Open access peer-reviewed chapter

Flood Risk Mapping in the Amazon

Written By

Milena Marília Nogueira de Andrade, Iris Celeste Nascimento Bandeira, Dianne Danielle Farias Fonseca, Paulo Eduardo Silva Bezerra, Ádanna de Souza Andrade and Rodrigo Silva de Oliveira

Submitted: 05 December 2016 Reviewed: 31 March 2017 Published: 30 August 2017

DOI: 10.5772/intechopen.68912

From the Edited Volume

Flood Risk Management

Edited by Theodore Hromadka and Prasada Rao

Chapter metrics overview

2,004 Chapter Downloads

View Full Metrics


Floods are part of the natural and cultural life in the Amazon. However, the issues and management of fluvial-disaster risks are poorly studied. Among the reasons for the lack of studies, the Amazon region has several gaps in information ranging from inadequate regional maps to spatially unsystematic local data. Flood patterns differ in urban and rural areas. Severe large-scale flooding took place during the previous and the current decades, such as those that occurred in 2009 and 2012. Between 1991 and 2010, official recorded data indicate about 3,292,888 people were affected in 6 regional states of the Amazon (Acre, Amapá, Amazonas, Pará, Rondônia, and Roraima) considering 7 different hazards. Because of the extensive damages, the national government started a mapping program for cities in Brazil that have a history of facing significant flood risks. The aim of this chapter is to analyse the flood-risk mapping conditions in the Amazon.


  • Amazon region
  • disaster risk
  • flood hazard
  • vulnerability
  • risk mapping
  • risk management
  • urban planning

1. Introduction

Brazil recorded 4691 flood events between 1991 and 2012, which represent 12% of all natural hazards in the country. In the Amazon, floods affected around 2379 people [1]. However, rivers are a fundamental component of Amazon life. Many highly populated cities are located along the major rivers and floodplains on the Amazon and Tocantins river basins, which together house over five billion inhabitants [2] (Figure 1).

Figure 1.

Study area showing the hydrographic networks and the pattern of the cities located nearby important rivers in the northern Amazon region.

Risk is a function of the probability that a particular hazard (such as flooding) might take place and the vulnerability of a particular location to being negatively affected by that hazard [3]. The likelihood of floods generating damage when river water overflows a river bank is a risk. Impacts are the generally negative effects of a hazard taking place in a given locale. Impacts vary from immaterial to material losses across cities such as individuals and families losing their homes and other dwellings, or losing access to such dwellings.

Included among material damages in urban areas are the destruction of public and private infrastructures, disruption of normal traffic flow, and reduction of accessibility to various locations and city spaces [4]. In rural areas, impacts include disruption of agricultural production, depopulation because of migration to the cities, and inflation of food prices at the local markets due to damage or destruction of crops near the floodplains. Small farming communities are particularly susceptible to extreme flood events because of the lack of adequate infrastructure for transporting people and their goods to industrial and commercial centers, the lack of information about extreme weather events at the community level, and the lack of sufficient economic resources to endure the effects of prolonged environmental catastrophes [5].

Since 2012, mapping flood risks has been one of the objectives of the National Program for Risk Management and Response to Disasters. Program priorities include investments in preventing, providing alerts for, monitoring, and responding to natural hazards. The program goal is to reduce the negative impacts of natural calamities on populations that live in risk-prone areas and guarantee the safety of communities from these calamities [6].

Therefore, response actions need precise physical aspects. Flood-hazard background information prioritizes the measures of frequency and magnitude of severe flooding, as well as the hydrodynamic and climatic scenarios [7, 8]. Response actions focus on the use of geoscience data and on structural engineering measures [9].

Another way to reduce risk is investments in prevention. Examples are the expansion of monitoring and warning systems, systematic mapping of high-risk areas [6], and preparation of vulnerability assessments. Vulnerability depends on the scale, time, and space units of analyses such as individuals, households, regional areas, and system-wide conditions [10]. Vulnerability definitions vary according to research approach and methodologies.

The International Strategy for Disaster Reduction (UN-ISDR) defines vulnerability as the combination of physical, social, economic, and environmental factors or processes that increase the susceptibility of a community to the impact of hazards [11]. The use of indicators is a common approach for vulnerability measurement [12, 13]. At a national scale, the social aspect of vulnerability displays higher levels of negative indicators for the Amazon region when compared to cities in the south-western region of Brazil [14].


