SWOT Altimetry Data Processing and Validation for Pantanal Wetland Hydrodynamic Analysis

• Grant number: 25/11406-5
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: August 28, 2025
• End date: February 27, 2026
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Evlyn Márcia Leão de Moraes Novo
• Grantee: Jahdy Moreno Oliveira
• Supervisor: Mark Trigg
• Host Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia e Inovação (Brasil). São José dos Campos , SP, Brazil
• Institution abroad: University of Leeds, England
• Associated to the scholarship: 24/12997-4 - SWOT Mission Data Validation for Pantanal Hydrodynamic Analysis, BP.MS

Abstract

Pantanal, the largest continuous wetland on the planet, is increasingly threatened by extreme hydrological events, such as prolonged droughts and intense floods, exacerbated by climate change. Monitoring surface water dynamics in this environment is essential for understanding and mitigating the impacts of these events. Satellite altimetry has emerged as a key tool in this context, offering consistent observations even in remote or inaccessible regions. The recent launch of the Surface Water and Ocean Topography (SWOT) mission presents new opportunities to monitor continental hydrology by providing high-resolution data on water surface elevation. Therefore, this research proposes an investigation into the potential of SWOT for characterizing the hydrodynamics of the Pantanal, with a particular focus on water surface elevation data. Specifically, the objectives are to generate, and analyze time series of virtual stations based on conventional satellite altimetry, to process SWOT-derived elevation products, and to validate these against conventional altimetry data. These activities will be carried out in collaboration with the School of Civil Engineering at Leeds University, through a six-month research internship abroad, with the aim of improving methodologies for the application of SWOT data and contributing to the operational monitoring of large floodplain systems.