Regional Environmental Change

, Volume 19, Issue 1, pp 193–204 | Cite as

Response of the river discharge in the Tocantins River Basin, Brazil, to environmental changes and the associated effects on the energy potential

  • Rita Casia Silva Von RandowEmail author
  • Daniel Andrés Rodriguez
  • Javier Tomasella
  • Ana Paula Dutra Aguiar
  • Bart Kruijt
  • Pavel Kabat
Original Article


Climate change is expected to impact the hydrological regime worldwide, and land use and land cover change may alter the effects of the former in some cases. Secondary growth in deforested and abandoned areas is one of the main consequences of land use and cover changes in Amazonia. Among land uses, the effects of the secondary growth in water availability in large scale basins are not well understood. This work analyzes the potential effects of secondary growth under climate and land use change on water availability and hydropower in the Tocantins basin, in the Legal Amazon region of Brazil, using the MHD-INPE hydrological model driven by different climate scenarios and two future socioeconomic-based potential land use scenarios. The model projects decrease on discharge under climate change scenarios, which further cause the simulated hydropower energy potential to decrease significantly. When only deforestation scenarios are included, the effects of climate change are weakened, but when secondary growth is also considered, the effects of climate change are enhanced. Results suggest that different aspects of environmental change, such as secondary growth, may affect water production and the sectors depending on it.


Hydrological modeling Climate change Land use and land cover change Secondary forest Hydropower potential 



The authors acknowledge European Union for financially supporting the EU-FP7 AMAZALERT project (Raising the alert about critical feedbacks between climate and long-term land use change in the Amazon - grant agreement no. 282664), of which this work is part. The authors also acknowledge the “Fundo Amazonia” program of the Brazilian Development Bank (BNDES), which partially supported the LUCC-ME modeling framework.

Supplementary material

10113_2018_1396_MOESM1_ESM.docx (1.7 mb)
ESM 1 (DOCX 1747 kb)


