This paper is about the assessment of social vulnerability (SV) as a critical component of comprehensive disaster risk assessment. This study was conducted in Medina Gounass Dakar, Senegal, to bring out evidence that flooding was a threat to human security. The aim of this present study is to assess the social vulnerability to flood in Medina Gounass. Survey was carried out using structured questionnaires drawn on one hundred randomly selected households. For vulnerability assessment, the Methods for the Improvement of Vulnerability Assessment in Europe (MOVE) framework and Arc GIS are used to characterize vulnerability through three key factors, namely, 1) exposure, 2) susceptibility, and 3) lack of resilience. As a result, Medina Gounass inhabitants have a particular relationship with the place they have been living for decades. Although facing diseases and many challenges in their everyday life, people actually resist the government’s relocation projects because of their symbolic relationship with the area.
For centuries, human progress has depended on access to water in sufficient quality and quantity to make possible life on earth. This water has a great number of sources; the most common and known by almost everyone is rainfall. Rainfall depends on the climate and it is known that the most brilliant civilisations that planet earth has ever known become prosperous in periods of favourable climate. Nowadays, this planet which produces the ecosystem services for human well-being has some disturbances in a pace that threatens the future of humankind. Thus, the earth is facing challenges, such as raising population, increasing desertification and, of course, climate change. Climate change, in IPCC (Intergovernmental Panel on Climate Change) usage, refers to a change in the state of the climate that can be identified (e.g., using statistical tests) by changes in the mean and/or the variability of its properties, and that persists for an extended period, typically decades or longer [
This usage differs from that in the United Nations Framework Convention on Climate Change (UNFCCC), where climate change refers to a change of climate that is attributed directly or indirectly to human activities that alter the composition of the global atmosphere and that is, in addition to natural climate variability, observed over comparable time periods [
An increase in the number of persons, population density, infrastructure and production is located in hazardous areas and in conditions of such vulnerability they are more susceptible to excessive damage and loss and face considerable difficulties in coping [
Generally, flooding occurs in periods of heavy rainfall. However, floods are not always caused by precipita- tions. In these last decades, many scholars from various disciplines are interested in the field of disasters caused by floods. In Africa for instance, the frequency of hydrological disasters represented 68.8% [
For instance, assessment of flood vulnerability in the city of Abeokuta in Nigeria during the flood event in 2007 used a questionnaire survey to reach its goals. In his study, flood vulnerability was assessed by examining exposure and susceptibility, and coping indicators in the study area. One of his key findings was that most of Abeokuta inhabitants did not anticipate a flood event of such magnitude to occur, despite its location on a flood plain and, therefore, they were unprepared for such hazard [
The concept of vulnerability has a multitude of definitions. This concept is fundamental to human-environ- ment research. The word “vulnerability” is derived from the Latin word vulnerare, meaning “to wound”. At a very basic level, vulnerability can be defined as “the capacity to be wounded” or the “potential for loss”. Therefore, social vulnerability encompasses many aspects. It is not limited to social weaknesses to withstand a natural or man-made hazard but it includes social discrepancies in terms of food security, health security, and all the components of human security at large in the flooding situation. Social vulnerability is also directly linked to the environment in which people are living [
Social vulnerability can have multiple forms: it can be the state of the system before the event, and the likelihood of outcomes in terms of economic losses and life lost, and it can also be the lack of capacities or weaknesses to face and recover quickly when the disaster strikes. The latter deals with the resilience of a system or a community to respond and recover with its internal means to the adverse impacts of the disaster. Studies on the social production of vulnerability as a central theme of research on the human dimensions of environmental change hold that vulnerability to environmental disasters is largely a product of the way that humans occupy and use the natural environment [
The occurrence of floods in the Dakar suburbs is a new phenomenon. The Senegalese capital is characterised by an out of control urbanisation process. Among the many impacts noted, flooding has appeared recently as a major threat to poor population leaving in the suburbs of Dakar. Nevertheless, the combination of population growth, lack of urban planning, and climatic conditions have led to an unprecedented flood disasters in different urban areas of Senegal [
Medina Gounass district is located between 14.769 latitude North and −17.387 longitude West in the Guédia- waye Department. It is limited in the North by the district of Sam Notaire and the Ndiarème Limamoulaye district; in the East by the district of Wakhinane Nimzath and to the South and West by the district of Djiddah Thiaroye Kao. Formerly, it belonged to the Pikine Department (
Medina Gounass has the smallest area (1.1 km2) but has the highest density of 31,086 inhabitants per square kilometre across the Guédiawaye department. The number of people living in the study area is not definitely established. It is mentioned 44,000 inhabitants while former Deputy Mayor of Medina Gounass has 43,000 inhabitants [
Peul” called Plan “Tawfekh” which is about 22 km North-East of Dakar, the country’s capital and near to the Keur Massar administrative district.
