The world community faces increasing flood risks as the pattern of flooding on all continents is changing and becoming more frequent, intense and unpredictable. Floods are the most devastating type of natural disaster affecting human lives around the world [1]. The impact corresponding to urban floods is significant due to factors such as high population density, large impermeable areas, and obstruction of drainage systems. The impact caused by flooding in urban areas can be physical, economic, social and environmental [2]. One of the most important indicators of the consequences of such hazards is measured by the high level of economic losses that are usually expressed as direct economic damages [3].

The word risk is used in several contexts. It is related, for example, to the environment, economy, and engineering discussions, among others. The attempt to give a single definition to risk, applicable to all areas, is not advisable in view of the difficulty in addressing different and specific aspects of each one. Therefore, it is usual and necessary to adopt a particular interpretation for risk analysis, consistent with the topic addressed [4].

The risk concept used by United Nations International Strategy for Disaster Reduction (UNISDR) [5] defines risk as the probability of harmful consequences or expected losses (deaths, injuries, interrupted economic activities or environmental damages) resulting from interactions between natural or induced risks vulnerable conditions of a socioeconomic system. Conventionally and in a simple way, the risk can be expressed by the relation: Risk = Hazard × Vulnerability × Damage.

Veyret [6] conceptualizes risk as perceiving a possible danger, more or less predictable by a social group or by an individual who has been exposed to it and can suffer from it. It can be emphasized that the hazardous event alone does not define the risk. It is necessary that the individual or social group has to be exposed and vulnerable to the hazard. Risk is inscribed within a social, economic and cultural context, therefore, it is not possible to examine risk representations without considering management practices.

It is important to highlight the concepts of susceptibility and social vulnerability, which are necessary for the discussion and analysis of flood risk. According to Alliance Development Network and United Nations University, Institute for Environment and Human Security (UNU-EHS) [7] susceptibility refers to conditions of exposed communities or exposed elements (infrastructure, ecosystems, etc.) that become more likely to experience damage and be adversely affected by a natural disaster.

For Intergovernmental Panel on Climate Change (IPCC) [8] vulnerability is the degree to which a system is susceptible and unable to cope with adverse effects of climate change (which is the particularly concern for IPCC), including climate variability and extremes. The social vulnerability can be expressed through socioeconomic and demographic parameters. The vulnerability is related to the social disadvantages that are reflections and products of poverty, which, in turn, is understood as a social condition that restrictively affects individuals, social groups, and places. In this sense, vulnerability corresponds both to limited access to knowledge and to the low capacity and inability to manage the resources and opportunities available to society for the development of its members. It is also reflected in the inability to recover from damages. This conceptual vision allows anticipating risks and potentiating eventual adaptations.

In the face of frequent flooding, it is necessary to improve the retention and infiltration of rainwater in urban river watersheds [9]. However, the traditional solution for urban stormwater problems in most countries refers to structural interventions involving storm drains, canals, and dams aiming to avoid local flooding. An usual consequence of this approach is that, by increasing the conveyance and flow velocity, it can change the river dynamics and transfer problems downstream [10]. A new approach is needed that includes both structural and non-structural measures, recovering natural responses, and maximizing multifunctional opportunities for land use [11].

However, cities located on riverbanks, in naturally fragile areas, subjected to flood risks (and residual flood risks) may require a management approach also based on resilience to floods and not only on resistance. Resisting floods through dams, channels and storm drains neglects inherent uncertainties stemming from human-nature interactions and does not address the extreme events that are expected to increase with climate change and therefore is not a reliable approach to face long-term flood safety demands [12].

Urban floods cannot be managed separately in the city scale and the responses to the possible impacts of the flood are complex because of political and socioeconomic issues linked to environmental changes. To understand the characteristics of the effects of urban floods, a space-time structure must be developed to clarify the causes of the vulnerability of cities [13]. According to Bobrov [14], urban planning is the design and regulation of space use which focus on the physical form, economic functions and social impacts of the urban environment and on the location of different activities within it.

