Effects on runoff caused by changes in land cover in a Brazilian southeast basin: evaluation by HEC-HMS and HEC-GEOHMS

  • Thalita Costa de Moraes
  • Vitor Juste dos Santos
  • Maria Lúcia Calijuri
  • Fillipe Tamiozzo Pereira Torres
Original Article


The Southeast Region of Brazil has undergone major changes in land cover, especially after the eighteenth century. It is currently the most populous region of the country, highly urbanized, with a high degree of industrial and agricultural development. Extensive areas of native vegetation have been replaced by pastures, crops and urban areas, which have increased runoff, causing environmental, economic and social problems related to flooding. The objective of this study was to analyze effects of land cover changes in a basin with rural and urban characteristics on the flow of its main river. Hydrological data, orbital images, soils and topographical maps were used for this purpose. Based on the land cover maps for the years of 1989, 2001 and 2015, and on the hydrological modeling performed using the Hec-HMS 4.1 software, scenarios were simulated and showed that the land cover changes in this basin significantly affect the flow behavior of the main river. The simulated runoff was calibrated using the data observed in the field during 2001, and validation was performed using data from 1989. After the calibration and validation processes, a scenario was simulated where the rainiest month of the whole series measured by the rainfall station (during December 1989) acted on the land cover of 2015. There was an increase in pasture areas and impermeable spaces in the basin, which caused a decrease in infiltration and an increase in surface runoff, and also an increase in the flow peaks and a reduction in the time of concentration. The hydrological modeling was satisfactory, since the uncertainties related to the simulation were low.


