A flood is that event that, due to the precipitation, swell, tide or failure of some hydraulic structure, causes an increase in the level of the free surface of the water of the rivers or of the sea, generating invasion or penetration of water in places where there is usually none and, generally, damage to the population, agriculture, livestock and infrastructure [1
]. Floods are a global phenomenon that implies multiple impacts ranging from economic loss to the loss of human life. According to the United Nations, an average of 102 million people are affected every year by floods, surpassing those affected by cyclones, hurricanes, or typhoons (37 million), and landslides (366,000) [2
], generating the greatest disasters throughout history [3
]. Between 1990 and 2012, flooding affected over 36 million people and led to 44,000 fatalities [4
]. Moreover, between 1973 to 2000 in Southern and Eastern Europe, the total amount of damages reported was around 27.6 billion Euros and 24.5 billion Euros, respectively [5
]. In addition, according to the World Health Organization (WHO) [6
], floods can potentially increase the transmission of waterborne diseases such as typhoid fever, cholera, leptospirosis, and hepatitis A; vector-borne diseases such as malaria, dengue and dengue hemorrhagic fever, yellow fever and West Nile fever, not counting the effects on mental health [7
The Sendai Framework [8
] defines factors such as rapid urban growth without planning, poverty, inequality, poor land management, deficient urban policies, climate variability and climate change as risk determinants. All those drivers might be found combined in low-income urban territories exposed to floods. For the quantification of this kind of risk, it is necessary to study both the physical conditions of floods and the vulnerability represented by the territorial occupation dynamics of the communities. According to the Intergovernmental Panel on Climate Change (IPCC), urban areas will be more exposed to extreme weather conditions, and therefore to flooding, increasing vulnerability and risk [9
]. In a climate change context, there is an open question relating to the quantification of vulnerability in urban flood-prone areas [11
] where information and resources are scarce, as is the case in most of the commonly flooded municipalities in developing countries.
Vulnerability is understood as the susceptibility to be adversely affected by natural hazards and is related to concepts that include sensitivity or susceptibility to harm and a lack of capacity to cope and adapt [10
]. There are multiple approaches for quantifying vulnerability, not only for people but also for infrastructure, all depending on the quality and availability of the information [11
]. Traditionally, vulnerability is evaluated with two frameworks—risk-hazard and pressure-and-release models [21
]. However, those models are not suitable for the definition of particular coping strategies in low-income urban territories in risk areas in developing countries, as proposed by Turner et al. [22
Although it is agreed that it is necessary to take into account the exposure, the views of the community, governance [15
], the socio-cultural, economic and environmental context [25
], these suggestions lack a scalable approach. The framework for vulnerability analysis in sustainable science, proposed by Turner et al. [22
], can be adapted to the conditions of low-income urban territories exposed to floods [29
] because it provides a detailed analysis by integrating more variables. Additionally, considering resilience as a component of vulnerability, it is possible to analyze which basic spatial units may recover faster after a disaster [30
According to the framework for vulnerability analysis in sustainable science [22
], there are three main elements that shape vulnerability, namely: Exposure to a hazard event, susceptibility, and resilience (Figure 1
, adapted from [22
]). Exposure is defined by the physical conditions of the system and its environment in order to face the threat [31
]. Susceptibility offers a measure of the possible consequences that stakeholders may endure during a disaster, according to social values that may be monetary, ecological, of human life and psychological (among others) [32
]. Resilience is the capacity of a system to react, resist, and recover from the impact of a disaster event [12
]. The main goal of measuring vulnerability is to know and understand a system at risk, in order to define coping alternatives [34
Vulnerability assessments rely on field data collection, generally through participatory techniques, in order to incorporate the local knowledge of the communities and to enhance the understanding and responsibilities of the communities and institutions in the disaster risk reduction process [37
]. The participatory approach produces large amounts of qualitative data that needs to be properly analyzed with techniques for the analysis of categorical data and social surveys [42
] such as multiple correspondence analysis (MCA) [43
MCA is a powerful methodology when using categorical variables from surveys. It is an extension of the Correspondence Analysis and can be interpreted as a generalization of the Principal Component Analysis using categorical variables [44
]. MCA has been used in many fields such as fire management [42
], diagnosis and prevention of accidents [45
], education and work insertion [46
], and human exposure to heavy metals [47
], among others. We have selected MCA for two reasons. The first is that data needs to be collected through surveys and the classification of variables resulting from expert evaluation renders data in qualitative scales, and the second is the great potential of the multivariate tool to perform an evaluation of each component of vulnerability or the joint analysis of the three (exposure, susceptibility, and resilience) in order to unveil its relative importance.
Colombia is a developing country [48
] that classifies its municipalities by categories from 1 to 6 depending on their income, (with the sixth category being the worst condition and category 1 being the best condition) [49
]; 87% of the Colombian municipalities are classified in category 6 [50
] and 53% of Colombian municipalities have more than 25% of their population with unsatisfied basic needs. In addition, the country is frequently affected by floods, as until 2012 it occupied the tenth and eighth place in the world by the number of deaths and damages, respectively, generated by this type of hydro-meteorological disasters [51
], with over 10 million people affected and more than two million fatalities between 1990 and 2012. It is worth noting that more than four million of those affected and almost 700 deaths were in the wet season of 2010–2011 [4
]. These circumstances led the country to formulate policies and regulations on disaster risk management that require detailed risk assessment studies, including the assessment of vulnerability [53
Most of Colombian territory presents a tropical fully humid climate, tropical monsoon, and savanna climates according to the Köppen–Geiger climate classification [55
]. These climates can be found in other South America countries such as Ecuador, Perú, Venezuela, and Brazil; in African countries like the Democratic Republic of the Congo, Uganda, the Republic of the Congo; and in almost all the countries in Southeast Asia. Although those are the main features of climate in the country, the three selected case studies differ between them on the basin response time. In the case of Amalfi, floods are sudden or torrential due to the mountainous regime of the river, and in the cases of Caucasia and Plato municipalities floods are slow due to their location on the floodplains of the rivers. The methodology proposed in the present study may apply not only communities in the developing world with similar climate features to those in Colombia but also to different kinds of flooding.