Tapia et al. [15] developed an indicator-for vulnerability assessment in European countries, based on potential hazard-receptor combinations (impact chains) (i.e., heatwaves, drought, and flooding). The vulnerability assessment can be used to allocate the international cooperation resources targeted to adaptation plans.

It is widely recognized that flood plains have always been attractive settlement areas. The time and space pattern of flood flows, and the exposure and vulnerability socioeconomic system define the risk. Exposure is dependent on the spatial extent of the hazard that threatens the population. Its magnitude and frequency is related to with the vulnerability [16]. The importance of integrating water management in urban planning to promote city resilience to flooding is emphasized in this context. Rapid and preliminary assessment of possible economic losses caused by outflows in an urban basin is very important for adopting disaster mitigation measures [17]. Disaster management is a process that includes activities before, during and after a risk event that aims to reduce disasters impacts and to recover from their losses [18].

The risk is very often evaluated subjectively, taking into account only a few factors that contribute to the problem and leaving aside other factors that affect its criticality. According to Ranzi and Vu [19], the quantification and assessment of flood damage is an important factor to be considered in the decision process to define specific measures for flood risk management. Risk assessment through the formulation of an index allows the introduction of a quantitative measure, although not precise, that is able to join different subjective matters and map the importance of a given risk.

The formulation of an index is given by the mathematical equation that expresses the relations between the indicators that compose it intending to represent what one wishes to measure. Its construction, in turn, aggregates information associated with indicators of different meanings and natures, translating them into a single representative value of reality, thus allowing comparisons in time and space [20]. On the other side, choosing the indicators adequately is crucial to the effective representativeness of the index.

For Kim [21], indices are necessary for any information collection, and the function of an index is to provide users with systematic and effective shortcuts to the information they need. Thus, indices can perform diverse functions, such as evaluating existing conditions, comparing places, situations or alternatives, providing advance notice of any effect or impact of an action and predicting future conditions and trends.

An index allows aggregating information associated with indicators of different constitutions, translating them into a single (and simple) value representative of a real complex situation. According to Alegre et al. [22], the process of creating these indicators and/or indices includes obtaining elementary data, which are filtered and transformed into variables that are combined to form indicators (and indices). Its ultimate goal is to provide relevant information to be used in the decision-making process especially in early planning or comparing alternative choices. Multi-criteria methodologies can play a very important role in the formulation of indices.

Geographic Information System (GIS) tools and mathematical modeling can also be used in this type of study. A GIS may be used to retrieve and exploit the spatial properties of the visual structure inherent to space [23]. GIS is an emerging tool for planning and application of projects to territory [24]. Thus, GIS provides better information for decision-making situations [25].

Mathematical modeling allows the simulation of real systems in order to predict their behavior. In the absence of sufficient historical observations about the floods, advances in remote sensing and computational power have created more attractive mathematical models, where spatial predictions of potential damage from future flood episodes are calculated [26]. Currently, mathematical modeling methods are effective tools for studying non-stationary processes found in the natural environment [27]. When combined with multi-criteria approaches, the mathematical models, which are usually more sophisticated, more expensive and more data and time consuming, may be used in a preliminary phase intending to calibrate and or validate the proposed index.

In this context, the main objective of this work is the development of a multicriteria methodology for flood risk analysis, to aid urban planning and to support flood risk management policies, in order to avoid the occupation and densification of areas susceptible to flooding. The Inundation Risk Index (IRI) seeks to aggregate simple indicators, combining physical characteristics of the river basin, related to the natural propensity to flooding, and the social features of the affected population.

The IRI was developed to identify, in a relatively simple and fast way, the flood risk areas of a basin. An evaluation of its effectiveness was made using the case of the Bacanga River basin, in the municipality of São Luís/Maranhão State, in the northeast region of Brazil. The IRI is composed by two sub-indices, one responding by the physical susceptibility to flooding, the other representing the social system vulnerabilities. The hydrodynamic model called MODCEL, developed by Miguez [28], was used to validate the susceptibility sub-index, comparing flooded areas modeled with those mapped by the sub-index. The methodological steps are described in the sequence following below.