Hydrologically, the watersheds of the district of Gounass are small in size. Degradation of the river system resulted in the formation of a chain of lakes or ponds. Flows are endorheic (having no outlet) as offshore bars prevent their escape to the Atlantic sea. Strong soil sealing in urban areas has changed the nature of runoff quantity (decrease losses flow, rapid movement of water). Over the past thirty years, this region has experienced very rapid urbanisation, linked to the rural exodus that climatic deterioration and degradation of living conditions in rural areas have caused in the entire Sahelian region [
Moreover, the ground water corresponds to outcropping geological formation consisting of sand dunes dating from the Quaternary or the continental terminal. These sands have been underlain by sedimentary geological formations [
Social vulnerability includes the climatic conditions, socioeconomic status, household composition and disabi- lity.
Key factors of the MOVE framework are related to the exposure of a society or system to a hazard or stressor, the susceptibility of the system or community exposed, and its resilience and adaptive capacity (
Exposure describes the extent to which a unit of assessment falls within the geographical range of a hazard event. Susceptibility (or fragility) describes the predisposition of elements at risk (social and ecological) to suffer harm. The Lack of resilience or societal response capacity is determined by limitations in terms of access to, and mobilisation of, the resources of a community or a social-ecological system in responding to an identified hazard, whereas the adaptation box deals with the ability of a community or a system to learn from the past disasters and to change existing practices for potential future changes in hazards as well as vulnerability contexts.
The MOVE framework characterizes vulnerability through three key factors, namely, 1) exposure (E)―re- flecting the extent to which a unit of assessment falls within the geographical range of a hazard event; 2) suscep- tibility (SUS)―which describes the predisposition of elements at risk to suffer harm; 3) lack of resilience (LoR), which is determined by limitations in terms of access to, and mobilization of, the resources of a community or social-ecological system in responding to a particular hazard. Based on data availability, previous research and personal judgement, the following indicators were selected under each vulnerability component (
This table gives the functional relationship between the indicators and the vulnerability.
All datasets were standardized, using linear min-max normalization (Equations (1) and (2)) according to (Iyengar and Sudarshan) [
When the indicators are related negatively with the vulnerability, the normalized value of the indicator is computed as follow.
Xij is the normalized value of the indicator i of the component j; xij, le value of the indicator i; max(xij) and min (xij) are respectively the maximum and minimum values of the indicators i of the component j.
It is assumed that there are M regions or districts, K indicators of vulnerability and xij
where w’s (
where c is a normalizing constant such that
Components | Number | Indicators | Functional relationship | |
---|---|---|---|---|
Exposure (E) | 1 | Household size | Positive | |
Susceptibility (SUS) | 1 | Number of children under 4 years | Positive | |
Lack of resilience (LoR) | 1 | Distance to nearest hospital | Positive |
The choice of the weights in this manner would ensure that large variation in any one of the indicators would not unduly dominate the contribution of the rest of the indicators and distort inter regional comparisons.
