Skip to main content

Advertisement

Log in

Climate change impacts on South American water balance from a continental-scale hydrological model driven by CMIP5 projections

  • Published:
Climatic Change Aims and scope Submit manuscript

Abstract

South America contributes to roughly 30% of global runoff to the oceans. Because the regional economy and biodiversity depend significantly on its water resources, assessing potential climate change impacts on the continental water balance is crucial to support water management planning. Here we evaluate the mean alterations of water balance variables and river discharge in South America by the end of this century using two different GHG scenarios (RCP4.5 and RCP8.5). An ensemble comprising 25 global climate models (GCM) from CMIP5 is used to force a continental-scale hydrologic-hydrodynamic model developed for that region. A negative signal with respect to changes in precipitation, evapotranspiration, and runoff is observed on most of the continent. Major decreases in the annual mean discharge are expected for the Orinoco, Tocantins, and Amazon basins, which would be around 8–14% at least (statistically significant – RCP4.5 and RCP8.5, respectively). Only the Uruguay Basin presents a positive trend for the mean discharge.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Adam K, Fan F, Pontes P et al (2015) Mudanças climáticas e vazões extremas na Bacia do Rio Paraná / Climate Change and Extreme Streamflows in Paraná River Basin. Rev Bras Recur Hídricos 20:999–1007. https://doi.org/10.21168/rbrh.v20n4.p999-1007

  • Arnell NW, Gosling SN (2013) The impacts of climate change on river flow regimes at the global scale. J Hydrol 486:351–364. https://doi.org/10.1016/j.jhydrol.2013.02.010

  • Asadieh B, Krakauer NY (2017) Global change in streamflow extremes under climate change over the 21st century. Hydrol Earth Syst Sci 21:5863–5874. https://doi.org/10.5194/hess-21-5863-2017

  • Beck HE, Van Dijk AIJM, Levizzani V et al (2017) MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data. Hydrol Earth Syst Sci 21:589–615. https://doi.org/10.5194/hess-21-589-2017

  • Bozkurt D, Rojas M, Boisier JP, Valdivieso J (2018) Projected hydroclimate changes over Andean basins in Central Chile from downscaled CMIP5 models under the low and high emission scenarios. Clim Chang 150:131–147. https://doi.org/10.1007/s10584-018-2246-7

  • Bravo JM, Collischonn W, da Paz AR et al (2014) Impact of projected climate change on hydrologic regime of the upper Paraguay River basin. Clim Chang 127:27–41. https://doi.org/10.1007/s10584-013-0816-2

  • Brunner GW (2010) HEC-RAS river analysis system: hydraulic reference manual. US Army Corps of Engineers, Institute for Water Resources, hydrologic …

  • Buytaert W, Bievre B De (2012) Water for cities: the impact of climate change and demographic growth in the tropical Andes. Water Resour Res 48:1–13. https://doi.org/10.1029/2011WR011755

  • Chevallier P, Pouyaud B, Suarez W, Condom T (2011) Climate change threats to environment in the Tropical Andes: glaciers and water resources. Reg Environ Chang 11:179–187. https://doi.org/10.1007/s10113-010-0177-6

  • Chiew FHS (2006) Estimation of rainfall elasticity of streamflow in Australia. Hydrol Sci J 51:613–625. https://doi.org/10.1623/hysj.51.4.613

  • Chou SC, Lyra A, Mourão C et al (2014a) Assessment of climate change over South America under RCP 4.5 and 8.5 downscaling scenarios. Am J Clim Chang 03:512–527. https://doi.org/10.4236/ajcc.2014.35043

  • Chou SC, Lyra A, Mourão C et al (2014b) Evaluation of the eta simulations nested in three global climate models. Am J Clim Chang 03:438–454. https://doi.org/10.4236/ajcc.2014.35039

