Abstract

Extreme floods are often devastating, directly affecting millions of people worldwide. Because of the lack of infrastructure and proper hydrological monitoring, flood-related hazards in developing countries are magnified. Therefore, regionalization approaches associated with flood indices stand out for allowing reliable design flood estimates and enabling the identification of their driving mechanisms. In this context, the present study aims to evaluate flood timing and regularity using directional statistics for hydrological regionalization. A robust methodological framework was proposed combining fuzzy logic algorithms and the seasonality index, considering maximum annual streamflow data for Southern Brazil. It was found that major floods take place between midwinter and early spring with no well-defined spatial pattern; however, a significant decrease in their regularity was observed westward. Based on these characteristics, two clustering scenarios were proposed. According to the heterogeneity measure, hydrologically homogeneous regions were formed for the entire study area, except for the mountainous region in the northeast. Four main flood-driving mechanisms were identified: frontal systems, maritime air masses, consecutive rainfall days, and antecedent soil moisture.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors wish to thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for scholarships to the second (308645/2017-0) and third (301556/2017-2) authors and for a research grant to the second author (485279/2013-4), Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS) for research grants (2082-2551/13-0; 16/2551-0000 247-9) to the second author, and the Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) for a research grant (PPM VIII 071/2014) to the third author. The data used in the present study may be found at the HidroWeb platform available at the National Water Agency of Brazil website.

