INTRODUCTION
Rationale of the study
Climate change is becoming the biggest challenge facing humanity on a global scale According to the Global Climate Risk Index 2021 (CRI) report, Vietnam ranked
On April 22, at the United Nations headquarters in New York, Vietnam joined 180 other countries in signing the Paris Agreement, marking a significant commitment to combat global climate change.
Over the past 50 years, Vietnam has experienced an average temperature increase of 0.5 to 0.7 °C and a sea level rise of approximately 20 cm Extreme weather events, including storms, floods, and droughts, are becoming more severe According to climate change and sea-level rise scenarios from MONRE in 2016, Vietnam's average temperature could rise by up to 4 °C, and sea levels may increase by 1 meter by 2100 Vulnerable regions include coastal areas prone to storms and flooding, as well as mountainous areas susceptible to flash floods and landslides.
Vietnam boasts a coastline of 3,260 km, contributing to the robust development of its marine economy However, the threats posed by climate change and rising sea levels heighten the risks of inundation, erosion, and salinity, which can adversely impact economic stability, livelihoods, and the integrity of coastal infrastructure.
Coastal erosion is a widespread issue affecting Vietnam's coastline, from North to South Research by Pham Huy Tien et al (2002) indicates that there are 397 eroded banks, spanning a total length of 920.21 km The average erosion rate ranges from 5 to 10 meters per year, with potential spikes reaching 50 to 100 meters, and in extreme cases, up to 200 to 250 meters over short periods.
Binh Dinh, a coastal province in Central Vietnam, boasts a 134 km coastline along the East Sea, offering significant natural advantages and substantial potential for marine economic development.
The Chairman of Binh Dinh Provincial People's Committee highlighted that Phu My district is the most affected area by erosion, with four communes—My Duc, My Thang, My An, and My Thanh—experiencing a total landslide length of 3,900 meters, impacting the livelihoods of 2,520 households In Phu Cat district, coastal erosion in An Quang village, Cat Khanh commune, has affected over 550 families along a stretch of more than 520 meters Notably, in 2015 and 2017, coastal erosion led to the uprooting of numerous casuarina trees, with waves encroaching inland by over 70 meters in certain areas Additionally, in Cat Tien commune, the sea has invaded Trung Luong village by over 500 meters, affecting 495 households.
Figure 1 1: Phu Cat coast was eroded in 2017
In June 2020, the Department of Science and Technology of Binh Dinh province recognized the potential risks posed by climate change and proposed an independent national science and technology mission This initiative aims to research integrated technology solutions that enhance resilience and proactive responses to erosion and accretion disasters affecting coastal villages and communes in Binh Dinh province amid ongoing urbanization and climate change challenges.
The research focuses on "Coastal Erosion in Phu Cat District, Binh Dinh Province," examining the effects of climate change on coastal erosion and identifying suitable adaptation measures that align with the local community's capacity to adapt.
Objectives of the research
This study has three main objectives: to analyze shoreline changes, to forecast shoreline changes in the context of climate change, and to propose adaptation measures h
Objects and Scope of the research
- Research object: shoreline changes (focus on coastal erosion)
- Research scope: the entire coastal strip in Cat Khanh, Cat Thanh, Cat Hai, Cat Tien and Cat Chanh.
Research questions and hypotheses
Table 1 1: Research objectives, questions and hypotheses
[Q1]: How have the shorelines changed?
[H1]: Coastal erosion takes place both in the long term and seasonally
[H2]: Shoreline would continue to recede under CC
[Q3]: Which countermeasures could respond to coastal erosion?
[H3]: For the long-term preventing coastal erosion and responding to climate change, a combination of hard and soft measures is needed.
Significance of the research
Scientific significance: This study contributes to enriching research series on coastal erosion for coastal provinces and cities of Vietnam in the context of climate change
Practical significance: The study provides some analysis of shoreline change (focus on coastal erosion) in the Phu Cat district and some anti-erosion countermeasures based on existing local conditions.
The novelty of the research
This groundbreaking study is the first to investigate the erosion phenomenon in Phu Cat district, integrating coastal erosion issues into spatial planning It also proposes anti-erosion solutions that leverage the local adaptive capacity, marking a significant advancement in addressing this environmental challenge.
The structure of the thesis
The thesis, apart from the Conclusions, consists of four chapters as below: h
Review related literature and studies
* Coastal zone: The coastal zone is “a zone of transition between the purely terrestrial and purely marine components on Earth‟s surface” [5]
(Source: Pearson Prentice Hall, Inc, 2009)
The coastal zone, as defined in the Ramsar handbooks for the use of wetlands, 4th edition, represents a narrow interface between land and sea, characterized by complex and intensive ecological and functional processes This area encompasses both terrestrial and aquatic ecosystems that are intricately connected to socio-economic systems, creating multifaceted functional units.
In the book " Vietnam coastal zone - structure and natural resources", the author
Le Duc An defined the coastal zone as comprising two ribbon-like areas that frame the shoreline: the coastal strip and the shallow coastal strip edge The inner boundary of the coastal strip aligns with the administrative limits of coastal districts and cities.
5 the outer border of the external coastal strip is the edge of the continental shelf, usually up to a depth of 200m [7]
The Food and Agriculture Organization (FAO) defines coastal areas as the transitional zones between land and sea The term "coastal zone" specifically pertains to geographical locations relevant to coastal management, while "coastal area" is a broader term that refers to the general region along the coast.
The coastline is the contact line dividing the land from the coastal water bodies
[6] In general, the coastline is the boundary between land and sea This boundary is also not stationary but always moves under waves, tides, currents, etc
The coastline is the highest boundary of waves during interaction with the mainland This boundary is usually cliffs, dunes or terrestrial vegetation [9]
DOLAN et al., 1980 defined shoreline is ideally defined as the physical interface between soil and water [10]
Anders et al., 1991 defined the shoreline as an intersection separated by land, sea, and air [11]
Coastal erosion occurs when a specific area of the coast loses its material supply and material export [12]
Coastline retreat is the process by which the shoreline moves landward due to long-term erosion trends or due to sea level rise [12] h
1.8.2 Overview of studies on coastal erosion
1.8.2.1 Overview of coastal erosion studies in the world
Historically, communities have congregated in coastal plains to utilize marine resources, leading to significant coastal erosion and shaping the trajectory of human development linked to the sea.
The IPCC report highlights that Louisiana's shoreline has experienced an increase in erosion rates, from an average of 0.61 meters per year between 1855 and 2002 to 0.94 meters per year since 1988 Similarly, coastal erosion in China affects nearly 50% of its coastline, with significant erosion rates of 49% in the Yellow Sea, 44% in the East China Sea, and 21% along the coasts of Guangdong province and Hainan Island.
Evidence of anti-erosion structures like ports and breakwaters at the Nile river-mouth, dating back to 2500 BC, highlights the long history of coastal erosion studies The coastal zone serves as a critical interface between land and sea, encompassing terrestrial and aquatic ecosystems that are intricately connected to socio-economic systems, creating complex ecological units Research on coastal erosion is essential and should be approached from geological, geomorphological, and hydrodynamic perspectives to better understand these interactions.
Strahler (1952) and Hack (1960) explored topographical evolution by analyzing erosion and accretion processes through morphological dynamics Zencovich (1962) focused on coastal evolution, investigating the factors that shape coastal topography and the influence of climate and vegetation on geomorphological development Subsequent studies by Eliot and Clark (1982), Thom and Hall (1991), and McLean and Shen (2006) further examined coastal erosion, emphasizing the importance of beach profiles This body of research highlights the critical relationship between coastal erosion and climate change.
The Bruun Rule, proposed by Bruun in 1962, asserts that a beach's horizontal profile achieves dynamic equilibrium when sea levels are stable, highlighting the relationship between sea-level rise and coastal dynamics In contrast, Zhang et al (2004) presented an alternative perspective on this phenomenon, emphasizing the complexities of coastal responses to changing sea levels.
7 the three possible causes of coastal erosion are: sea-level rise, storm regime changes, and human intervention [20]
Before 1990, coastal erosion studies primarily relied on fundamental theories and practical measurement techniques The launch of the first Landsat satellite in 1972 marked a significant turning point, as it enabled researchers to begin utilizing satellite imagery to analyze shoreline changes.
