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Towards a comprehensive characterization of evidence in synthesis assessments: the climate change impacts on the Brazilian water resources

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Abstract

The Intergovernmental Panel on Climate Change (IPCC) has put a lot of efforts to describe uncertainties and to judge the confidence level of its major conclusions. Despite a guidance to communicate uncertainty, the assignment of confidence is not sufficiently clear and, thus, hard to be reproduced by the extern community. By conducting a synthesis assessment about the impacts of climate change on the Brazilian water resources, we identified an opportunity to illustrate the characterization of evidence as adopted in IPCC reports. We propose a method to describe the evidence from model outputs wherein the quality and amount of studies, as well as the consistency among their conclusions, are subject of a transparent rating procedure. In summary, the more comprehensive the study in sampling uncertainties, the higher its quality. Likewise, the amount and consistency among conclusions is assigned in a systematic way. The method is applied for synthesizing a collection of 42 peer-reviewed articles. It reveals important aspects about the evidence of the potential impacts of climate change in the Brazilian water resources, such as changes into a drier hydrological regime. However, the use of multi-model ensemble, the evaluation of models, and the observational data is limited. The proposed method enables consistent communication of the degree of evidence in a transparent, traceable, and comprehensive fashion. The method can be used as a tool to support experts on their judgment. The approach is reproducible and can guide synthesis work not only in Brazil but anywhere else.

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Abbreviations

ALT:

Atlântico Leste

AMZ:

Amazônica

AOC:

Atlântico Nordeste Ocidental

AOR:

Atlântico Nordeste Oriental

ASD:

Atlântico Sudeste

ASU:

Atlântico Sul

BC:

Bias correction

BCS:

Bias correction score

CBC:

Score of the calibration criteria of BC

CDS:

Score of the calibration criteria of DS

CHM:

Score of the calibration criteria of HM

CM:

Climate modeling

CMIP3:

Coupled Model Intercomparison Project Phase 3

CMIP5:

Coupled Model Intercomparison Project Phase 5

CMS:

Climate modeling score

DS:

Downscaling

DSS:

Downscaling score

ECM:

Score of ensemble size of CM

EDS:

Score of the ensemble size of DS

EHM:

Score of the ensemble size of HM

ES:

Emission/radiative forcing scenarios

ESD:

Empirical statistical downscaling

ESS:

Emission/radiative forcing scenarios score

GCM:

Global climate model

HM:

Hydrological modeling

HMS:

Hydrological modeling score

IPCC:

Intergovernmental Panel on Climate Change

OBC:

Score of observational network density of rainfall data of BC

ODH:

Score of observational network density of river discharge data of HM

ODS:

Score of observational network density of rainfall data of DS

OND:

Observational network density

ORH:

Score of observational network density of rainfall data of HM

PNB:

Parnaíba

PRG:

Paraguai

PRN:

Paraná

Qmax:

Maximum discharge

Qmean:

Mean discharge

Qmin:

Minimum discharge

QS:

Quality score

RCM:

Regional climate model

RCP:

Representative concentration pathways

RES:

Score of range of ES

SFO:

São Francisco

SRES:

Special report on emissions scenarios

TBC:

Score of the type of BC

TES:

Score of type of ES

THM:

Score of the type of HM

TOC:

Tocantins-Araguaia

URU:

Uruguai

VBC:

Score of the validation criteria of BC

VCM:

Score of version of CM

VDS:

Score of the validation criteria of DS

VHM:

Score of the validation criteria of HM

References

  • Adam KN, Fan FM, Pontes PR, Bravo JM, Collischonn W (2015) Mudanças climáticas e vazões extremas na Bacia do Rio Paraná. Rev Bras Recur Hídr 20:999–1007. https://doi.org/10.21168/rbrh.v20n4.p999-1007

    Google Scholar 

  • Alvarenga LA, de Mello CR, Colombo A, Cuartas LA, Chou SC (2016) Hydrological responses to climate changes in a headwater watershed. Ciênc E Agrotecnologia 40:647–657. https://doi.org/10.1590/1413-70542016406027716

    Article  Google Scholar 

  • ANA (2017) Conjuntura dos recursos hídricos no Brasil 2017: relatório pleno. Agência Nacional de Águas, Brasília

    Google Scholar 

  • Arroio Junior P, Mauad F (2015) Simulação dos Impactos das Mudanças Climáticas na Vazão da Bacia do Ribeirão do Feijão - SP. Rev Bras Recur Hídr 20:741–751. https://doi.org/10.21168/rbrh.v20n3.p741-751

    Google Scholar 

  • Bárdossy A, Das T (2008) Influence of rainfall observation network on model calibration and application. Hydrol Earth Syst Sci 12:77–89. https://doi.org/10.5194/hess-12-77-2008