2. Flood hazards in the Amazon region

Floods occur in the Amazon and Tocantins river basins in the northern region of Brazil. The Amazon river basin has flood water levels variability between 2 and 18 m [15]. The Amazon river receives the discharge of other big rivers (e.g., Negro and Tapajós), and floods occur periodically depending on the seasonal rainfall for each river. Floods usually occur in June for the Amazonas, Branco, and Negro rivers. At the Macapá station, tidal influences mean that river seasonality is barely noticeable throughout the year (Figure 2).

Figure 2.

Historical river-level fluctuations (in cm) for the Amazon, Negro, and Branco rivers and their northern tributaries.

The historical data series varies according to the station. The water-level data from stream gauging stations cover 112 years at Manaus (1902–2014); 48 years at Boa Vista (1967–2015), Barcelos (1967–2015), Rio Branco (1967–2015), and Madeira (1967–2015); 39 years at Macapá (1976–2015) and São Felix (1977–2016); and 20 years at Baião (1971–1991). Some of the stations have been deactivated [16].

On many southern rivers and tributaries, water levels remain high during the first semester. Highest river stages occur during February and March, and there are more incidences of floods during this period (Figure 3). Flooding in the Tocantins river basin is limited to its eastern area with the Tocantins river being the main tributary that reaches a 10-m water level.

Figure 3.

Historical river-level fluctuations (in cm) for the Acre, Madeira, Tocantins, and Xingu rivers.

In 2009, the Amazon river basin experienced extreme flooding. At the Manaus station of the Negro river, the water level reached 29.75 m, the highest mark in 107 years since stage data became available [8]. At the reference point of the Obidos gauge station, the river reached 8.42 m. For the Tapajós river (Santarém station), the highest water-level mark was 8.31 m [4].

A complex combination of factors contributed to these recent extreme-hazard events; namely, large- and regional-scale climatic events, unusual flood mechanisms that produced complex interactions in time and space between the main system and its tributaries [7, 8], and recent urban growth without adequate planning. Long-term climate models show extreme precipitation events over the Amazon region [17].

Landsat and shuttle radar topography mission (SRTM) data were used to define aspects of the morphologies of the fluvial systems in the Amazon and to construct the corresponding hydrodynamic models for these systems [18, 19]. Nevertheless, detailed geomorphologic maps that are fundamental to refining the fluvial models were not available [20]. For downscaling analysis, susceptibility maps for floods at 1:50,000 scale became available for some municipalities since 2013 [21]. The analysis covers 23 urban municipalities covering respective areas that have high, moderate, and low susceptibility to flooding. The methodological approach includes hypsometric, declivity, geomorphological, and drainage analyses [2224]. Currently available status-of-susceptibility flood maps include 18 municipalities from Pará, 2 from Amapá, and 1 each from Acre, Rondônia, and Roraima.

The National Water Agency produced a flood-hazard atlas considering the frequency of floods and the impacts probability associated with each part of the river. The flood frequency corresponds to 5, 10, or more years of recurrence intervals, and the impact was measured according to the damage extension. The results aggregate the flood severity assessment according to international terminologies [25].

In total, 68 different rivers were integrated in the analysis and 4756 km of river extension is considered with high impacts and frequencies to flooding (Table 1). The percentage for river high-hazard stretches are 27% for Acre, 30% for Amapá, 16% for Amazonas, 10% for Pará, 37% for Roraima, and 31% for Rondônia. The map is at national scale displaying areas with low, medium, and high impact frequencies [26] (Figure 4).

State/flood-hazard stretch (km)LowMediumHigh

Table 1.

Flood hazard stretches for rivers in the Amazon region grouped according to state.

Figure 4.

Flood map with parts of the river more susceptible to floods and impacts based on ANA data.


3. Vulnerability in the Amazon

Vulnerability is multidimensional and refers to social, economic, environmental, and physical categories [11]. Socio-economic vulnerability often describes the characteristics of people or groups of peoples [27]. Environmental vulnerability refers to natural-resources depletion and degradation [28]. Physical vulnerability refers to the susceptibility of particular locations to particular hazards and therefore represents the civilian infrastructure of a given place.

To deal with diverse research frameworks, the index of methodologies links natural-hazard risks and vulnerabilities. This means that when an extreme event leads to impacts, the latter is determined by the hazards aspect and by the respective vulnerabilities of communities, societal groups, or civilian infrastructures to such impacts [29].