  1. Aguiar APD, Ometto JP, Nobre C, Lapola DM, Almeida C, Vieira IC, Soares JV, Alvala R, Saatchi S, Valeriano D, Castilla-Rubio JC (2012) Modeling the spatial and temporal heterogeneity of deforestation-driven carbon emissions: the INPE-EM framework applied to the Brazilian Amazon. Glob Chang Biol 18:3346–3366. CrossRefGoogle Scholar
  2. Aguiar APD, Vieira ICG, Assis TO, Dalla-Nora EL, Toledo PM, Santos-Junior RAO, Batistella M, Coelho AS, Savaget EK, Aragão LEOC, Nobre CA, Ometto JPH (2016) Land use change emission scenarios: anticipating a forest transition process in the Brazilian Amazon. Glob Chang Biol 22:1821–1840.
  3. Alcamo J (2001) Scenarios as tools for international environmental assessments. Environmental issue report No 24. European Environment Agency. Accessed 15 Jan 2018
  4. ANA - Agência Nacional de Águas s/d (2006) Plano Estratégico de Recursos Hídricos da Bacia dos Rios Tocantins e Araguaia: Relatório Diagnóstico, Anexo 14, Geração de Energia No 1329-R-FIN-PLD-15-01 ANA, Brasília, DF 56 p, Accessed 15 Jan 2018
  5. ANTAQ – Agência Nacional de Transportes Aquaviários (Brasil) (2013) Bacia do Tocantins-Araguaia: Plano Nacional de Integração Hidroviária: Desenvolvimento de Estudos e Análises das Hidrovias Brasileiras e suas Instalações Portuárias com Implantação de Base de Dados Georreferenciada e Sistema de Informações Geográficas UFSC. Acessed 15 Jan 2018
  6. Aquino Martins PT, Póvoa Matos RM, Bueno AF, Sene Paixão ACAS (2015) Land use and land cover change of high Tocantins river basin (Goias, Brazil): influence of physical characteristics and the relation with the indigenous communities. Ciência e Natura 37:392–404. Google Scholar
  7. Bárdossy A, Pegram G (2011) Downscaling precipitation using regional climate models and circulation patterns toward hydrology. Water Resour Res 47:W04505. CrossRefGoogle Scholar
  8. BRASIL (2013) PAC2 - Programa de Aceleração do Crescimento 8° BALANÇO MAIO - AGOSTO 2013 Available at: Accessed 15 Jan 2018
  9. Bravo JM, Collischonn W, da Paz AR, Allasia D, Domecq F (2014) Impact of projected climate change on hydrologic regime of the Upper Paraguay River basin. Clim Chang 127:27–41. CrossRefGoogle Scholar
  10. Bruijnzeel LA (1991) Predicting the hydrological impacts of land cover transformation in the humid tropics: the need for integrated research. In: Gash JHC, Nobre CA, Roberts JM, Victoria RL (eds) Amazonian deforestation and climate. Wiley, Chichester, pp 15–55Google Scholar
  11. Chou SC, Marengo JA, Lyra AA, Sueiro G, Pesquero JF, Alves LM, Kay G, Betts R, Chagas DJ, Gomes JL, Bustamante JF, Tavares P (2012) Downscaling of South America present climate driven by 4-member HadCM3 runs. Clim Dyn 38:635–653. CrossRefGoogle Scholar
  12. Christensen JH, Kanikicharla KK, Aldrian E, An S-I, Cavalcanti IFA, de Castro M, Dong W, Goswami P, Hall A, Kanyanga JK, Kitoh A, Kossin J, Lau N-C, Renwick J, Stephenson DB, Xie S-P and Zhou T (2013) Climate phenomena and their relevance for future regional climate change. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V and Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 1217–1308Google Scholar
  13. Cidade Tucuruí (2016) Technical specifications (in Portuguese), Accessed 15 Jan 2018
  14. Cloke HL, Wetterhall F, He Y, Freer JE, Pappenberger F (2013) Modelling climate impact on floods with ensemble climate projections. Q J R Meteorol Soc 139:282–297. CrossRefGoogle Scholar
  15. Coe MT, Costa MH, Soares Filho BS (2009) The influence of historical and potential future deforestation on the stream flow of the Amazon River—land surface processes and atmospheric feedbacks. J Hydrol 369:165–174. CrossRefGoogle Scholar
  16. Collins M, Tett SFB, Cooper C (2001) The internal climate variability of a HadCM3, a version of the Hadley centre coupled model without flux adjustments. Clim Dyn 17:61–81. CrossRefGoogle Scholar
  17. Collins M, Booth BBB, Harris GR, Murphy JM, Sexton DMH, Webb MJ (2006) Towards quantifying uncertainty in transient climate change. Clim Dyn 27:127–147. CrossRefGoogle Scholar
