Abstract
The estimation of the flood area inaccuracies by the propagation of Manning’s coefficient uncertainty is crucial for safety plans of dam-breaks. However, the probabilistic studies of fluvial inundation concentrate on the 1D models, and those that address to evaluate the variable floodplain roughness based on the land cover are deterministic approaches. Thus, this study proposed to analyze the propagation of Manning's coefficient uncertainty, whose variation was obtained by (1) floodplain land use; (2) Monte Carlo method considering different distributions, in a 2D model for Três Maria's dam (Brazil). The results indicated: (1) the distributed coefficient reduced by 9% the flood area from deterministic scenarios with the fixed coefficient; (2) the normal distribution created higher variability in analyzed parameters than a uniform distribution, although we found no significant difference between the distributions. The understanding of input variables in 2D models may contribute to the management of dam failure risk.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability statement
All simulation cases and scripts that support the findings of this study are available from the corresponding author upon reasonable request.
References
Agência Nacional de Águas e Saneamento Básico (ANA) (2016) Guia de orientação e formulários do plano de ação de emergência—PAE. https://www.snisb.gov.br/Entenda_Mais/volume-iv-guia-de-orientacao-e-formularios-dos-planos-de-acao-de-emergencia-2013-pae/@@download/file/GuiaOrientacaoFormulariosPlanosAcaoEmergencia_PAE.PDF. Accessed 31 May 2022
Agência Nacional de Águas e Saneamento Básico (ANA) (2019) Relatório de segurança de barragens. https://www.snisb.gov.br/relatorio-anual-de-seguranca-de-barragem/2019/rsb19-v0.pdf. Accessed 05 Aug 2023
Alfieri L, Salamon P, Bianchi A et al (2013) Advances in pan-European flood hazard mapping. Hydrol Process 28:4067–4077. https://doi.org/10.1002/hyp.9947
Ávila JP de, Bicudo RI, Pierre LF (1982) Main brazilian dams: design, construction and performance. Brazilian Committee on Large Dams, São Paulo
Bates PD, Horritt MS, Aronica G, Beven K (2004) Bayesian updating of flood inundation likelihoods conditioned on flood extent data. Hydrol Process 18:3347–3370. https://doi.org/10.1002/hyp.1499
Bellos V, Tsakiris VK, Kopsiaftis G, Tsakiris G (2020) Propagating dam breach parametric uncertainty in a river reach using the HEC-RAS software. Hydrol 7:72. https://doi.org/10.3390/hydrology7040072
Beven K, Freer J (2001) Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. J Hydrol 249:11–29. https://doi.org/10.1016/S0022-1694(01)00421-8
Brasil (2010) Política Nacional de Segurança de Barragens. https://www.planalto.gov.br/ccivil_03/_ato2007-2010/2010/lei/l12334.htm. Accessed 31 May 2022
Call BC, Belmont P, Schmidt JC, Wilcock PR (2017) Changes in floodplain inundation under nonstationary hydrology for an adjustable, alluvial river channel. Water Resour Res 53:3811–3834. https://doi.org/10.1002/2016WR020277
Celik IB, Ghia U, Roache PJ et al (2008) Procedure for estimation and reporting of uncertainty due to discretization in CFD applications. J Fluids Eng DOI 10(1115/1):2960953
Chaudhry MH (1993) Open-channel flow. Prentice Hall, Englewood Cliffs, p 2008
Chow VT (1959) Open-channel hydraulics. McGraw-Hill Book Company, Tokyo
Companhia Energética de Minas Gerais (CEMIG) (2020) Usina hidrelétrica de Três Marias. https://www.cemig.com.br/usina/tres-marias/. Accessed 05 Aug 2023
Costabile P, Costanzo C, Kalogiros J, Bellos V (2023) Toward street‐level nowcasting of flash floods impacts based on HPC hydrodynamic modeling at the watershed scale and high‐resolution weather radar data. Water Resour Res 59:e2023WR034599. https://doi.org/10.1029/2023WR034599
Curtis J (2016) Manning’s n values for various land covers to use for dam breach analyses by NRCS in Kansas. Sustainable Environmental Consultants. https://rashms.com/wp-content/uploads/2021/01/Mannings-n-values-NLCD-NRCS.pdf. Accessed 06 August 2023
Di Baldassarre G, Schumann G, Bates PD et al (2010) Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches. Hydrol Sci J 55:364–376. https://doi.org/10.1080/02626661003683389
Dimitriadis P, Tegos A, Oikonomou A et al (2016) Comparative evaluation of 1D and quasi-2D hydraulic models based on benchmark and real-world applications for uncertainty assessment in flood mapping. J Hydrol 534:478–492. https://doi.org/10.1016/j.jhydrol.2016.01.020