    Article  Google Scholar 

  • Beven KJ (2012) Rainfall-runoff modelling: the primer, 2nd edn. Wiley-Blackwell, Chichester

    Book  Google Scholar 

  • Blázquez J, Nuñez MN (2013) Analysis of uncertainties in future climate projections for South America: comparison of WCRP-CMIP3 and WCRP-CMIP5 models. Clim Dyn 41:1039–1056. https://doi.org/10.1007/s00382-012-1489-7

    Article  Google Scholar 

  • Bosshard T, Carambia M, Goergen K, Kotlarski S, Krahe P, Zappa M, Schär C (2013) Quantifying uncertainty sources in an ensemble of hydrological climate-impact projections. Water Resour Res 49:1523–1536. https://doi.org/10.1029/2011WR011533

    Article  Google Scholar 

  • 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. https://doi.org/10.1007/s10584-013-0816-2

  • Brazil (2006a) Caderno da Região Hidrográfica Amazônica. Ministério do Meio Ambiente (MMA), Secretaria de Recursos Hídricos, Brasília

    Google Scholar 

  • Brazil (2006b) Caderno da Região Hidrográfica do Paraná. Ministério do Meio Ambiente (MMA), Secretaria de Recursos Hídricos, Brasília

    Google Scholar 

  • Brazil (2016) National Adaptation Plan to Climate Change: volume I: general strategy. Ministry of Environment (MMA), Brasília

  • Burkett VR, Suarez AG, Bindi M, Conde C, Mukerji R, Prather MJ, St. Clair AL, Yohe GW (2014) In: Field CB, Barros VR, Dokken DJ, Mach KJ, Mastrandrea MD, Bilir TE, Chatterjee M, Ebi KL, Estrada YO, Genova RC, Girma B, Kissel ES, Levy AN, MacCracken S, Mastrandrea PR, White LL (eds) Point of departure. In: Climate change 2014: impacts, adaptation, and vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 169–194

    Google Scholar 

  • CEPED UFSC (2013) Atlas brasileiro de desastres naturais 1991 a 2012: volume Brasil. Universidade Federal de Santa Catarina. Centro Universitário de Estudos e Pesquisas sobre Desastres (CEPED UFSC), Florianópolis

    Google Scholar 

  • Chagas VBP, Chaffe PLB (2018) The role of land cover in the propagation of rainfall into streamflow trends. Water Resour Res 54:5986–6004. https://doi.org/10.1029/2018WR022947

    Article  Google Scholar 

  • de Queiroz AR, Marangon Lima LM, Marangon Lima JW, da Silva BC, Scianni LA (2016) Climate change impacts in the energy supply of the Brazilian hydro-dominant power system. Renew Energy 99:379–389. https://doi.org/10.1016/j.renene.2016.07.022

    Article  Google Scholar 

  • Ehret U, Zehe E, Wulfmeyer V, Warrach-Sagi K, Liebert J (2012) Should we apply bias correction to global and regional climate model. Hydrol Earth Syst Sci 16:3391–3404. https://doi.org/10.5194/hess-16-3391-2012

    Article  Google Scholar 

  • Eisner S, Flörke M, Chamorro A, Daggupati P, Donnelly C, Huang J, Hundecha Y, Koch H, Kalugin A, Krylenko I, Mishra V, Piniewski M, Samaniego L, Seidou O, Wallner M, Krysanova V (2017) An ensemble analysis of climate change impacts on streamflow seasonality across 11 large river basins. Clim Chang 141:401–417. https://doi.org/10.1007/s10584-016-1844-5

    Article  Google Scholar 

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. Int J Climatol 27:1547–1578. https://doi.org/10.1002/joc.1556

    Article  Google Scholar 

  • Guimberteau M, Ciais P, Ducharne A, Boisier JP, Dutra Aguiar AP, Biemans H, De Deurwaerder H, Galbraith D, Kruijt B, Langerwisch F, Poveda G, Rammig A, Rodriguez DA, Tejada G, Thonicke K, Von Randow C, Von Randow RCS, Zhang K, Verbeeck H (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

    Article  Google Scholar 

  • Hawkins E, Sutton R (2011) The potential to narrow uncertainty in projections of regional precipitation change. Clim Dyn 37:407–418. https://doi.org/10.1007/s00382-010-0810-6

    Article  Google Scholar 

  • Kattenberg A, Giorgi R, Grassl H, Meehl GA, Mitchell JFB, Stouffer RJ, Tokioka T, Weaver AJ, Wigley TML (1996) Climate models - projections of future climate. In: Houghton JT, Meira Filho LG, Callander BA, Harris N, Kattenberg A, Maskell K (eds) Climate change 1995 - the science of climate change. Cambridge University Press, Cambridge, pp 285–358