Since 1990, coastal erosion analysis has evolved through the integration of traditional geomorphological research, advanced geomorphic technology, and modeling techniques Notable studies include Kay's (1990) assessment of coastal erosion influenced by sea level rise (SLR) and greenhouse effects (GHE), and Corwell's (1991) examination of shoreline change trends alongside the uncertainties in volatility assessment methods Cambers (1998) focused on coastal retreat through investigative methods linked to satellite image interpretation for planning purposes, while Woodroffe (2002) evaluated coastal topography and sediment changes using both traditional methods and satellite imagery.
The Coastal Vulnerability Index (CVI) has gained significant attention since the early 2000s, with key contributions from researchers such as Gornitz et al (1994), Thieler and Hammar (1999), and Dwarakish et al (2009).
Currently, studies of coastal evolution have come a long way by combining many different methods such as satellite image interpretation, statistics, mathematical modelling, hydrodynamic modelling, etc
1.8.2.2 Overview of coastal erosion studies in Vietnam
In Vietnam, research on coastal erosion has only been popular since the 90s of the
20 th century until now Studies on coastal erosion in central Vietnam are also of interest to domestic scientists
The foundation research on coastal evolution in Vietnam is a State-level research project of author Nguyen Thanh Nga, with code KT-03-14, which assessed the current h
8 state and the causes of coastal erosion in Vietnam and proposed technical solutions Following that, the studies of Cu et al (2001, 2003, 2005) [29], Nguyen Manh Hung
Recent studies, including works by Pham Huy Tien et al (2005), Mimura (2008), and Le Phuoc Trinh et al (2011), have focused on the trends of coastal erosion and accretion in Vietnam These researchers advocate for the use of remote sensing technology to develop sensitive coastal maps Their findings highlight the current volatility of Vietnam's coastline, emphasizing the anticipated impacts of global climate change, such as rising sea levels and increased storm surges, on future coastal dynamics.
Vietnamese scientists primarily employ geomorphology research methods, including morpho-dynamic and hydrodynamic analyses, alongside techniques utilizing topographic maps, aerial photography, and remote sensing images These methodologies are essential for examining shoreline changes in their studies.
Binh Dinh province has seen significant research on coastal erosion in the Central region, with a notable focus on the accretion phenomena at various estuaries, particularly the Tam Quan and De Gi estuaries, as highlighted in studies by Do Minh Duc et al (2017) and Dinh Thi Quynh (2017).
A study by Vo Ngoc Duong et al (2019), published in the proceedings of the 10th International Conference on the Coasts of Asia and the Pacific (APAC 2019), focused on analyzing shoreline fluctuations in Binh Dinh province from 1975 to 2017 The research utilized remote sensing technology and the Digital Shoreline Analysis System (DSAS) to achieve its objectives.
1.8.3.1 Adaption measures in the world
Site descriptions
According to the website of Phu Cat district [41], Phu Cat is a coastal plain district of Binh Dinh province, located on 13 o 54'N- 14 o 32'N and 108 o 55'E- 109 o 05'E
- The North and the Northwest border Phu My district and Hoai An district
- The South borders An Nhon town
- The West and the Southwest border the districts of Vinh Thanh and Tay Son
- The East borders the East Sea with a length of 35 km
- The Southeast borders Tuy Phuoc district and Quy Nhon city
Figure 1 8: Location map of the study area
The Phu Cat coastal strip is about 30 kilometres in length, stretches through 5 communes Cat Khanh, Cat Thanh, Cat Hai, Cat Tien and Cat Chanh
Phu Cat district has a pretty favourable position for economic development associated with benefits from the sea h
Phu Cat features a diverse topography characterized by deltas, low mountainous regions, and coastal lagoons, particularly in Cat Minh, Cat Khanh, and Cat Thanh Additionally, the southern part of Ba Mountain encompasses Cat Chanh and Cat Tien communes.
Figure 1 9: Topography map of the study area
The region is defined by a coastal plain featuring agricultural land along the banks of the Dai An River In contrast, the Cat Khanh, Cat Thanh, and Cat Hai communes are situated in the hilly coastal zone of Phu Cat district.
Hills and mountains in this area account for more than half, but most are bare hills
South of De Gi estuary, the coastline is arc- shaped, concave to the West The intertidal topography in the study area is quite steep, with an average width of 30 - 50 m
With a total length of more than 20km, the beaches of Phu Cat district have much potential for tourism development but not yet fully exploited
Phu Cat experiences a tropical monsoon climate, marked by hot, humid, and rainy conditions The year is divided into two distinct seasons: the dry season, which lasts from December to August, and the rainy season, occurring from September to November During the dry season, hot southwest winds prevail from March to August, while the northeast winds bring drizzling and cooler rains from September to February of the following year.
The region experiences its lowest air temperatures during winter months, from November to March, and its highest temperatures in summer, from May to August Over the years, the average annual temperature hovers around 24.3°C, with daily temperature variations ranging between 7 to 10°C.
Average relative humidity for many years ranges from 85 to 90% Average evaporation for many years is in the range of 1,200 -1,300mm
Binh Dinh experiences highly irregular rainfall patterns throughout the year, with significant variations in average annual precipitation between the wettest and driest locations Historical data indicates that the highest rainfall is typically recorded in October and November.
Table 1 4: Average rainfall in years at Phu Cat station
The coastal area is affected by both monsoon and land-sea breeze Therefore, the distribution of wave direction by month of the year also varies by region
From November to April, waves on the continental shelf of Binh Dinh predominantly travel in a Northeast direction May marks a transitional period characterized by unstable and weak waves From June to September, southwest waves dominate, while other wave directions occur infrequently The maximum recorded wave height reaches 12 meters, with summer averages ranging from 1.2 to 1.7 meters, and winter averages at 1 meter, with rogue waves peaking at 2.2 meters In summer, average wave heights drop to 0.5 meters, with rogue waves reaching 2.3 meters.
Measuring waves is quite complicated According to the research by Duc et al
(2013) [42], the wave characteristics measured with an AWAC system Table 1.5 and Figure 1.10 showed that the Northeast-wave was dominant in September 2012, and the East-wave dominated in June 2013 h
Table 1 5: Wave and current characteristics at the De Gi estuary
Dominant wave direction 61.7° (NE) 111.2° (SE)
Figure 1 10: Wave rose at the De Gi estuary a) September 2012 and b) June 2013 b) Current
The characteristics of flow in Binh Dinh vary with the seasons, predominantly moving in the West and Southeast directions during the dry season Other directions, such as East, Southwest, and Northwest, occur less frequently The flow is mainly diurnal and is influenced by tidal currents throughout the study area, affecting both surface and bottom layers The maximum surface flow rate during the tidal phase reaches 10 cm/s, while during the ebb tide phase, it can peak at 13 cm/s at the surface and 17 cm/s at the bottom.
During the rainy and stormy season, the surface flow through Binh Dinh is mainly in the East and Southeast directions, the West flow accounts for a tiny proportion c) Tide
Binh Dinh experiences primarily irregular diurnal tides, with the number of diurnal days in a month varying between 18 to 26 Both Thi Nai lagoon and the river mouth share a similar tidal regime with the Quy Nhon coastal area, although the tidal amplitude in the lagoon is notably smaller than that of the coastal region.
The tidal amplitude in the lagoon ranges from 1.3m to 1.4m, whereas in the sea, it varies between 1.5m and 2.0m during the same period Notably, the tidal peaks observed in the lagoon and at the Quy Nhon station remain relatively stable.
Phu Cat district, according to the Binh Dinh Statistical Office, covers a total area of 680.49 km² and has an average population of 193,262 residents The district comprises 18 administrative units, which include 17 communes: Cat Son, Cat Lam, Cat Hiep, Cat Hanh, Cat Tai, Cat Minh, Cat Khanh, Cat Thanh, Cat Hai, Cat Tien, Cat Chanh, Cat Thang, Cat Hung, Cat Nhon, Cat Tuong, Cat Trinh, and Cat Tan, along with the town of Ngo May.
The study area includes five communes: Cat Khanh, Cat Thanh, Cat Hai, Cat Tien, and Cat Chanh, with the population shown in table 1.5
Table 1 6: Population of 5 coastal communes of Phu Cat district
No Commune Population in 2019 (people)
(Source: Binh Dinh Statistical Office)
Between 2011 and 2015, the average labor force represented 54.03% of the district's population, rising to 58.36% in 2018 During this period, the employment rate for individuals over 15 years old was 70.2%, though it decreased to 67.54% by 2018 Notably, there is no significant disparity between the number of male and female workers in the district.
