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Shoreline Dynamics of South Africa Using Satellite Imagery

Version 2 2024-10-09, 06:23
Version 1 2024-10-08, 14:10
dataset
posted on 2024-10-09, 06:23 authored by DANIE TheronDANIE Theron

Most South African beaches lack sufficient monitoring, which impedes a holistic understanding of shoreline dynamics amid increasing environmental and anthropogenic pressures. This study addressed this critical knowledge gap by utilising a satellite-derived shoreline algorithm (CoastSat) to rectify years of inadequate monitoring and to contribute to a thorough understanding of South African shoreline dynamics. Enhancements were made to the open-source CoastSat algorithm to enable a semi-automated, nationwide application. As a result, a pioneering database was created, spanning from 1984 to 2023 and covering nearly all sandy areas of the South African coastline. This extensive and coherent database represents the first of its kind for South Africa. The accuracy of the satellite-derived shoreline data (SDS) was assessed by comparing it with Lidar-surveyed data from 27km of beach area across six different beaches in the eThekwini Municipality. The results showed a very strong correlation (R = 0.95) between the SDS and the surveyed data, although an overall landward bias of 11.2m was observed. By incorporating wave runup in the analysis the accuracy was significantly improved, reducing bias by up to 79%. These findings were consistent with previous CoastSat studies from abroad.

In addition to developing this extensive shoreline dynamics database, four local case studies and four regional assessments were carried out. These efforts served two primary objectives: to further the understanding of South African coastal dynamics both locally and regionally, and to demonstrate the utility of the database. For example, (i) A study of the Tugela River Mouth revealed shoreline erosion of several hundred metres from 2005 to 2023, which is important information for ongoing and planned catchment projects, such as large dams, that impact fluvial sand yield to the coast. (ii) The consistent extreme accretion south of the Richards Bay port entrance sharply contrasted with the extreme erosion to the north. This highlighted the impacts of various coastal engineering interventions, providing valuable insights into their effectiveness and guiding future coastal management strategies based on the lessons learned. (iii) Studies of the seasonal shoreline responses at St Helena Bay and Cape Town bays (Table Bay and False Bay) showed how the magnitude of these responses was related to the degree of wave exposure. (iv) Regional investigations found interesting distinctions in shoreline evolution: for instance, the west coast typically experienced shoreline retreat during winter, the south coast had less extreme winter erosion, and the east coast, particularly from Port St Johns northward, saw the greatest erosion shifting from winter to spring. This information is invaluable for informing local, regional, and provincial vulnerability assessments and guiding resource allocation more effectively.

This study successfully established the first comprehensive database of shoreline dynamics for the entire South African sandy coastline. The data and insights provided could serve as a valuable resource for coastal managers, policymakers, engineers, researchers, and other stakeholders, facilitating the development of informed, effective, and sustainable coastal management strategies that address both current and future challenges. Future research can build on these data and insights by exploring new, unresearched avenues or enhancing methods and technologies to mitigate the identified errors and limitations.

Funding

Harry Crossley Foundation Scholarship

Stellenbosch University - Postgraduate Scholarship Programme

History

Publisher

Stellenbosch University

Contributor

Theron, D.

Date

2024-10-01

Format

.pdf .zip .csv .jpg .pkl .geojson

Language

en

Geographical Location

South Africa

Academic Group

  • Engineering

Recommended Citation

Theron, D. 2024. Shoreline Dynamics of South Africa Using Satellite Imagery. Stellenbosch University. Dataset. DOI: https://doi.org/10.25413/sun.26779372