The Impact Of Climate Change On The São Francisco River s Hydroelectric Production

Transcription

1 The Impact Of Climate Change On The São Francisco River s Hydroelectric Production Pieter de Jong Doutorado em Engenharia Industrial (PEI - UFBA ); Mestrado em Engenharia Industrial (PEI - UFBA ); Bacharel em Engenharia Elétrica (Universidade Monash). Universidade Federal da Bahia, Salvador-BA, Brazil 2017

2 Background The NE region s hydroelectric potential is saturated. The Northeast (NE) is driest part of Brazil and suffers from droughts. The drought in the NE from is the worst in recorded history the São Francisco streamflow has been the lowest on record. Climate change will negatively impact rainfall in the NE and hydroelectric availability. São Francisco basin (SF) & the Northeast region of Brazil Northeast region SF

3 Schematic of hydroelectric plants along the São Francisco River Northeast region Sobradinho Paulo Alfonso Luiz Gonzaga/ Itaparica Apolônio Sales Xingó APOLÔNIO SALES / Source: ONS Três Marias Hydroelectric Dam

4 Sobradinho Hydroelectric plants Apolônio Sales Paulo Alfonso Nov 2015 & 2017 the NE s hydroelectric availability dropped to only 5% of its total storage capacity. Itaparica Xingó

5 NE Reservoir Volume Levels / Stored Energy (percentage of the total capacity) Disponibilidade hidroeléctrica mensal Source: ONS - Operador Nacional do Sistema Elétrico, 2017

6 Sources of the Northeast s Electricity Fontes de energia elétrica para o Nordeste 30% 25% 25% Thermal electricity generation in the NE is from fossil fuels & biomass. Imported consists mostly of hydro from other Brazilian regions. From hydro was responsible for more than 87% of the NE s electricity supply, however, by 2016 this figure dropped to 25%. Source: ONS (2016).

7 Objective, method and materials IPCCC model rainfall projections are compared to the linear trend-line of historical average rainfall extrapolated until Various studies that predict the percentage of average rainfall reduction by 2100, considering different IPCCC models, are examined. Historical data from for the average monthly rainfall within the São Francisco basin area was provided by CPTEC/INPE (Centro de Previsão de Tempo e Estudos Climáticos / Instituto Nacional de Pesquisas Espaciais). Historical monthly streamflow data for the São Francisco River is sourced from the ONS (Operador Nacional do Sistema Elétrico). The elasticity factor, which is the reduction in streamflow relative to the decline in rainfall during periods of low rainfall, is estimated from

8 Projected changes in precipitation until Northeast region Source: Marengo, 2008 and Marengo & Ambrizzi et al, Climate change will cause reduced rainfall (up 60% reductions in the semi-arid NE).

9 Projected temperature increases until Northeast region Source: Marengo, 2008 and Marengo & Ambrizzi et al, Climate change will cause higher temperatures and wind speeds.

10 Projected climate change for Brazilian river basins Source: Marengo et al (2012) considering the IPCC B2 emission scenario.

11 IPCC Projections of rainfall in the São Francisco basin According to Tanajura et al (2010) rainfall could decline 25 50% in the in semi-arid areas of Bahia and up to 80% in coastal areas by According to Marengo et al (2012) annual rainfall in the São Francisco basin will decrease by 35% by 2100 relative to the baseline considering the B2 ( RCP6.0) reduced emissions scenario. Considering the A2 (RCP8.5) high emission scenario the predicted rainfall reduction could be 40-60% (Marengo, 2008). However, the linear trend-lines of historical rainfall and streamflow (see next slide) show that they have already declined by 25% and 33%, respectively, relative to the baseline. This show that the IPCC models have large uncertainties and could have underestimated the decline in rainfall in the region.

12 São Francisco (SF) basin Monthly Rainfall and Streamflow (2 year rolling average) Source: ONS (2017) and CPTEC / INPE (2017).

13 Extrapolating Rainfall and Streamflow relative to long term averages Table 1 (based on linear trend-lines) Rainfall Rainfall reduction relative to avg: Year (mm) (mm) (%) Decrease per year % Decrease in 20 years % Decrease in 41 years % Decrease in 55 years % Decrease in 75 years % Decrease in 110 years % Decrease in 125 years % Streamflow Streamflow reduction relative to avg: Year (MWavg) (MWavg) (%) Decrease per year % Decrease in 20 years % Decrease in 41 years % Decrease in 55 years % Decrease in 75 years % Decrease in 110 years % Decrease in 125 years %

14 Annual rainfall (trend-lines) in the São Francisco basin Annual rainfall has been below its long-term average every year since Source: CPTEC / INPE (2017) and and Marengo et al (2012).

15 Linear projections for the São Francisco basin Linearly extrapolating rainfall reduction in the São Francisco basin from to (110 years) (as per the table in the previous slide) would see a reduction of approximately 70%. Due to non-linear hydrologic processes, reductions in streamflow can actually be amplified 2 to 3 times relative to reductions in rainfall (SAFT et al, 2015 and TIMBAL et al, 2015). This elasticity factor is due to a larger percentage of rainfall being lost to infiltration, irrigation and reservoir evaporation. It was estimate that irrigation and reservoir evaporation equate to 7% and 11%, respectively, of the São Francisco s long term average streamflow ( ). However, as a result of the drought, irrigation and reservoir evaporation equated to 20% and 30%, respectively, of the São Francisco s streamflow in 2015.