    Google Scholar 

  • Krysanova V, Vetter T, Eisner S, Huang S, Pechlivanidis I, Strauch M, Gelfan A, Kumar R, Aich V, Arheimer B, Chamorro A, van Griensven A, Kundu D, Lobanova A, Mishra V, Plötner S, Reinhardt J, Seidou O, Wang X, Wortmann M, Zeng X, Hattermann FF (2017) Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide—a synthesis. Environ Res Lett 12:105002. https://doi.org/10.1088/1748-9326/aa8359

    Article  Google Scholar 

  • Krysanova V, Donnelly C, Gelfan A, Gerten D, Arheimer B, Hattermann F, Kundzewicz ZW (2018) How the performance of hydrological models relates to credibility of projections under climate change. Hydrol Sci J 63:696–720. https://doi.org/10.1080/02626667.2018.1446214

    Article  Google Scholar 

  • Kundzewicz ZW, Krysanova V, Dankers R, Hirabayashi Y, Kanae S, Hattermann FF, Huang S, Milly PCD, Stoffel M, Driessen PPJ, Matczak P, Quevauviller P, Schellnhuber H-J (2017) Differences in flood hazard projections in Europe – their causes and consequences for decision making. Hydrol Sci J 62:1–14. https://doi.org/10.1080/02626667.2016.1241398

    Google Scholar 

  • Kundzewicz ZW, Krysanova V, Benestad RE, Hov ø, Piniewski M, Otto IM (2018) Uncertainty in climate change impacts on water resources. Environ Sci Pol 79:1–8. https://doi.org/10.1016/j.envsci.2017.10.008

    Article  Google Scholar 

  • Mach KJ, Mastrandrea MD, Freeman PT, Field CB (2017) Unleashing expert judgment in assessment. Glob Environ Chang 44:1–14. https://doi.org/10.1016/j.gloenvcha.2017.02.005

    Article  Google Scholar 

  • Manning M, Petit M, Easterling D, Murphy D, Patwardhan A, Rogner H-H, Swart R, Yohe G (2004) IPCC workshop on describing scientific uncertainties in climate change to support analysis of risk and of options: workshop report. Intergovernmental Panel on Climate Change (IPCC), Geneva

    Google Scholar 

  • Maraun D, Widmann M (2018) Statistical downscaling and bias correction for climate research, 1st edn. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Maraun D, Widmann M, Gutiérrez JM, Kotlarski S, Chandler RE, Hertig E, Wibig J, Huth R, Wilcke RAI (2015) VALUE: a framework to validate downscaling approaches for climate change studies. Earths Future 3:1–14. https://doi.org/10.1002/2014EF000259

    Article  Google Scholar 

  • Maraun D, Shepherd TG, Widmann M, Zappa G, Walton D, Gutiérrez JM, Hagemann S, Richter I, Soares PMM, Hall A, Mearns LO (2017) Towards process-informed bias correction of climate change simulations. Nat Clim Chang 7:664–773. https://doi.org/10.1038/nclimate3418

    Article  Google Scholar 

  • Mastrandrea MD, Field CB, Stocker TF, Edenhofer O, Ebi KL, Frame DJ, Held H, Kriegler E, Mach K, Matschoss PR, Plattner G-K, Yohe GW, Zwiers FW (2010) Guidance note for lead authors of the IPCC fifth assessment report on consistent treatment of uncertainties

    Google Scholar 

  • Mastrandrea MD, Mach KJ, Plattner G-K, Edenhofer O, Stocker TF, Field CB, Ebi KL, Matschoss PR (2011) The IPCC AR5 guidance note on consistent treatment of uncertainties: a common approach across the working groups. Clim Chang 108:675–691. https://doi.org/10.1007/s10584-011-0178-6

    Article  Google Scholar 

  • Mitchell J, Manabe S, Meleshko V, Tokioka T (1990) Equilibrium climate change - and its implications for the future. In: Houghton JT, Jenkins GJ, Ephraums JJ (eds) Climate change: the IPCC scientific assessment. Cambridge University Press, Cambridge, pp 131–164

    Google Scholar 

  • Moss R, Schneider S (2000) Uncertainties in the IPCC TAR: recommendations to lead authors for more consistent assessment and reporting. In: Pachauri R, Taniguchi T, Tanaka K (eds) Guidance papers on the cross-cutting issues of the third assessment report of the IPCC. World Meteorological Organization, Geneva, pp 33–51

    Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756. https://doi.org/10.1038/nature08823

    Article  Google Scholar 

  • Nakićenović N, Swart R (eds) (2000) Special report on emissions scenarios: a special report of working group III of the intergovernmental panel on climate change. Cambridge University Press, Cambridge