The aggregation of the three components (i.e., E, SUS and LoR) into the final composite indicator of socioeconomic vulnerability was then performed using the equation below, while taking into account specific weights for the three components as detailed below:
In the equation VU refers to the vulnerability index for a given neighbourhood, m equals the number of components, wj represents the weights for domain j and xj is the index of component j (i.e., E, SUS, LoR). In this study, the three components have the same number of indicators. So, the weight w is equal to 1 for each of them and m is represented by 3. The vulnerability index so computed lies between 0 and 1, with 1 indicating maximum vulnerability and 0 indicating no vulnerability at all.
Climate data involved in this study were monthly values of minimum and maximum temperatures and rainfall amount sorted by decades for the whole time series. These data are from the Dakar Yoff station and the dataset covers the time period 1947 to 2012. For the analysis, descriptive statistics for both monthly mean temperature and monthly total rainfall amount were firstly extracted. With Excel, the diagram average monthly mean temperature and rainfall is made.
The following formula is used for the Lamb index determination who proposed a rainfall analysis method named “rainfall anomaly index. This index is calculated by the following formula:
where rij is the rainfall measured in a year j at a station i, mi and σi are respectively the average and standard deviation of the rainfall recorded at the station i, and Nj is the number of stations that have recorded rainfall in the year j. Since the study area has one station (Dakar Yoff station), the above-mentioned formula becomes:
where Xi is the rainfall anomaly index for the year i, ri is the total annual rainfall for the year i, m and σ are respectively the average and standard deviation of the annual rainfall recorded during the period of time chosen for this study [
Quantitative method is used for the socio-economic analysis. The advantage of quantitative research is that the findings from the sample under study will more accurately reflect the overall population from which the sample was drawn [
where n is the sample size, N is the population size and e is the level of precision. 44,000 people live in Medina Gounass our sample comprises 100 households, because we apply P = 10% with the formula above.
This research equally adopts an exploratory approach, using predominantly qualitative methods. Qualitative research provides a richer and more in-depth understanding of the population under study. Techniques such as interviews and focus groups allow research participants to give very detailed and specific answers [
EpiData, excel and the Statistical Package for the Social Sciences (SPSS) are used for data entry and statistical analysis for data analysis. For EpiData, questions should be coded in quantitative form so that it could be easily analysed. This software is very useful because it can allow us to convert different variables from the field survey to an excel file for the statistical analysis in SPSS. Thus Pie charts and bar graphs are drawn.
Generally speaking, precipitation in Sénégal is closely related to the one that prevails in the Sahel. It occurs with the advent of the African Monsoon. During the second half of May and June, the ITCZ (Intertropical Convergence Zone) is stable around 5 degrees north. It is the first rainy season in the Gulf of Guinea. While in July, the ITCZ has moved rapidly to the north, reaching its second equilibrium position at 10 degrees North and remains there until mid-August. It is the wet season in the Sahelian region [
In the same vein, 2005 is characterised by the frequency of heavy rainfall within a short period. Therefore, with an annual total of 590 mm rainfall, 270 mm with a percentage of 46% have fallen within seven days in mid-August and 360 mm in fourteen days which represent 61% by the end of August and the beginning of September. Comparing these information with our data which are sorted per decade, in 2005, Dakar Yoff station recorded 188.9 mm and 145 mm for the second and third decades, respectively, for a monthly total of 336 mm. In the first decade of September, 106.8 mm were recorded [
The annual rainfall index variation has a long history in climatology for the determination of dry years and wet years. For instance the Sahel drought was a recurrent concern for populations, hydrologists and ecologists. Actually, West Africa, as a whole, experienced a widespread drought in the 1970s and 1980s [
For this index, the negative values below −0.5 are considered dry years and positive values above 0.5 are wet years, the Lamb index used to perform rainfall analysis based on daily data precipitation collected at ten synoptic stations of Sénégal from 1921 to 2000 [
Furthermore, a survey has been conducted and using the same station data ranging from 1970 to 2009. Climate variability is obvious through the rainfall totals throughout the Sahel. Normalized standard deviation for Dakar-Yoff station can vary considerably from one year to another. This variability due to type of disturbances; squall lines and cyclonic disturbances in the atmosphere bring most of the rainfall in Dakar. Additionally, the rainfall trend is on an increase from 1970 to 2009 and shows positive differences during the 2000s [
Looking at
One might be tempted to say that we are at the end of the cycle of drought and beginning of a new wet phase in Sénégal, but it’s too earlier to argue that it is the return period to wet years in Sénégal. As an example, in an interview during the data collection, the 2014 rainy season was forecasted by ANACIM (Agence National de l’aviation Civile et de la Meteorologie) to be a normal to deficit one. Thus, until the beginning of September, many areas in the country did not have much rainfall for agricultural activities.
