Long‐term and short‐term analysis of shoreline change and cliff retreat on Brazilian equatorial coast

• Published in: Earth surface processes and landforms 2023-11, Vol.48 (14), p.2987-3002
• Main Authors: Leisner, Melvin Moura, Paula, Davis Pereira, Alves, Deivid Cristhian Leal, Guia Albuquerque, Miguel, Holanda Bastos, Frederico, Vasconcelos, Yan Gurgel
• Format: Article
• Language: English
• Subjects: Aerial photography; Beaches; beach–cliff system; Cliffs; coastal cliffs; Coastal erosion; Coastal management; Coastal zone management; Erosion processes; Mapping; Photogrammetry; remote sensing; Satellite imagery; Shoreline changes; Shorelines; Statistical analysis; Statistical methods; Stochasticity; Time; UAV survey; Unmanned aerial vehicles
• ISSN: 0197-9337; 1096-9837
• DOI: 10.1002/esp.5668

Assessing historical changes in the shoreline and retreat of cliffs is essential for understanding the evolution and behaviour of specific coastal systems. The present study focused on shoreline changes and cliff base retreat trends at different time scales (annual/decadal) along a 680‐m stretch of Pacheco Beach (Caucaia, Northeast Brazil), which are characterized by coastal erosion and mass movements that have posed risks to residents and visitors to this beach. Shoreline position data were obtained through images collected by satellites and field campaigns for precision mapping through unmanned aerial vehicle (UAV) photogrammetry. The spatiotemporal variations of the shoreline were acquired through an extension of the ArcGIS Digital Shoreline Analysis System (DSAS) and the linear regression rate (LRR) statistical method that reflects the variations that have occurred in the coastal segment. The long‐term results show constant erosion patterns in the study area, with a shoreline retreat of −31 m in the last 17 years at an average rate of −1.8 m/year. In the short term, the average rate of retreat between May 2021 and Jan 2022 was −2.9 m, indicating that 88.78% of the evaluated section was in a continuous process of erosion. Several factors and processes cause the short‐term rates to be more severe than historical rates, demonstrating the stochastic nature of the Pacheco Beach cliff system. This research provides essential data for understanding and predicting shoreline changes on different time scales, thereby contributing to the identification and zoning of unstable cliffs and allowing for the mapping of risk areas to direct coastal management strategies. The data generated from the application of the Digital Shoreline Analysis System (DSAS) V.5.0 suggest that the beach–cliff system studied is in a continuous process of erosion. The use of UAV, photogrammetry techniques and precision georeferencing has enabled the construction of DEMs with excellent spatiotemporal resolution. These techniques allow for ongoing monitoring studies in coastal environments by providing short‐term instrumental data for assessing coastal erosion along the rapidly retreating coasts. This information obtained in this survey is fundamental for identifying and zoning unstable coastal cliffs and helping map risk areas where strategic actions for sustainable management of the coastal zone are required.