Quantifying social vulnerability using various indicators can help identify which places are most vulnerable and which dimensions of social vulnerability are most relevant and therefore constitute the key drivers for change [30]. The Amazon region has 41% of its municipalities that are considered to have high social vulnerability. The analysis considered urban infrastructure, human capital, incomes, and work status as indicators [31]. This high percentage signifies a very low to medium-low Human Development Index (HDI) rating for rural and urban areas in the Amazon [32].

For a specific natural-hazard assessment, the Amazon region also has a very high social-vulnerability index. The indicators were (among others) gender, race and ethnicity, employment loss, social dependency, and migration rate [14]. Vulnerability to floods in rural communities is determined based on residency patterns, access to fishing and planting grounds, access to transportation and markets, water quantity and quality, and the prevalence of infectious diseases [33].

In large cities in the Amazon estuary, vulnerability was measured considering indicators of exposure (places and people located at hazardous areas), socio-economic situation, and condition of civilian infrastructure in terms of the availability and quality of sanitation services and housing structures (Figure 5). In these urban spaces, around 37,000 people live under very high-vulnerability conditions and 988,000 people live under high-vulnerability conditions [34].

Figure 5.

The first and second photos showing Manaus (Amazonas state) infrastructure livelihood patterns and structural measures for accessibility in the central areas during the 2012 flood (photos in clockwise direction: CPRM, 2012). Santarem city (Pará state) during the 2012 flood showing wooden bridges and a view taken from the dike in front of the city during the 2009 flood (photos in clockwise direction: Milena Andrade 2012, Santarém Civil Defense 2009).

Previous studies compiled for several locations along the Amazon coast in Pará state utilized vulnerability indices in addition to spatial information on floods and storm surges related to climate change and structural vulnerabilities [35]. Downscaling studies in vulnerability use methodological approaches based on the social-vulnerability index and an index on responses to hazards [36], on a methodological approach for community participation in flood mapping [4], and on a hazard-response identification scheme for urban planning for natural disasters issues [37].

An effective vulnerability reduction plan should include adaptive capacity assessments. The human capacity to prepare for, respond to, and recover from natural disasters highlights local characteristics and situations [12, 38]. The structural and nonstructural measures for coping with hazards result from adaptive capacity. Pilot local-scale studies in the Amazon take into account qualitative variables and the influence of community participation in vulnerability assessments. These studies identify local knowledge as fundamentally important in coping and adaptation strategies and vulnerability reduction [4, 39].


4. Sectors of risk in the Amazon

The Geological Service of Brazil (CPRM) is responsible for mapping flood hazard-risk areas following the prevention criteria in the National Plan for Management and Response for Natural Hazards. The selection criteria for mapping emergency areas included the numbers of fatal victims and affected people, decreed state or level of emergency and calamity, and the official assistance requests from municipalities [40]. Between 2012 and 2016, CPRM mapped 1206 municipalities all over Brazil, of which 140 are located in the Amazon region.

Considering Pará, Amazonas, Acre, Rondônia, and Roraima states, around 180,000 people live within 418 risk sectors inside 99 municipalities with either high or very high risk of flooding [6] (Figures 6 and 7).

Figure 6.

Graph of numbers of people in risk sectors of Amazonas, Pará, Rondônia, Acre, and Roraima states.

Figure 7.

Sectors of risk in Epitaciolândia (Acre state) during the 2015 flood and Marabá City (Pará state) during the 2011 flood (photos in clockwise direction: Epitaciolândia and Marabá Civil Defense, respectively).

To delineate the risk sectors, the methodology included previous classifications was proposed in Refs. [4143]. Some adaptations were necessary for the risk sectors in the Amazon region that considered the following situations: a riverine community’s location within a large floodplain, local water-level historical observations in existing infrastructures, lack of drainage and sanitation systems, household infrastructure fragility to flood effects (for wooden or brick houses), and measures of material and immaterial losses [6]. Very high-risk and high-risk areas were prioritized in the sector-mapping program because of the immediate need to prevent fatalities in these areas during hazard emergencies (Figure 8).

Figure 8.

Map of municipalities in very high-risk and high-risk areas that are prone to flooding, according to CPRM data.