Curve number Flow rate Hydrology Hydrological modeling Simulation 


  1. Ab’Saber AN (2006) Os domínios de natureza no Brasil: potencialidades paisagísticas [The domains of nature in Brazil: land scape potential]. 6. ed. São Paulo: Ateliê Editorial, p 159 (in Portuguese)Google Scholar
  2. Andrade MC (1961) Aspectos geográficos da região de Ubá [Geographical aspects of the Ubá region]. Anais da associação dos geógrafos brasileiros, São Paulo, SP, Brasil, Avulso n. 1 (in Portuguese)Google Scholar
  3. Andréassian V (2004) Water and forests: from historical controversy to scientific debate. J Hidrol 291:1–27CrossRefGoogle Scholar
  4. Assis LC (2014) Simulação de processos hidrológicos na bacia hidrográfica do rio Piranga [Simulation of hydrological processes in the catchment area of the Piranga river]. Tese (Modelagem Hidrológica)—UFV, Viçosa, MG, Brasil, p 111 (in Portuguese)Google Scholar
  5. Associação Pró-Gestão das Águas da Bacia Hidrográfica do Rio Paraíba do Sul—AGEVAP (2014) Plano integrado de recursos hídricos da Bacia Hidrográfica do Rio Paraíba do Sul e planos de ação de recursos hídricos das bacias afluentes [Integrated water resources plan for the Paraíba do Sul River Basin and action plans for water resources in the tributaries]. RP-06, Tomo I, p 226 (In Portuguese)Google Scholar
  6. Azama M, Kimb HS, Maenga SJ (2017) Development of flood alert application in Mushim stream watershed Korea. Int J Disaster Risk Reduct 21:11–26CrossRefGoogle Scholar
  7. Bai Y et al (2016) Impacts of land management on ecosystem service delivery in the Baiyangdian river basin. Environ Earth Sci 75:258CrossRefGoogle Scholar
  8. Bressiani DA et al (2015) Review of soil and water assessment tool (SWAT) applications in Brazil: challenges and prospects. Int J Agric Biol Eng 8(3):9–35Google Scholar
  9. Brown AE, Zhang L, McMahon TA, Western AW, Vertessy RA (2005) A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation. J Hydrol 310:28–61CrossRefGoogle Scholar
  10. Calijuri ML, Castro JS, Costa LS, Assemany PP, Alves JEM (2015) Impact of use/land cover changes on water quality and hydrological behavior of an agricultural sub watershed. Environ Earth Sci 74:5373–5382CrossRefGoogle Scholar
  11. Chen W et al (2016) Land use/land cover change and driving effects of water environment system in Dunhuang Basin, northwestern China. Environ Earth Sci 75:1027CrossRefGoogle Scholar
  12. Deng Z, Zhang X, Li D, Pan G (2015) Simulation of land use/land cover change and its effects on the hydrological characteristics of the upper reaches of the Hanjiang Basin. Environ Earth Sci 73:1119–1132CrossRefGoogle Scholar
  13. Fialho ES, Santos VJ (2012) Análise dos eventos pluviais extremos que ocorreram no município de Ubá/MG e suas repercussões [Analysis of the extreme rainfall events that occurred in the city of Ubá/MG and its repercussions]. In: XVII Encontro Nacional de Geógrafos, Belo Horizonte (in Portuguese)Google Scholar
  14. Foody GM et al (1992) Derivation and applications of probabilistic measures of class membership from the maximum-likelihood classification. Photogramm Eng Remote Sens 58(9):1335–1341Google Scholar
  15. Huang IB, Keisler J, Linkov I (2011) Multi-criteria decision analysis in environmental sciences: ten years of applications and trends. Sci Total Environ 409:3578–3594CrossRefGoogle Scholar
  16. Instituto Brasileiro de Geografia e Estatística—IBGE (2011) Economia—PIB Municípios [Economy—GDP Municipalities]. Accessed 25 Oct 2016
  17. Kabiri R, Bai VR, Chan A (2015) Assessment of hydrologic impacts of climate change on the runoff trend in Klang Watershed, Malaysia. Environ Earth Sci 73:27–37CrossRefGoogle Scholar
  18. Kheereemangkla Y, Shrestha RP, Shrestha S, Jourdain D (2016) Modeling hydrologic responses to land management scenarios for the Chi River Sub-Basin Part II, Northeast Thailand. Environ Earth Sci 75:793CrossRefGoogle Scholar
  19. Knebla MR et al (2005) Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event. J Environ Manag 75:325–336CrossRefGoogle Scholar
  20. Kumar DS, Arya DS, Vojinovic Z (2013) Modeling of urban growth dynamics and its impacts on surface runoff characteristics. Comput Environ Urban Syst 41:124–135CrossRefGoogle Scholar
  21. Machado RE, Vettorazzi CA, Xavier AC (2003) Simulação de cenários alternativos de uso da terra em uma microbacia utilizando técnicas de modelagem e geoprocessamento [Alternative scenario simulation of land use in a watershed through geoprocessing and modeling techniques]. Revista Brasileira de Ciências do Solo 27:727–733 (in Portuguese) CrossRefGoogle Scholar
  22. Narimani R, Erfanian M, Nazarnejad H, Mahmodzadeh A (2017) Evaluating the impact of management scenarios and land use changes on annual surface runoff and sediment yield using GeoWEPP: a case study from the Lighvanchai watershed, Iran. Environ Earth Sci 76:353CrossRefGoogle Scholar