  18. Correa da Silva R, de Marchi Neto I, Silva Seifert S (2016) Electricity supply security and the future role of renewable energy sources in Brazil. Renew Sust Energ Rev 59:328–341. CrossRefGoogle Scholar
  19. Costa MH, Botta A, Cardille JA (2003) Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia. J Hydrol 283:206–217. CrossRefGoogle Scholar
  20. Dalagnol R, Borma LS, Mateus P, Rodriguez DA (2017) Assessment of climate change impacts on water resources of the Purus Basin in the southwestern Amazon. Acta Amazon 47:213–226. CrossRefGoogle Scholar
  21. D’Almeida C, Vörösmarty CJ, Hurtt GC, Marengo JA, Dingman SL, Keim BD (2007) The effects of deforestation on the hydrological cycle in Amazonia: a review on scale and resolution. Int J Climatol 27(5):633–647.
  22. Davidson EA, de Araújo AC, Artaxo P, Balch JK, Brown IF, Bustamante MMC, Coe MT, DeFries RS, Keller M, Longo M, Munger JW, Schroeder W, Soares-Filho BS, Souza CM, Wofsy SC (2012) The Amazon basin in transition. Nature 481:321–328. CrossRefGoogle Scholar
  23. Demaria EMC, Maurer EP, Thrasher B, Vicuña S, Meza FJ (2013) Climate change impacts on an alpine watershed in Chile: do new model projections change the story? J Hydrol 502:128–138. CrossRefGoogle Scholar
  24. Dijkshoorn JA, Huting JRM, Tempel P (2005) Update of the 1:5 million soil and terrain 9 database for Latin America and the Caribbean (SOTERLAC; version 20) report 10 2005/01, ISRIC – World Soil Information, WageningenGoogle Scholar
  25. Duan Q, Sorooshian S, Gupta HV, Gupta V (1992) Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour Res 28:1015–1031. CrossRefGoogle Scholar
  26. Duan Q, Sorooshian S, Gupta VK (1994) Optimal use of the SCE-UA global optimization method for calibrating watershed models. J Hydrol 158:265–284. CrossRefGoogle Scholar
  27. ENGIE (2016) Datasheet (in Portuguese) Accessed 15 Jan 2018
  28. EPE - Empresa de Pesquisa Energética (2006–2007) Plano Nacional de Energia 2030 (in Portuguese)/ Ministério de Minas e Energia Empresa de Pesquisa Energética Brasília: MME/EPE. Accessed 15 Jan 2018Google Scholar
  29. EPE - Empresa de Pesquisa Energética (2012) Plano Decenal de Expansão de Energia 2021 (in Portuguese)/ Ministério de Minas e Energia Empresa de Pesquisa Energética Brasília: MME/EPE. Accessed 15 Jan 2018Google Scholar
  30. Falck AS, Maggioni V, Tomasella J, Vila DA, Diniz FLR (2015) Propagation of satellite precipitation uncertainties through a distributed hydrologic model: a case study in the Tocantins–Araguaia basin in Brazil. J Hydrol 527:943–957. CrossRefGoogle Scholar
  31. Farr TG, Rosen PA, Caro E, Crippen R, Duren R, Hensley S, Kobrick M, Paller M, Rodriguez E, Roth L, Seal D, Scott Shaffer S, Shimada J, Umland J, Werner M, Oskin M, Burbank D, Alsdorf D (2007) The shuttle radar topography mission. Rev Geophys 45:1–33. CrossRefGoogle Scholar
  32. Folhes RT, de Aguiar APD, Stoll E, Dalla-Nora EL, Araújo R, Coelho A, do Canto O (2015) Multi-scale participatory scenario methods and territorial planning in the Brazilian Amazon. Futures 73:86–99. CrossRefGoogle Scholar
  33. FURNAS Centrais Elétricas SA (1996) Reservatório UHE Serra da Mesa Minaçu, Goiás Accessed 15 Jan 2018
  34. Giambelluca TW (2002) Hydrology of altered tropical forest. Hydrol Process 16:1665–1669. CrossRefGoogle Scholar
  35. Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean heat transport in a version of the Hadley centre coupled model without flux adjustments. Clim Dyn 16:147–168. CrossRefGoogle Scholar
  36. Hahner I (2009) Luis Eduardo Magalhães – Lajeado Hydroelectric Power Plant on The Tocantins River In: Main Brazilians Dams III – Design, Construction and Performance, 2009 ISBN 978-85-62967-01-6 Accessed 15 Jan 2018
  37. Horner N, de Paula Oliveira AG, Silberglitt R, Poppe MK, Rocha BB (2016) Energy foresight, scenarios and sustainable energy policy in Brazil. Foresight 18(5):535–550. CrossRefGoogle Scholar
  38. IBGE (1992) RADAM - Banco de dados georeferenciado sobre recursos naturais Instituto Brasileiro de Geografia e Estatística, Accessed 15 Jan 2018
  39. Jones RN (2000) Managing uncertainty in climate change projections: issues for impact assessment. Clim Chang 45:403–419. CrossRefGoogle Scholar