The Phu Cat district socio-economic report indicates a growth in the total value of production fields compared to previous years, with the Agriculture, Forestry, and Fishery sectors contributing 25.32% to the economic structure.
Industry and Construction accounted for 26.83%; Trade - Service accounts for 47.85%
The economic structure has shifted towards reducing agriculture, increasing the proportion of Trade and services
Figure 1 11: Economic structure of Phu Cat district Table 1 7: Land use status of 5 coastal communes of Phu Cat district in 2013
No Type of land Cat
Cat Thanh Cat Hai Cat Tien Cat
2 Non-agricultural land 568.04 462.74 190.61 255.57 195.11 2.1 Residential land 58.64 58.63 32.53 75.48 33.42 2.2 Specialized land 60.13 232.54 83.8 112.04 94.83
2.2.1 Land for offices, non-business works 0.73 0.66 0.65 0.91 0.38
2.2.3 Non-agricultural production and business land 9.06 165.78 22.05 15.43 0.5
2.5 River, stream land and specialized water surface 376.38 77.62 57.48 40.72 53.61
No Type of land Cat
Cat Thanh Cat Hai Cat Tien Cat
(Source: Binh Dinh Department of Statistic)
From table 1.6, it can be clearly seen that unused land still accounts for a large proportion
The coastal area of Phu Cat district, stretching from Cat Khanh to Cat Chanh commune, features stunning, unspoiled beaches largely untouched by human activity This pristine environment positions Phu Cat district as a prime location for economic development linked to the sea The district's potential includes diverse agricultural production, encompassing cultivation, husbandry, fisheries, and afforestation, alongside tourism and services, all supported by its beautiful landscapes and efficient transportation infrastructure, including Phu Cat International Airport and the 1A National Highway.
De Gi Lagoon, a vital lagoon in our country, significantly contributes to the economic development of Phu Cat district's coastal area Currently, the aquaculture zone spans 391 hectares, with a total fishery and aquaculture production of 35,000 tons in 2012 Notably, 94% of this output comes from exploitation, while farming contributes 6%.
In addition to the advantages of the beach, the infrastructure of Phu Cat District also has many potentials For example, according to the airport system planning, by
By 2030, Phu Cat Airport is set to transform into an international airport, significantly boosting tourism and commerce in the region This development presents a vital opportunity for Phu Cat District to enhance its economic growth and tourism potential, paving the way for the establishment of an aviation logistics center.
METHODOLOGY
Approaches
Challenges of climate change in coastal areas need to be addressed through integrated and interdisciplinary perspectives
Rapid development activities utilizing marine resources are significantly altering both the quantity and quality of these resources, leading to negative impacts on ecological conditions and environmental quality in coastal zones These changes are resulting in heightened conflicts of interest and spatial disputes over the exploitation and use of coastal areas, ultimately jeopardizing the livelihoods of coastal communities Furthermore, coastal management practices vary considerably among localities, and the coordination mechanisms among stakeholders—including local communities—across provinces and sectors have proven ineffective over the long term.
To promote sustainable management and utilization of marine resources while reducing coastal erosion, the Government, along with the Ministry of Natural Resources and Environment (MONRE) and local authorities, has established and enforced laws and policies focused on natural disaster prevention, climate change adaptation, and strategies to address rising sea levels in coastal regions.
The traditional "top-down" approach to assessing climate change impacts on coastal areas focuses on forecasting future shoreline changes by analyzing various causes, including endogenous, exogenous, and human factors, through climate scenarios and coastal models However, this method is fraught with uncertainties due to the complexities of datasets and models, often leading to theoretical solutions that lack local relevance In contrast, the "bottom-up" approach emphasizes understanding an area's historical and current conditions to inform future adaptation strategies By integrating both approaches, urban planners can gain a comprehensive perspective on coastal management, as illustrated in the shoreline change research framework.
Data collection
This study uses a variety of sources of documents and data, both primary data and secondary data
In recent years, the global adoption of Unmanned Aerial Vehicles (UAVs), commonly known as drones, has surged, particularly in environmental surveying and monitoring Drones excel in applications such as erosion monitoring, coastal vegetation assessment, and analyzing changes in land use and shoreline conditions, providing data with exceptional spatial accuracy and resolution This study focuses on utilizing UAVs to gather data on the shoreline status in Phu Cat district.
The study utilized images captured by the DJI Phantom 4 Advance+, a multi-rotor UAV provided by the MCCD program, featuring an impressive image resolution of up to 20 megapixels Weighing 1,380g and measuring 350mm diagonally, the Phantom 4 Advance+ boasts a flight time of nearly 30 minutes, making it an effective tool for aerial imaging.
The Phantom 4 Advance+ drone is equipped with advanced features such as GPS, obstacle detection, and an automatic flight system Users can directly observe the camera feed through the DJI GS PRO app on an iPad, which is specifically designed for controlling and planning automated flights for DJI aircraft Over two days, this drone captured 1,517 photos along a 12km stretch of coastline, following a downwind route and maintaining equal distance between each shot.
Figure 2 3: UAV photos of Phu Cat coastal area, captured by the DJI Phantom 4
Images captured by drones are processed using Agisoft Metashape version 1.7.2, a photogrammetry software developed by Agisoft LLC based in St Petersburg, Russia This versatile software is compatible with three major operating systems: Microsoft Windows, macOS, and Linux.
The author conducted a study by collecting ten sand samples from a depth of 50 cm underwater and an additional 15 cm above the sand surface The sampling locations comprised the top, middle, and end sections of Cat Khanh, Cat Hai, Vinh Hoi, and Trung Luong beaches.
This study involved interviews with three distinct groups: local residents, local officials, and experts Local residents participated through on-site consultations, while both experts and local officials were interviewed using a combination of online and on-site methods For detailed information on the interview format, please refer to Appendix 2.
The study utilized three topographic maps of Hai Dong, Quy Nhon, and Phu My, all within UTM zone 49 and based on the Indian 1960 geographic coordinate system, with a scale of 1:50,000 These maps, numbered 6836-I, 6836-IV, and 6836-III, were published by the U.S Army Topographic Command and reprinted in 1965, 1969, and 1970.
Hai Dong (6836-I) Quy Nhon (6836-IV) Phu My (6836-III)
(Source: University of Texas Libraries)
Figure 2 4: Topographic maps of study area published by U S Army Topographic
In addition, this study also uses topographic maps at scale 1: 10,000, coordinate system VN2000, meridian 108, projection zone 3 (provided by the Institute of Geotechnical Engineering, VNU)
This study utilized Level-2 Surface reflectance data from Landsat 5 TM and Landsat 8 OLI/TIRS sensors to examine shoreline change rates between 1988 and 2016 The satellite image data, available at no cost, was sourced from NASA's Aerospace Agency.
The Geological Survey (USGS) utilizes satellite images adjusted to the WGS-84 UTM frame of reference, specifically zone 49N, prioritizing those with less than 20% cloud cover For images exceeding this threshold, cloud removal is sometimes necessary The shoreline derived from satellite image processing is converted from raster to vector format for accurate calculations Landsat satellite images can be downloaded from the USGS Earth Explorer website.
Information of bands of Landsat 8 OLI satellite images area presented in Table 2.1
Table 2 1: Landsat 8-9 OLI/TIRS (L2SP) Band Specifications
(Source: https://docs.sentinel-hub.com/) Band number Band Description Band Range
6 Short Wavelength Infrared (SWIR) (OLI) 1566-1651 30
10 Thermal Infrared Sensor (TIRS) 1 10600-11190 100 (30) (*) (*) TIRS bands are acquired at the 100-meter resolution but were resampled to 30- meter in the delivered data product
Information of bands of Landsat 5 TM satellite images area presented in Table 2.2
Table 2 2: Landsat 4-5 TM (L2SP) Band Specifications
(Source: https://docs.sentinel-hub.com/) Band number Band Description Band Range
(**) The thermal band is acquired at 120-meter resolution and then resampled to 30- meter in the delivered data product h
Table 2.3 presents the Landsat images utilized in this study, collected between 1989 and 2016 at a consistent tidal level of 1.5 meters, ensuring the reliability of shoreline change comparisons.