Geoprocessing as a decision support tool

Geoprossessing tools were used to manipulate and agggreate information in the watershed space. Figure 1 briefly shows the geoprocessing steps developed as a preliminary activity to operate the IRI.

Figure 1.

Procedure flowchart

The occupation of São Luis privileged, in a first moment, the flat lands not subjected to the floods. With the rapid urban growth, many slopes and fluvial channels were modified by man in a disorderly way, disregarding the fluvial geomorphology and its natural processes, leading to the occupation of risk areas.

Bacanga River basin presents 63.08% of its watershed in flat relief area, with altitudes of up to 3 meters, in the fluvial-marine plains, and from 4 to 7 meters, in the fluvial plains. The absence of vegetation cover associated with certain characteristics of its soils, slope and altimetry, lead to great flow velocities, little amount of water stored in the soil and usually result in expressive floods. Figure 2 shows the map of physical susceptibility to flooding for the Bacanga watershed, spatially mapped by census tracts.

According to Coelho [43], relatively flat regions or low slopes present natural drainage difficulties.

The sub-index representing physical susceptibility to flooding may also be used separately for pre-identifying the sites with the highest degrees of flood susceptibility, with the main objective of assisting urban planning. This is not a specific or rigorous flood mapping, since the process is not deterministically modeled. Therefore, it was not intended to precisely detail the phenomenon – this is not the role of the indexes. The goal is to provide a simple tool that can quickly and consistently indicate which areas require more attention in urban planning and which require more detailed studies to house urban sprawl.

According to data from the Demographic Census 2010, conducted by the IBGE, 232 census tracts are considered subnormal clusters in São Luís, 52.58% of which are located in the Bacanga basin. In the IBGE indicator on illiteracy, Maranhão was the fourth worst result in the country, with 19.1% of people over 15 years old, unable to read or write. Of the 312,063 inhabitants of the Bacanga river basin, 5% are illiterate.

For the calculation of the Income indicator, monthly nominal income information of all households was used for each census sector in the IBGE database for the Bacanga basin. Of the 78,154 households surveyed, 5% had no income, 87.94% had an income of up to 2 minimum wages, 5.67% had an income of 2 to 5 minimum wages, 1.09% had an income of 5 to 10 minimum wages and only 0.30% had incomes of more than 10 minimum wages.

Figure 2.

Map of susceptibility to flooding in the Bacanga basin

The distribution of the population of the Bacanga basin by age presents: 47.56% of the population between 20 and 50 years, 31.68% of the population between < 15 and > 65 years and 20.75% of the population between 15-20 and 50-65 years.

Figure 3 shows the specialized result of the mapped vulnerabilities. From these results, something about 27% of the territory are classified as very low vulnerable – despite the pressure exerted by informal urban occupation, the basin still has a large vegetation cover, due to the Bacanga State Park and the permanent preservation area (APA) of Maracanã and an industrial region, 17% are classified as having low vulnerability, where the basin presents some urban voids close to the tributaries of the main river, 20% of the basin is classified as moderately vulnerable, in an area of the historical center of São Luís, 21% are classified as vulnerable and about 15% as very vulnerable.

Figure 3.

Map of social vulnerability of the Bacanga watershed

Flood risk

The association of the physical and social aspects of the catchment area of the Bacanga River results in a flood risk map defined by the IRI formulation.

The weights were taken as equal for both sub-indices, since it was considered that there is no risk without the susceptibility to flooding being able to reach a vulnerable area. Since both indices are associated with the same subdivisions of the domain, that is, census tracts, it is possible to easily operate them to obtain the IRI value. Figure 4 shows the results for the IRI.

It is possible to observe that the areas at greatest risk are located in the floodplain of the Bacanga River, in relatively flat and low areas. From time to time, these areas receive excess waters that overflow from the watercourses and reach the installed population there. The results show that, in a qualitative evaluation, the most critical areas are those with low slopes and with great social vulnerability, as previously expected by construction.

