2009
DOI: 10.1016/j.enpol.2008.10.029
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The vulnerability of renewable energy to climate change in Brazil

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Cited by 169 publications
(77 citation statements)
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“…The argument for this type of model over more complex physical models, such as distributed models (Vetter et al 2015), is that application of these latter can be challenging since their inputs can be difficult to acquire in developing countries especially in the spatially continuous manner, thus hindering the calibration and validation process (Babur et al 2016). Intercomparison between catchment basins is also made possible with conceptual models since historical precipitation and temperature values are more likely to exist for a larger number of basins (De Lucena et al 2009). The first step uses 30 years of observed monthly time series of precipitation and inflow to assess the relationship between rainfall and inflow in each hydropower station through a logarithmic linear regression model 5 (Jones et al 2006) represented by the following equation:…”
Section: Hydrological Modelmentioning
confidence: 99%
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“…The argument for this type of model over more complex physical models, such as distributed models (Vetter et al 2015), is that application of these latter can be challenging since their inputs can be difficult to acquire in developing countries especially in the spatially continuous manner, thus hindering the calibration and validation process (Babur et al 2016). Intercomparison between catchment basins is also made possible with conceptual models since historical precipitation and temperature values are more likely to exist for a larger number of basins (De Lucena et al 2009). The first step uses 30 years of observed monthly time series of precipitation and inflow to assess the relationship between rainfall and inflow in each hydropower station through a logarithmic linear regression model 5 (Jones et al 2006) represented by the following equation:…”
Section: Hydrological Modelmentioning
confidence: 99%
“…For the hydrological component, a conceptual hydrological model consisting of a two-step approach similar to De Lucena et al (2009), was selected to assess the sensitivity of runoff to climate change precipitation projections. The argument for this type of model over more complex physical models, such as distributed models (Vetter et al 2015), is that application of these latter can be challenging since their inputs can be difficult to acquire in developing countries especially in the spatially continuous manner, thus hindering the calibration and validation process (Babur et al 2016).…”
Section: Hydrological Modelmentioning
confidence: 99%
“…Projections indicate a considerable change in Brazil's climate within this century (Baettig et al 2007;Marengo et al 2009Marengo et al , 2010a, and there are several reasons to believe Brazil will be highly impacted by such climatic change: its economy depends heavily on exports of agricultural commodities (IPEA 2011); the provision of staple foods is strongly reliant on smallholder agriculture (responsible, for example, for 87 % of the national production of cassava, 70 % of dry beans, 46 % of maize, and 58 % of milk) (IBGE 2009); it has an energy matrix dominated by renewable energy, which is highly susceptible to climate variations (Lucena et al 2009); and it still suffers widespread poverty, significant social inequality and epidemic outbreaks (IPEA 2003;Magrin et al 2007;Confalonieri et al 2009). The floods in São Paulo city in the summer of 2010 (Folha de São Paulo 2010), the landslides in the state of Rio de Janeiro in the summer of 2011 (Folha de São Paulo 2011), the annual dengue fever epidemics throughout the entire country, and the succession of intense droughts and floods events in Amazonia and Northeast (NE) Brazil (Marengo et al 2011c, d;Ponce 1995) reveal how unprepared Brazil is for climate change.…”
Section: Introductionmentioning
confidence: 99%
“…Schaeffer, Lucena & Szklo (2008) estimated losses from 1.0% to 2.2% in electricity production of hydraulic origin for the case of Brazil as a whole. The projections by Lucena et al (2009) indicated a mean potential loss in some electricity generation in the basins of the rivers Paraná, Grande, Paranaíba, Paranapanema, Parnaíba, São Francisco and Tocantins of 1.58% for A2 scenario and 3.15% for the B2 scenario (Note 1). According to Cleto (2008), electricity production in Portugal will decrease from 5% to 6% loss in the fall and spring, a 15% loss in the winter and a slight 1-2% increase in the summer.…”
mentioning
confidence: 99%