  23. Sahin V, Hall MJ (1996) The effects of afforestation and deforestation on water yields. J Hydrol 178:293–309CrossRefGoogle Scholar
  24. Sajikumar N, Remya RS (2015) Impacts of land cover and land use change on runoff characteristics. J Environ Manag 161:460–468CrossRefGoogle Scholar
  25. Salvador MM (2014) Identificação e avaliação de eventos extremos na bacia hidrográfica do rio Piranga [Identification and evaluation of extreme events in the catchment area of the Piranga river]. Dissertação (Modelagem Hidrológica)—UFV, Viçosa, MG, Brasil, p 60 (in Portuguese)Google Scholar
  26. Santos VJ (2013a) Episódios pluviais intensos: o caso da cidade de Ubá/MG [Intense rainfall events: the case of the city of Ubá/MG]. Monografia (Especialização em Climatologia)—UFV, Viçosa, MG, Brasil, p 115 (in Portuguese)Google Scholar
  27. Santos VJ (2013b) Análise temporal dos casos de inundação registrados na cidade de Ubá/MG [Temporal analysis of flood cases recorded in the city of Ubá/MG]. In: XV Semana Acadêmica de Geografia e II Seminário de Pós-Graduação da Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, MG, Brasil, pp 135–150 (in Portuguese)Google Scholar
  28. Santos VJ (2014) Crescimento Urbano e Impactos Pluviais na Cidade de Ubá/MG [Urban Growth and Pluvial Impacts in the City of Ubá/MG]. In: I Simpósio Mineiro de Geografia, Alfenas, MG, Brasil, p 229–244 (in Portuguese)Google Scholar
  29. Santos VJ, Fialho ES (2012) Percepção de um desastre ambiental climático: o caso de Guidoval/MG, em janeiro de 2012 [Perception of a climatic environmental disaster: the case of Guidoval/MG, January 2012]. In: XVII Encontro Nacional de Geógrafos, Belo Horizonte (in Portuguese)Google Scholar
  30. Shamsudin S, Dan’azumi S, Rahman AA (2011) Uncertainty analysis of Hec-HMS model parameters using Monte Carlo Simulation. Int J Model Simul 31(4):279–286Google Scholar
  31. Silva EA et al (2017) Forest cover analysis through the weights of evidence method in the campanha ocidental region—RS (Brazil). Rev Árvore 41(1):e410105Google Scholar
  32. USACE (2000) Hydrologic Modeling System HEC-HMS: technical reference manual. U.S. Army Corps of engineers, [S.l.], p 145Google Scholar
  33. USACE (2009) HEC-GeoHMS geospatial hydrologic modeling extension: user’s manual. U.S Army Corps of Engineers, Washington, D.C., p 197Google Scholar
  34. Vaighan AA, Talebbeydokht N, Bavani AM (2017) Assessing the impacts of climate and land use change on streamflow, water quality and suspended sediment in the Kor River Basin, Southwest of Iran. Environ Earth Sci 76:543CrossRefGoogle Scholar
  35. Valverde O (1958) Estudo regional da Zona da Mata, de Minas Gerais[Regional study of the Zona da Mata, Minas Gerais]. Revista Brasileira de Geografia 20(1):3–82 (in Portuguese) Google Scholar
  36. Weng Q (2001) Modeling urban growth effects on surface runoff with the integration of remote sensing and GIS. Environ Manag 28(6):737–748CrossRefGoogle Scholar
  37. Worku T, Khare D, Tripathi SK (2017) Modeling runoff-sediment response to land use/land cover changes using integrated GIS and SWAT model in the Beressa watershed. Environ Earth Sci 76:550CrossRefGoogle Scholar
  38. Yan R, Gao J, Li L (2016) Streamflow response to future climate and land use changes in Xinjiang basin, China. Environ Earth Sci 75:1108CrossRefGoogle Scholar
  39. Yira Y, Diekkrugger B, Steup G, Bossa AY (2016) Modeling land use change impacts on water resources in a tropical West African catchment (Dano, Burkina Faso). J Hidrol 537:187–199CrossRefGoogle Scholar
  40. Zare M, Samani AAN, Mohammady M (2016) The impact of land use change on runoff generation in an urbanizing watershed in the north of Iran. Environ Earth Sci 75:1279CrossRefGoogle Scholar
  41. Zounemat-Kermania M et al (2017) Estimating the aeration coefficient and air demand in bottom outlet conduits of dams using GEP and decision tree methods. Flow Meas Instrum 54:9–19CrossRefGoogle Scholar
  42. Zuo D et al (2016) Assessing the effects of changes in land use and climate on runoff and sediment yields from a watershed in the Loess Plateau of China. Sci Total Environ 544:238–250CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Thalita Costa de Moraes
    • 1
  • Vitor Juste dos Santos
    • 2
  • Maria Lúcia Calijuri
    • 2
  • Fillipe Tamiozzo Pereira Torres
    • 3
  1. 1.Department of Civil EngineeringPontifical Catholic University of Rio de JaneiroRio de JaneiroBrazil
  2. 2.Department of Civil EngineeringFederal University of ViçosaViçosaBrazil
  3. 3.Department of Forest EngineeringFederal University of ViçosaViçosaBrazil

Personalised recommendations