A very high-risk designation corresponds to a drainage with a high frequency (at least three events in the last 5 years) of flooding and a very high-damage probability because of the presence of vulnerable structures. High risk corresponds to a drainage with a moderate frequency (at least one event in the last 5 years) of flooding and a high-damage probability because of the presence of vulnerable household structures. Moderate risk corresponds to a moderate frequency (at least one event in the last 5 years) and low susceptibilities of structures to flood damage. Low risk corresponds to the absence of flood events in the last 5 years and the absence or presence of structures with low susceptibility to flood damage [43].


5. Conclusions

This study presented the developments in flood-risk mapping in the Amazon region. Flood-risk mapping projects are mostly by the national program for disaster reduction and counts on the support of national institutions. The effort to reach a nationwide methodology is a challenge due to the regional differences in Brazil.

Background information on flood hazards rely on fluvial water-level data taken along the river basins, on delineation of flood hazard-prone areas presented on 1:1,000,000-scale maps, and on semi-detail (1:50,000 scale) flood susceptibility maps for specific locations. These maps are the starting point for identifying critical areas for detailed hydrologic modeling. Extreme weather events have the potential to cause worse impacts on these high flood-risk areas.

The vulnerability studies in the Amazon region show some initial advances in understanding the effects of the various types of vulnerabilities on the impact of flood hazards. National hazard-risk studies provide the bases for national indicators. Therefore, some adaptations would be valuable for understanding the complex effects of vulnerabilities in the country. Some specific conditions in the Amazon should be taken into account. Infrastructure vulnerability is the main type of vulnerability that is most relevant in mapping flood-hazard risks.

Flood-risk mapping is a fundamental part of disaster-risk management. It is crucial in information-based decision-making and in providing guidance for defining priorities for risk reduction. In urban areas, the anthropogenic factors that influence or intensify flooding are considered for the minimization or elimination of risk sectors. Demographic and land-use changes have a direct impact on the intensity of floods. All sector risk maps generated by the CPRM have been made available for the civil defense activities of the municipalities, alert centers, ministers, and institutions associated with the National Program for Risk Management and Response to Disasters. This policy is a driver for transformative change that should continue over time.