16 São Francisco monthly rainfall and streamflow vs long term averages (streamflow 1931 to 1990 & rainfall ) Source: ONS (2017) and CPTEC / INPE (2017). The slope of the respective trend-lines demonstrate that the drop in the São Francisco s streamflow is more extreme when compared to the decline in rainfall. E.g From June to November streamflow in the São Francisco reservoirs is at its lowest level which are typically the months that wind energy generation is at its highest.

17 São Francisco monthly rainfall, streamflow, hydro storage and hydro generation (12 month rolling averages) Streamflow in the São Francisco basin dropped below 3000MWavg and is continuing to drop. Source: ONS (2017) and CPTEC / INPE (2017).

18 Elasticity factor for the São Francisco basin During the last 4 years average rainfall dropped 34% to below 60mm per month. As a result, since 2015 the average streamflow in the São Francisco dropped by 60% below its baseline and is continuing to drop. The average streamflow for 2017 is predicted to be 75% below the baseline average. Therefore, an elasticity factor of is assumed for the basin Rainfall and streamflow under non-drought conditions Linearly extrapolating the long term average monthly rainfall would see it drop to only 60mm by 2030, which is a reduction of 34% relative to the baseline (see table). Applying the elasticity factor means that by 2030, the long term average streamflow could actually drop approximately 60% compared to the baseline average ( ).

19 Summary of results Linearly extrapolating rainfall data to 2050 sees a 47% decline in average rainfall and an 80% reduction in average streamflow. This means the rainfall estimates for 2100 based on IPCC B2 and A2 projections could actually eventuate as early as 2030 and 2050, respectively. In short, the deficits in rainfall and streamflow experienced during the last 4 years could become the norm by Moreover, by 2030 the reduced streamflow in the São Francisco will only allow hydroelectricity to generate approximately 10-15% of the NE s electricity demand. Therefore, in the coming decades the São Francisco river will be more important for urban water supplies, farming and irrigation.

20 Jucazinho Reservoir full Pernambuco

21 Jucazinho Reservoir Pernambuco 2017

22 PRINCIPAL REFERENCES ANEEL Agência Nacional da Energia Elétrica, BIG Banco de Informações de Geração; Available at: accessed on 14/03/2017. CPTEC / INPE - Centro de Previsão de Tempo e Estudos Climáticos / Instituto Nacional de Pesquisas Espaciais; de Jong P, Kiperstok A, Torres E A. Economic and environmental analysis of electricity generation technologies in Brazil. Renewable and Sustainable Energy Reviews 2015; Accepted for publication. de Jong P, Sánchez A S, Esquerre K, Kalid R A, Torres E A. Solar and wind energy production in relation to the electricity load curve and hydroelectricity in the Northeast region of Brazil. Renewable and Sustainable Energy Reviews 2013; 23: Lucena A F P, Szklo A S, Schaeffer R, Dutra R M. The vulnerability of wind power to climate change in Brazil. Renewable Energy 2010; 35: Lucena A F P de, SZKLO A S, SCHAEFFER R, SOUZA R R de, BORBA B S M C, COSTA I V L da, JÚNIOR A O P, CUNHA S H F da, The vulnerability of renewable energy to climate change in Brazil. Energy Policy 2009; 37: Marengo J A. Regional Climate Change Scenarios for South America-The CREAS project. Conference on Climate Change and Official Statistics, Oslo Norway, Marengo J A, Chou S C, Kay G, Alves L M, Pesquero J F, Soares W R, et al. Development of regional future climate change scenarios in South America using the Eta CPTEC/HadCM3 climate change projections: climatology and regional analyses for the Amazon, São Francisco and the Paraná River basins. Climate Dynamics 2012; 38: Marengo J A, Jones R, Alvesa L M, Valverde M C. Future change of temperature and precipitation extremes in South America as derived from the PRECIS regional climate modeling system. International Journal Of Climatology 2009; 29: ONS Operador Nacional do Sistema Elétrico. RE PEL ; ONS Operador Nacional do Sistema Elétrico. 2ª Revisão Quadrimestral das Projeções da demanda de energia elétrica do Sistema Interligado Nacional EPE - Empresa Pesquisa Energética/ONS; ONS Operador Nacional do Sistema Elétrico. Históricas da Operação - Geração de Energia; Available at: Accessed on 14/04/2017. Tanajura C A S, Genz F, Araujo H. Mudanças climáticas e recursos hídricos na Bahia: validação da simulação do clima presente do HadRM3P e comparação com os cenários A2 e B2 para Revista Brasileira de Meteorologia ed. online; vol. 3. p

23 THANK YOU Pieter de Jong. Contact Universidade Federal da Bahia, Salvador-BA, Brazil. Escola Politécnica, Rua Aristides Novis, n 2, 6 Andar - Federaçáo, CEP