Table 2 3: List of satellite images used in the study
No Product Identifier Acquisition time
NE monsoon season LT05_L2SP_123050_19891001_20200916_02_T1 10/1/1989 28
LT05_L2SP_123050_19930214_20200914_02_T1 2/14/1993 26 LT05_L2SP_123050_19990319_20200908_02_T1 3/19/1999 0 LT05_L2SP_123050_20040401_20200903_02_T1 4/1/2004 1 LT05_L2SP_124050_20080318_20200829_02_T1 3/18/2008 5.45 LC08_L2SP_123050_20140208_20200912_02_T1 2/8/2014 0.16 LC08_L2SP_123050_20160418_20200907_02_T1 4/18/2016 22.96
SW monsoon season LT05_L2SP_123050_19890627_20200916_02_T1 6/27/1989 19
LT05_L2SP_123050_19930724_20200913_02_T1 7/24/1993 28 LT05_L2SP_123050_20000609_20200907_02_T1 6/9/2000 6 LT05_L2SP_123050_20050506_20200902_02_T1 5/6/2005 0 LT05_L2SP_123050_20080903_20200829_02_T1 9/3/2008 6 LC08_L2SP_123050_20140920_20200910_02_T1 9/20/2014 10.24
Meteorological and hydrological data were sourced from various agencies, including the General Statistics Office (GSO), Binh Dinh Statistical Office, and Phu Cat Meteorological Station, as well as the Vietnam Oceanography Center and the Binh Dinh Provincial Commanding Committee for Natural Disaster Prevention and Control This comprehensive data collection encompasses key parameters such as temperature, precipitation, wave activity, wind patterns, and tidal movements, alongside insights from several domestic studies.
Besides, this study also uses the Climate Change Scenario and sea-level rise published by MONRE in 2016
Planning data used in this study include:
- The reports on socio-economic development (approved),
- The reports on natural disaster prevention (approved), h
- Construction plan of Binh Dinh province region to 2035 (approved),
- Construction planning of Phu Cat district until 2040, vision to 2050 (browsed),
- Action plan to respond to climate change in Binh Dinh province (approved)
Table 2 4: Summary of data used in the research
No Type of data Data sources
1.1 Maps of Hai Dong (6836-I), Phu My (6836-IV),
Quy Nhon (6836-III) published by U S Army
Topographic Command, the scale of 1:50,000
1.2 Maps of Binh Dinh province, scale 1:10,000 Department of Geology, VNU
2 Satellite images Level 2 Surface reflectance
2.1 Seven images generations of NE monsoon season
2.2 Six images generations of SW monsoon season
3.1 Monitoring data GSO, Binh Dinh Statistical
Meteorological Station, Binh Dinh CCNDPCSR
4.1 Phu Cat socio-economic development reports Phu Cat PC
4.2 Phu Cat natural disaster prevention reports Binh Dinh CCNDPCSR
4.3 Construction plan of Binh Dinh province region to 2035 Binh Dinh DC
4.4 Construction plan of Phu Cat district region to
4.5 Action plan to respond to climate change in
Binh Dinh province Binh Dinh DONRE h
Methods
A type of research method (qualitative or quantitative) is insufficient to answer research questions and solve the research problems Therefore, the study orient uses mixed methods, which are listed below:
Table 2 5: List of research methods
M1 Interview Identify erosion hotspots, interview experts and local officials to find adaptive solutions
M2 Case study Compare, choose the suitable adaptive measures
M3 Survey Observation and measurement in some key areas
M4 Experiment Determination of sand particle size and distribution M5 Inheritance
Identify research methods, collect necessary databases (emission scenarios, climate models, development scenarios, etc.)
M6 Statistic Identify correlations among the historical shoreline changes and predict erosion
M7 Modelling Predict shoreline change under CC M8
Satellite image interpretation and map overlay
Analyze shoreline change, quantifying the shoreline change rate by spatial and temporal scale (using ArcGIS, QGIS, DSAS, etc.)
Interviewing is the most common way of data collection in qualitative research
[49] This study used a semi-structured format to collect data from three types of subjects: local people, local officials, and experts (For details, see appendix 2)
In March 2021, a questionnaire survey was conducted to gather insights from local participants regarding their livelihoods and perceptions of climate change and coastal issues The interview questions focused on understanding the opinions of the interviewees about these critical topics.
35 erosion; the interview questions for local officials mainly related to coastal management, coastal erosion prevention solutions
The research used case studies as a tool to make decisions for appropriate adaptive solutions based on a complete analysis of investigated similar cases in actual conditions [50]
This study employed various field survey methods, including UAV surveys, field observations, sediment sampling, and beach descriptions, to analyze coastal morphology and vegetation cover While UAV technology is costly and influenced by weather, it is instrumental in monitoring coastal erosion and accretion GPS measuring points are crucial for geometrical corrections of satellite images and topographic maps, enhancing the analysis of shoreline variations The combination of GPS data with UAV imagery provides a more reliable assessment of shoreline fluctuations and predictions of erosion and accretion Essential equipment for this research includes a drone, a smartphone, a laptop or computer, and software such as Agisoft Photoscan Pro (or Agisoft Metashape), QGIS, and ArcGIS for image processing and analysis.
Figure 2 5: UAV photos processing flowchart h
The images were processed using geolocation and camera information, involving steps such as photo alignment, dense cloud construction, DEM creation, and orthomosaic image generation Field data results were combined with satellite image interpretation methods to validate the accuracy of the satellite imagery.
This study experiments on grain size classification The experimental procedure is as follows:
Figure 2 6: Sand samples after drying (Left) and sampling location (Right) of coastal sand in Phu Cat district
After being dried at 80 o C (Please see Figure
2.6), the sand samples were sized by manual sieving method in the Geotechnical Laboratory,
Department of Geology, University of Natural
Sciences The identification of sand color based on the Munsell color chart [51]
Particle composition analysis tools used are sieves ranging in size from 0.075mm to 5mm,
37 based on sediment classification of Wentworth grain size chart (Please see Figure 2.7) classification by manual sieving method
This study inherits some results from previous studies, combined with the use of climate change and sea-level rise scenarios published by MONRE in 2016 to forecast future shoreline change
This study employs the Digital Shoreline Analysis System (DSAS) version 5.0, which utilizes statistical methods including End Point Rate (EPR) and Net Shoreline Movement (NSM) for shoreline analysis While the DSAS tool can predict future shorelines, its reliability in such predictions is limited.
This study employs Bruun's rule model to forecast shoreline retreat due to climate change-induced sea-level rise First introduced by Per Bruun in 1962, this model establishes a crucial link between rising sea levels and coastal degradation It is based on the equilibrium platform theory, which posits that beach profiles strive to maintain a balanced shape Consequently, as sea levels rise, shorelines are expected to retreat inland and upward to adapt to the new equilibrium.
Figure 2 8: Illustration of the Bruun Rule, by the Scientific Committee on Ocean
The equation of the Bruun Rule is: h
- S: Sea level rise (unit: meter)
- L: The horizontal length of the bottom affected by the sea level rise (from the dune peak to the depth of closure) (unit: meter)
- h: the depth of closure (unit: meter)
- B: the dune height above sea level (unit: meter)
- β: the average slope of the active profile
Several models effectively align field and laboratory data for bay-shaped shorelines, including the spiral, tan-hyperbolic, and parabolic models Among these, the parabolic model, which simulates the static equilibrium of headland bay-shaped shorelines and was developed by Hsu and Evans in 1989, is widely utilized.
Figure 2 9: Parabolic bay-shape model (after Hsu and Evans, 1989)
The empirical equation of this model as:
- R n : the distance between the control point and coastline
- β: the angle between the wave crest in the diffraction point and the control line R β h
The correlation coefficients: C 0 , C 1 , C 2 are determined by curve fitting from the field and laboratory data as the wave angle β changes
Vargas, Hsu, Klein, and Raabe created MEPBAY software for quick estimation of shoreline equilibrium The adoption process for the MEPBAY model involves selecting a loading image and identifying the coastline direction along with wave movement.
→ determine upcoast control point, downcoast control point, and an endpoint along the tangent to the beach → change Rn and β to determine the equilibrium shoreline
RS analysis is an advanced technique for efficiently addressing macro-level spatial issues In this study, the author utilized ArcGIS and QGIS to analyze satellite imagery The primary objective is to automatically delineate land and sea boundaries through segmentation algorithms that assess the surface reflectance of Landsat satellite images.
