Geospatial Analysis of Shoreline Changes and their Socio-Economic Implications for Littoral Communities in Effiat, Akwa Ibom State, Nigeria

system and feature-type requirements of the shoreline files were corrected. The multiple shapefiles of the shorelines were appended into a single feature class using the Append tool from ArcToolbox. For verification, GPS control points were used to evaluate the extracted shorelines. Statistical analysis was carried out by fixing transect lines along the shoreline. The starting points between the transect lines were determined by the baseline. 3. Results Shoreline Position from 1989 - 2019 The multi-temporal Landsat satellite data were used to extract shorelines from 1989 to 2019. The shorelines were extracted through supervised classification and NDWI. The shorelines are represented in different colors. The lines indicate the shoreline positions for the different periods, as shown in Figure 2. The baseline is the starting point for all transects and is therefore one of the most important components of the shoreline change analysis process. Its shape and relative location to the shorelines impact the rate calculations determined by transect-shoreline intersections. The baseline can be created either onshore or offshore, or as a combination of both, and can be manually edited based on the study area. The baseline was created using DSAS. For this study, the offshore baseline was used, and perpendicular transects were cast at an interval of 10 m. Figure 2: Shoreline Extracted for the four Epochs IIARD International Journal of Geography & Environmental Management 3.2 Determination of the Rate of Change in Terms of Accretion and Erosion along the Shoreline The Digital Shoreline Analysis System was used to calculate the endpoint rate. The EPR is measured by determining the distance between the oldest and most recent shorelines in the data and dividing it by the number of years between them. The EPR is reported in meters per year (m/yr), with positive values indicating accretion and negative values indicating erosion. Net shoreline movement is the actual distance between the oldest and youngest shorelines for each transect laid perpendicular to the shorelines. As shown in Figure 3, the results were categorized into five (5) color variations indicating erosion and accretion rates. The lowest value is shown in red, representing the most severe erosion. Green represents the highest value of accretion. The intermediate categories are moderate erosion, neutral processes, and moderate accretion, represented by orange, yellow, and light green, respectively. A high-resolution image was used as a base map, and the statistical results were overlaid on it to underscore the severity of the situation. Table 2 presents the statistical values of Net Shoreline Movement for the four (4) epochs. The values were generated with the aid of the Digital Shoreline Analysis System , an extension of ArcGIS software. The values show the segments of the shoreline affected by erosion or accretion. The results show that Segments C and D were the most erosive. Figure 3: Shoreline change analysis of the study area for the four epochs. Figure 3: Shoreline Changes Analysis of the Study Area for the four Epoch IIARD International Journal of Geography & Environmental Management Table 2: Statistical Analysis of Shoreline Movement Strata Period ENDPOINT RATE (m/yr) Accretion Erosion Net Shoreline Movement (m) Description A 1989 64.6 -112.4 -47.8 High erosion 1999 90.56 -101.23 -10.67 Moderate erosion 2009 87.45 -89.4 -1.95 Very low erosion 2019 91.21 -86.89 4.32 Accretion B Period Accretion Erosion Net Shoreline Movement 1989 56.5 -66 -9.4 Moderate erosion 1999 96.23 -94.2 2.03 Accretion 2009 85.3 -71.2 14.1 Moderate accretion 2019 78.4 -98.3 -19.9 High erosion Period Accretion Erosion Net Shoreline Movement C 1989 66.4 -91.8 -25.4 High erosion 1999 69.6 -43.2 26.4 High accretion 2009 45.3 -89.4 -44.1 High erosion 2019 48.4 86.3 -17.9 High erosion Period Accretion Erosion Net Shoreline Movement D 1989 79.6 -93.8 -14.2 Moderate erosion 1999 62.3 -83.2 -20.9 High erosion 2009 45.3 68.3 -23 High erosion 2019 66.7 -81.3 -14.6 Moderate erosion Source: Fieldwork 2021 IIARD International Journal of Geography & Environmental Management 4. Discussion Rate of Change in Shoreline from 1989 to 2019 Segment A In Segment A, the shoreline was observed to be stable, as indicated by the yellow perpendicular lines; neither erosion nor accretion was observed, except in 1989 and 1999. The Focus Group Discussion revealed that this segment experienced remarkable erosion in 1989 and 1999. However, erosion activity has reduced due to the construction of seawalls in the study area. Seawalls are large coastal protection structures built using different construction materials, such as rubble mounds, granite masonry, or reinforced concrete. Segment B In 1989, the Net Shoreline Movement was -9.4 m, representing moderate erosion in Segment B, while in 1999 the recorded NSM was 2.03 m, indicating accretion. Moderate accretion was also observed in 2009, with a recorded value of 14.1 m. According to Uwem et al. (2014), this is usually triggered by human activities at the river estuary. However, no significant human footprint was observed in the study area during field data gathering. In 2019, the NSM value recorded was -19.9 m, representing high erosion. Olutoyin et al. (2011) reported that global warming causes sea-level rise and makes storm patterns more energetic. Therefore, it could be interpreted that the increased erosion activity in Segment B in 2019 is partially due to climate change and sea-level rise factors. This also supports the work of Cowell and Thorn (1994), who identified that shoreline changes largely depend on geology and geomorphology (rocky or sandy coasts), the nature of tidal waves impacting the shoreline, sea-level rise, and sediment transported by longshore currents, among other factors. Segment C In 1989, the Net Shoreline Movement value was -25.4 m, representing high erosion within the segment. In 1999, the segment showed significant accretion, with an NSM value of 26.4 m. In 2009 and 2019, the NSM values were -44.1 m and -17.9 m, respectively. The rate of change here is significant when compared to other places. This is because human activity around the segment is relatively high. The presence of oil companies such as Addax Petroleum Development Nigeria Limited, Oriental Energy Resources Limited, and Moni Pulo Nigeria Limited, among others, is partially responsible for the erosion due to their onshore drilling activities. Human activities such as oil exploration and sand dredging within the river estuary may also indirectly cause additional land losses by changing