  1. 1. CEPED. Atlas Brasileiro de Desastres Naturais 1991-2012. Florianópolis: UFSC; 2013
  2. 2. IBGE. Dados censitários das cidades [Internet]. 2016. [Accessed: February 15, 2016]
  3. 3. Wisner B, Blaikie P, Cannon T, Davis I. At Risk: Natural Hazards, People’s Vulnerability and Disasters. 2nd ed. London: Routledge; 2004
  4. 4. Andrade MMN de, Szlafsztein CF. Community participation in flood mapping in the Amazon through interdisciplinary methods. Natural Hazards. 2015;78(3):1491-1500
  5. 5. Szlafsztein CF. Development projects for small rural communities in the Brazilian Amazon region as potential strategies and practices of climate change adaptation. Mitigation and Adaptation Strategies for Global Change. 2012;19:143-160. DOI 10.1007/s11027-012-9431-1
  6. 6. CPRM Companhia de Pesquisa de Recursos Minerais. Setorização de Riscos Geológicos [Internet]. 2017. Available from: [Accessed: 10 February, 2017]
  7. 7. Espinoza JC, Marengo JA, Ronchail J, Carpio JM, Flores LN, Guyot JL. The extreme 2014 flood in south-western Amazon basin: the role of tropicalsubtropical South Atlantic SST gradient. Environmental Research Letters. 2014;9:1-9
  8. 8. Marengo JA, Tomasella J, Soares WR, Alves LM, Nobre CA. Extreme climatic events in the Amazon basin. Theoretical and Applied Climatology. 2012;107:73-85
  9. 9. Rodrigues AC, Günther WMR, Vasconcellos MdaP, Di Giulio G, Boscov MEG. An overview of Brazilian scientific production on disasters in the beginning of this century. Desenvolvimento e Meio Ambiente. 2015;34:61-73
  10. 10. Turner II B, Matson P, McCarthy J, Corell R, Christensen L, Eckley N, Hovelsrud-Broda G, Kasperson J, Kasperson R, Luers A, Martello M, Mathiesen S, Naylor R, Polsky C, Pulsipher A, Schiller A, Selin H, Tyler N. Illustrating the coupled human–environment system for vulnerability analysis: Three case studies. Proceedings of the National Academy of Sciences of the United States of America. 2003;100(14):8080-8085
  11. 11. UN-ISRD (United Nations-International Strategy for Disaster Reduction). Living with Risk: A Global Review of Disaster Reduction Initiatives. Geneva: UN Publications; 2004. p. 429. ISBN/ISSN: 9211010640
  12. 12. Adger N. Vulnerability. Global Environmental Change. 2006;16(3):268-281
  13. 13. Kuhlicke C, Scolobig A, Tapsell S, Steinführer A, De Marchi B. Contextualizing social vulnerability: Findings from case studies across Europe. Natural Hazards. 2011;52(2):789-810
  14. 14. Hummel BMdeL, Cutter SL, Emrich CT. Social vulnerability to natural hazards in Brazil. International Journal of Disaster Risk Science. 2016;7:111-122
  15. 15. Filizola N, Guyot JL, Molinier M, Guimarães V, Oliveira Ede, Freitas MA de. Caracterização hidrológica da Bacia Amazônica. In: Rivas A, Freitas C, editors. Amazônia uma perspectiva interdisciplinar. Manaus: Manaus; 2002. pp. 33-53
  16. 16. ANA Agência Nacional de Águas (Brasil). Dados sobre a Rede Hidrológica de Monitoramento em operação na bacia Amazônica [Internet]. 2016. Available from: [Accessed: 10 November 2016]
  17. 17. Marengo J, Jones R, Alves L, Valverde M. Future change of temperature and precipitation extremes in South America as derived from the PRECIS regional climate modeling system. International Journal of Climatology. 2009;29(15):2241-2255
  18. 18. Hall A, Schumann G, Bamber J, Bates P. Tracking water levels changes of the Amazon Basin with space-borne remote sensing and integration with large scale hydrodynamic modeling: A review. Physics and Chemistry of the Earth. 2011;36:223-231
  19. 19. Martinez J, Toan T. Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data. Remote Sensing of Environment. 2007;108:209-223
  20. 20. Stevaux J, Latrubesse E, Hermann M, Aquino S. Floods in urban areas of Brazil. Development in Earth Surface Processes. 2009;13:245-266
  21. 21. CPRM Companhia de Pesquisa de Recursos Minerais. Cartas de Suscetibilidade a Movimentos Gravitacionais de Massa e Inundações [Internet]. 2016. Available from: [Accessed: December 27, 2016]
  22. 22. Bandeira ICN, Conceição RAC, Mello LB, João XSJ. Carta de suscetibilidade a movimentos gravitacionais de massa e inundação do município de Itaituba—PA. In: Anais do 15° Congresso Brasileiro de Geologia de Engenharia e Ambiental; 18-21 October 2015; Bento Gonçalves, Rio Grande do Sul. 2015. ISBN: 978-8572700696
  23. 23. Simões P, Conceição RAC, Vasconcelos K. Contribuição da carta de padrões de relevo para o mapeamento de suscetibilidade a inundação e movimentos de massa de Oriximiná-PA. In: Anais do 15° Congresso Brasileiro de Geologia de Engenharia e Ambiental; 18-21 October 2015; Bento Gonçalves, Rio Grande do Sul. 2015. ISBN: 978-8572700696
