Water scarcity in Brazil: part 1—regionalization of the AWARE model characterization factors

Abstract

Purpose

This paper presents the regionalized water scarcity characterization factors (CFs) of the available water remaining (AWARE) model, which was found by a previous study, on the water scarcity in Brazil, to be the most indicative characterization model for the water-scarce regions in Brazil. We used the national database and hydrographic delimitations defined by the National Water Agency (Agência Nacional de Águas — ANA) to generate the regionalized AWARE BR CFs.

Methods

The CFs were regionalized by hydrographic delimitations used by ANA: (i) State Hydrographic Units (SHU) and (ii) Hydrographic Regions (HR). These AWARE BR CFs were compared with the factors originally proposed by WULCA (2018) and with the Scarcity Index used by ANA to identify the scarcest regions in the country. Finally, the AWARE and AWARE BR factors were applied to a case study of Brazilian melons, evaluating the regionalization effects on the results of water scarcity analysis.

Results and discussion

The AWARE BR CFs demonstrate most consistency with the regions recognized by ANA to have water scarcity problems, such as the semiarid region. Approximately 12% of the SHUs exhibited maximum water scarcity (CF = 100) during the entire year, while 11% presented minimum scarcity factors (CF = 0.1). The comparison of hydrologic data from ANA with those from WaterGAP indicated that water availability was overestimated in WaterGAP, while demand was underestimated in different basins. The comparison of AWARE BR CFs with ANA Scarcity Index values indicated more similarity (smaller residual error) than the comparison of AWARE BR CFs with AWARE. The case study regarding the impact of water scarcity on melons showed a significant difference between characterization factors and, consequently, in the values of impact.

Conclusions

AWARE BR factors generated with national characterization data are adapted to the different regions of Brazil, exhibiting higher sensitivity to the semiarid region. This regionalization provided a more accurate representation of the scarcity in smaller basins located in larger basins, characterized by large climate variation.

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References

  1. Agência Nacional de Águas (2005) Portal Hidroweb. Brasília, DF. http://www.snirh.gov.br/hidroweb/publico/medicoes_historicas_abas.jsf. Accessed 18 Sept 2018

  2. Agência Nacional de Águas (2013) Conjuntura dos Recursos Hídricos no Brasil. Brasília, DF. http://www3.snirh.gov.br/portal/snirh/centrais-de-conteudos/conjuntura-dos-recursos-hidricos/conj2013_rel.pdf. Accessed 15 May 2018

  3. Agência Nacional de Águas (2015) Nota Técnica n° 56/2015/SPR. Brasília, DF

  4. Agência Nacional de Águas (2016) Nota Técnica n° 16/2016/SPR. Brasília, DF

  5. Álcamo J, Döll P, Henrichs T, Kaspar F, Lehner B, Rösch T, Siebert S (2003) Development and testing of the WaterGAP 2 global model of water use and availability. Hydrolog Sci J 48(3):317–337

    Article  Google Scholar 

  6. Almeida Castro AL, Andrade EP, de Alencar Costa M, de Lima Santos T, Ugaya CML, de Figueirêdo MCB (2018) Applicability and relevance of water scarcity models at local management scales: review of models and recommendations for Brazil. Environ Impact Assess Rev 72:126–136

    Article  Google Scholar 

  7. Ashley C, Cadilhon JJ (2018) Reforming water policies in agriculture: lessons from past reforms. OECD food, agriculture and fisheries papers (OECD) eng no. 113. https://www.oecd-ilibrary.org/docserver/1826beee-en.pdf?expires=1550230354&id=id&accname=guest&checksum=F55EEFF0C4760CC387AE0C5A146B9E3F. Accessed 15 Feb 2019

  8. Boulay AM, Bare J, Benini L, Berger M, Lathuillière MJ, Manzardo A, Ridoutt B (2018) The WULCA consensus characterization model for water scarcity footprints: assessing impacts of water consumption based on available water remaining (AWARE). Int J Life Cycle Assess 23(2):368–378

    Article  Google Scholar 

  9. BRASIL. MMA-Ministério do Meio Ambiente. Secretaria de Recursos Hídricos (2006a) Caderno da região hidrográfica do Atlântico Nordeste Oriental. http://www.mma.gov.br/estruturas/161/_publicacao/161_publicacao03032011024510.pdf. Accessed 08 Aug 2018

  10. BRASIL. MMA-Ministério do Meio Ambiente. Secretaria de Recursos Hídricos (2006b) Caderno da região hidrográfica do São Francisco. http://www.mma.gov.br/estruturas/161/_publicacao/161_publicacao03032011023538.pdf. Accessed 09 Aug 2018

  11. de Moura MSB, Galvincio J, Brito LDL, Souza LD, Sá I, da Silva TGF (2006) Clima e água de chuva no Semi-Árido. Embrapa Semiárido-Capítulo em livro científico (ALICE)

