Skip to main content

Advertisement

SpringerLink
Log in

Integration of morphometric attributes and the HAND model for the identification of Flood-Prone Area

  • Original Article
  • Published:
Environmental Earth Sciences Aims and scope Submit manuscript

Abstract

Climate change projections indicate an increase in intense rainfall events with consequent river flooding, which could lead to devastating natural disasters with serious consequences for the quality of life of populations. The main objective of this work was to determine and analyze the flooding potential of watersheds by integrating morphometric attributes and the HAND (Height Above Nearest Drainage) model. The study focused on the Bocaina Stream Basin (BSB), located in the State of Minas Gerais in southeastern Brazil. The BSB fully covers the urban area of the city of Passos, which has long suffered from flooding. In this work, the following cartographic products were generated at a scale of 1:50,000: a map of the morphometric susceptibility to flooding, which classifies the subbasins of the BSB based on five morphometric parameters; a map of the height above the nearest drainage, which was obtained via the HAND model; and map of the topographic predisposition to flooding, which was obtained through the integration of the morphometric flood susceptibility information and the HAND model information. Based on the map of the topographic predisposition to flooding, the BSB area shows the following classes of flood susceptibility: 75%—very low, 11%—low, 9%—medium, and 6%—high. Although the high and medium classes represent the lowest percentages in terms of basin area, they are predominantly located in areas near the drainage channels. When these areas are occupied, as is the case in the city of Passos, flooding can have considerable impacts.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Afshari S, Tavakoly AA, Rajib MA et al (2018) Comparison of new generation low-complexity flood inundation mapping tools with a hydrodynamic model. J Hydrol 556:539–556. https://doi.org/10.1016/j.jhydrol.2017.11.036

    Article  Google Scholar 

  • Bajabaa S, Masoud M, Al-Amri N (2014) Flash flood hazard mapping based on quantitative hydrology, geomorphology and GIS techniques (case study of Wadi Al Lith, Saudi Arabia). Arab J Geosci 7:2469–2481. https://doi.org/10.1007/s12517-013-0941-2

    Article  Google Scholar 

  • Brandimarte L, Brath A, Castellarin A, Di BG (2009) Isla Hispaniola: a trans-boundary flood risk mitigation plan. Phys Chem Earth 34:209–218. https://doi.org/10.1016/j.pce.2008.03.002

    Article  Google Scholar 

  • Campos S, Stefani FL, Paulon N, Faccini LG, Bitar OU (2015) Cartas de suscetibilidade à inundação. In: Congresso Brasileiro de Geologia de Engenharia e Ambiental, 15, Bento Gonçalves. Anais. Bento Gonçalves: ABGE, 2015. p. 1–8

  • Carvalho ACP (2017) Integração de atributos morfométricos e geotécnicos para definição de zonas sujeitas à inundação na Bacia do Ribeirão Bocaina (MG). 228f. Dissertação (Mestrado)—Curso de Geotecnia, Escola de Engenharia de São Carlos, Universidade de São Paulo, São Carlos

  • CCST/INPE, CEMADEN. HAND Model: a new look over the landscape (2020) CCST / INPE. Available at: https://handmodel.ccst.inpe.br/?page_id=101#ffs-tabbed-12. Accessed on: 2 Apr 2020

  • CEPED—Centro Universitário de Estudos e Pesquisas sobre Desastres, Universidade Federal de Santa Catarina (2012) Atlas Brasileiro de Desastres Naturais: 1991–2010, vol Brasil. CAD UFSC, Florianópolis

    Google Scholar 

  • Chinaiwala VA, Dalia TS, Dave DP, Gaekwad JR, Jariwala YD, Soni N (2018) Flood hazard assessment and identification of Danger Zones using. Int J Tech Innov Mod 4:10–14

    Google Scholar 

  • Cian F, Marconcini M, Ceccato P (2018) Normalized difference flood index for rapid flood mapping: taking advantage of EO big data. Remote Sens Environ 209:712–730. https://doi.org/10.1016/j.rse.2018.03.006

    Article  Google Scholar 

  • Collares EG, Gomes DM (2013) Geologia. In: Collares EG (ed) Zoneamento Ambiental das Sub-bacias Hidrográficas dos Afluentes Mineiros do Médio Rio Grande: Aspectos dos Meios Físico e Biótico, vol 6. Edifesp, Passos, pp 154–164

    Google Scholar 

  • Collares EG, Gomes DM, Santos BM (2013) Aspectos metodológicos: Compartimentação em macrounidades e unidades ambientais. In: Collares EG (ed) Zoneamento Ambiental das Sub-bacias Hidrográficas dos Afluentes Mineiros do Médio Rio Grande: Aspectos metodológicos, vol 4. Edifesp, Passos, pp 49–62

    Google Scholar 

  • Dias CC, Pejon OJ, Silva JA, Collares ACZB, Collares EG (2013) Clima. In: Collares EG (ed) Zoneamento Ambiental das Sub-bacias Hidrográficas dos Afluentes Mineiros do Médio Rio Grande: Aspectos dos Meios Físico e Biótico, vol 1. Edifesp, Passos, pp 31–81

    Google Scholar 

  • dos Santos KA (2015) Utilização de modelo hidrodinâmico para mapeamento de áreas inundáveis. 2015. 89 f. Dissertação (Mestrado)—Curso de Engenharia do Meio Ambiente. Universidade Federal do Goiás, Goiânia

    Google Scholar 

  • Gain AK, Giupponi C, Wada Y (2016) Measuring global water security towards sustainable development goals. Environ Res Lett. https://doi.org/10.1088/1748-9326/11/12/124015

