Multicriteria Decision Model for Intelligent Selection of Surface Water Sampling Sites in the Marajó Bay Estuary, PA

• Grant number: 25/19786-1
• Support Opportunities: Scholarships in Brazil - Master
• Start date: October 01, 2025
• End date: March 31, 2027
• Field of knowledge: Engineering - Production Engineering - Operational Research
• Agreement: CONFAP - National Council of State Research Support Foundations
• Principal Investigator: Luiz Leduíno de Salles Neto
• Grantee: Karen Viviana Pinilla Moreras
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
• Associated research grant: 24/22444-2 - Innovation in Water Monitoring in the Amazon: Cataloging and integration of field data with emerging technologies for predicting water quality parameters in the estuary of Marajó Bay, PA, AP.R

Abstract

The Marajó Bay estuary, situated in the Brazilian Amazon, is an area of high biodiversity and significant environmental, economic, and social importance; however, it faces challenges due to increasing anthropogenic pressures and the need for effective water monitoring. This project proposes addressing the problem of strategically selecting surface water sampling sites by developing a multicriteria decision model that integrates environmental, logistical, and representativeness variables. The primary objective is to optimize the monitoring network, thereby reducing operational costs and enhancing the accuracy of collected data to support effective environmental management. The methodology incorporates methods such as the Analytic Hierarchy Process (AHP) and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), along with the integration of data into a Geographic Information System (GIS). Environmental, logistical, and socioeconomic data will be collected through field visits, public databases, and satellite imagery. The model will be validated based on the representativeness and effectiveness of the selected sites, with potential for replication in other estuaries. Additionally, the project's social impact will be considerable, enhancing the management of natural resources and improving the public health of riverside communities. It will also contribute to international discussions and strategies, such as those to be addressed at the United Nations Climate Change Conference (COP 30), reinforcing the commitment to sustainability and the preservation of Amazonian ecosystems.