The dynamic coast of Bangladesh is constantly deformed and reshaped by sediments carried by the three mighty river systems: the Ganges, Brahmaputra, and Meghna rivers. While there is a net accumulation of sediment (delta building) at the river mouth (Broadus, 1993; Amin, 2008), a substantial amount of sediment is entrained by waves and currents. Sediment replenishment plays an important role in deltaic stability by hindering natural compaction and subsidence (Dixon et al., 2006) and is thus considered one of the main factors in this coastal zone for shoreline changes caused by sea level rise (Amin, 2008; Emran et al., 2019). Along with a gentle slope into the Bay of Bengal, this wide sandy beach area has patches of mangrove trees behind it which withstand the perpetual forces of the tides. In addition, population dynamics (Ericson et al., 2006) of this coastal area and how the shoreline change may affect livelihoods (Mukherjee et al., 2019) are important considerations.

Kuakata, situated on the central coast of Bangladesh on the western side of the Meghna estuary at the sedimentary outlet of the Padma, Meghna, and Brahmaputra, is selected as the study area because of the dynamic nature of its shoreline and its economic and cultural significance. The convex shape of the Kuakata coast (Figure 1) invites the significant, simultaneous impact of erosion and accretion from both fluvial and marine processes. About 41 percent of the cyclones originating in the Bay of Bengal travel through this funnel-shaped central region each year, such as Cyclone Sidr in 2007 (Ikeuchi et al., 2017), which makes the central coast of Bangladesh vulnerable to storm surge (Paul and Rahman, 2006). A complete analysis of processes that shape the landscape in this tidal-to-fluvial transition zone of Bangladesh is beyond the scope of this research but is detailed effectively elsewhere (Goodbred and Kuehl, 1999; Wilson and Goodbred, 2015; Bomer et al., 2019).

From a human-environment-interactions perspective, Kuakata is an economically active zone that offers access to fisheries and commerce, proximity to rich agricultural lowlands, and recreational opportunities, which form the basis for economic opportunities for a large community. The percentages of jobs in agriculture, fishing, commerce, service, agricultural laborer, wage laborer, and “other” in this region are approximately 45.6, 5.7, 10.0, 3.6, 18.9, 4.6, and 11.7, respectively (Bangladesh Bureau of Statistics, 2009). While 19 percent of Kuakata’s land is classified as agricultural, this percentage is decreasing gradually, as the land is in high demand for commercial development, particularly by the recently emerging tourism industry. The inland area of Kuakata is protected from tidal waves by an earthen flood embankment, which was constructed few hundred meters away from the shoreline (Rahman et al., 2013). The extension of the embankment/levee and newly created roads has increased this demand further.

The shoreline change is detected over an approximately four-decade interval by comparing satellite imagery from 12 January 1989, 19 December 2003, and 30 January 2010 using Landsat Thematic Mapper (TM) imagery, and 11 February 2020 using Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) satellite images, all at 30 m resolution. These dates are selected to enhance shoreline delineation by balancing the needs for clear sky cover, low tides, and maintenance of a similar time in the dry season, all amid the limitation of a once-in-sixteen-day flyover by the satellite sensor (United States Geological Survey (USGS), 2021). For unavoidable cases of tidal interference, tidal data are used to verify the tidal condition at the acquisition time, and the exact shore line position is determined by adding or subtracting the tidal data. Although several tidal stations managed by the Bangladesh Water Development Board exist, none with reliable, continuous records are located on Kuakata. Mirzaganj (Station ID—SW19), located ∼61.0 km northwest from the study area, is the nearest tidal station with a continuous record of the daily semi-diurnal tidal conditions, ranging from 0.01 m at neap tide to 2.04 m at spring tide at the Barisal-Buriswar River; its data are applied to approximate the tidal condition at the image acquisition time.

Band Combination (BC; Dwivedi and Rao, 1992; Sutikno et al., 2020), Ratio Transformation (RT; Mavraeidopoulos et al., 2019), Normalized Difference Vegetation Index (NDVI; Carlson and Ripley, 1997; Huang et al., 2021), and Normalized Difference Water Index (NDWI; Gao, 1996; Su et al., 2021) algorithms are often used to extract the shoreline from the land/water boundary. Among the four methods of shoreline detection, BC—a method of combining bands with wavelengths of the electromagnetic spectrum sensitive to shoreline detection, is selected primarily because of its higher accuracy of boundary-matching with the already georeferenced, cross-checked Local Government Engineering Department (LGED) maps. For the BC method, combining the TM’s Bands 4 (0.76–0.90 μm), 5 (1.55–1.75 μm), and 7 (2.08–2.35 μm), and Bands 5 (0.85–0.88 μm), 6 (1.57–1.65 μm), and 7 (2.11–2.29 μm) for OLI and TIRS, provides the best result for shoreline detection (United States Geological Survey, 2020). This is because these bands operate in the best spectral region to emphasize land-water contrast, distinguishing water bodies in a darker tone from other land use categories in a lighter tone. This sets a sharp contrast between the land-water boundary, as for both Landsat Image types Band 7 spectral has a strong water absorption region and a strong reflectance region for soil and rock, thereby causing water bodies to appear in dark tones and exposed land surfaces to appear in bright tones. Thus, the combination of these three bands results in the most accurate and distinct shoreline boundary. A minimal percentage of inaccuracy in boundary detection may be caused by diurnal tidal variations, vegetation coverage, and indistinguishable land-water area in Landsat satellite images.