  40. Krause P, Boyle DP, Bäse F (2005) Comparison of different efficiency criteria for hydrological model assessment. Adv Geosci 5:89–97. CrossRefGoogle Scholar
  41. Lathuillière MJ, Johnson MS, Donner SD (2012) Water use by terrestrial ecosystems: temporal variability in rainforest and agricultural contributions to evapotranspiration in Mato Grosso, Brazil. Environ Res Lett 7:024024. CrossRefGoogle Scholar
  42. Leite CC, Costa MH, Lima CA, Ribeiro CAAS, Sediyama GC (2011) Historical reconstruction of land use in the Brazilian Amazon (1940–1995). J Land Use Sci 6:33–52. CrossRefGoogle Scholar
  43. Lenderink G, Buishand A, van Deursen W (2007) Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrol Earth Syst Sci 11:1145–1159. CrossRefGoogle Scholar
  44. Ley R, Casper MC, Hellebrand H, Merz R (2011) Catchment classification by runoff behaviour with self-organizing maps (SOM). Hydrol Earth Syst Sci 15:2947–2962. CrossRefGoogle Scholar
  45. Marengo JA, Chou S, Kay G, Alves LM, Pesquero J, Soares W, Santos DC, Lyra A, Sueiro G, Betts R, Chagas D, Gomes J, Bustamante J, Tavares P (2012) 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 Parana River basins. Clim Dyn 38:1829–1848. CrossRefGoogle Scholar
  46. Martins Filho G, Porto MA, Werner Jr D (2009) The Peixe Angical Hydroelectric Development on the Tocantins River In: Main Brazilians Dams III – Design, Construction and Performance ISBN 978-85-62967-01-6 Accessed 15 Jan 2018
  47. MMA (2006) Caderno da Região Hidrográfica do Tocantins-Araguaia Ministério do Meio Ambiente Brasília, DF, Brazil Accessed 15 Jan 2018
  48. Mohor GS, Rodriguez DA, Tomasella J, Siqueira Junior JL (2015) Exploratory analyses for the assessment of climate change impacts on the energy production in an Amazon run-of-river hydropower plant. J Hydrol Reg Stud 4:41–59. CrossRefGoogle Scholar
  49. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900. CrossRefGoogle Scholar
  50. Nakicenovic N, Alcamo J, Davis G, De Vries B,  Fenhann J, Gaffin S, Gregory K, Griibler A, Jung TY, Kram T, La Rovere EL, Michaelis L, Mori S, Morita T, Pepper W, Pitcher H, Price L, Riahi K, Roehrl A, Rogner HH, Sankovski A, Schlesinger M, Shukla P, Smith S, Swart R, Van Rooijen S, Victor N, Dadi Z (2000) IPCC Special Report on Emissions Scenarios Cambridge University Press, Cambridge, United Kingdom/New York, NY, USA, pp 570, Accessed 17 Jan 2018
  51. Nóbrega MT, Collischonn W, Tucci CEM, da Paz AR (2011) Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil. Hydrol Earth Syst Sci 15:585–595. CrossRefGoogle Scholar
  52. Oliveira Mesquita SH (2006) Consequências de sítios arqueológicos escavados e não inundados pelo lago da usina Hidrelétrica de Serra da Mesa. Trabalho de Conclusão de Curso (Graduação em Engenharia Ambiental) - Pontifícia Universidade Católica de Goiás (in portuguese)Google Scholar
  53. Paish O (2002) Small hydro power: technology and current status. Renew Sust Energ Rev 6:537–556. CrossRefGoogle Scholar
  54. Prestele R, Alexander P, Rounsevell MDA, Arneth A, Calvin K, Doelman J, Eitelberg DA, Engström K, Fujimori S, Hasegawa T, Havlik P, Humpenöder F, Jain AK, Krisztin T, Kyle P, Meiyappan P, Popp A, Sands RD, Schaldach R, Schüngel J, Stehfest E, Tabeau A, Van Meijl H, Van Vliet J, Verburg PH (2016) Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison. Glob Chang Biol 22:3967–3983. CrossRefGoogle Scholar
  55. Raskin P, Monks F, Ribeiro T, van Vuuren D, Zurek M (2005) Global scenarios in historical perspectives. In: Carpenter PLPSR, Bennett EM, Zurek MB (eds) Ecosystems and human well-being: scenarios volume 2: findings of the scenarios working group of the millennium ecosystem assessment. Island Press, Washington, DC, pp 35–44Google Scholar
  56. Roberts JM (2009) The role of forests in the hydrological cycle. Forests and forest plants - Volume III: 42 Eolss PublishersGoogle Scholar
  57. Rodriguez DA, Tomasella J (2016) On the ability of large-scale hydrological models to simulate land use and land cover change impacts in Amazonian basins. Hydrol Sci J 61(10):1831–1846. Google Scholar