  • Christensen JH, Boberg F, Christensen OB, Lucas-Picher P (2008) On the need for bias correction of regional climate change projections of temperature and precipitation. Geophys Res Lett 35:. https://doi.org/10.1029/2008GL035694

  • Clark EA, Sheffield J, van Vliet MTH et al (2015) Continental runoff into the oceans (1950–2008). J Hydrometeorol 16:1502–1520. https://doi.org/10.1175/JHM-D-14-0183.1

  • Dankers R, Arnell NW, Clark DB et al (2014) First look at changes in flood hazard in the inter-sectoral impact model Intercomparison project ensemble. Proc Natl Acad Sci 111:3257–3261. https://doi.org/10.1073/pnas.1302078110

  • Ehret U, Zehe E, Wulfmeyer V, et al (2012) HESS Opinions “should we apply bias correction to global and regional climate model data?” Hydrol Earth Syst Sci 16:3391–3404. https://doi.org/10.5194/hess-16-3391-2012

  • Eyring V, Bony S, Meehl GA et al (2016) Overview of the coupled model Intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci Model Dev 9:1937–1958. https://doi.org/10.5194/gmd-9-1937-2016

  • Fan FM, Buarque DC, Pontes PRM (2015) An Hydrological Response Units Maps for all South America. XXI Brazilian Simp Water Resources 8

  • Flato G, Marotzke J, Abiodun B et al (2013) Evaluation of climate models. Clim Chang 2013 Phys Sci basis Contrib work gr I to fifth assess rep Intergov panel Clim Chang 741–866. https://doi.org/10.1017/CBO9781107415324

  • Fleischmann A, Siqueira V, Paris A et al (2018) Modelling hydrologic and hydrodynamic processes in basins with large semi-arid wetlands. J Hydrol 561:943–959. https://doi.org/10.1016/j.jhydrol.2018.04.041

  • Global Runoff Data Centre (GRDC) (2014) Global freshwater fluxes into the world oceans, Koblenz

  • Guimberteau M, Ciais P, Pablo Boisier J et al (2017) Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: a multi-model analysis with a new set of land-cover change scenarios. Hydrol Earth Syst Sci 21:1455–1475. https://doi.org/10.5194/hess-21-1455-2017

  • Gulizia C, Camilloni I (2015) Comparative analysis of the ability of a set of CMIP3 and CMIP5 global climate models to represent precipitation in South America. Int J Climatol 35:583–595. https://doi.org/10.1002/joc.4005

  • Hagemann S, Chen C, Clark DB et al (2013) Climate change impact on available water resources obtained using multiple global climate and hydrology models. Earth Syst Dyn 4:129–144. https://doi.org/10.5194/esd-4-129-2013

  • Hattermann FF, Krysanova V, Gosling SN et al (2017) Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins. Clim Chang 141:561–576. https://doi.org/10.1007/s10584-016-1829-4

  • Hess LL, Melack JM, Affonso AG et al (2015) Wetlands of the lowland Amazon Basin: extent, vegetative cover, and dual-season inundated area as mapped with JERS-1 synthetic aperture radar. Wetlands 35:745–756. https://doi.org/10.1007/s13157-015-0666-y

  • Knutti R, Sedláček J (2013) Robustness and uncertainties in the new CMIP5 climate model projections. Nat Clim Chang 3:369–373. https://doi.org/10.1038/nclimate1716

  • Koirala S, Hirabayashi Y, Mahendran R, Kanae S (2014) Global assessment of agreement among streamflow projections using CMIP5 model outputs. Environ Res Lett 9. https://doi.org/10.1088/1748-9326/9/6/064017

  • Krysanova V, Donnelly C, Gelfan A et al (2018) How the performance of hydrological models relates to credibility of projections under climate change. Hydrol Sci J 00:1–25. https://doi.org/10.1080/02626667.2018.1446214

  • Marengo JA, Bernasconi M (2015) Regional differences in aridity/drought conditions over Northeast Brazil: present state and future projections. Clim Chang 129:103–115. https://doi.org/10.1007/s10584-014-1310-1

