Estimate and evaluation of reservoir metrics in Serra da Mesa dam (GO) using the Google Earth Engine platform
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...
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creator | Xavier, Gabrielle De Oliveira Tati De Almeida Oliveira, Carlos Magno Moreira De Oliveira, Petronio Diego Silva De Costa, Victor Hugo Barros Granado, Larissa Moreira Alves |
description | 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. |
doi_str_mv | 10.6084/m9.figshare.14290514 |
format | Dataset |
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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. 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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. 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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.</abstract><pub>SciELO journals</pub><doi>10.6084/m9.figshare.14290514</doi><oa>free_for_read</oa></addata></record> |
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title | Estimate and evaluation of reservoir metrics in Serra da Mesa dam (GO) using the Google Earth Engine platform |
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