References

Abida, H., and M. Ellouze. 2008. “Probability distribution of flood flows in Tunisia.” Hydrol. Earth Syst. Sci. 12 (1): 703–714. https://doi.org/10.5194/hess-12-703-2008.
Alvares, C. A., J. L. Stape, P. C. Sentelhas, J. L. M. Gonçalves, and G. Sparovek. 2013. “Köppen’s climate classification map for Brazil.” Meteorol. Z. 22 (6): 711–728. https://doi.org/10.1127/0941-2948/2013/0507.
ANA (Agência Nacional de Águas). 2017. “Conjuntura dos Recursos Hídricos no Brasil 2017—Relatório Pleno. Brasília—Distrito Federal.” Accessed February 19, 2018. http://conjuntura.ana.gov.br/.
Basu, B., and V. V. Srinivas. 2015. “Analytical approach to quantile estimation in regional frequency analysis based on fuzzy framework.” J. Hydrol. 524 (1): 30–43. https://doi.org/10.1016/j.jhydrol.2015.02.026.
Berghuijs, W. R., R. A. Woods, C. J. Hutton, and M. Sivapalan. 2016. “Dominant flood generating mechanisms across the United States.” Geophys. Res. Lett. 43 (9): 4382–4390. https://doi.org/10.1002/2016GL068070.
Beskow, S., D. N. Lloyd, and C. R. Mello. 2013. “Hydrological prediction in a tropical watershed dominated by oxisols using a distributed hydrological model.” Water Resour. Manage. 27 (2): 341–363. https://doi.org/10.1007/s11269-012-0189-8.
Beskow, S., C. R. Mello, M. M. Vargas, L. L. Corrêa, T. L. Caldeira, M. F. Durães, and M. S. Aguiar. 2016. “Artificial intelligence techniques coupled with seasonality measures for hydrological regionalization of Q90 under Brazilian conditions.” J. Hydrol. 541 (1): 1406–1419. https://doi.org/10.1016/j.jhydrol.2016.08.046.
Bich, T. H., L. N. Quang, L. T. T. Ha, T. T. D. H. Hanh, and D. Guha-Sapir. 2011. “Impacts of flood on health: Epidemiologic evidence from Hanoi, Vietnam.” Global Health Action 4 (1): 6356. https://doi.org/10.3402/gha.v4i0.6356.
Black, A. R., and A. Werritty. 1997. “Seasonality of flooding: A case study of North Britain.” J. Hydrol. 195 (1–4): 1–25. https://doi.org/10.1016/S0022-1694(96)03264-7.
Brazilian Ministry of National Integration. 2018. “Reconhecimentos de Situação de Emergência (SE) e Estado de Calamidade Pública (ECP) realizadas entre 01/01/2016 e 31/12/2016—Rio Grande do Sul.” Accessed February 11, 2018. http://www.mi.gov.br/reconhecimentos-realizados.
Burn, D. H. 1997. “Catchment similarity for regional flood frequency analysis using seasonality measures.” J. Hydrol. 202 (1–4): 212–230. https://doi.org/10.1016/S0022-1694(97)00068-1.
Burn, D. H., P. H. Whitfield, and M. Sharif. 2016. “Identification of changes in floods and flood regimes in Canada using peaks over threshold approach.” Hydrol. Processes 30 (18): 3303–3314. https://doi.org/10.1002/hyp.10861.
Caldeira, T. L., S. Beskow, C. R. Mello, L. C. Faria, M. R. Souza, and H. A. S. Guedes. 2015. “Modelagem probabilística de eventos de precipitação extrema no estado do Rio Grande do Sul.” [In Portuguese.] Revista Brasileira de Engenharia Agrícola e Ambiental 19 (3): 197–203. https://doi.org/10.1590/1807-1929/agriambi.v19n3p197-203.
Cassalho, F., S. Beskow, C. R. Mello, M. M. Moura, L. Kerstner, and L. F. Ávila. 2018. “At-site flood frequency analysis coupled with multiparameter probability distributions.” Water Resour. Manage. 32 (1): 285–300. https://doi.org/10.1007/s11269-017-1810-7.
Cassalho, F., S. Beskow, C. R. Mello, M. M. Moura, L. F. Oliveira, and M. S. Aguiar. 2019. “Artificial intelligence for identifying hydrologically homogenous regions: A state-of-the-art regional flood frequency analysis.” Hydrol. Processes 33 (7): 1101–1116. https://doi.org/10.1002/hyp.13388.
Castellarin, A., D. H. Burn, and A. Brath. 2001. “Assessing the effectiveness of hydrological similarity measures for flood frequency analysis.” J. Hydrol. 241 (3–4): 270–285. https://doi.org/10.1016/S0022-1694(00)00383-8.
Chen, L., V. P. Singh, S. Guo, B. Fang, and P. Liu. 2013. “A new method for identification of flood seasons using directional statistics.” Hydrol. Sci. J. 58 (1): 28–40. https://doi.org/10.1080/02626667.2012.743661.
Collischonn, W., and C. E. M. Tucci. 2005. “Previsão sazonal de vazão na Bacia do Rio Uruguai 1: Ajuste e verificação do modelo hidrológico distribuído.” Revista Brasileira de Recursos Hídricos 10 (4): 43–59. https://doi.org/10.21168/rbrh.v10n4.p43-59.
Corrêa, L. L. 2014. “Implementação e Análise de Técnicas de Inteligência Artificial Aplicadas à Clusterização em Recursos Hídricos.” Ph.D. Dissertação, Center for Technological Development, Universidade Federal de Pelotas.
Cunderlik, J. M., and D. H. Burn. 2006. “Switching the pooling similarity distances: Mahalanobis for Euclidean.” Water Resour. Res. 42 (3): W03409. https://doi.org/10.1029/2005WR004245.
Cunderlik, J. M., T. B. Ourda, and B. Bobée. 2004. “Determination of flood seasonality from hydrological records.” Hydrol. Sci. J. 49 (3): 511–526. https://doi.org/10.1623/hysj.49.3.511.54351.
Farsadnia, F., M. R. Kamrood, A. M. Nia, R. Modarres, M. T. Bray, D. Han, and J. Sadatinejad. 2014. “Identification of homogenous regions for regionalization of watersheds by two-level self-organizing feature maps.” J. Hydrol. 509 (1): 387–397. https://doi.org/10.1016/j.jhydrol.2013.11.050.
Hosking, J. R. M., and J. R. Wallis. 1997. Regional frequency analysis: An approach based on L-moments, 224. Cambridge: Cambridge University Press.
IBGE (Instituto Brasileiro de Geografia e Estatística). 2016. “Estimativas da população residente no Brasil e unidades da federação com data de referência em 1º de julho de 2016.” Accessed December 2, 2016. ftp://ftp.ibge.gov.br/Estimativas_de_Populacao/Estimativas_2016/estimativa_dou_2016_20160913.pdf.
INMET (Instituto Nacional de Meteorologia). 2017. “Normais Climatológicas do Brasil 1961-1990.” Accessed August 11, 2017. http://www.inmet.gov.br/portal/index.php?r=clima/normaisclimatologicas.
Jeneiová, K., S. Kohnová, J. Hall, and J. Parajka. 2016. “Variability of seasonal floods in the Upper Danube river basin.” J. Hydrol. Hydromechanics 64 (4): 357–366. https://doi.org/10.1515/johh-2016-0037.
Köplin, N., B. Schädler, D. Viviroli, and R. Weingartner. 2014. “Seasonality and magnitude of flood in Switzerland under future climate change.” Hydrol. Processes 28 (4): 2567–2578. https://doi.org/10.1002/hyp.9757.
Koutroulis, A. G., I. K. Tsanis, and I. N. Daliakopoulos. 2010. “Seasonality of flood and their hydrometeorologic characteristics in the island of Crete.” J. Hydrol. 394 (1–2): 90–100. https://doi.org/10.1016/j.jhydrol.2010.04.025.
Marengo, J. A., L. M. Alves, W. R. Soares, and D. A. Rodriguez. 2013. “Two contrasting severe seasonal extremes in tropical South America in 2012: Flood in Amazonia and drought in Northeast Brazil.” Am. Meteorol. Soc. 26 (22): 9137–9154. https://doi.org/10.1175/JCLI-D-12-00642.1.
Ouarda, T. B. M. J., J. M. Cunderlik, A. St-Hilaire, M. Barbet, P. Bruneau, and B. Bobée. 2006. “Data-based comparison of seasonality-based regional flood frequency methods.” J. Hydrol. 330 (1–2): 329–339. https://doi.org/10.1016/j.jhydrol.2006.03.023.
Parajka, J., et al. 2010. “Seasonal characteristics of flood regimes across the Alpine-Carpathian range.” J. Hydrol. 394 (1–2): 78–89. https://doi.org/10.1016/j.jhydrol.2010.05.015.
Pewsey, A., M. Neuhäuser, and G. D. Ruxton. 2013. Circular statistics in R, 182. Oxford, UK: Oxford University Press.
Rao, A. R., and K. H. Hamed. 2000. Flood frequency analysis, 376. Boca Raton, FL: CRC Press.
Rao, A. R., and V. V. Srinivas. 2008. Regionalization of watersheds: An approach based on cluster analysis, 241. Dordrecht, Netherlands: Springer.
Reboita, M. S., M. A. Gan, R. P. Rocha, and T. Ambrizzi. 2010. “Regimes de precipitação na América do Sul: uma revisão bibliográfica.” [In Portuguese.] Revista Brasileira de Meteorologia 25 (2): 185–204. https://doi.org/10.1590/S0102-77862010000200004.
Rossum G. V. 1995. Python tutorial. Amsterdam, Netherlands: Centrum voor Wiskunde en Informatica.
Sadri, S., and D. H. Burn. 2011. “A fuzzy c-means approach for regionalization using a bivariate homogeneity and discordancy approach.” J. Hydrol. 401 (3–4): 231–239. https://doi.org/10.1016/j.jhydrol.2011.02.027.
Sarhadi, A., and R. Modarres. 2011. “Flood seasonality-based regionalization methods: A data-based comparison.” Hydrol. Processes 25 (23): 3613–3624. https://doi.org/10.1002/hyp.8088.
Villarini, G. 2016. “On the seasonality of flooding across the continental United States.” Adv. Water Resour. 87 (1): 80–91. https://doi.org/10.1016/j.advwatres.2015.11.009.
Ye, S., H. Li, L. R. Leung, J. Guo, Q. Ran, Y. Demissie, and M. Sivapalan. 2017. “Understanding flood seasonality and its temporal shifts within the contiguous United States.” J. Hydrometeorol. 18 (7): 1997–2009. https://doi.org/10.1175/JHM-D-16-0207.1.