A close observation of the Lamb index graph, suggests that there are wet years during the period 1947-1970 and 1970 to 1989 corresponds to a long period of dryness. This period corresponds to the long droughts which hit the Sahel in general. In 1989, there was a wet year and after that we fall again in drier years till the early 2000s where wet years seem to be more frequent. In this last decade, rainfall is not without negative consequences for urban inhabitants. Hence, Dakar suburban particularly those from Medina Gounass, are constantly on rain water mixed with sewage, and drainage water which obstruct people’s activities. This particular aspect is emphasised that in August and September 2005, nearly 200,000 people in poor suburbs of Dakar had their feet in the water and were later displaced and resettled in precarious sanitary conditions [
The sample size of the survey is 100 household administrated within the study area. These filled questionnaires related to a certain number of social, economic, educational, environmental, and existential issue in the area where they live.
The education level shows sometimes the degree to which a community in able to withstand and recover quickly when a disaster strikes.
In the same vein, the informal sector employs the youngest workers, the less educated and more females in Medina Gounass. This is also the area where we have the lower income, where social benefits are the lowest and the social welfare is almost null [
The literacy rate sometimes determines the level of income. Thus, Medina Gounass residents are not highly paid. Consequently, their level of income cannot allow them to afford housing in the well planned urban areas where viable and liable amenities already exist.
It appears clearly in
East and the South. This situation is exacerbated by the droughts of 1972-1983 which generated inter-regional migration. The main migration flows are directed towards the Dakar region (49% of flows in 1976) [
These situations are the driving forces behind the high population density in many suburbs including Medina Gounass. The socio-economic situation, the governance issues and climatic conditions encouraged people to settle haphazardly in these areas and no one at that time could imagine what would happen if there is a return period of rainfall. Additionally, the population growth in an unplanned site aggravated people’s suffering during flood events. The land ownership was so cheap that people with moderate income prefer to have their houses in that risky area. These factors put Medina Gounass populations in a permanent situation of human insecurity.
Thus, the main driving force behind generates social inequities which are exacerbated by governance leniency, lack of preventive measures, bad behaviours and risk unawareness. “The inability to sustain stresses is produced by on-the-ground social inequality, unequal access to resources, poverty, poor infrastructure, lack of representation, and inadequate systems of social security, early warning, and planning. These are the factors that translate climate vagaries into suffering and loss” [
Internal mobility to access critical infrastructures is important too.
The exposure is the first element analysed and it is determined by the size of household.
The exposure (
The susceptibility index is composed of the number of children less than 4 years of age in a given household. These households have the predisposition to suffer the most harm due to flood events during the rainy season. The susceptibility as highlighted in
The lack of resilience is determined by the distance from the nearest health centre within Medina Gounass. Therefore, the nearer the household to the health centre, the higher their resilience is. In contrast, the farther a household from the health centre the lower is the resilience and, by extension, the higher the vulnerability in terms of health. The households located in the North and North-East are highly vulnerable, and those from the East and South experience medium vulnerability. These households living permanently in flood situation during the rainy seasons encounter many challenges regarding their health (
capacity to anticipate, cope and recover from the adverse effects of recurrent flood events. Medina Gounass inhabitants are not resilient.