Step 1: Pre-processing and converting DNs to surface reflectance (using QGIS) Step 2: Calculate the MNDWI index
This study employs the automatic threshold classification method for delineating land and water boundaries using the Modified Normalized Difference Water Index (MNDWI) Developed by Xu in 2006, MNDWI has gained widespread application globally, as evidenced by research from Singh et al (2015), Sarp and Ozcelik (2017), and Nandi et al (2018).
The Modified Normalized Difference Water Index (MNDWI) is recognized as an effective technique for shoreline extraction from Landsat imagery, outperforming other indices such as the Normalized Difference Water Index (NDWI) and the Automated Water Extraction Index (AWEI) This method utilizes the green band and the short-wave infrared band, specifically band 3 and band 6 in Landsat 8 OLI, and band 2 and band 5 in Landsat 5 TM.
The MNDWI index is determined as follows:
For Landsat 5, MNDWI = (Band 2 – Band 5) / (Band 2 + Band 5) (4.4)
For Landsat 8, MNDWI = (Band 3 – Band 6) / (Band 3 + Band 6) (4.5)
Step 3: Binary land and water based on automatic thresholding algorithm (Otsu,
After calculating the Modified Normalized Difference Water Index (MNDWI) using ArcGIS, the reclassify tool was employed to differentiate between water and land, with positive values indicating water and negative values representing land It is essential to verify the automatic shoreline delineation results to identify and manually correct any inaccuracies Subsequently, the raster data was transformed into vector data to facilitate the calculation of shoreline variations, resulting in line-shaped representations of the shorelines.
Step 4: Shoreline change analysis using DSAS
The DSAS v5.0, developed by the United States Geological Survey (USGS), is an essential ArcGIS add-in that enables users to statistically assess shoreline change rates This powerful tool is widely recognized for its capability to analyze geographic information series and effectively calculate shoreline alterations over time, making it a valuable resource for researchers and professionals in the field (Kaliraj et al., 2013; Oyedotun, 2014; Nassar et al., 2018).
The DSAS shoreline variation analysis process involves several key steps: first, creating shorelines; next, establishing a baseline; then, generating transects; followed by calculating the distances between the baseline and the shorelines at each transect; and finally, computing the shoreline change rate.
In this study, the shoreline was segmented into 50-meter transects to analyze shoreline changes The Net Shoreline Movement (NSM) method was employed to measure the distances between two shorelines, considering the time elapsed between the oldest and newest shorelines available Additionally, the End Point Rate (EPR) method was utilized to determine the rate of shoreline change by dividing the distance between the furthest and most recent coastlines by the time interval EPR is currently the most widely used method for assessing shoreline fluctuations.
NSM time between oldest and most recent shoreline
(Source: DSAS Version 5.0 User Guide, USGS)
In summary, the logical framework of this study is presented in Figure 2.10. h
RESULTS AND DISCUSSION
Results
Analysis results of grain composition of ten sand samples collected in the Phu Cat coastal area shown in Figure 3.1
Figure 3 1: Particle size distribution along Phu Cat coastline
The beaches in Phu Cat district are characterized by sandy compositions, with coastal sediments primarily consisting of fine, medium, and coarse sand Near De Gi jetty, sediment is notably coarse and includes gravel, while Trung Luong beach also features coarse-grained sediments Other surveyed areas exhibit a range of particle sizes, encompassing fine, medium, and coarse grains.
Grain size sedimentation reflects the hydrodynamic conditions of coastal areas, with coarser sediments indicating stronger hydrodynamic regimes Consequently, deposition beaches typically feature finer sediments, while eroding beaches are characterized by coarser sediment sizes.
From figure 3.1, D 50 for ten sampling positions ranges from 0.32mm to 1.72mm Such particle size is suitable for sandy beach material characteristics, which satisfied h
44 hydrodynamic regime to apply the Bruun model in section 3.1.5.3; and meet the necessary conditions to apply the parabolic equilibrium model to the headland bay beach presented in section 3.1.5.2
A total of 1,517 overlapping images were analyzed for five small shoreline segments, including Cat Khanh (North near De Gi estuary and South near Ong Lop headland), Cat Hai, Vinh Hoi, and Trung Luong, utilizing Agisoft Photoscan® for processing.
UAV image interpretation products, integrated with Google Earth in KMZ format, are illustrated in Figure 3.2 The UAV's limited survey time restricted coverage to only a few segments of the coastal strip of Phu Cat, as shown in the figure.
Figure 3 2: UAV images interpretation results (overlap on Google Earth background) 3.1.3 Shoreline change analysis
The beach features an accumulation-erosion topography shaped by dominant wave action, resulting in noticeable seasonal variations in its landscape.
This study evaluates the spatial and temporal variations of the shoreline in Phu Cat, focusing on long-term, short-term, and seasonal changes Shoreline alterations are analyzed across the entire coastline and in specific sections for each designated time period Utilizing the DSAS tool, the study calculates the rate of change of shorelines post-extraction, as detailed in chapter 4.
This study categorizes the shoreline of Phu Cat into four distinct segments—Cat Khanh, Cat Hai, Vinh Hoi, and Trung Luong—based on their location and morphological characteristics to evaluate erosion rates The specific positioning and lengths of these segments are illustrated in Figure 3.3.
Cat Khanh segment: about 12.6 km in length; the largest width is 250m, the coast is gentle
Cat Hai segment: about 1.8 km in length; the largest width is 182m, the coast is gentle
Vinh Hoi segment: about 2.6 km in length; the largest width is 320m, the coast is gentle
Trung Luong segment: about 6.9 km in length; the largest width is 380m, the coast is gentle
The results of extracting the Phu Cat coastline through interpretation of Landsat 5
TM and Landsat 8 OLI satellite images from 1989 to 2016 are shown in Figure 3.4
Figure 3 4: Result of the shoreline extraction
Considering the EPR index, the shoreline change rate is classified into nine classes, as shown in Figure 3.5 h
Figure 3 5: Erosion - Accretion classification (EPR) 3.1.3.1 Long-term change
Long-term coastal evolution involves cumulative effects of storms, sea-level rise, changes in sediment supplies, and human activities (construction of shore protection, sand mining, etc.)
The analysis of long-term shoreline change in the Northeast monsoon season was performed using 7 Landsat level 2 Surface reflectance images, collected in 1989, 1993,
1999, 2004, 2008, 2014 and 2016 (with same tidal level) Below are the results of the shoreline change analysis for each period a) The period from 1989 to 2016
Table 3.1 shows the result of the analysis of erosion and accretion using the EPR index of DSAS software
From 1989 to 2016, the Phu Cat shoreline experienced both accretion and erosion processes, resulting in a relatively stable coastline overall The erosion rate averaged -3 meters per year, while the mean accretion rate was 0.7 meters per year for the entire shoreline.
Table 3 1: Shoreline change rate in NE monsoon season (1989-2016)
3 Mean shoreline change rate (m/yr) 0.27 0.24 -0.04 0.02
6 Total transects that record erosion 2 1 6 11
7 Total transects that record accretion 79 9 10 16
- The mean erosion rate in each segment was: Cat Khanh (-9.9m/yr), Cat Hai (- 0.59m/yr), Vinh Hoi (-0.97m/yr), Trung Luong (-0.95m/yr)
- The most vital erosion area: De Gi headland (erosion speed was -10m/yr)
- The segment of Cat Hai was stable during the whole period
Figure 3 6: Shoreline change map (EPR) in NE monsoon season (1989-2016) b) The period from 1989 to 1999
Table 3.2 shows the result of the analysis of erosion and accretion using the EPR index of DSAS software from 1989 to 1999
Table 3 2: Shoreline change rate in NE monsoon season (1989-1999)
3 Mean shoreline change rate (m/yr) 0.20 0.03 -1.02 -1.50
6 Total transects that record erosion 73 10 23 137 h
7 Total transects that record accretion 60 11 3 0
Between 1989 and 1999, shoreline change analysis in Phu Cat revealed a trend of both erosion and accretion, with erosion being more prevalent The overall average erosion rate was approximately -1.6m/yr, while the accretion rate was around 1.2m/yr At Cat Khanh beach, accretion outpaced erosion, with rates of 2.31m/yr for accretion and -0.94m/yr for erosion Conversely, Vinh Hoi beach experienced significant erosion, with a rate of -2.43m/yr, while accretion was limited to 0.99m/yr.
During the specified period, the Trung Luong segment experienced significant coastal erosion, with an average erosion rate of 1.6 meters per year along its 7-kilometer shoreline (refer to Table 3.2).
