Chemical weathering detection in the periglacial landscapes of Maritime Antarctica: New approach using geophysical sensors, topographic variables and machine learning algorithms

• Published in: Geoderma
• Main Authors: Danilo César de Mello, Gustavo Vieira Veloso, Cassio Marques Moquedace, Isabelle de Angeli Oliveira, Márcio Rocha Francelino, Fabio Soares de Oliveira, José João Lelis Leal de Souza, Lucas Carvalho Gomes, Carlos Ernesto Gonçalves Reynaud Schaefer, Elpídio Inácio Fernandes-Filho, Edgar Batista de Medeiros Júnior, José Alexandre Melo Demattê
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2023
• Subjects: Gamma-ray spectrometry; Weathering intensity; Periglacial Process; Geophysical survey; Machine learning; Science; Q; The ''Y''; Antarc*; Antarctica
• Online Access: https://doi.org/10.1016/j.geoderma.2023.116615; https://doaj.org/article/db5eefcf7a794d8f954c4bf33746b477

The chemical weathering intensity in Antarctica is underestimated. As the chemical weathering intensity increases, hydrological, geochemical and geophysical changes occur in the different environmental spheres and at their interfaces through reactions and energy flows. Thus, once chemical weathering rates are understood and estimated, they can be used to predict and assess changes and trends in different environmental spheres. Few studies on the chemical weathering intensity have been performed in Antarctica. We used radiometric and magnetic properties associated with terrain attributes and the chemical degree of alteration of the igneous rock to model the chemical weathering intensity in Maritime Antarctica by using machine learning. Then, we related the chemical weathering intensity and geophysical variables with periglacial processes. To do this, gamma-spectrometric and magnetic readings were carried out using proximal-field sensors at 91 points located on different lithologies in a representative area of Maritime Antarctica. A qualitative analysis of chemical alteration for the different lithologies was carried out based on field observations and rock properties, and the levels of the chemical weathering degree were established. The geophysical data associated with terrain attributes were used as input data in the modeling of the weathering intensity. Then, the levels of the rock weathering degree were used as the “y” variable in the models. The results indicated that the C5.0 algorithm had the best performance in predicting the weathering intensity, and the most important variables were eTh, 40K, 40K/eTh, 40K/eU, the magnetic susceptibility and terrain attributes. The contents of radionuclides and ferrimagnetic minerals in different lithologies, concomitantly with the intensity at which chemical weathering occurs, determine the contents of these elements. However, the stability and distribution of these elements in a cold periglacial environment are controlled by periglacial processes. The chemical ...