  58. Sellers PJ, Mintz Y, Sud YC, Dalcher A (1986) A simple biosphere model (SiB) for use within general circulation models. J Atmos Sci 43(6):505–531.;2 CrossRefGoogle Scholar
  59. Sestini MF, Alvala RCS, Mello EMK, Valeriano DM, Chou SC, Nobre CA, Paiva JAC, Reimer ES (2002) Elaboração de Mapas de Vegetação para Utilização em Modelos Meteorológicos e Hidrológicos – PROVEG (In Portuguese) Technical Report, INPE, Sao Jose dos Campos, SP, Brazil Accessed 15 Jan 2018
  60. Siqueira Junior JL, Tomasella J, Rodriguez DA (2015) Impacts of future climatic and land cover changes on the hydrological regime of the Madeira River basin. Clim Chang.
  61. Stickler CM, Coe MT, Costa MH, Nepstad DC, McGrath DG, Dias LCP, Rodrigues HO, Soares-Filho BS (2013) Dependence of hydropower energy generation on forests in the Amazon Basin at local and regional scales. Proc Natl Acad Sci 110:9601–9606. CrossRefGoogle Scholar
  62. Teutschbein C, Seibert J (2013) Is bias correction of regional climate model (RCM) simulations possible for non-stationary conditions? Hydrol Earth Syst Sci 17:5061–5077. CrossRefGoogle Scholar
  63. Tomasella J, Rodriguez D, Cuartas L, Ferreira M, Ferreira J, Marengo J (2009) Estudo de impacto das mudanças climáticas sobre os recursos hídricos superficiais e sobre os níveis dos aquíferos na bacia do rio Tocantins. Technical Report. Convênio de Cooperação Técnico-Científica INPE-VALE, INPE, São José dos Campos, SP, BrazilGoogle Scholar
  64. Tractebel Energia (2010) Demonstrações contábeis dos exercícios de 2009 e de 2008 (in portuguese) Accessed 15 Jan 2018
  65. Vogel RM, Fenessey NM (1994) Flow–duration curves I: new interpretation and confidence intervals. J Water Resour Plan Manag 120:485–504. CrossRefGoogle Scholar
  66. Vogel RM, Fenessey NM (1995) Flow–duration curves II: review of applications in water resources planning. JAWRA Journal of the American Water Resources Association 31:1029–1039. CrossRefGoogle Scholar
  67. Von Randow RCS, Tomasella J, Von Randow C, Araújo AC, Manzi AO (2017) Secondary Forest as a counterbalance on the deforestation effects: its role on evapotranspiration and water use efficiency. In: EGU General Assembly 2017, Vienna - Austria. Geophysical Research Abstracts. vol 19, EGU2017–10724, 2017Google Scholar
  68. Walker RT, Moran E, Anselin L (2000) Deforestation and cattle ranching in the Brazilian Amazon: external capital and household processes. World Dev 28:683–699. CrossRefGoogle Scholar
  69. Wang YQ, Shao MA (2013) Spatial variability of soil physical properties in a region of the Loess Plateau of PR China subject to wind and water erosion. Land Degrad Dev 24:296–304. CrossRefGoogle Scholar
  70. Wood AW, Maurer EP, Kumar A, Lettenmaier DP (2002) Long-range experimental hydrologic forecasting for the eastern United States. J Geophys Res Atmos 107(D20):ACL 6-1–ACL 6-15. CrossRefGoogle Scholar
  71. Wood AW, Leung LR, Sridha V, Lettenmaier DP (2004) Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs. Clim Chang 62:189–216. CrossRefGoogle Scholar
  72. Yilmaz KK, Gupta HV, Wagener T (2008) A process-based diagnostic approach to model evaluation: application to the NWS distributed hydrologic model. Water Resour Res 44:W09417-1–W0941718. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Rita Casia Silva Von Randow
    • 1
    Email author
  • Daniel Andrés Rodriguez
    • 2
  • Javier Tomasella
    • 3
  • Ana Paula Dutra Aguiar
    • 1
    • 4
  • Bart Kruijt
    • 5
  • Pavel Kabat
    • 6
  1. 1.Earth System Science Center (CCST)National Institute for Space Research (INPE)São José dos CamposBrazil
  2. 2.Instituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de Engenharia (COPPE)Universidade Federal do Rio de Janeiro (UFRJ)Rio de JaneiroBrazil
  3. 3.CEMADEN, Centro de Monitoramento e Alertas de Desastres NaturaisCachoeira PaulistaBrazil
  4. 4.Stockholm Resilience CentreStockholm UniversityStockholmSweden
  5. 5.Water Systems and Global ChangeWageningen UniversityWageningenThe Netherlands
  6. 6.IIASA, International Institute for Applied System AnalysisLaxenburgAustria

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