A model for the data extrapolation of greenhouse gas emissions in the Brazilian hydroelectric system

Hydropower reservoirs are artificial water systems and comprise a small proportion of the Earth’s continental territory. However, they play an important role in the aquatic biogeochemistry and may affect the environment negatively. Since the 90s, as a result of research on organic matter decay in manmade flooded areas, some reports have associated greenhouse gas emissions with dam construction. Pioneering work carried out in the early period challenged the view that hydroelectric plants generate completely clean energy. Those estimates suggested that GHG emissions into the atmosphere from some hydroelectric dams may be significant when measured per unit of energy generated and should be compared to GHG emissions from fossil fuels used for power generation. The contribution to global warming of greenhouse gases emitted by hydropower reservoirs is currently the subject of various international discussions and debates. One of the most controversial issues is the extrapolation of data from different sites. In this study, the extrapolation from a site sample where measurements were made to the complete set of 251 reservoirs in Brazil, comprising a total flooded area of 32 485 square kilometers, was derived from the theory of self-organized criticality. We employed a power law for its statistical representation. The present article reviews the data generated at that time in order to demonstrate how, with the help of mathematical tools, we can extrapolate values from one reservoir to another without compromising the reliability of the results

Climate change · Extrapolation · Fossil fuel · Geography · Global warming · Greenhouse effect · Greenhouse gas · Hydroelectricity · Hydrology (agriculture · Hydropower · Meteorology · Statistics · Work (physics · Engineering · Environmental Science · Mathematics · Transboundary Water Resource Management · Water resources management and optimization · Water-Energy-Food Nexus Studies · Ecology · Geology · Oceanography