The accuracy of the extracted shorelines is verified with georeferenced standard maps collected from the LGED of Bangladesh. The position is also cross-checked with the recorded ground control point (GCP) data, which are used for quality control. Also, 2010 is considered as the reference year to detect shoreline change.

The GIS and RS tools, Integrated Land and Water Information System (ILWIS) and ArcGIS^® Desktop, are used for image processing, geometric correction, visual interpretation, and manual digitization to develop a vector data series for each of the images, to compare and measure the changes. The vector line dataset enables the comparison of shoreline shift over the years and vector polygon data series facilitates measurement of the rate of shoreline accretion and erosion using GIS tools. Application of GIS and RS is also required for ground truthing, which is done by conducting field verifications and GCP data collection using Global Positioning System (GPS) for more accurate measurements. The RS-GIS technique tests and quantifies the information collected from PRA tools.

Most research on shoreline change is directed toward using technical tools and applications rather than incorporating the human perceptive. PRA (Chambers, 1994; Kukielka et al., 2016), a growing family of research methods, involves a series of qualitative multidisciplinary approaches to learning about local-level conditions and individual perspectives based on first-hand knowledge, experiences, and intergenerational accumulated wisdom. The PRA tools described below were implemented in 2010 to elucidate the major causes and impacts of coastline shifting associated with the different natural settings and livelihoods, including forest, agriculture, aquaculture, fishing, fish drying, sea salt production, and trading. The PRA employed here relies on field observations and group meetings with communities and stakeholders, such as fisherman, farmers, small business owners, and tourism-related employees. More specifically, PRA verifies the results through a transect walk (Dooley et al., 2018; Schäffler et al., 2021), timeline (historical mapping) analysis (Mueller et al., 2010; Tomlinson et al., 2018), cause and effect diagram (Holme and Chalauisaeng, 2006; Saja et al., 2021), key informant interview (KII; Chenais et al., 2015; Balgah, 2016; Nicholson and Valentine, 2019; Dureab et al., 2021; Roothaert et al., 2021), and focus group discussion (FGD; Shamsuddin et al., 2007; Ng et al., 2021). These tools emphasize the following questions: What is the perception about shoreline change along the coast of Kuakata? What is the rate of this change? Is the face of change (i.e., erosion or accretion) happening similarly along the entire coast? What natural and/or anthropogenic features are affecting the rate of change? How have the local people adopted their livelihood to this change? What is the impact of this change?

The main aim of the transect walk is to observe land use from the 30 m buffer zone of the Bay of Bengal to 500 m inland. Six transect walks were conducted in the central and western-central parts of the island while avoiding the mangrove forests and sand dune piles. The land use pattern is generalized to a cross section profile, with the help of pre-downloaded Google imagery, GPS, and local knowledge, to convey the impact of shoreline change on coastal land use and livelihood patterns.

The timeline analysis is designed to appraise the historical change in people’s observations. This analysis facilitates acquisition of substantive qualitative information regarding the chronology of shoreline change in a short amount of time across a remote area poorly covered by PRA study. The timeline analysis is based on the assumption that to understand past events it is necessary to identify the shoreline location over time, cause of changes, and impacts due to the change. Twelve people, in groups of six, participated in drawing the relative shoreline positions over time, from that provided to them in a timeline table. They then offered their opinions on the causes and impacts of the changes. The majority (i.e., four to five from each group) of the participants were fishermen who live near the coast. Based on the common responses from the two groups, numbers in the table have been reported.

The cause and effect diagram is also implemented to assess causes of changes and their impacts, based on the participant opinions. It involves a visual tool to help the participants to compare the relative importance of the causes and effects due to shoreline change in a tree-like diagram where the consequences (effects) of shoreline change are represented by the trunk of the tree diagram, while physical mechanisms (causes) which result from those consequences by accelerating shoreline change are shown as roots. Three different groups (one with ten fishermen, another group of ten farmers, and six small businessmen associated with tourism activities) participated separately to complete the tree diagram.