Ding Y, Jia Y, Wang SSY (2004) Identification of Manning’s roughness coefficients in shallow water flows. J Hydraul Eng 130:501–510. https://doi.org/10.1061/(ASCE)0733-9429(2004)130:6(501)
Domeneghetti A, Vorogushyn S, Castellarin A et al (2013) Probabilistic flood hazard mapping: effects of uncertain boundary conditions. Hydrol Earth Syst Sci 17:3127–3140. https://doi.org/10.5194/hess-17-3127-2013
D’Oria M, Maranzoni A, Mazzoleni M (2019) Probabilistic assessment of flood hazard due to levee breaches using fragility functions. Water Resour Res 55:8740–8764. https://doi.org/10.1029/2019WR025369
Forzieri G, Moser G, Vivoni ER et al (2010) Riparian vegetation mapping for hydraulic roughness estimation using very high resolution remote sensing data fusion. J Hydraul Eng 136:855–867. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000254
Froehlich DC (2016) Empirical model of embankment dam breaching. In: Constantinescu G, Garcia M, Hanes D (eds) River flow 2016, 1st edn. CRC Press, Iowa
Horrit MS, Bates PD (2002) Evaluation of 1D and 2D numerical models for predicting river flood inundation. J Hydrol 268:87–89. https://doi.org/10.1016/S0022-1694(02)00121-X
Infraestrutura de Dados Espaciais (IDE-Sisema) (2017) Cobertura da terra—modis 2012. http://idesisema.meioambiente.mg.gov.br/. Accessed 20 Aug 2021
International Commission on large dams (ICOLD) (2011) Constitution Statuts. https://www.icold-cigb.org/userfiles/files/CIGB/INSTITUTIONAL_FILES/Constitution2011.pdf. . Accessed 31 May 2022
Jung Y, Merwade V (2012) Uncertainty quantification in flood inundation mapping using generalized likelihood uncertainty estimate and sensitivity analysis. J Hydrol Eng 17:507–520. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000476
Landau DP, Binder K (2009) A guide to Monte Carlo simulations in statistical physics. Cambridge University Press, Cambridge
Li Z, Zhang J (2001) Calculation of field Manning’s roughness coefficient. Agric Water Manag 49:153–161. https://doi.org/10.1016/S0378-3774(00)00139-6
Lim NJ, Brandt SA (2019) Flood map boundary sensitivity due to combined effects of DEM resolution and roughness in relation to model performance. Geomat Nat Hazard Risk 10:1613–1647. https://doi.org/10.1080/19475705.2019.1604573
Liu Z, Merwade V, Jafarzadegan K (2019) Investigating the role of model structure and surface roughness in generating flood inundation extents using one- and two-dimensional hydraulic models. J Flood Risk Manag 12:e12347. https://doi.org/10.1111/JFR3.12347
Massad F (2010) Obras de terra. Oficina de Textos, São Paulo
Matos AJS, Pioltine A, Mauad FF, Barbosa AA (2011) Metodologia para a caracterização do coeficiente de manning variando na seção transversal e ao longo do canal estudo de caso bacia do alto sapucaí-MG. Rev Bras Recur Hídr 16:21–28. https://doi.org/10.21168/rbrh.v16n4.p21-28
Melo M, Eleutério J (2023) Probabilistic analysis of floods from tailings dam failures: a method to analyze the impact of rheological parameters on the HEC-RAS Bingham and Herschel–Bulkley models. Water 15:2866. https://doi.org/10.3390/w15162866
Milanez B, Ali SH, Oliveira JAP (2021) Mapping industrial disaster recovery: lessons from mining dam failures in Brazil. The Extr Ind Soc 8:100900. https://doi.org/10.1016/j.exis.2021.100900
Papaioannou G, Vasiliades L, Loukas A, Aronica GT (2017) Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling. Adv Geosci 44:23–24. https://doi.org/10.5194/adgeo-44-23-2017
Pappenberger F, Beven K, Horritt M, Blazkova S (2005) Uncertainty in the calibration of effective roughness parameters in HEC-RAS using inundation and downstream level observations. J Hydrol 302:46–69. https://doi.org/10.1016/j.jhydrol.2004.06.036
Pinto EJA, Alves MMS (2001) Regionalização de vazões das sub-bacias 40 e 41: alto São Francisco. Repositório Institucional de Geociências—CPRM. https://rigeo.sgb.gov.br/handle/doc/20881. Accessed 31 May 2022
Qi H, Altinakar MS (2012) GIS-based decision support system for dam break flood management under uncertainty with two-dimensional numerical simulations. J Water Res Plan Manag 38:334–341. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000192
