Monitoring river turbidity after a mine tailing dam failure using an empirical model derived from Sentinel-2 imagery

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dc.contributor.authorCrioni, Pedro L. B. [UNESP]
dc.contributor.authorTeramoto, Elias H. [UNESP]
dc.contributor.authorChang, Hung K. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2023-07-29T13:53:34Z
dc.date.available2023-07-29T13:53:34Z
dc.date.issued2023-01-01
dc.description.abstractSudden failure of a mine tailing dam occurred in the municipality of Brumadinho, Minas Gerais, Brazil, on January 25, 2019. Approximately 12 million cubic meters of mine tailings discharged into the Paraopeba River, producing strong environmental and societal impacts, mainly due to a massive increase in turbidity (occasionally exceeding 50,000 Nephelometric Turbidity Units [NTU] (CPRM 2019). Remote sensing is a well-established tool for quantifying spatial patterns of turbidity. However, a few empirical models have been developed to map turbidity in rivers impacted by mine tailings. Thus, this study aimed to develop an empirical model capable of producing turbidity estimates based on images from the Sentinel-2 satellite, using the Paraopeba River as the study area. We found that river turbidity was most strongly correlated with the sensor’s near-infrared band (NIR) (band 8). Thus, we built an empirical single-band model using an exponential function with an (R2 of 0.91) to characterize the spatial-temporal variation of turbidity based on satellite observations of NIR reflectance. Although the role of discharged tailings in the seasonal variation of turbidity is not well understood, the proposed model enabled the monitoring of turbidity variations in the Paraopeba River associated with seasonal resuspension or deposition of mine tailings. Our study shows the capability of single-band models to quantify seasonal variations in turbidity in rivers impacted by mine tailing pollution.en
dc.description.affiliationUniversidade Estadual de São Paulo (UNESP) Laboratório de Estudos de Bacias (LEBAC), Avenida 24A, 1515, Bela Vista, SP
dc.description.affiliationUniversidade Estadual de São Paulo (UNESP) Centro de Estudos Ambientais, Avenida 24A, 1515, Bela Vista, SP
dc.description.affiliationUniversidade Estadual de São Paulo (UNESP) Departamento de Geologia Aplicada, Avenida 24A, 1515, Bela Vista, SP
dc.description.affiliationUnespUniversidade Estadual de São Paulo (UNESP) Laboratório de Estudos de Bacias (LEBAC), Avenida 24A, 1515, Bela Vista, SP
dc.description.affiliationUnespUniversidade Estadual de São Paulo (UNESP) Centro de Estudos Ambientais, Avenida 24A, 1515, Bela Vista, SP
dc.description.affiliationUnespUniversidade Estadual de São Paulo (UNESP) Departamento de Geologia Aplicada, Avenida 24A, 1515, Bela Vista, SP
dc.identifierhttp://dx.doi.org/10.1590/0001-3765202320220177
dc.identifier.citationAnais da Academia Brasileira de Ciencias, v. 95, n. 1, 2023.
dc.identifier.doi10.1590/0001-3765202320220177
dc.identifier.issn1678-2690
dc.identifier.issn0001-3765
dc.identifier.scopus2-s2.0-85158012152
dc.identifier.urihttp://hdl.handle.net/11449/248783
dc.language.isoeng
dc.relation.ispartofAnais da Academia Brasileira de Ciencias
dc.sourceScopus
dc.subjectMine tailings
dc.subjectParaopeba river
dc.subjectRemote Sensing
dc.subjectSentinel-2
dc.subjectturbidity
dc.subjectwater quality
dc.titleMonitoring river turbidity after a mine tailing dam failure using an empirical model derived from Sentinel-2 imageryen
dc.typeArtigo
unesp.author.orcid0000-0003-1500-738X[1]
unesp.author.orcid0000-0002-3072-6801[2]
unesp.author.orcid0000-0002-6274-4510[3]

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