water circulation patterns, decreasing sediment supply, and increasing water depths (https://pubs.usgs.gov/of/2003/of03-337/excavation.html). For example, mining large volumes of shells from estuaries removes natural breakwaters, such as reefs and marine grass flats, and increases wave energy along the shoreline segments. Segment D In 1989, the NSM value was -14.2 m, while that of 1999 was -20 m, indicating moderate and high erosion of the segment, respectively. Erosion activity increased in 2009 at a rate of -23 m, and a slight reduction was recorded in 2019, with a value of -14.6 m. In this segment, erosion activity was generally significant. The reasons given in Segment C also apply, as the oil companies’ activities affect both segments. IIARD International Journal of Geography & Environmental Management Effects of Shoreline Change on the Socio-Economic Characteristics of the Study Area Income Level Over 50% of the respondents in Strata A earned between ₦41,000 and ₦60,000, 30% earned between ₦61,000 and ₦80,000, 8% earned between ₦21,000 and ₦40,000 and above ₦80,000, respectively, and 4% earned between ₦1,000 and ₦20,000. In Strata B communities, 42% of the respondents earned between ₦61,000 and ₦80,000, 36% earned between ₦41,000 and ₦60,000, and 6% earned between ₦1,000 and ₦20,000, ₦21,000 and ₦40,000, and above ₦80,000, respectively. The reverse was observed in Strata C and D, where income distribution across the communities declined. Over 36% of the respondents earned between ₦21,000 and ₦40,000. According to the respondents, the decline in income is partially attributed to disturbances to fishing activities due to shoreline changes. From the viewpoint of discussants during the Focus Group Discussion , crude oil pollution was also responsible for the decline in fish catch and income levels. Fishing was observed to be the major source of income in the study area, as most income was derived from fishing activities. Impact on Freshwater Resources The direct influences of sea-level rise on freshwater resources come principally from seawater intrusion into surface waters and coastal aquifers, further encroachment of salt water into estuaries and coastal river systems, more extensive coastal inundation, and higher levels of sea flooding, increases in the landward reach of sea waves and storm surges, and new or accelerated coastal erosion (Hay and Mimura, 2005). The Focus Group Discussion also confirmed that freshwater resources were under threat due to shoreline changes. According to Hay and Mimura (2005), as sea levels rise along the coasts, saltwater can move onto the land. This is known as saltwater intrusion. They explained that it occurs when storm surges or high tides overtop low-elevation areas. In another explanation, it occurs when saltwater infiltrates freshwater aquifers and raises the groundwater table below the soil surface. Effect on Settlement and Other Infrastructure The respondents were certain that storm surges were responsible for the physical damage to settlements and infrastructure along the shoreline. The severity of coastal flooding depends on a combination of factors. These include the geomorphology of the coastal area; the bathymetry; how any fringing reefs can dissipate wave energy; and the topography of the impact area, including whether it is low-lying and flat, broad or narrow, or how steeply the land rises. Another factor is the extent to which human activities have altered coastal ecosystems, including how degraded the reef ecosystems are, how intact the dune fields are, and whether mangrove and swamp areas have been filled in and built over (Cashman et al., 2017). As mentioned during the Focus Group Discussion, the impact is much more severe during the rainy season. This could also result in internal displacement and relocation of people living within particular segments of the shoreline, as well as increased outward migration (Cashman et al., 2017). Awareness of the Problem The littoral communities showed reasonable awareness of the key physical environmental changes along the coastline, such as shoreline erosion due to sand harvesting, submergence of coastal lands, IIARD International Journal of Geography & Environmental Management intrusion of seawater into near-shoreline freshwater bodies, and breakage of coral beds and/or rocks for use in construction. For instance, many of the respondents (88%) across all strata, including fishermen, identified these changes and their disastrous results. The Focal Group Discussion revealed some of the socio-economic impacts related to shoreline changes as follows: 1. Notable physical changes along the shoreline, especially on the beaches. In some segments, the beaches have grown in terms of sand deposits, while in others, they have lost sand; 2. Disruption of education 3. Increased domestic tension and psychological conditions 4. Portions of the shoreline with vegetation were not eroded; and 5. Physical damage to buildings and other local infrastructure, such as jetties. 5. Conclusion and Recommendations Conclusion Based on the outcome of this study, it is concluded that there was significant change in the shoreline from 1999 to 2019. The observed trend is similar to that of other parts of the Niger Delta region, especially portions with the same geomorphological characteristics. Change detection was conducted using multi-temporal Landsat satellite data from 1989, 1999, 2009, and 2019. A survey technique was also used to obtain socio-economic data on the area. The overall results of the image extraction showed that the shoreline will continue to change in response to hydrographic dynamics and processes such as waves, tides, currents, and sea level, as well as anthropogenic activities such as dredging and deforestation. The changes occurred in the form of accretion or erosion, depending on the processes acting on the shoreline. The accretion rate varied between 4.32 m and 26.14 m, while the erosion rate ranged from -1.95 m to -42.8 m. Furthermore, this study revealed diverse impacts of shoreline changes on the socio-economic status of the littoral communities, including a decline in fishing activities and income levels, physical damage to buildings and other local infrastructure, and saltwater intrusion, among others. Recommendations Based on the outcome of this study, the following recommendations are made: 1. Regular assessment and monitoring of the shoreline should be conducted to model the scenario and identify safe zones for effective adaptation and mitigation measures for the littoral communities. 2. Awareness should be created on the effects of shoreline changes on local communities. 3. Existing legislation on the protection of the coastal environment should be enforced.