Estimate and evaluation of reservoir metrics in Serra da Mesa dam (GO) using the Google Earth Engine platform

  • Gabrielle de Oliveira Xavier Instituto de Geociências. Universidade de Brasília (UnB), Campus Darcy Ribeiro, CEP: 70910-900, Brasília, DF, Brazil.
  • Tati de Almeida Instituto de Geociências. Universidade de Brasília (UnB), Campus Darcy Ribeiro, CEP: 70910-900, Brasília, DF, Brazil.
  • Carlos Magno Moreira de Oliveira Instituto Federal do Norte de Minas Gerais (IFNMG), Rodovia MG 202, Km 407, s/n, CEP: 38680-000, Arinos, MG, Brazil.
  • Petronio Diego Silva de Oliveira Instituto do Meio Ambiente e dos Recursos Hídricos do Distrito Federal (IBRAM), SEPN 511, Bloco C, CEP: 70750-543, Brasília, DF, Brazil.
  • Victor Hugo Barros Costa Ministério da Agricultura, Pecuária e Abastecimento (Mapa), Esplanada dos Ministérios, Bloco D, CEP: 70043-900, Brasília, DF, Brazil.
  • Larissa Moreira Alves Granado Instituto de Geociências. Universidade de Brasília (UnB), Campus Darcy Ribeiro, CEP: 70910-900, Brasília, DF, Brazil.
DOI: https://doi.org/10.4136/ambi-agua.2584
Keywords: accumulation reservoir, dam, time series.

Abstract

The goal of this study was to assess the temporal dynamics of an accumulation reservoir in an accessible and accurate way. The study was conducted on the Serra da Mesa Dam (GO) using orbital images. To estimate the flat area of the dam surface, Landsat TM and OLI images for the period 1998 to 2018 were used. The images were processed using the Google Earth Engine platform (GEE) in order to obtain the dam surface area (km²) and relate it to the flow, altimetric height and volume of the reservoir over the years. The dam showed constant variation of water since its inception, with a decreasing trend. The highest values of the reservoir measurement metrics were observed in the years coincident with the largest areas of the dam, and inversely proportional to the years of the appearance of new dams upstream. More than 90% of the altimetric height variation of water could be explained by the flat area of the dam. The processing platform using the GEE is effective to provide extensive temporal analysis using a large volume of data in a short time, with accurate and robust results.


Published
15/09/2020
Issue
Vol. 15 No. 5 (2020)
Section
Papers

Authors maintain the copyrights for their work. However, they grant rights of first publication to Ambiente e Agua - An Interdisciplinary Journal of Applied Science. In compensation, the journal can transfer the copyrights, allowing non-commercial use of the article including the right of sending the article to other data bases or publication media. The journal uses the CC BY 4.0 license"