Romanowicz R, Beven K (2003) Estimation of flood inundation probabilities as conditioned on event inundation maps. Water Resour Res. https://doi.org/10.1029/2001WR001056
Rotta LHS, Alcântara E, Park E et al (2020) The 2019 Brumadinho tailings dam collapse: possible cause and impacts of the worst human and environmental disaster in Brazil. Int J Appl Earth Obs Geoinformation 90:102119. https://doi.org/10.1016/j.jag.2020.102119
Santamarina JC, Torres-Cruz LA, Bachus RC (2019) Why coal ash and tailings dam disasters occur. Science 364:526–528. https://doi.org/10.1126/science.aax1927
Santos HA, Pompeu PS, Kenji DOL (2012) Changes in the flood regime of São Francisco River (Brazil) from 1940 to 2006. Reg Environ Chang 12:123–132. https://doi.org/10.1007/s10113-011-0240-y
Shustikova I, Domeneghetti A, Neal JC et al (2019) Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography. Hydrol Sci J 64:1769–1782. https://doi.org/10.1080/02626667.2019.1671982
Stephens TA, Bledsoe BP (2020) Probabilistic mapping of flood hazards: depicting uncertainty in streamflow, land use, and geomorphic adjustment. Anthr 29:100231. https://doi.org/10.1016/j.ancene.2019.100231
Tayefi V, Lane SN, Hardy RJ, Yu D (2007) A comparison of one- and two-dimensional approaches to modelling flood inundation over complex upland floodplains. Hydrol Process 21:3190–3202. https://doi.org/10.1002/hyp.6523
Teng J, Jakeman AJ, Vaze J et al (2017) Flood inundation modelling: a review of methods, recent advances and uncertainty analysis. Environ Model Softw 90:201–216. https://doi.org/10.1016/j.envsoft.2017.01.006
Tsai CW, Yeh JJ, Huang CH (2019) Development of probabilistic inundation mapping for dam failure induced floods. Stoch Environ Res Risk Asses 33:91–110. https://doi.org/10.1007/s00477-018-1636-8
Tschiedel AF, Fan FM, Paiva RCD, Tassinari LCS (2019) Barragens e rompimentos: compilação histórica nacional e internacional. XXIII SBRH—Simpósio Brasileiro de Recursos Hídricos. https://anais.abrhidro.org.br/job.php?Job=5724&Name=barragens_e_rompimentos_compilacao_historica_nacional_e_internacional. Accessed 19 July 2023
United States Army Corps of Engineers (2023) Hydrologic engineering center. https://www.hec.usace.army.mil/software/hec-ras/download.aspx. Acessed 05 Aug 2023
Yalcin E (2020) Assessing the impact of topography and land cover data resolutions on two-dimensional HEC-RAS hydrodynamic model simulations for urban flood hazard analysis. Nat Hazards 101:995–1017. https://doi.org/10.1007/s11069-020-03906-z
Ziya O, Safaie A (2023) Probabilistic modeling framework for flood risk assessment: a case study of Poldokhtar city. J Hydrol Reg Stud 47:101393. https://doi.org/10.1016/j.ejrh.2023.101393
Acknowledgements
The authors are grateful to the Centro Federal de Educação Tecnológica de Minas Gerais (CEFET-MG) for supporting the student scholarships of I.M.A., the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil (CAPES) for student scholarships of I.M.A., and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPQ) through the Projeto Universal (456390/2014-6). This study was also partly funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil (CAPES), Finance Code 001. The authors are grateful to the staffers of Gabriel L. Paula and Carlos Coelho for support in the computational simulations.
Funding
The funding was provided by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Grant Nos. 001, 001), Centro Federal de Educação Tecnológica de Minas Gerais, Conselho Nacional de Desenvolvimento Científico e Tecnológico (Grant No. 456390/2014-6).
Author information
Authors and Affiliations
Contributions
I. M. A: Conceptualization, Investigation, Methodology, Results from analyses, Writing original draft. H. A. S.: Conceptualization, Investigation, Methodology, Results from analyses, Writing original draft, Writing review & editing. O. V. C.: Investigation, Methodology, Results from analyses, Writing review & editing. V. B. G.: Results from analyses, Writing review & editing.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Almeida, I.M., Santos, H.A., de Vasconcelos Costa, O. et al. Uncertainty reduction in flood areas by probabilistic analyses of land use/cover in models of two-dimensional hydrodynamic model of dam-break. Stoch Environ Res Risk Assess 38, 1335–1350 (2024). https://doi.org/10.1007/s00477-023-02635-6
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00477-023-02635-6