  • Marengo JA, Jones R, Alves LM, Valverde MC (2009) Future change of temperature and precipitation extremes in South America as derived from the PRECIS regional climate modeling system. Int J Climatol 29:2241–2255. https://doi.org/10.1002/joc.1863

  • Marengo JA, Chou SC, Kay G et al (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 Paraná River basins. Clim Dyn 38:1829–1848. https://doi.org/10.1007/s00382-011-1155-5

  • Melack J, Coe M (2012) Climate change and the floodplain lakes of the Amazon basin. Clim Chang glob warm … 295–310. https://doi.org/10.1002/9781118470596.ch17

  • Middleton N, Thomas D (1997) World atlas of desertification, 2nd edn. Oxford Univ. Press

  • Milly PCD, Dunne KA, Vecchia A V. (2005) Global pattern of trends in streamflow and water availability in a changing climate. Nature 438:347–350. https://doi.org/10.1038/nature04312

  • Muerth MJ, Gauvin St-Denis B, Ricard S, et al (2013) On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff. Hydrol Earth Syst Sci 17:1189–1204. https://doi.org/10.5194/hess-17-1189-2013

  • New M, Lister D, Hulme M, Makin I (2002) A high-resolution data set of surface climate over global land areas. Clim Res 21:1–25. https://doi.org/10.3354/cr021001

  • Nóbrega MT, Collischonn W, Tucci CEM, Paz AR (2011) Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil. Hydrol Earth Syst Sci 15:585–595. https://doi.org/10.5194/hess-15-585-2011

  • Paiva RCD, Buarque DC, Collischonn W et al (2013) Large-scale hydrologic and hydrodynamic modeling of the Amazon River basin. Water Resour Res 49:1226–1243. https://doi.org/10.1002/wrcr.20067

  • Pierce DW, Cayan DR, Maurer EP, et al (2015) Improved Bias Correction Techniques for Hydrological Simulations of Climate Change*. J Hydrometeorol 16:2421–2442. doi: 10.1175/JHM-D-14-0236.1

  • Pontes PRM, Fan FM, Fleischmann AS et al (2017) MGB-IPH model for hydrological and hydraulic simulation of large floodplain river systems coupled with open source GIS. Environ Model Softw 94:1–20. https://doi.org/10.1016/j.envsoft.2017.03.029

  • Reyer CPO, Adams S, Albrecht T et al (2017) Climate change impacts in Latin America and the Caribbean and their implications for development. Reg Environ Chang 17:1601–1621. https://doi.org/10.1007/s10113-015-0854-6

  • Riahi K, Rao S, Krey V et al (2011) RCP 8.5-a scenario of comparatively high greenhouse gas emissions. Clim Chang 109:33–57. https://doi.org/10.1007/s10584-011-0149-y

  • Ribeiro Neto A, da Paz AR, Marengo JA, Chou SC (2016) Hydrological processes and climate change in hydrographic regions of Brazil. J Water Resour Prot 08:1103–1127. https://doi.org/10.4236/jwarp.2016.812087

  • Scarpati O, Kruse E, Gonzalez M et al (2014) Updating the hydrological. In: handbook of engineering hydrology: environmental hydrology and water management. CRC Press, p 445

  • Schewe J, Heinke J, Gerten D et al (2014) Multimodel assessment of water scarcity under climate change. Proc Natl Acad Sci 111:3245–3250. https://doi.org/10.1073/pnas.1222460110

  • Shuttleworth WJ (1993) Evaporation. In: Maidment DR (ed) Handbook of hydrology. McGraw-Hill

  • Silveira C da S, Souza Filho F de A de, Vasconcelos Jr F das C(2017) Streamflow projections for the Brazilian hydropower sector from RCP scenarios. J Water Clim Chang 8:114–126. https://doi.org/10.2166/wcc.2016.052