The North of Trung Luong beach and the northern section of Vinh Hoi beach experience the highest erosion rates, reaching approximately -5 meters per year In contrast, the De Gi area has shown significant accretion, recording a maximum growth of 22.4 meters per year during the same period.
Figure 3 7: Shoreline change map (EPR) in NE monsoon season (1989-1999) c) The period from 1999 to 2008
Table 3 3: Shoreline change rate in NE monsoon season (1999-2008)
3 Mean shoreline change rate (m/yr) -0.15 0.27 0.59 0.05
6 Total transects that record erosion 76 3 6 32
7 Total transects that record accretion 105 9 27 41
Between 1999 and 2008, the shoreline exhibited both accretion and erosion, yet overall, the coastline remained stable The Cat Khanh and Trung Luong segments experienced more erosion than accretion, while the Cat Hai and Vinh Hoi segments showed significant accretion Notably, Cat Khanh beach had areas of erosion, with the De Gi jetty experiencing the highest erosion rate of -60m/year.
Figure 3 8: Shoreline change map (EPR) in NE monsoon season (1999-2008) d) The period from 2008 to 2016
Table 3 4: Shoreline change rate in NE monsoon season (2008-2016)
3 Mean shoreline change rate (m/yr) 0.90 0.36 0.45 1.79
6 Total transects that record erosion 33 8 12 0 h
7 Total transects that record accretion 170 25 29 123
Table 3.4 indicates a slight overall accretion trend along the coastline during this period, with the Cat Hai, Cat Khanh, and Vinh Hoi segments experiencing both erosion and accretion Specifically, the average erosion rates were recorded at -1.86 m/yr for Cat Khanh, -2.37 m/yr for Cat Hai, and -1.66 m/yr for Vinh Hoi, while the average accretion rates were 1.73 m/yr, 1.33 m/yr, and 1.50 m/yr for the same segments, respectively.
The Trung Luong segment has shown a significant accretion, with an average rate of 2.1 meters per year In contrast, several areas are experiencing erosion, including De Gi, which has an erosion rate of -9 meters per year, and Ong Lop headland and Ganh hill near Vu Nam eco-resort, both recording erosion rates of approximately -4 meters per year Additionally, the Trung Luong headland at Vinh Hoi beach is facing erosion at a rate of about -3 meters per year.
Figure 3 9: Shoreline change map (EPR) in NE monsoon season (2008-2016)
The study of shoreline changes during the southwest monsoon season utilized six satellite images from the years 1989, 1993, 2000, 2005, 2008, and 2014, all aligned with the same tidal level This analysis covers a significant timeframe from 1989 to 2014, providing valuable insights into coastal dynamics.
Discussion
In general, with the primary objective of analyzing shoreline change in Phu Cat district under CC and proposing solutions, the problems raised have been solved
Firstly, this study used Landsat level 2 Surface reflectance satellite images from
From 1989 to 2016, a consistent tidal level was utilized to analyze both long-term and short-term shoreline changes, minimizing errors caused by tidal fluctuations and enhancing shoreline extraction accuracy The author employed the Digital Shoreline Analysis System (DSAS) tool in ArcGIS to assess erosion and accretion rates using the End Point Rate (EPR) and Net Shoreline Movement (NSM) indices Following the guidelines set by the US Geological Survey (USGS), the classification of erosion and accretion levels was established based on these indices The main findings of the study are summarized as follows:
During the NE monsoon season from 1989 to 2016, the Phu Cat coastline experienced both accretion and erosion, with overall stability observed Erosion was predominant from 1989 to 1999, with an average shoreline erosion rate of approximately -1.6m/yr The period from 1999 to 2008 saw a generally stable shoreline, followed by slight accretion from 2008 to 2016 The most significant erosion occurred at De Gi beach and the northern section of Trung Luong beach, with De Gi beach experiencing a maximum erosion rate of 60m/yr.
Between 1989 and 2014, the coastal area of Phu Cat experienced slight accretion during the SW monsoon season, with an average rate of 0.8m per year However, from 1989 to 2000, the region faced significant erosion, averaging -1.37m per year Erosion continued to be a concern until 2008, after which accretion prevailed until 2014 Notably, the most severe erosion occurred at De Gi beach, Ong Lop headland, and the northern part of Trung Luong beach.
De Gi in 1999-2008 (-9.5m/yr) and the North of Trung Luong in the period 2008-2014 (7.9m/yr)
Figure 3 40: Comparison of erosion rate (EPR index) in NEMS and SWMS
From Figure 3.39, it can be seen that the erosion rate in the northeast monsoon season is higher than in the southwest monsoon season
This study on seasonal shoreline changes at Phu Cat revealed a pattern of oscillation between erosion and accretion Notably, the shorelines remained stable in 1989 and 2008, while periods of accretion were observed in 1993 and 2014.
Between 1989 and 2000, Phu Cat district experienced significant coastal erosion, influenced by a series of storms Data indicates that 15 storms impacted Binh Dinh during this period, notably Typhoon Linda in 1997, which struck with winds of 102 kph, resulting in severe damage to central provinces Additionally, three consecutive storms in November and December 1998 further exacerbated shoreline changes, highlighting the profound effect of hurricanes on coastal dynamics.
Among the analyzed erosion hotspots, De Gi is the one confirmed by most local people through interviews h
This study employs the Digital Shoreline Analysis System (DSAS) as a key predictor for future shorelines, utilizing the End Point Rate (EPR) and Linear Regression (LPR) indexes alongside statistical methods and historical shoreline data The findings indicate that the projected shorelines for 2025 and 2035 are expected to experience accretion.
The PBSE analysis revealed that the shorelines of Cat Hai, Vinh Hoi, Ong Lop headland, and Trung Luong are in static equilibrium planform (SEP), indicating long-term stability with no erosion or accretion In contrast, Cat Khanh beach is classified as being in dynamic equilibrium planform (DEP), suggesting a tendency towards erosion, which aligns with the findings from the shoreline change assessment.
This study assessed the impact of climate change and sea-level rise on the Phu Cat coastline, calculating shoreline recession at four key cross-sections using the Bruun model Findings indicate that by 2100, the shoreline is projected to recede by approximately 5 meters under the RCP 4.5 scenario and by 7 meters under the RCP 8.5 scenario.
This study's findings on long-term shoreline change analysis and prediction align closely with previous research that employed modeling methods to examine accretion and erosion trends.
The Binh Dinh coastal safety corridor, established under Decision 4383/QD-UBND by the People's Committee of Binh Dinh province, aligns with the coastal setback proposal outlined in this study.
Table 3 22: Compare the results of the study with related studies
Authors Result Compare to this study Review of the planning The shoreline from 1973 to 2017 showed Consistent h
88 of coastal dike system from Quang Ngai to
Kien Giang (2017) [63] that the coast in this area was alternating erosion-accretion The beach of Cat Hai and Cat Tien communes is relatively stable
The southern coast of De Gi did not change significantly in the period 1965 -2012; the primary trend is erosion
Long et al., 2017 [67] Beach of Trung Luong is and will have a predominant accretion trend In Phu Cat district, accretion-erosion is alternating
Duong et al., 2019 [68] The period 1988-1997 recorded the most significant erosion in Binh Dinh Consistent
Limitation on UAV data: the author used UAV to investigate the beaches of Phu
The flight route for the field survey was insufficient to cover the entire length and width of the Phu Cat shoreline, making it impossible to utilize UAV interpretation products for comparison with satellite image analysis Nevertheless, these results can serve as a valuable database for small-scale shoreline management through segmented analysis.
Limitations on shoreline change analysis and prediction:
The remote sensing method effectively detected current erosion and accretion phenomena across spatial and temporal scales; however, it overlooked the physical processes driving changes along the coastline.
The PBSE method or Bruun's model only qualitatively predicts shoreline change
The shoreline prediction method using the Digital Shoreline Analysis System (DSAS) has notable limitations It necessitates at least four historical shoreline data points and relies on the assumption that past shoreline trends will continue similarly into the future, which may not always hold true Additionally, the method faces challenges due to various environmental factors that can influence shoreline dynamics.
The study utilized 89 satellite images with a spatial resolution of 30 meters; however, the limited time series of these images introduced uncertainties in estimating future shoreline changes using the DSAS tool.
Therefore, it is necessary to apply some supplementary mathematical models to explain the causes of shoreline change and predict future shoreline changes
The assessment of adaptive capacity in Phu Cat district was limited to qualitative analysis, relying on a few interviews and local documents To enhance the evaluation, it is essential to gather a comprehensive number of interview samples.