The survey and the focus group interviews showed that people use bags of sand and power-driven pumps to fight against floods. These measures are not sustainable because they did not offer perspective for the future. These power-driven pumps are provided by the government which spends money for fuelling and monitoring flood events instead of putting in place sustainable adaptation measures. Additionally, an old person notes during our interview in managing flooding events, those who have means put a great quantity of sand near their houses, generating conflicts in the neighbourhood.
These actions block the water ways and water enter in the houses of those who do not have means to do so. Sometimes, conflicts are so violent that the police have to intervene. As a result, flood generates conflicts between friends and relatives. In such situations, individualism prevails over the community.
However, the description of the results obtained through the spatial analysis for all single and composite indicators are aggregated for the calculation of the final map of vulnerability.
The combination of the three composite indicators shows the vulnerability of people living in Medina Gounass to floods. The interactions of these three major aspects of the MOVE framework are a crucial part of vulnerability assessment. From the map above, one can observe a concentration of the biggest bullets in the North- Eastern part of Medina Gounass. This result is not surprising because this part is a low land compared to other part of Medina Gounass. Additionally, they are the farthest from the health centre and the interview I conducted with the former Deputy Mayor details the new project of the construction of a basin at that place in order to collect the running waters in the area. This project can reduce considerably the social vulnerability of Medina Gounass to floods. Furthermore, Medina Gounass is among precarious neighbourhoods that suffer from the lack of drainage network wastewater and storm water. The streets are narrow and winding and do not facilitate fast and safe movement of people and goods. Thus, flooding is the most obvious risk in these illegal settlements and is a latent scourge behind much vulnerability and especially in rainy season. Based on rainfall, topographic criteria, hydrogeological, environmental and hygiene, Medina Gounass is one of the most affected areas. Although Medina Gounass belongs to the city of Guédiawaye, located on a dune site where soils are more permeable and therefore the infiltration of runoff is more obvious 75% of its area is flooded. In 2005, 911 houses were flooded [
As a result, social vulnerability index in
Medina Gounass is really vulnerable to floods. This vulnerability is not solely related to climatic conditions but it is a combination of a set of factors. The analysis of climatic data highlights a raise in temperature from May to October where the peak reaches. Consequently, in Dakar, the hottest month is October. Thus, temperature parameter cannot solely determine the changing climate. Therefore, rainfall data have been used jointly and the reason is that precipitation in Sénégal is related to the one of the Sahel. Then, rainfall is by far the most crucial variable on the climate and people’s lives.
Extreme rainfall is one of the manifestations of climate change which causes floods events. Hence, Dakar suburban particularly those from Medina Gounass are constantly on rain waters mixed with sewage and drainage water which obstruct people’s activities and become a threat for human security generally.
Moreover, the survey highlights that those who have a salary paid in cash represent 39%, family support 18%, job wage 25%, other 5% and no answer 13%. So they are not highly paid. The statistics with the linkage to the literacy rate confirm that the Medina Gounass inhabitants in general have limited economic means to buy houses elsewhere where the amenities already exist. Additionally, Medina Gounass lacks amenity plan for a district which is said to be on its own.
Finally, the social vulnerability index to floods is limited to a few numbers of indicators. The reason for this restriction is due to the absence and lack of accurate data to have a more composite index. However, the household size for the exposure, children under four years of age for susceptibility and the distance from the nearest
health centre for the lack of resilience appear to be relevant in assessing the vulnerability of community to flood. As a result, flooding in Medina Gounass through this study shows how inhabitants are in a tricky situation and it is a real threat for human security.
We express our thanks to WASCAL, BMBF, ANACIM, Kouami Kokou, Boubacar Sane (Keba), Benilde Oudiane, Gadedjisso-Tossou Agossou, and M. Lamine Diop.
Ousmane DioufSané,Amadou ThiernoGaye,MoussaDiakhaté,MawuliAziadekey, (2015) Social Vulnerability Assessment to Flood in Medina Gounass Dakar. Journal of Geographic Information System,07,415-429. doi: 10.4236/jgis.2015.74033