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A new approach to assess ancient marine slope instability using a bivariate statistical method

Piedade, Aldina ORCID: https://orcid.org/0000-0002-4155-7740, Alves, Tiago M. ORCID: https://orcid.org/0000-0002-2765-3760 and Zêzere, José Luís 2018. A new approach to assess ancient marine slope instability using a bivariate statistical method. Marine Geology 401 , pp. 129-144. 10.1016/j.margeo.2018.04.006

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Abstract

Slope instability is one of the most effective processes shaping the sea floor of continental margins. The end-products of slope instability, mass-transport deposits (MTDs), have been documented in the literature using diverse approaches. This paper tests a new methodology, applied to a region offshore Espírito Santo (SE Brazil), for the evaluation of MTDs' occurrence on continental slopes. A MTD inventory was, in a first stage, made for a cropped region of SE Brazil using a high resolution three-dimensional (3D) seismic volume. This MTD inventory consists of four MTDs that were mapped and exported into a Geographic Information Systems (GIS) database. MTD favourability scores were computed in a second stage using algorithms based on statistical/probabilistic analyses (Information Value Method), over unique terrain conditions, in a raster basis. Terrain attributes derived from the Digital Terrain Model (DTM) were used as proxies to several driving factors of MTDs, and as predictors in the models. As a result, three models are discussed independently in this paper according to the different datasets used to interpret MTDs (Models 1, 2 and 3). The results were prepared by sorting all pixels according their favourability value, in descending order, and the robustness and accuracy of the MTD favourability models were evaluated by success-rate curves. The curves aided the quantitative interpretation of the models expressing their goodness of fit to the interpreted MTDs. This work is important because the outputs resulting from the methodology confirm that this new method can be applied to submarine slopes. From the three models, Model 3 obtained the highest goodness of fit (0.862). Based on our results, a sensitivity analysis was undertaken and key predisposing factors were identified. This new methodology has the potential to become a very important and valid approach for the recognition of submarine slopes prone to failure on continental margins around the world.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Earth and Environmental Sciences
Publisher: Elsevier
ISSN: 0025-3227
Funders: FCT - Portugal
Date of First Compliant Deposit: 18 April 2018
Date of Acceptance: 15 April 2018
Last Modified: 07 Nov 2023 04:37
URI: https://orca.cardiff.ac.uk/id/eprint/110785

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