The flood hazard areas of the Bacanga river basin are also socially vulnerable areas. Approximately 90% of households earn less than two minimum wages. It is verified that the results obtained by the IRI express the order of magnitude of the problems associated with flooding in the study area. The weighting adopted for the selected indicators shows consistency, given the results of the simulation, although the discussion on which weights to use is always open.

Figure 4.

Flood risk map in the Bacanga watershed

In order to validate the applicability of the proposed formulation, susceptibility to floods was compared with a hydrodynamic simulation. It should be noted that, in this model, it is possible to simply measure flooding, without quantification of effects on the socioeconomic system. Therefore, the sub-index VUL, which involves socioeconomic aspects cannot be measured by the model. Figure 5 shows the flood map obtained with MODCEL for the current urbanization conditions of the Bacanga River basin, for actual rainfall of April 11, 2009, resulting in a total precipitation of 155.6 mm. The time of concentration of the Bacanga watershed is 3.5 hours. This time was considered as equal to the duration time of the rainfall event, and the temporal distribution was defined by applying the Alternate Blocks Method, also called the Bureau of Reclamation Method [44], in order to supply this missing information, once only the total rainfall was measured.

In the IRI application, the susceptibility to flooding of the physical environment, represented by the SUS sub-index (which measures the hazard and therefore has a conceptual analogy with the flood mapped by a hydrodynamic model) can be compared with the result of Figure 5, for purposes of validation of the indirect representation that was proposed. In this way, the result of the proposed index can be considered satisfactory, since it is compatible with the modeled results, which represent observed reality. The SUS results showed good adherence to the results of the MODCEL hydrodynamic model. Note that the water level classes in which this event was mapped are presented in Table 13.

Figure 5.

Flood of the Bacanga/Rain river (11/04/2009)

Table 13.

Flood level classes

Classes	Water levels
Very low flood levels	0.00-0.10
Low flood levels	0.10-0.20
Medium flood levels	0.20-0.35
High flood levels	0.35-0.50
Very high flood levels	More than 0.50

The IRI results show that the areas with the most critical risk values are also the most urbanized, with subnormal clusters and with high demographic density, in addition to being located near the watercourses. When compared to the flood map presented in the cell model, IRI result shows that the population density indicator ends up incorporating critical effects, even in areas with higher altimetry where the flood hazard is not likely to occur.

IRI appears to be a useful tool for the interpretation of the territory, with respect to its propensity to flood and to evaluate (albeit qualitatively) the effects of these possible floods on society.

The IRI establishes a multi-criteria methodology for determining the risk of flooding in a simple way, using easily available data, avoiding more sophisticated tools of mathematical modeling in the planning stage.

The study carried out in the Bacanga river basin, located in the city of São Luís do Maranhão, shows the effectiveness of the proposed and developed index. In addition, the subscript referring to the natural characteristics of the basin, whose statement pretends to simulate the physical susceptibility to floods, is corroborated by the MODCEL hydrodynamic model, used to produce flood maps for the studied area.

With regard to the indicators chosen for the composition of the index, they worked in a satisfactory and representative way. Its characteristics allowed to spatialize areas prone to flooding, so that the greater the susceptibility of the region associated with the social vulnerability of the population, the greater the risk.

The normalization scales were elaborated in an intuitive way, using indirect references, constituting a possible fragility of this study, which suggests that other alternatives can be tested. It is recommended to add a sensitivity test to the study, for weights and also for the proposed scales. These aspects, however, do not invalidate the general methodology.

Both the formulation and the composition of the index are positive points of this methodology, since each sub-index represents the main components of risk assessment. The formulation clearly works in associating hazard and vulnerability through a product that makes risk null if one of these components is null, and the indicators use simple data usually available at the municipal level.

It should also be emphasized that the use of GIS for data storage, analysis and processing proved to be very convenient and efficient, as it allowed combining, analyzing and visualizing several types of information in the same area, allowing the results to be presented clearly and adequately, even for a non-specialized audience.

By identifying areas at risk of flooding, IRI can assist in the formulation of guidelines, regulations and legal standards to land use and urban growth planning, in addition to indicating areas already occupied and fragile, that demand attention and mitigation actions from the public power.