RECOMMENDATIONS
Recommendation for using research results
Coastal managers can utilize the findings of this study to effectively address and choose appropriate solutions for regions vulnerable to erosion Implementing annual seasonal monitoring data is essential for predicting shoreline changes influenced by climate change scenarios.
Urban planners must integrate coastal erosion considerations into all levels of planning prior to local government approval to mitigate potential damage Effective planning serves as a crucial mechanism for balancing socio-economic development with anticipated changes to physical shorelines.
Scientists emphasize that the findings of this study are preliminary and require further in-depth investigation Additional specific surveys and calculations are necessary, particularly involving detailed physical and mathematical models Moreover, practical solutions must be evaluated in accordance with economic and technical criteria.
The findings of the study provide valuable insights for coastal engineers, planners, and management authorities, aiding in the development of effective strategies to combat coastal erosion exacerbated by climate change.
Further research orientations
First, the complete addition of interview data and survey of the entire shoreline by UAV will increase the reliability of the study
The implementation of advanced models, such as those for waves, currents, and sediment transport, will enhance understanding of coastal erosion in the Phu Cat area To achieve this, it is essential to gather comprehensive input data and calibrate the models with real-time measurements throughout different seasons.
To effectively combat erosion in Phu Cat district and safeguard the coastline against climate change impacts, integrating green and grey infrastructure solutions is essential Research into both natural and artificial anti-erosion materials could provide crucial insights for sustainable long-term protection.
This study analyzed shoreline changes in Phu Cat district, Binh Dinh province, by utilizing Landsat 5 TM and Landsat 8 OLI satellite images (Level 2 Surface Reflectance) from 1989 to 2016.
The shoreline of Phu Cat observed erosion and deposition change irregularly in all periods, including short-term (20 years) and seasonal change
Between 1989 and 2016, the Phu Cat coastline experienced both accretion and erosion during the NE monsoon season, yet overall, the coast remained relatively stable Erosion was dominant from 1989 to 1999, while the shoreline showed general stability in the periods from 1999 to 2008 and 2008 to 2016 The areas most affected by erosion were De Gi beach and the northern section of Trung Luong beach.
Between 1989 and 2014, the coastal area of Phu Cat experienced slight accretion during the SW monsoon season, with a notable shift from erosion to accretion over the years Specifically, from 1989 to 2000, erosion was prevalent, while accretion dominated from 2000 to 2008 and continued through to 2014 The most significant erosion was observed at De Gi beach, Ong Lop headland, and the northern part of Trung Luong beach.
In terms of seasonal shoreline change, the calculation results show that the primary trend of Phu Cat shoreline is accretion from the NE monsoon to the SW monsoon in
The future shoreline predicted using DSAS would not shift landward; in other words, in 2025, 2035, the shoreline tends to be accreted
The PBSE analysis revealed that the shoreline segments of Cat Hai, Vinh Hoi, Ong Lop headland, and Trung Luong are in a stable static equilibrium planform (SEP) In contrast, the Cat Khanh segment is identified as being in a dynamic equilibrium planform (DEP).
This study assessed shoreline recession along four segments of the Phu Cat coastline, utilizing the Bruun model to analyze the effects of climate change and rising sea levels Under the RCP 8.5 scenario, projections indicate that by 2100, the Phu Cat coastline could experience a recession of approximately 7 meters.
This study presents adaptation strategies for Phu Cat district, focusing on three approaches: "do-nothing," "peaceful coexistence," and "proactive defense." The primary recommendation is to integrate erosion concerns into planning by establishing coastal setbacks and stabilizing dunes In An Quang village, where erosion is persistent, the study suggests implementing structural solutions like T-groins Ultimately, a balanced approach combining both green and grey solutions is crucial for long-term effectiveness.
[1] David Eckstein, Vera Kỹnzel, and Laura Schọfer, “Global Climate Risk Index 2021,” Jan 2021
[2] “Vietnam ratifies Paris climate change agreement,” Embassy of the Socialist Republic of Vietnam in Japan https://vnembassy-jp.org/en/vietnam-ratifies- paris-climate-change-agreement (accessed Apr 15, 2021)
[3] P H Tien, T D Thanh, B H Long, and N V Cu, “Main results of research on erosion and accretion in coastal estuaries of Vietnam,” J Mar Sci Technol., vol
Binh Dinh faces significant challenges in addressing riverbank and coastal erosion, as well as sedimentation in its estuaries These environmental issues pose threats to local ecosystems and communities, highlighting the urgent need for effective management strategies The situation requires comprehensive efforts to mitigate the impacts of erosion and sedimentation, ensuring the preservation of Binh Dinh's natural resources and coastal infrastructure.
[5] C J Crossland, D Baird, J P Ducrotoy, and H Lindeboom, “The Coastal Zone
- a Domain of Global Interactions,” in Coastal Fluxes in the Anthropocene, 2005, pp 1–37
[6] Ramsar Convention Secretariat, 2010 Coastal management: Wetland issues in Integrated Coastal Zone Management Ramsar Convention Secretariat, 2010
[7] An L D., Vietnam coastal zone - structure and natural resources Natural
[8] FAO, “Integrated coastal area management and agriculture, forestry and fisheries,” 1998 http://www.fao.org/3/W8440e/W8440e00.htm
[9] B Q Dung and U D Khanh, “Calculation of Vietnam‟s coastline length (mainland) based on topographic map system at scale 1/50,000,” Vietnam J Mar
Sci Technol., vol 16, no 3, pp 221–227, Aug 2016
[10] E H Boak and I L Turner, “Shoreline Definition and Detection: A Review,” J
Coast Res., vol 214, pp 688–703, Jul 2005
[11] F J Anders and M R Byrnes, “Accuracy of shoreline change rates as determined from maps and aerial photographs,” Shore Beach, vol 59, pp 17–26, Jan 1991
[12] “Definitions of coastal terms.” http://www.coastalwiki.org/wiki/Definitions_of_coastal_terms#Beach_face (accessed Apr 16, 2021)
[13] F Cai, X Su, J Liu, B Li, and G Lei, “Coastal erosion in China under the condition of global climate change and measures for its prevention,” Prog Nat Sci., vol 19, no 4, pp 415–426, Apr 2009
[14] A N Strahler, “Hypsometric (area-altitude) analysis of erosional topography,”
Geol Soc Am Bull., vol 63, no 11, p 1117, 1952 h
[15] T H John, “Interpretation of erosional topography in humid temperate regions,”
[16] V V Phai, “Geomorphology of modern central coast of Vietnam (from Ngang Pass to Da Vach cape),” 1996
[17] D J Clarke and I G Eliot, “Mean sea-level and beach-width variation at Scarborough, Western Australia,” Mar Geol., vol 51, no 3, pp 251–267, Apr
[18] B G Thom and W Hall, “Behaviour of beach profiles during accretion and erosion dominated periods,” Earth Surf Process Landf., vol 16, no 2, pp 113–
[19] R McLean and J.-S Shen, “From Foreshore to Foredune: Foredune Development over the Last 30 Years at Moruya Beach, New South Wales, Australia,” J Coast Res., vol 22, no 1, pp 28–36, 2006
[20] K Zhang, B C Douglas, and S P Leatherman, “Global Warming and Coastal Erosion,” Clim Change, vol 64, no 1/2, pp 41–58, May 2004
[21] F Jones, D Kay, R Stanwell-Smith, and M Wyer, “An Appraisal of the Potential Health Impacts of Sewage Disposal to UK Coastal Waters,” Water Environ J., vol 4, no 3, pp 295–303, Jun 1990
[22] M Crowell, S P Leatherman, and M K Buckley, “Historical Shoreline Change: Error Analysis and Mapping Accuracy,” J Coast Res., vol 7, no 3, pp 839–
[23] G Cambers, Coping with beach erosion: with case studies from the Caribbean
[24] C D Woodroffe, Coasts: form, process, and evolution Cambridge University
[25] V M Gornitz, R C Daniels, T W White, and K R Birdwell, “The Development of a Coastal Risk Assessment Database: Vulnerability to Sea-Level Rise in the U.S Southeast,” J Coast Res., pp 327–338, 1994
[26] E R Thieler and E S Hammar, “National Assessment of Coastal Vulnerability to Sea-Level Rise: Preliminary Results for the U.S Atlantic Coast,” U.S Geological Survey, 1999
The study conducted by Dwarakish et al (2009) focuses on assessing the vulnerability of the Udupi coastal zone in Karnataka, India, in relation to future sea level rise Published in the journal Ocean & Coastal Management, this research highlights the potential impacts of climate change on coastal areas, emphasizing the need for proactive management strategies to mitigate risks associated with rising sea levels The findings are crucial for understanding coastal resilience and informing policy decisions aimed at protecting vulnerable regions.