  • Siqueira Júnior 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 129:117–129. https://doi.org/10.1007/s10584-015-1338-x

  • Siqueira VA, Paiva RCD, Fleischmann AS et al (2018) Toward continental hydrologic – hydrodynamic modeling in south America. 1–50. https://doi.org/10.5194/hess-2018-225

  • Sorribas MV, Paiva RCD, Melack JM et al (2016) Supplementary Material: Projections of climate change effects on discharge and inundation in the Amazon basin

  • Sperna Weiland FC, Van Beek LPH, Kwadijk JCJ, Bierkens MFP (2012) Global patterns of change in discharge regimes for 2100. Hydrol Earth Syst Sci 16:1047–1062. https://doi.org/10.5194/hess-16-1047-2012

  • Teutschbein C, Seibert J (2012) Bias correction of regional climate model simulations for hydrological climate-change impact studies: review and evaluation of different methods. J Hydrol 456–457:12–29. https://doi.org/10.1016/j.jhydrol.2012.05.052

  • Thomson AM, Calvin K V., Smith SJ et al (2011) RCP4.5: a pathway for stabilization of radiative forcing by 2100. Clim Chang 109:77–94. https://doi.org/10.1007/s10584-011-0151-4

  • Todini E (1996) The ARNO rainfall-runoff model. J Hydrol 175:339–382. https://doi.org/10.1016/S0022-1694(96)80016-3

  • Torres RR, Marengo JA (2013) Uncertainty assessments of climate change projections over South America. Theor Appl Climatol 112:253–272. https://doi.org/10.1007/s00704-012-0718-7

  • Vicuña S, Garreaud RD, McPhee J (2011) Climate change impacts on the hydrology of a snowmelt driven basin in semiarid Chile. Clim Chang 105:469–488. https://doi.org/10.1007/s10584-010-9888-4

  • Vuille M, Carey M, Huggel C et al (2018) Rapid decline of snow and ice in the tropical Andes – impacts, uncertainties and challenges ahead. Earth-Science Rev 176:195–213. https://doi.org/10.1016/j.earscirev.2017.09.019

  • Yang Y, Zhang S, McVicar TR et al (2018) Disconnection between trends of atmospheric drying and continental runoff. Water Resour Res 54:4700–4713. https://doi.org/10.1029/2018WR022593

  • Zhao T, Bennett JC, Wang QJ, et al (2017) How suitable is quantile mapping for postprocessing GCM precipitation forecasts? J Clim 30:3185–3196. https://doi.org/10.1175/JCLI-D-16-0652.1

  • Zhao M, Golaz JC, Held IM et al (2016) Uncertainty in model climate sensitivity traced to representations of cumulus precipitation microphysics. J Clim 29:543–560. https://doi.org/10.1175/JCLI-D-15-0191.1

Download references

Acknowledgements

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. This paper results related to streamflow are summarized on the South America Climate Change Impacts on water resources (SACCI) available at https://www.ufrgs.br/hge/modelos-e-outros-produtos/sacci/.

Funding

This work is part of the project “Desenvolvimento do Modelo Regional do Sistema Terrestre ETA e Geração de Cenários de Mudanças Climáticas e de Usos da Terra visando Estudos de Impacto Sobre os Recursos Hídricos” funded by the Brazilian National Water Agency (ANA) and the “Coordenação de Aperfeiçoamento de Pessoal de Nível Superior” (CAPES). It is also included on the project SAFAS “South America Flood Awareness System” funded by the “Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to João Paulo Lyra Fialho Brêda.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 158 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brêda, J.P.L.F., de Paiva, R.C.D., Collischon, W. et al. Climate change impacts on South American water balance from a continental-scale hydrological model driven by CMIP5 projections. Climatic Change 159, 503–522 (2020). https://doi.org/10.1007/s10584-020-02667-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10584-020-02667-9

Keywords

Navigation