Information & Authors

Information

Published In

Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 24Issue 8August 2019

History

Received: Jul 23, 2018
Accepted: Mar 14, 2019
Published online: Jun 11, 2019
Published in print: Aug 1, 2019
Discussion open until: Nov 11, 2019

Permissions

Request permissions for this article.

Authors

Affiliations

Water Resources Engineer, Remote Sensing Dept., National Institute for Space Research, Remote Sensing Graduate Program, 1758 dos Astronautas Ave., Jardim da Granja, São José dos Campos, SP 12227-010, Brazil (corresponding author). ORCID: https://orcid.org/0000-0001-9496-2910. Email: [email protected]
Samuel Beskow, Ph.D.
Associate Professor, Center for Technological Development, Water Resources Engineering, Hydrology and Hydrological Modeling Laboratory, Federal Univ. of Pelotas, 1 Gomes Carneiro St., Pelotas, RS 96010-610, Brazil.
Carlos Rogério de Mello, Ph.D. https://orcid.org/0000-0002-6033-5342
Associate Professor, Dept. of Water Resources, Federal Univ. of Lavras, Caixa Postal 3037, Lavras, MG 37200-000, Brazil. ORCID: https://orcid.org/0000-0002-6033-5342
Leroi Floriano Oliveira
Master Student, Center for Technological Development, Computer Science Graduate Program, Federal Univ. of Pelotas, 1 Gomes Carneiro St., Pelotas, RS 96010-610, Brazil.
Marilton Sanchotene de Aguiar, Ph.D. https://orcid.org/0000-0002-5247-6022
Associate Professor, Center for Technological Development, Computer Science Program, Federal Univ. of Pelotas, 1 Gomes Carneiro St., Pelotas, RS 96010-610, Brazil. ORCID: https://orcid.org/0000-0002-5247-6022

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share