11C Sublittoral Cell 12A
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αs = 97.2° αs = 100° Sublittoral Cell 12B Sublittoral Cell 12C
αs = 79.4° Sublittoral Cell 13
References References 1. Andrade, T.S.; Sousa, P.H.G.O.; Siegle, E. Vulnerability to beach erosion based on coastal processes 1. Andrade, T.S.; Sousa, P.H.G.O.; Siegle, E. Vulnerability to beach erosion based on coastal processes approach. approach. Appl. Geogr. 2019, 102, 12–19. Appl. Geogr. 2019, 102, 12–19. [CrossRef] 2. Semoshenkova, V.; Newton, A. Overview of erosion and beach quality issues in three Southern European 2. Semoshenkova, V.; Newton, A. Overview of erosion and beach quality issues in three Southern European countries: Portugal, Spain and Italy. Ocean Coast. Manag. 2015, 118, 12–21. countries: Portugal, Spain and Italy. Ocean Coast. Manag. 2015, 118, 12–21. [CrossRef] 3. Sousa, P.H.G.O.; Siegle, E.; Tessler, M.G. Vulnerability assessment of Massaguachu beach (SE Brazil). Ocean 3. Coast.Sousa, Manag. P.H.G.O.; 2013, 77, Siegle, 24–30. E.; Tessler, M.G. Vulnerability assessment of Massaguachu beach (SE Brazil). 4. Brown,Ocean A.C.; Coast. McLachlan, Manag. 2013 A. Sandy, 77, 24–30. shore ecosystems [CrossRef] and the threats facing them: Some predictions for the 4. yearBrown, 2025. Environ. A.C.; McLachlan, Conserv. 2002 A., Sandy29, 62– shore77. ecosystems and the threats facing them: Some predictions for the 5. Europeanyear 2025. Commission.Environ. Conserv.Climate Change2002, 29Adaptation,, 62–77. [CrossRefCoastal and] Marine Issues; An EU Strategy on adaptation 5. to climateEuropean change. Commission. ComissionClimate staff working Change document, Adaptation, accompanying Coastal and Marine the document, Issues; An Communication EU Strategy on from adaptation the tocommission climate change. to the ComissionEuropean Parliament, staff working the document,Council; The accompanying European Economic the document, and Social Communication Committee from andthe the commission Committee of to the the Regions: European Brussels, Parliament, Belgium the, 2013; Council; 26p. The European Economic and Social Committee 6. Schlacher,and the T.A.; Committee Schoeman, of the D.S.; Regions: Dugan, Brussels, J.; Lastra, Belgium, M.; Jones, 2013; A.; Scapini, 26p. F.; McLachlan, A. Sandy beach 6. ecosystems:Schlacher, Key T.A.; features, Schoeman, management D.S.; Dugan, challenges, J.; Lastra, climate M.; change Jones, impacts, A.; Scapini, and sampling F.; McLachlan, issues. Mar. A. SandyEcol. beach 2008ecosystems:, 29, e70–e90. Key features, management challenges, climate change impacts, and sampling issues. Mar. Ecol. 7. Rangel2008-Buitrago,, 29, e70–e90. N.; Anfuso, [CrossRef G.] Assessment of coastal vulnerability in La Guajira Peninsula, Colombia 7. CaribbeanRangel-Buitrago, sea. J. Coast. N.; Res. Anfuso, 2009 G., 792 Assessment–796. Lisbon, of coastal Portugal, vulnerability ISSN 0749 in-0258. La Guajira Peninsula, Colombia Caribbean 8. Bergillos,sea. J. Coast. R.J.; López Res. 2009-Ruiz,, 792–796. A.; Ortega-Sánchez, M.; Masselink, G.; Losada, M.A. Implications of delta 8. retreatBergillos, on wave R.J.; propagation López-Ruiz, and A.; longshore Ortega-Sá nchez,sediment M.; tra Masselink,nsport-Guadalfeo G.; Losada, case M.A. study Implications (southern Spain). of delta retreat Mar.on Geol. wave 2016 propagation, 382, 1–16. and longshore sediment transport-Guadalfeo case study (southern Spain). Mar. Geol.