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Oliveira GG, Pedrollo OC, Castro NMR (2015) Stochastic approach to analyzing the uncertainties and possible changes in the availability of water in the future based on scenarios of climate change. Hydrol Earth Syst Sci 19:3585–3604. https://doi.org/10.5194/hess-19-3585-2015

    Article  Google Scholar 

  • Oppenheimer M, Little CM, Cooke RM (2016) Expert judgement and uncertainty quantification for climate change. Nat Clim Chang 6:445–451. https://doi.org/10.1038/nclimate2959

    Article  Google Scholar 

  • Perazzoli M, Pinheiro A, Kaufmann V (2013) Assessing the impact of climate change scenarios on water resources in southern Brazil. Hydrol Sci J 58:77–87. https://doi.org/10.1080/02626667.2012.742195

    Article  Google Scholar 

  • Pinheiro A, Graciano RLG, Kaufmann V (2013) Simulating effects of climate scenarios on hydrological processes in southern Brazil using a lysimeter. Int J Climatol 33:2206–2214. https://doi.org/10.1002/joc.3591

    Article  Google Scholar 

  • Prudhomme C, Davies H (2009) Assessing uncertainties in climate change impact analyses on the river flow regimes in the UK. Part 1: baseline climate. Clim Chang 93:177–195. https://doi.org/10.1007/s10584-008-9464-3

    Article  Google Scholar 

  • Ribeiro Júnior L, Zuffo A, Silva B (2016) Development of a tool for hydroeletric reservoir operation with multiple uses considering effects of climate changes. Case study of Furnas HPP. Rev Bras Recur Hídr 21:300–313. https://doi.org/10.21168/rbrh.v21n2.p300-313

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Sorribas MV, Paiva RCD, Melack JM, Bravo JM, Jones C, Carvalho L, Beighley E, Forsberg B, Costa MH (2016) Projections of climate change effects on discharge and inundation in the Amazon basin. Clim Chang 136:555–570. https://doi.org/10.1007/s10584-016-1640-2

    Article  Google Scholar 

  • Stainforth DA, Downing TE, Washington R, Lopez A, New M (2007) Issues in the interpretation of climate model ensembles to inform decisions. Philos Trans R Soc A Math Phys Eng Sci 365:2163–2177. https://doi.org/10.1098/rsta.2007.2073

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498. https://doi.org/10.1175/BAMS-D-11-00094.1

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Torres RR, Lapola DM, Marengo JA, Lombardo MA (2012) Socio-climatic hotspots in Brazil. Clim Chang 115:597–609. https://doi.org/10.1007/s10584-012-0461-1

    Article  Google Scholar 

  • Vetter T, Reinhardt J, Flörke M, van Griensven A, Hattermann F, Huang S, Koch H, Pechlivanidis IG, Plötner S, Seidou O, Su B, Vervoort RW, Krysanova V (2017) Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins. Clim Chang 141:419–433. https://doi.org/10.1007/s10584-016-1794-y

    Article  Google Scholar 

  • Viola MR, de Mello CR, Chou SC, Yanagi SN, Gomes JL (2015) Assessing climate change impacts on upper Grande River basin hydrology, Southeast Brazil. Int J Climatol 35:1054–1068. https://doi.org/10.1002/joc.4038

    Article  Google Scholar 

  • WMO (2008) Guide to hydrological practices volume I. hydrology – from measurement to hydrological information, vol 2, 6th edn. World Meteorological Organization (WMO), Geneva

    Google Scholar 

  • Yohe G, Oppenheimer M (2011) Evaluation, characterization, and communication of uncertainty by the intergovernmental panel on climate change—an introductory essay. Clim Chang 108:629–639. https://doi.org/10.1007/s10584-011-0176-8

    Article  Google Scholar 

  • Zaninelli PG, Menéndez CG, Falco M, López-Franca N, Carril AF (2018) Future hydroclimatological changes in South America based on an ensemble of regional climate models. Clim Dyn. https://doi.org/10.1007/s00382-018-4225-0

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Funding

The authors acknowledge the Brazilian National Council for Scientific and Technological Development (CNPq) for funding this study (Grant Numbers: 150768/2017-6 and 159528/2018-6)

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Authors and Affiliations

  1. Graduate Program in Environmental Engineering, Federal University of Santa Catarina, Florianópolis, 88040-900, Brazil

    Pablo Borges de Amorim

  2. Department of Sanitary and Environmental Engineering, Federal University of Santa Catarina, Florianópolis, 88040-900, Brazil

    Pedro B. Chaffe

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  1. Pablo Borges de Amorim
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Correspondence to Pablo Borges de Amorim.

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Borges de Amorim, P., Chaffe, P.B. Towards a comprehensive characterization of evidence in synthesis assessments: the climate change impacts on the Brazilian water resources. Climatic Change 155, 37–57 (2019). https://doi.org/10.1007/s10584-019-02430-9

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