Semi-analytic algorithm parameterization assessment of CDOM/DOC in Brazilian eutrophic inland waters

• Grant number: 24/09108-3
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Effective date (Start): September 01, 2024
• Effective date (End): February 28, 2025
• Field of knowledge: Physical Sciences and Mathematics - Geosciences - Physical Geography
• Principal Investigator: Cláudio Clemente Faria Barbosa
• Grantee: Pedro Ferrini Manhães Bacellar
• Supervisor: Qian Yu
• Host Institution: Instituto Nacional de Pesquisas Espaciais (INPE). Ministério da Ciência, Tecnologia e Inovação (Brasil). São José dos Campos , SP, Brazil
• Research place: University of Massachusetts, Amherst (UMass Amherst), United States
• Associated to the scholarship: 23/07443-7 - Mapping of Dissolved Organic Carbon (DOC) in Brazilian Continental Aquatic Systems by Remote Sensing, BP.MS

Abstract

Over the last decade, inland waters has been related to its active role across long-range-loop global carbon cycle. Globally, these areas receive a significative but ill-defined amount of carbon content from terrestrial runoff watershed and anthropic sources. These uncertainties are highlighted in humid tropical zones, where high temperature and trophic conditions, favors fast synthesis of metabolic compounds and long spread watershed hinder the acquisition of extensive data. To fill out this gap of knowledge, optical Remote Sensing (RS) techniques have been successfully supported biogeochemical and multispectral analysis of water quality parameters in a fast and cost-effective way. Remote sensed imagery assessment of inland water carbon content are based on bio-optical algorithms that use Colored Dissolved Organic Matter (CDOM) absorption coefficient aCDOM(») as a proxy of Dissolved Organic Carbon DOC due to its generally well correlation. In this sense, this research project aims to test and develop bio-optical semi-analytic algorithms to estimate CDOM/DOC in three eutrophic reservoirs across São Paulo state by using MSI/Sentinel-2 and OLI/Landsat-8/9 multispectral images. Semi-analytical approach are based on simplified solutions of Radiative Transfer Equation alliance with mathematical optimizations to precisely describe each step of physical propagation of electromagnetic radiation interacting with Optical Significant Constituents of the water, until reach the orbital sensor. Applying this robust physical-theoretical framework, potentially will lead to suitable and accurate results recovering carbon dynamics in both three reservoirs. The performance obtained from analysis results will support intercomparison to Machine Learning empirical algorithms already developed in context of (FAPESP 2023/07443-7) and accept to publish https://sil2024.org/.