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Title

Simplified Marsh Response Model (SMRM): A Methodological Approach to Quantify the Evolution of Salt Marshes in a Sea-Level Rise Context

Authors
Inácio, Miguel
Freitas, M. Conceição
Cunha, Ana Graça
Antunes, Carlos
Leira, Manel
Lopes, Vera
Andrade, César
Published in Remote sensing. 2022, vol. 14, no. 14, 3400
Abstract

Salt marshes are highly valued coastal environments for different services: coastline protection, biodiversity, and blue carbon. They are vulnerable to climate changes, particularly to sea-level rise. For this reason, it is essential to project the evolution of marsh areas until the end of the century. This work presents a reduced complexity model to quantify salt marshes’ evolution in a sea-level rise (SLR) context through combining field and remote sensing data: SMRM (Simplified Marsh Response Model). SMRM is a two-dimensional rule-based model that requires four parameters: a digital terrain model (DTM), local tidal levels, a sea-level rise projection, and accretion rates. A MATLAB script completes the process, and the output is a GeoTIFF file. Two test areas were selected in Tróia sandspit (Setúbal, Portugal). Additionally, a sensitivity analysis for each parameter’s influence and a comparison with SLAMM (another rule-based model) were undertaken. The sensitivity analysis indicates that SLR is the most relevant parameter, followed by accretion rates. The comparison of SMRM with SLAMM shows quite similar results for both models. This new model application indicates that the studied salt marshes could be resilient to conservative sea-level rise scenarios but not to more severe sea-level rise projections.

Identifiers
Full text
Structures
Research groups Limnology and Environmental Geology
ISE Pôle Sciences
ISE Eau
Projects
Fundação para a Ciência e a Tecnologia, I.P.: PD/BD/106074/2015
Fundação para a Ciência e a Tecnologia, I.P.: PD/BD/142781/2018
Citation
(ISO format)
INÁCIO, Miguel et al. Simplified Marsh Response Model (SMRM): A Methodological Approach to Quantify the Evolution of Salt Marshes in a Sea-Level Rise Context. In: Remote sensing, 2022, vol. 14, n° 14, p. 3400. doi: 10.3390/rs14143400 https://archive-ouverte.unige.ch/unige:163991

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Deposited on : 2022-10-05

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