[28] G ệzyurt and A Ergin, “Application of Sea Level Rise Vulnerability Assessment Model to Selected Coastal Areas of Turkey,” J Coast Res., no 56, p 4, 2009
[29] N V Vuong, “Assessment of vulnerability to climate change of people in Phu Cat district, Binh Dinh province,” 2020 h
[30] N M Hung, Shoreline and estuary change in Vietnam 2010
[31] P H Tien, “Forecasting erosion - accretion of coastlines, estuaries and prevention solutions,” Institute of Geography, Jan 2005
[32] N Mimura, Ed., Asia-Pacific Coasts and Their Management: States of Environment, vol 11 Springer Netherlands, 2008
[33] L P Trinh, B H Long, L D Mau, and P B Trung, “Specific hydro-dynamic structures induced erosion-accumulation in the South-central coastal of Vietnam,” J Mar Sci Technol., vol 3, pp 15–30, Nov 2011
[34] D M Duc, Ed., Research on accretion in coastal estuaries of Binh Dinh province Science and technics publishing house, 2017
[35] D T Quynh, “Research on the current status and causes of accretion in some coastal estuaries in Binh Dinh province,” Vietnam National University, 2017
[36] K Yasuhara, M Tamura, T C Van, and D M Duc, “Geotechnical Adaptation to the Vietnamese Coastal and Riverine Erosion in the Context of Climate Change,” Geotech Eng J SEAGS AGSSEA, vol 47, no 1, Mar 2016
[37] Hao V., “Preventing erosion of the South-Central Coast: Lesson 1 - Current status and causes,” Jul 17, 2018 https://baotintuc.vn/news- 20180717114944524.htm (accessed May 28, 2021)
[38] “Binh Dinh: Worry about the sea „swallowing‟ people‟s houses,” Natural Resources and Environment Newspaper https://baotainguyenmoitruong.vn/binh- dinh-noi-lo-bien-ngoam-nha-dan-238500.html (accessed May 28, 2021)
On January 25, 2019, Binh Dinh province issued Decision 296/QD-UBND, which approves the establishment of a protection corridor for coastal areas This decision aims to safeguard the coastal environment and ensure sustainable development in the region For more details, visit the official document at [Thukyluat.vn](https://thukyluat.vn/vb/quyet-dinh-296-qd-ubnd-2019-khu-vuc-phai-thiet-lap-hanh-lang-bao-ve-bo-bien-tinh-binh-dinh-69977.html).
[40] Binh Dinh province, “Decision 4383/QĐ-UBND on approving the width and boundaries of the coastal protection corridor of Binh Dinh province.” Nov 25,
2019 [Online] Available: https://thuvienphapluat.vn/van-ban/Tai-nguyen-Moi- truong/Quyet-dinh-4383-QD-UBND-2019-Chieu-rong-ranh-gioi-hanh-lang-bao- ve-bo-bien-tinh-Binh-Dinh-432492.aspx
[41] “Land and people,” Phu Cat District People’s Committee https://phucat.binhdinh.gov.vn/vi/about/Manh-dat-con-nguoi.html (accessed Mar
The study by Duc et al (2021) explores sediment transport trends and the stability of cross-sections in a lagoonal tidal inlet located on Vietnam's Central Coast Published in the International Journal of Sediment Research, the research highlights key findings on the dynamics of sediment movement and the implications for coastal management, emphasizing the importance of understanding these processes for maintaining the ecological balance of tidal inlets.
[43] Vietnam Institute for Water Resources Research, “Research on dealing with black mud at Quy Nhon beach and solutions,” 2018 h
[44] Phu Cat district, “Report on the socio-economic situation in 2019; socio- economic development tasks in 2020,” Dec 2019
[45] H L T Thuy, “Research on the level and trend of changes of basic climate factors and phenomena in the Central Central region.”
[46] MONRE, “Climate Change and Sea Level Rise scenarios for Vietnam 2016,”
[47] DJI, Phantom 4 Advanced - Quick Start Guide Accessed: Apr 24, 2021
[Online] Available: https://dl.djicdn.com/downloads/Phantom_4_Advanced/20170413/Quick_Start_ Guide/Phantom+4+Advanced+plus_Quick+Start+Guide_V1.0_EN.pdf
[48] DJI, “ DJI GS Pro,” App Store https://apps.apple.com/us/app/dji-gs- pro/id1183717144 (accessed Apr 24, 2021)
[49] A Bryman, S Becker, and J Sempik, “Quality Criteria for Quantitative, Qualitative and Mixed Methods Research: A View from Social Policy,” Int J Soc Res Methodol., vol 11, no 4, pp 261–276, Oct 2008, doi:
[50] W M Tellis, “Application of a Case Study Methodology,” p 21
[51] “Munsell colour chart.” Accessed: Apr 24, 2021 [Online] Available: https://soils.uga.edu/files/2016/08/Munsell.pdf
[52] J R C Hsu and C Evan, “Parabolic Bay shapes and applications,” Proc Inst Civ Eng., pp 557–570, 1989
[53] H Xu, “Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery,” Int J Remote Sens., vol 27, no 14, pp 3025–3033, Jul 2006, doi: 10.1080/01431160600589179
[54] K V Singh, R Setia, S Sahoo, A Prasad, and B Pateriya, “Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level,” Geocarto Int., vol 30, no 6, pp 650–
[55] G Sarp and M Ozcelik, “Water body extraction and change detection using time series: A case study of Lake Burdur, Turkey,” J Taibah Univ Sci., vol 11, no 3, pp 381–391, May 2017, doi: 10.1016/j.jtusci.2016.04.005
[56] D Nandi, R Chowdhury, J Mohapatra, K Mohanta, and D Ray, “Automatic Delineation of Water Bodies Using Multiple Spectral Indices,” vol 4, pp 498–
In their 2019 study, A Wicaksono and P Wicaksono conducted a geometric accuracy assessment of shorelines in Jepara Regency, utilizing Landsat 8 OLI imagery from 2018 The research focused on various coastal physical typologies and employed NDWI, MNDWI, and AWEI transformations to enhance shoreline delineation accuracy The findings, published in the Geoplanning Journal of Geomatics and Planning, underscore the significance of remote sensing techniques in coastal management and environmental monitoring.
The study by Kaliraj, Chandrasekar, and Magesh (2014) investigates the effects of wave energy and littoral currents on shoreline erosion and accretion along the south-west coast of Kanyakumari, Tamil Nadu Utilizing the Digital Shoreline Analysis System (DSAS) and geospatial technology, the research provides valuable insights into coastal dynamics, highlighting the interplay between natural forces and shoreline changes The findings contribute to understanding coastal erosion and management strategies in the region.
[59] K Nassar, W E Mahmod, H Fath, A Masria, K Nadaoka, and A Negm,
“Shoreline change detection using DSAS technique: Case of North Sinai coast, Egypt,” Mar Georesources Geotechnol., vol 37, no 1, pp 81–95, Jan 2019, doi: 10.1080/1064119X.2018.1448912
[60] E A Himmelstoss, R E Henderson, M G Kratzmann, and A S Farris,
“Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide,” 1179,
[61] N A Thinh and L Hens, “A Digital Shoreline Analysis System (DSAS) applied on mangrove shoreline changes along the Giao Thuy coastal area (Nam Dinh, Vietnam) during 2005-2014,” Vietnam J Earth Sci., vol 39, no 1, pp 87–96,
[62] USAID, Adapting to Coastal Climate Change: A Guidebook for Development Planners 2009
[63] Southern Institute for Water Resources Planning, “Reviewing the master plan on sea dike system from Quang Ngai to Kien Giang,” 2017
A study conducted by M T Nhuan et al evaluates the adaptive capacity of coastal urban households in Lien Chieu District, Da Nang City, Vietnam, in response to climate change The research highlights the challenges faced by these households and assesses their strategies for adaptation This assessment is crucial for understanding how urban communities can effectively respond to the impacts of climate change, ensuring resilience and sustainability in coastal regions.