The purpose of the KII is to assign local specification of the consequences and investigate common impacts and adaptation measures. Relying on the list of issues found from the transect walk, timeline analysis, and cause and effect diagram, a descriptive question structure was formed to allow free flow of information for collecting in-depth and spontaneous responses from the two key interviewees about the shoreline change that they have observed over the years and its impact on the community’s livelihood. The key informants are from two different backgrounds who were interviewed individually, after obtaining their written consent, to determine their perceptions of the causes of shoreline change and its impacts on local people. At the time, one of the interviewees was a surveyor with 35 years of professional experience regarding land use survey and land use change. Another key informant was a land developer and was still working there for a land reclamation project. Notes taken during the interview process were evaluated and elaborated shortly afterward.

Finally, one group of ten fishermen and a separate group of ten farmers participated in two FGDs, as it became apparent that they are the primary victimized occupational groups from the change of shoreline. They were asked whether they have noticed coastal accretion or erosion and the effects or impacts of this land change.

The Kuakata shoreline has shifted inward (Figure 2). The central and eastern regions have a retrograding shoreline on a net basis, and the western part of the western region of the island has an elongating shoreline, likely owing to fluvial deposition. The BC method reveals that erosional activity is more prominent than accretional activity. The western horn of the island is elongating because of accretion. In the central and eastern coast both erosional and accretional processes have taken place to modify the coastline. The shoreline change implies that Kuakata’s seaward coast is dominated by the effects of erosional activities and/or sea level rise. Approximately 13.59 km² of land has been lost, and 3.27 km² land has been gained since 1989, resulting in a net loss of 10.32 km² of land over the last four decades. The fastest accretion rate across the study period is for the eastern zone, at 0.05 km² yr^–1 (Table 1), despite a net shoreline retreat. The central zone has the most rapid erosion rate, at 0.19 km² yr^–1 and the strongest net rate of shoreline retreat (Table 1), likely because of less fluvial impact and marine influence.

Comparison between the range of years 1989–2003, 2003–2010, and 2010–2020 provides a more detailed perspective. The erosion rate from 2003 to 2010 (0.76 km² yr^–1) exceeded that from 1989 to 2003 (0.46 km² yr^–1) and 2010 to 2020 (0.18 km² yr^–1). At the same time, the accretion rate was less from 2003 to 2010 (0.07 km² yr^–1) than from 1989 to 2003 (0.13 km² yr^–1) and 2010 to 2020 (0.09 km² yr^–1). Thus, land loss from 2003 to 2010 exceeded that from 1989 to 2003 and 2010 to 2020. For the entire range of years (i.e., from 1989 to 2020), the erosion rate was 0.44 km² yr^–1, and the rate of accretion was 0.11 km² yr^–1. These relationships are depicted graphically by region in Figure 3, with specific locations where net accretion and erosion occurred during the sub-intervals shown in Figure 4. Only very small coastal areas, mostly in the west, have net accretion, with net erosion elsewhere. The results corroborate those of other studies (Shibly and Takewaka, 2012; Bushra, 2013; Islam et al., 2013; Mitra et al., 2013; Rahman et al., 2013) which concluded that erosion dominates over accretion in this region. For example, Islam et al. (2013) found that from 1973 to 2012 the erosion rate was 0.29 km² yr^–1, and the rate of accretion was 0.09 km² yr^–1 in the Kuakata.

In addition to the satellite image study and geospatial interpretation, The PRA tools described in the previous sections provide new information.

Figure 5 summarizes the results of the transect walk. According to the local people, the establishment of embankments since 1966 and the presence of fluvial tidal creeks, canals, and sand dunes have important roles in maintaining the stable shoreline in the central zone and accretion in the eastern zone. The locals believe that the western part is protected by a newly formed extension of the embankment which was built after Cyclone Aila destroyed the previous one in 2009, and even though erosion still persists, the rate is less than in years before embankment construction. The satellite imagery confirms this observation, as for the western zone over the 2010–2020 period, erosion was 0.46 km², but over the 1989–2003 and 2003–2010 periods it was 2.33 km² and 1.63 km², respectively. During the transect walk, the local community confirms that among all major economic activities fishing and tourism were affected most by shoreline erosion.

The timeline analysis reveals that except for the Cauer Char (L8) area (Figure 6), which is situated at the eastern side of the landmass, the shoreline has retreated inland substantially (Table 2). This finding corroborates the results from the satellite imagery analysis. According to the local people, at Lebur Char (L1) and Khajura (L2), the shoreline had been reduced by about 7–8 km from 1989 to 2003 and about 2.5 km from 2003 to 2010. The Computer (L3) and Mirabari (L4) areas had shown nearly the same amount of erosion for 1989–2003 and about 1.5–2.5 km of erosion for 2003–2010. In comparison to the above area, the Ghatla (L5), Jhauban (L6), and Gangamoti (L7) locations had less shoreline erosion, which was about 5 km for the years 1989–2003 and 1–7.5 km for 2003–2010. Though the Cauer Char (L8) did not exist in 1989, its establishment was prominent in 2003, and it became extended by about 2 km from 2003 to 2010.