    Article  Google Scholar 

  • Instituto Brasileiro de Geografia e Estatística—IBGE (Brasil) ( 2010) Informações Estatíticas. 2010. Disponível em: < https://cidades.ibge.gov.br/brasil/mg/passos/panorama>. Acesso em: 29 out 2018

  • Instituto Nacional de Meteorologia—INMET (Brasil) (2017) Temperatura. Disponível em: <https://www.inmet.gov.br/portal/index.php?r=home/page&page=rede_estacoes_auto_graf>. Acesso em: 07 nov. 2018

  • Instituto Nacional de Pesquisas Espaciais—INPE (Brasil) (2017) Divisão de Processamento de Imagens. Grupo de Modelagem para Estudos da Biodiversidade. HAND Distância Vertical à drenagem mais próxima. São José dos Campos, SP. Disponível em:<https://www.dpi.inpe.br/Ambdata/hand.php>. Acesso em: 13 mar. 2017

  • Lee EH, Kim JH (2018) Development of a flood-damage-based flood forecasting technique. J Hydrol 563:181–194. https://doi.org/10.1016/J.JHYDROL.2018.06.003

    Article  Google Scholar 

  • Magri RAF et al (2013) Materiais Inconsolidados. In: Collares EG (ed) Zoneamento Ambiental das sub-bacias hidrográficas dos afluentes mineiros do Médio Rio Grande: Aspectos dos Meios Físico e Biótico. Edifesp, Passos, pp 171–187

    Google Scholar 

  • Mapa de Clima do Brasil (1978) Disponível em: <ftp://geoftp.ibge.gov.br/mapas_tematicos/mapas_murais/clima.pdf>. Acesso em: 01 abr. 2016

  • Nobre AD, Cuartas LA, Hodnett M et al (2011) Height Above the Nearest Drainage—a hydrologically relevant new terrain model. J Hydrol 404:13–29. https://doi.org/10.1016/j.jhydrol.2011.03.051

    Article  Google Scholar 

  • Nobre AD, Cuartas LA, Momo MR et al (2016) HAND contour: A new proxy predictor of inundation extent. Hydrol Process 30:320–333. https://doi.org/10.1002/hyp.10581

    Article  Google Scholar 

  • Pinheiro MC, Pinheiro VB, Lima AA, Costa TT, Vinicius M, Costa UB (2006) Elaboração de diagnóstico e proposição de soluções conceituais para o problema das enchentes na área urbana: Volume 1: Diagnóstico e Apresentação de Soluções Conceituais. Potamos Engenharia e Hidrologia Ltda, Passos

    Google Scholar 

  • Rahmati O, Pourghasemi HR (2017) Identification of critical flood prone areas in data-scarce and ungauged regions: a comparison of three data mining models. Water Resour Manag 31:1473–1487. https://doi.org/10.1007/s11269-017-1589-6

    Article  Google Scholar 

  • Rahmati O, Kornejady A, Samadi M et al (2018) Development of an automated GIS tool for reproducing the HAND terrain model. Environ Model Softw 102:1–12. https://doi.org/10.1016/j.envsoft.2018.01.004

    Article  Google Scholar 

  • Rennó CD, Nobre AD, Cuartas LA et al (2008) HAND, a new terrain descriptor using SRTM-DEM: mapping terra-firme rainforest environments in Amazonia. Remote Sens Environ 112:3469–3481. https://doi.org/10.1016/j.rse.2008.03.018

    Article  Google Scholar 

  • Šraj M, Viglione A, Parajka J, Blöschl G (2016) The influence of non-stationarity in extreme hydrological events on flood frequency estimation. J Hydrol Hydromech. 64:426–437. https://doi.org/10.1515/johh-2016-0032

    Article  Google Scholar 

  • Strahler AN (1957) Quantitative analysis of watershed geomorphology. New Halen: Trans Am Geophys Union 38:913–920

    Google Scholar 

  • Tehrany MS, Pradhan B, Mansor S, Ahmad N (2015) Flood susceptibility assessment using GIS-based support vector machine model with different kernel types. CATENA 125:91–101. https://doi.org/10.1016/j.catena.2014.10.017

    Article  Google Scholar 

  • Zhao G, Pang B, Xu Z et al (2018) Mapping flood susceptibility in mountainous areas on a national scale in China. Sci Total Environ 615:1133–1142. https://doi.org/10.1016/j.scitotenv.2017.10.037

    Article  Google Scholar 

Download references

Acknowledgements

We thank the Grande Minas Project team for making the data available and the National Council for Scientific and Technological Development (CNPq) and Brazilian Federal Agency for the Support and Evaluation of Graduate Education (CAPES) for financially supporting this study.

Author information

Authors and Affiliations

  1. Department of Environmental Sciences, Federal University of São Carlos, São Carlos, Brazil

    Ana Claudia Pereira Carvalho

  2. Department of Geotechnical Engineering, University of São Paulo, São Carlos, Brazil

    Osni José Pejon

  3. Geoprocessing and Environmental Zoning Laboratory, State University of Minas Gerais, Passos, Brazil

    Eduardo Goulart Collares

Authors
  1. Ana Claudia Pereira Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Osni José Pejon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eduardo Goulart Collares
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ana Claudia Pereira Carvalho.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Carvalho, A.C.P., Pejon, O.J. & Collares, E.G. Integration of morphometric attributes and the HAND model for the identification of Flood-Prone Area. Environ Earth Sci 79, 367 (2020). https://doi.org/10.1007/s12665-020-09058-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12665-020-09058-4

Keywords

Search

Navigation