RECENT COASTLINE TRENDS ON THE EAST MARGIN OF THE MIDDLE PARÁ ESTUARY

Authors

DOI:

https://doi.org/10.4215/rm2023.e22019

Abstract

The main objective of this article is to quantify the erosion and accretion rates on the eastern margin of the middle Pará Estuary within 32 years (1987, 1993, 1999, 2004, 2008, 2013, and 2019) with the use of remote sensing and data Digital Shoreline Analysis System (DSAS) extension. These methodological procedures recently applied in the Amazon region are effective in the search for intended results. To calculate with significant accuracy the rates of CL changes, select the parameters Net Shoreline Movement (NSM), Linear Regression Rate (LRR), and End Point Rate (EPR) to obtain the variations. In the middle estuary, the rates showed a tendency towards CL retreat in the onshore direction, with an average rate of -38 m and an average accretion rate of 22.97 m prevailing on Mosqueiro Island, related to average rates of variation of -0.58 m/ year (EPR) and -0.54 m/year (LRR) and in Santo Antônio do Tauá with LRR and EPR parameters identifying average rates of variation of -1.67 m/year (LRR) and -1.55 m/year (EPR). Only on Colares island, there was a tendency to accretion, with an average erosion rate of -96.29 m and an average accretion rate of 116.49 m, where the maximum accretion and erosion rates are 405.61 m and -396.87 m, respectively.

Keywords: Eastern Amazon, Coastal Dynamics, Estuarine Environment, LANDSAT

Author Biographies

  • Diandra Karina Martins Guimarães, Federal University of Pará, Belém (PA), Brazil

    Master in Oceanography and Bachelor in Geography both from the Federal University of Pará (UFPA). Carrying out research in the area of Coastal Geomorphology and Coastal Dynamics with an emphasis on Remote Sensing. I participated as a scholarship holder in the Geography Tutorial Education Program (PET-Geography) and was also part of the UFPA/CNPq Coastal Geography Studies of Marajó (EGC) research group.

  • Maâmar El-Robrini, Federal University of Pará, Belém (PA), Brazil

    Master in Physiographie des Oceans et des Littoraux (1982) and PhD in Marine Geology - Université de la Sorbonne Paris IV/Paris IV (1986). He is currently a Full Professor at the Federal University of Pará, Deputy Director of the Faculty of Oceanography, teaches Undergraduate courses (Faculties of Geology, Naval Engineering and Oceanography) and Postgraduate courses (Naval Engineering, Oceanography and Water Resources). He coordinates the Marine & Coastal Studies Group (GEMC / CNPQ) and the Ocean Geology Laboratory (LAGEOC). He has experience in the areas of Oceanography, Marine Geology/Geophysics, working in the following areas: Amazon Coastal Zone, Brazilian Economic and Exclusive Zone, Equatorial and Mediterranean Continental Margin. Participated in LEPLAC III and IV, AMASSEDS, JOPS, PROARQUIPÉLAGO. Coordinated the REVIZEE Program, REMPLAC, Adaptation to Sea Level Rise in the Amazon Delta Project. Currently: National Institute of Ocean Energies (INEOF - Managing Member), Project Coordinator: Sedimentation of the Equatorial Continental Slope, Bottom Instability (Mediterranean Sea), River/Ocean Edges.

  • Renan Peixoto Rosário, Federal University of Pará, Belém (PA), Brazil

    PhD in Geophysics, Marine Geophysics subarea at the Federal University of Pará (2016). He is currently Adjunct Professor I at the Institute of Geosciences, Faculty of Oceanography-UFPA. He has experience in the area of physical oceanography, working mainly on the following topics: estuarine and shelf hydrodynamics, saline intrusion in estuaries and data analysis in physical oceanography.

  • Rafael Alexandre Alves Menezes, Federal University of Pará, Belém (PA), Brazil

    PhD student in the Postgraduate Program in Geography (PPGEO-UFPa) and external professor at the Faculty of Geography and Cartography at the Federal University of Pará (FGC/UFPA). Develops research in the areas of: Coastal Geomorphology, Coastal Vulnerability, Remote Sensing, Geoprocessing, Modeling, Machine Learning, Deep Learning, Programming language: Python, Javascript and R; and Cloud Geoprocessing (Google Earth Engine-GEE).

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Published

2023-12-02

Issue

Vol. 22 (2023)

Section

Artigos

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