Both RS-GIS and PRA outcomes (Tables 1, 2) establish that in the western (Lebur Char, Khajura, and Computer) and central (Mirabari, Ghatla, and Jhauban) zones, erosional activity is dominating over accretion. The concave shape of the coast also explains why the central zone is more responsive to these factors. In the eastern zone (Cauer Char), accretion is dominating. These findings corroborate those of Rahman et al. (2013), who found that from 1973 to 2010 the western part of Kuakata beach suffered an average erosion of 350–450 m. Table 2 shows that, on average from 1989 to 2010, the erosion rate in Lebur Char, Khajura, and Computer is approximately 500 m yr^–1.

The cause and effect diagram (Figure 7) depicts the main causes of shoreline change in that locality, as expressed by community members. Most prominent among the community-identified causes are marine and climatic actions for shoreline erosion, including tide, current, wave actions, tidal flood, cyclone, storm surges, and sea level rise. A few people mentioned that in some parts of Kuakata, accretion activities caused by sedimentation by fluvial and marine actions and landform structure are occurring. This accretion occurs along the low gradient and gentle slope of the continental shelf and is enhanced by construction of the embankment and polders at the coastal boundary. Landfilling at the shoreline boundary and destruction of sand dunes, which accelerate the wave/wind action inland, are also the causes for shoreline modification at the coastal boundary. Respondents concur that the shoreline is mainly retreating, but there are some accretional activities in some parts of the lands where the fluvial and marine processes have deposited sediments over the last 20 years. The main causes of shoreline change and their subsequent effects are listed in Table 3.

The key informant who was a surveyor expressed that poor coastal management, monitoring, and maintenance are among the causes of coastal land degradation and land loss, rather than natural processes. The informant who at the time was a land developer expressed that by being a famous tourist spot in Bangladesh, land reclamation has accelerated over the last 30 years, and that initially no one monitored the process of land cover change for commercial purposes (i.e., building hotels, resorts, and shopping complexes). That same informant noted that the excavation of sand from the sea was also destroying many dune fields. The informant also noted that these are common occurrences for the development of many hotels along the beachside. Such activities ultimately result in disruption of the natural processes and acceleration of coastal erosion. Both key informants agree that the lack of planning and proper implementation of laws and legislation for coastal management and maintenance are responsible for this coastal land degradation. Although the government has undertaken some initiatives to maintain this famous tourist spot, land reclamation by the developer and the development of high-rise buildings continues.

According to the fishermen in the FGD, marine waves, ocean currents, and tides are the major causes of shoreline change. The participants felt that these regular phenomena are more prevalent during the monsoon season, which causes land loss and shoreline erosion. In addition to these regular phenomena, the recent increase in the frequency of coastal cyclones and in the intensity of storm surge (Bushra, 2016; Bushra et al., 2019) and tidal flooding have accelerated the erosional process along the coast. As these phenomena destroy the vegetation coverage, sand dune fields, and sand piles along the coast, the erosional effects of regular waves, currents, and tides are exacerbated. Because the seasonal winds typically blow from the southwest, the erosional activities are more prominent along the west coast of Kuakata. Thus, the fishing community has less buffer zone around the seashore for their fishing activities.

The farmers noted that as the sea encroaches on their homeland, they themselves become more dependent on shrimp cultivation rather than cropping. According to the respondents, saltwater intrusion complicates the problem even more. As the sea is advancing, windblown sand from the beach has become so abundant on their fertile land that it can become uncultivable. The farmers who have land near the coast sometimes face enormous pressure from land developers and are sometimes swindled into selling their land to occupiers. They have also mentioned that the establishment of the embankment has acted as a barrier to many tidal creeks and canals inland, causing flow diversion or discontinuous and reduced flow sedimentation. These problems invite further unobstructed encroachment by the sea.

While fluvial processes contribute considerably to seaward shoreline advancement through delta building, embankment/levee construction has hindered that process. On the other hand, establishment of the embankment reduces coastal erosion from waves, tides, ocean currents, and storm surges, thus protecting the coast from marine processes. It is difficult to evaluate which processes—fluvial or marine—contribute more toward coastal land formation and therefore the shoreline change. Not surprisingly, farmers emphasized the fluvial processes, which bring sediments to nourish their agricultural lands, while the fishermen are more concerned about marine processes.