9. Bergillos,2016, 382 R.J.;, 1–16.Masselink, [CrossRef G.; Ortega] -Sánchez, M. Coupling cross-shore and longshore sediment transport to model storm response along a mixed sand-gravel coast under varying wave directions. Coast. Eng. 2017, 9. Bergillos, R.J.; Masselink, G.; Ortega-Sánchez, M. Coupling cross-shore and longshore sediment transport to 129, 93–104. model storm response along a mixed sand-gravel coast under varying wave directions. Coast. Eng. 2017, 10. Bergillos, R.J.; Rodríguez-Delgado, C.; Ortega-Sánchez, M. Advances in management tools for modeling 129, 93–104. [CrossRef] artificial nourishments in mixed beaches. J. Mar. Syst. 2017, 172, 1–13. 10. Bergillos, R.J.; Rodríguez-Delgado, C.; Ortega-Sánchez, M. Advances in management tools for modeling 11. Bergillos, R.J.; López-Ruiz, A.; Principal-Gómez, D.; Ortega-Sánchez, M. An integrated methodology to artificial nourishments in mixed beaches. J. Mar. Syst. 2017, 172, 1–13. [CrossRef] forecast the efficiency of nourishment strategies in eroding deltas. Sci. Total Environ. 2018, 613, 1175–1184. 11. Bergillos, R.J.; López-Ruiz, A.; Principal-Gómez, D.; Ortega-Sánchez, M. An integrated methodology 12. de Alegria-Arzaburu, A.R.; Masselink, G. Storm response and beach rotation on a gravel beach, Slapton Sands,to forecast UK. Mar. the Geol. effi 2010ciency, 278, of 77 nourishment–99. strategies in eroding deltas. Sci. Total Environ. 2018, 613, 1175–1184. [CrossRef]
J. Mar. Sci. Eng. 2020, 8, 749 19 of 19
12. de Alegria-Arzaburu, A.R.; Masselink, G. Storm response and beach rotation on a gravel beach, Slapton Sands, UK. Mar. Geol. 2010, 278, 77–99. [CrossRef] 13. Badan Pusat Statistik (BPS) Provinsi Bali, 2018. Provinsi Bali Dalam Angka Tahun 2018. CV Bhineka Raya. 14. Crossland, C.J.; Kremer, H.H.; Lindeboom, H.J.; Marshall Crossland, J.I.; Le Tissier, M.D.A. (Eds.) Coastal Fluxes in the Anthropocene. The Land-Ocean Interactions in the Coastal Zone Project of the International Geospherebiosphere Programme; Springer: Berlin/Heidelberg, Germany, 2005; 232p, ISBN 9783540278511. 15. Defeo, O.; McLachlan, A.; Schoeman, D.S.; Schlacher, T.A.; Dugan, J.; Jones, A.; Lastra, M.; Scapini, F. Threats to sandy beach ecosystems: A review. Estuar. Coast. Shelf Sci. 2009, 81, 1e12. [CrossRef] 16. Nordstrom, K.F. Beaches and Dunes of Developed Coasts; Cambridge University Press: Cambridge, UK, 2000; 338p. 17. Renaud, F.G.; Syvitski, J.P.M.; Sebesvari, Z.; Werners, S.E.; Kremer, H.; Kuenzer, C.; Ramesh, R.; Jeuken, A.; Friedrich, J. Tipping from the Holocene to the Anthropocene: How threatened are major world deltas? Curr. Opin. Environ. Sustain. 2013, 5, e644–e654. [CrossRef] 18. Sherman, D.J.; Barron, K.M.; Ellis, J.T. Retention of beach sands by dams and Debris Basins in Southern California. J. Coast. Res. 2002, 36, e662–e674. [CrossRef] 19. Syvitski, J.P.M.; Vorosmarty, C.J.; Kettner, A.J.; Green, P. Impact of humans on the flux of terrestrial sediment to the global coastal ocean. Science 2005, 308, e376–e380. [CrossRef][PubMed] 20. Davis, R.A., Jr.; Fitzgerald, D.M. Beaches and Coasts, 1st ed.; Blackwell Science Ltd.: UK, 2004; p. 419. 21. European Commission. Living with Coastal Erosion in Europe—Sediment and Space for Sustainability. Part I—Major Findings and Policy Recommendations of the EUROSION Project;Office of Official Publications of the European Communities: Luxembourg, 2004; 54p. 22. Tsuchiya, Y. Formation of Stable Sandy Beaches and Beach Erosion Control: A Methodology for Beach Erosion Control Using Headlands and Its Applications. Bull. Disaster Prev. Res. Inst. 1994, 44, 139–173. 23. Rosati, J.D.; Krauss, N.C. Formulation of sediment budgets at inlets. In Coastal Engineering Technical Note CETN-IV-15 (Revised September 1999); U.S. Army Research and Development Center: Vicksburg, MS, USA, 1999. 24. Rosati, J.D. Concepts in Sediment Budgets. J. Coast. Res. 2005, 21, 307–322. [CrossRef] 25. Gonzalez, M.; Medina, R. On the application of static equilibrium bay formulations to natural and man-made beaches. Coast. Eng. 2001, 43, 209–225. [CrossRef] 26. Hsu, J.C.R.; Evans, C. Parabolic bay shapes and applications. Inst. Civ. Eng. Proc. Lond. Engl. 1989, 87, 556–570. [CrossRef] 27. Yasso, W.E. Plan geometry of headland-bay beaches. J. Geol. 1965, 73, 702–714. [CrossRef] 28. Moreno, L.J.; Krauss, N.C. Equilibrium Shape of Headland-Bay Beaches for Engineering Design. Proc. Coast. Sediments 1999, 1, 860–875. 29. Benedet, L.; Klein, A.H.; Hsu, J.C.R. Practical Insights and Applicability of Empirical bay Shape Equations. In Coastal Engineering 2004 (Vol. 4); World Scientific: Singapore, 2005; pp. 2181–2193. 30. Ministry of Oceans and Fisheries (MOF) Korea. Establishment of Korean Coastal Morphological Prediction System (K-CoSMoS); Korea Institure of Marine Science & Technology Promotion: Gyeonggi-do, Korea, 2018. 31. Cooper, N.J.; Legget, D.J.; Lowe, J.P. Beach? Profile Measurement, Theory and Analysis: Practical Guidance and Applied Case Studies. Water Environ. J. 2007, 14, 79–88. [CrossRef] 32. Dean, R.G.; Dalrymple, R.A. Coastal Processes with Engineering Applications. Cambridge University Press: Cambridge, UK, 2004. 33. Walton, T.L., Jr.; Dean, R.G. Longshore sediment transport via littoral drift rose. Ocean Eng. 2010, 37, 228–235. [CrossRef]
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