The main goal of this research is to formulate a vulnerability indicator for low-income urban territories in flood-prone areas. For that purpose, we evaluated exposure, susceptibility, and capacity, adapting the framework proposed by [22
] and we used MCA to identify and classify the most important variables regarding vulnerability in order to calculate a particular indicator for each case study. This paper is organized as follows. Section 2
outlines the case studies and the methods used in the present study. In Section 3
we present the results for each one of the case studies, and in Section 4
we present the discussion and conclusions.
4. Discussion and Conclusions
This paper shows a methodology for the assessment of vulnerability in low-income urban areas at the household level. Working at the smallest geographical unit facilitates the aggregation of the results in other geographical scales such as urban blocks, neighborhoods, or cities, which is essential for social and physical infrastructure investment decisions, maximizing the probability of resources being assigned to those who need it most. The property of scalability represents a bottom-up approach for vulnerability assessments in any urban flood-prone territories. Our methodology can be also used to generate maps relative to the vulnerability, by merging the results of the MCA with geographic data. The geographical representation of vulnerability will help decision-makers in risk reduction with the identification of areas in need of preventive measures, and the spatially differential levels of resilience to floods.
In addition, the formulation of the indicator uses a flexible framework that can be adapted to the social, physical, institutional, economic and environmental conditions of various low-income urban territories. The MCA results are obtained based on these specific conditions, which allows finding a particular weight for each specific variable according to its context. Also, by identifying which variables are more representative, interventions can be determined according to the variables’ importance for the reduction of vulnerability.
From the results presented, we have identified that whether it is a sudden or slow-onset flood, the susceptibility (S) component of vulnerability is the most significant. By reducing the predisposition of communities to suffer damages from the flood events, it is possible to achieve a reduction of total vulnerability. The S component is related to public management and planning for development. One approach for intervention in low-income territories could be an initial corrective intervention to attend these S variables, and then with more resources, implement more resource-consuming interventions such as the relocation of families and households in order to reduce susceptibility.
Considering the results from the slow-onset floods case studies, we argue that the long-term exposure to flooding of parts of the housing structures results in a permanent deterioration, affecting the ability to prevent further damage. This progressive deterioration of the structures is additional to the damages to belongings, such as furniture, appliances and other items inside the house, as well as low household income and the lack of public services. This means that the residents will not be able to invest in the maintenance of the household and in replacing the items at the same time. This situation increases their vulnerability and their unsatisfied basic needs. As for the variables related to the resilience (R) component of vulnerability, they reflect the relationship between a protectionist government ready to attend in case of an event and the preparedness of the communities to floods. Due to the nature of the flood (slow onset), people with access to early warning or alert systems are more likely to avoid damage to life and property.
On the other hand, regarding sudden floods, the timing of the event is most relevant. The variables with the most significance are related to the structural damage to the foundations of the buildings due to the impact of the flood. The age of the households and the structural type of the foundations may define the capacity to withstand flood and maintain the structural integrity. Also, the timing of the flood is of utmost importance for evacuation processes, and therefore a relevant variable for vulnerability. Additionally, for the specific case of Amalfi, where streets may act as waterways during a flood, the shape of the block is an important factor to reduce the energy of the flood.
For this case study, the other most important variables were those of exposure (E). Conditions such as the distance to the nearest drainage or river and the number of windows and doors in the most exposed façade, increase vulnerability.
Thus, for slow-onset floods, susceptibility and resilience are the most significant components for vulnerability; while for sudden floods the components are susceptibility and exposure. Other studies might further test this result and extend this framework. Our results reinforce the current approach to risk management (Sendai Framework [8
]) in which susceptibility interventions can be compared with risk reduction processes, resilience with residual risk management processes (after reduction), and the increase in exposure with the reduction or generation of new risks.
The Sendai Framework [8
] promotes risk reduction and avoidance of risk generation. With susceptibility being identified as the most relevant component of vulnerability, risk reduction and development planning should become priority activities in urban territories with low income, which are prone to slow as well as sudden floods.
We would like to clarify that we have applied the MCA results with the prioritization of certain situations, but that all the variables and components are important for the vulnerability assessment. Thus, all variables should be analyzed and interventions be designed for them, but given our focus on municipalities with particularly limited resources, this analysis provides a starting point for identifying the most effective investment strategy in flood risk management.
Regarding the methodology, the use of variables with statistical information from national programs and social services facilitates the replication of and longitudinal analyses to identify how vulnerability reduction evolves in the specific territories. We presented three case studies for two types of floods. With an adequate characterization of the vulnerability variables, it is possible to replicate this methodology for other hazards such as fires, avalanches, hurricanes, and flash floods. It is also important to emphasize that the information provided by the communities is used to generate spatialized knowledge and, thus, is useful for community decision-making.
The MCA has turned out to be a useful tool for community vulnerability assessment. The construction of a vulnerability indicator allows the evaluation of vulnerability conditions in a global manner and also for the evaluation of each component of vulnerability, such as susceptibility, exposure, and capacity.
According to Colombian legislation, the results of this research are equivalent to detailed technical studies for the incorporation of disaster risk management in territorial planning. The use of open-source software and statistical tools extends the audience of its application in methodologies, such as the one presented in this paper, which allows local administrations to work within tight budgets. Therefore, the application of the proposed methodologies is particularly useful for municipalities with a high occurrence of disasters and limited resources.