  24. 24. Nogueira AC, Machado MF. Carta de suscetibilidade a movimentos gravitacionais de massa e inundação do município de Santarém—Pará. In: Anais do 15° Congresso Brasileiro de Geologia de Engenharia e Ambiental; 18-21 October 2015; Bento Gonçalves, Rio Grande do Sul. 2015. ISBN: 978-8572700696
  25. 25. EEA (European Environmental Agency). Flood Risks and Environmental Vulnerability: Exploring the Synergies Between Floodplain Restoration, Water Policies and Thematic Policies. Luxemburg: EEA; 2016. p. 84
  26. 26. ANA Agência Nacional de Águas (Brasil). Atlas de vulnerabilidade às inundações [Internet]. 2014. Available from: [Accessed: November 15, 2016]
  27. 27. Cutter S, Boruff B, Shirley W. Social vulnerability to environmental hazards. Social Science Quarterly. 2003;84(2):242-261
  28. 28. Cardona, OD. The need for rethinking the concepts of vulnerability and risk from a holistic perspective: A necessary review and criticism for effective risk management. In: Bankoff G, Frerks G, Hilhorst D, editors. Mapping Vulnerability: Disasters, Development and People. London: Earthscan; 2004. pp. 37-51
  29. 29. Birkmann J, Welle T. The WorldRiskIndex 2016: Reveals the necessity for regional cooperation in vulnerability reduction. Journal of Extreme Events. 2005;3:1650005-01-1650005-21. DOI: 10.1142/S2345737616500056
  30. 30. Rufat S, Tate E, Burton CG, Marrof AS. Social vulnerability to floods: Review of case studies and implications for measurement. International Journal of Disaster Risk Reduction. 2015;14:470-486
  31. 31. IPEA Instituto de Pesquisa Econômica Aplicada. Atlas da Vulnerabilidade Social nos municípios Brasileiros [Internet]. 2015. Available from: [Accessed: October 9, 2016]
  32. 32. PNUD Programa das Nações Unidas para o Desenvolvimento. Atlas do Desenvolvimento Humano no Brasil [Internet]. 2013. Available from: [Accessed: November 20, 2016]
  33. 33. Brondízio ES, Moran E. Human dimensions of climate change: The vulnerability of small farmers in the Amazon. Philosophical Transactions of the Royal Society B. 2008; 363:1803-1809. DOI: 10.1098/rstb.2007.0025
  34. 34. Mansur AV, Brondízio ES, Roy S, Hetrick S, Vogt N, Newton A. An assessment of urban vulnerability in the Amazon Delta and Estuary: A multi-criterion index of flood exposure, socio-economic conditions and infrastructure. Sustainability Science. 2016;11:625-643
  35. 35. Szlafsztein C, Sterr H. A GIS-based vulnerability assessment of coastal natural hazards, state of Pará, Brazil. Journal of Coastal Conservation. 2007;11:53-66
  36. 36. Szlafsztein C, Marques O, Maia H, Prette M, Fischenich P, Altieri F. Referências Metodológicas para mapeamento de Riscos Naturais na Amazônia: Mapeando as vulnerabilidades. Brasília: MMA/GTZ; 2010. p. 59
  37. 37. Silva Junior MO, Szlafsztein C. Análise de risco como critério a gestão do território: um estudo do plano diretor do município de Alenquer (PA). Olam: Ciência & Tecnologia. 2010;10:1-29
  38. 38. Wiréhn L, Danielsson A, Neset T-S. Assessment of composite index methods for agricultural vulnerability to climate change. Journal of Environmental Management. 2015;156:70-80
  39. 39. Vogt N, Pinedo-Vasquez M, Brondízio ES, Rabelo FG, Fernandes K, Almeida O, Riveiro S, Deadman PJ, Dou Y. Local ecological knowledge and incremental adaptation to changing flood patterns in the Amazon delta. Sustainability Science. 2016;11:611-623
  40. 40. Fonseca D, Szlafsztein C. Riscos geológicos. In: João XS, Teixeira SG, Fonseca DDF, editors. Geodiversidade do Estado do Pará. Belém: CPRM; 2013. pp. 119-130
  41. 41. PimenteL J, Ferreira CEO, Shinzato E, Maia MAM, Silva SF, Hoelzel M, Pfaltzgraff PA, Morais JM. de, Parisi GN, Silva CN, Filho IB. de O, Fregolentte A. Atuação do Serviço Geológico do Brasil no mapeamento de risco geológicos para a redução de impactos decorrentes de eventos extremos. In: Proceedings of Congresso Brasileiro de Geologia CD-Rom; 30 September–05 October 2012; Santos, São Paulo; 2012
  42. 42. Bandeira ICN, Di Salvio LPP. Resultado da setorização das áreas de alto risco a inundações na zona urbana de Altamira no estado do Pará. In: Anais do 14° Congresso Brasileiro de Geologia de Engenharia e Ambiental; 1-6 December 2013; Rio de Janeiro. 2013. ISBN: 978-8572700696
  43. 43. Ministério das Cidades. Capacitação em Mapeamento e Gerenciamento de Risco [Internet]. 2007. Available from: [Accessed: December 12, 2016]

Written By

Milena Marília Nogueira de Andrade, Iris Celeste Nascimento Bandeira, Dianne Danielle Farias Fonseca, Paulo Eduardo Silva Bezerra, Ádanna de Souza Andrade and Rodrigo Silva de Oliveira

Submitted: 05 December 2016 Reviewed: 31 March 2017 Published: 30 August 2017