  12. Farell BC (2013) Diseño de una metodología para reportar la huella de agua. Thesis

  13. Figueirêdo MCB, de Boer IJ, Kroeze C, da Silva Barros V, de Sousa JA, de Aragão FS, Potting J (2014) Reducing the impact of irrigated crops on freshwater availability: the case of Brazilian yellow melons. Int J Life Cycle Assess 19(2):437–448

    Article  Google Scholar 

  14. Instituto Brasileiro de Geografia e Estatística (IBGE) (2011) Censo demográfico 2010. Características da população e dos domicílios: resultados do universo. Rio de Janeiro: IBGE. https://biblioteca.ibge.gov.br/visualizacao/periodicos/93/cd_2010_caracteristicas_populacao_domicilios.pdf

  15. Instituto Brasileiro de Geografia e Estatística (IBGE) (2018) Produção agrícola municipal. http://www.sidra.ibge.gov.br. Accessed 18 June 2018

  16. ISO, International Organization for Standardization (2014) 14046 environmental management, water footprint—principles, requirements and guidelines. International Organization for Standardization, Geneva

    Google Scholar 

  17. Kounina A, Margni M, Bayart JB, Boulay AM, Berger M, Bulle C, Núñez M (2013) Review of methods addressing freshwater use in life cycle inventory and impact assessment. Int J Life Cycle Assess 18(3):707721

    Article  Google Scholar 

  18. Marengo JA, Alves LM, Beserra EA, Lacerda FF (2011) Variabilidade e mudanças climáticas no semiárido brasileiro. Recursos hídricos em regiões áridas e semiáridas, pp 384–422

  19. Marengo JA, Nobre CA, Seluchi ME, Cuartas A, Alves LM, Mendiondo EM, Sampaio G (2015) A seca e a crise hídrica de 2014-2015 em São Paulo. Revista USP (106):31–44

  20. Mekonnen MM, Hoekstra AY (2016) Four billion people facing severe water scarcity. Sci Adv 2(2):e1500323. https://doi.org/10.1126/sciadv.1500323

    Article  Google Scholar 

  21. Ministério do Desenvolvimento, Indústria e Comércio (MDIC) [Brazilian Ministry of Development, Industry and Commerce] (2018) COMEX STATE. http://comexstat.mdic.gov.br/pt/geral. Accessed 25 June 2018

  22. Núñez M, Pfister S, Vargas M, Antón A (2015) Spatial and temporal specific characterisation factors for water use impact assessment in Spain. Int J Life Cycle Assess 20(1):128–138. https://doi.org/10.1007/s11367-014-0803-5

    CAS  Article  Google Scholar 

  23. Pastor AV, Ludwig F, Biemans H, Hoff H, Kabat P (2013) Accounting for environmental flow requirements in global water assessments. Hydrol Earth Syst Sci Discuss 10(12):14987–15032. https://doi.org/10.5194/hess-18-5041-2014

    Article  Google Scholar 

  24. Peña CA, Huijbregts MA (2014) The blue water footprint of primary copper production in northern Chile. J Ind Ecol 18(1):49–58

    Article  Google Scholar 

  25. Pfister S, Bayer P (2014) Monthly water stress: spatially and temporally explicit consumptive water footprint of global crop production. J Clean Prod 73:52–62

    Article  Google Scholar 

  26. Pfister S, Koehler A, Hellweg S (2009) Assessing the environmental impacts of freshwater consumption in LCA. Environ Sci Technol 43(11):4098–4104

    CAS  Article  Google Scholar 

  27. Santos TL, Nunes ABA, Giongo V, da Silva Barros V, de Figueirêdo MCB (2018) Cleaner fruit production with green manure: the case of Brazilian melons. J Clean Prod 181:260–270

    Article  Google Scholar 

  28. WULCA (2018) The AWARE method: available WAter REmaning. http://www.wulca-waterlca.org/aware.html. Accessed 03 March 2018

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Acknowledgements

We acknowledge the National Water Agency (Agência Nacional de Águas — ANA) for providing hydro-geographic data, and the National Council for the Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq) for the financial support. We also wish to extend our thanks to the Brazilian Life-Cycle Impact Assessment Research Network (Rede Brasileira de Pesquisa em Impacto da Avaliação do Ciclo de Vida — RAICV) for the scientific support.

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Correspondence to Edilene Pereira Andrade.

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Andrade, E.P., de Araújo Nunes, A.B., de Freitas Alves, K. et al. Water scarcity in Brazil: part 1—regionalization of the AWARE model characterization factors. Int J Life Cycle Assess 25, 2342–2358 (2020). https://doi.org/10.1007/s11367-019-01643-5

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Keywords

  • Brazilian semiarid
  • Characterization factors
  • Hydrographic regions
  • State hydrographic units
  • Water scarcity