Flood Risk Mapping during the Extreme February 2021 Flood in the Juruá River, Western Brazilian Amazonia, State of Acre

José Mantovani, Enner Alcântara (), José A. Marengo, Luciana Londe, Edward Park, Ana Paula Cunha and Javier Tomasella
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José Mantovani: Institute of Science and Technology, São Paulo State University (Unesp), São José Dos Campos 12245-000, SP, Brazil
Enner Alcântara: Institute of Science and Technology, São Paulo State University (Unesp), São José Dos Campos 12245-000, SP, Brazil
José A. Marengo: Graduate Program in Natural Disasters, (Unesp/CEMADEN), São José Dos Campos 12247-004, SP, Brazil
Luciana Londe: Graduate Program in Natural Disasters, (Unesp/CEMADEN), São José Dos Campos 12247-004, SP, Brazil
Edward Park: National Institute of Education, Earth Observatory of Singapore and Asian School of the Environment, Nanyang Technological University (NTU), Singapore 639798, Singapore
Ana Paula Cunha: Graduate Program in Natural Disasters, (Unesp/CEMADEN), São José Dos Campos 12247-004, SP, Brazil
Javier Tomasella: Graduate Program in Natural Disasters, (Unesp/CEMADEN), São José Dos Campos 12247-004, SP, Brazil

Sustainability, 2024, vol. 16, issue 7, 1-23

Abstract: Cruzeiro do Sul, a municipality in Northwestern Brazil is recurrently impacted by floods, particularly along the Juruá River. This study presents a comprehensive flood risk analysis by integrating geoprocessing, remote sensing, and hydraulic modeling techniques. Our objectives are to simulate flood extents, identify high-risk areas, and guide sustainable territorial management. Our findings illustrate that the flood impacts are distributed across urban (27%), agricultural (55%), and forest/grassland (17%) landscapes. Historical records and literature reviews also underscore a recurring pattern of extreme floods in the municipality, notably during February’s La Niña events. Some vulnerable urban neighborhoods were identified: Vila Cruzeirinho, Centro, Miritizal, and Da Várzea. These areas are especially susceptible due to their proximity to the river and increased surface runoff during high flood events. By amalgamating various data sources and methods, this research aids decision making for flood mitigation and urban development, fostering resilience against recurrent flooding events in Cruzeiro do Sul.

Keywords: natural hazards; floods; remote sensing; environmental modeling; Brazil (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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