The main purpose of this study is to identify the socio-economic implications of re-current flooding on women development in southern Ijaw Local Government Area. Generally, flooding may result in socio-economic, ecological and health problems. This study assumes that on flood days the movement of customers and sellers tends to be hindered, thus resulting in the retardation of transactions and the reduction of daily income earned. The study compared the situation of female traders with that of male traders. Both primary and secondary data were used in this study. Primary data were collected using an open-ended questionnaire. A total of 83 questionnaires were randomly distributed to members of four communities, which were selected through stratified random sampling procedures. Also 33 randomly selected women and men respectively, engaged in marketing activities from open and locked-up shops, were sampled to observe the level of their personal income (in Naira), from customers patronage during 3 flood days and 3 non-flood days. Other data and information were obtained through Key Informants Interview (KII), and observations. Hypotheses I and II were tested using Analysis of Variance (ANOVA) statistical model. Null hypothesis I (H 0), which states that “There is no statistically significant difference in the income earned by men and women traders from marketing activities on flood days and non-flood days in Southern Ijaw Local Government Area, Bayelsa State”, is accepted (F-value: 3.8723939, P-value: 2.494E-05), whereas null hypothesis II (H 0), which states that “There is no statistically significant difference in the income earned by women traders from marketing activities on flood and non-flood days in Southern Ijaw Local Government Area, Bayelsa State, is rejected (F-value: 2.524902, P-value: 0.030069). Thus while there is no significant difference in the earnings of male and female traders on flood and non-flood days, there are significant differences in sales earning among women traders on those days. Factors affecting trading income on flood and non-flood days include accessibility to business premises by customers, ability of male marketers to afford non-easily flooded business premises; and women traders with limited resources often have less suitably drained premises. Reduced total household income can detrimentally affect food affordability, availability, household nutrition, family health and wellbeing. Recommendations highlighting the roles of communities, government and stakeholders in flood management are proffered.
Flood is defined in a variety of ways, according to type, origin and magnitude. Generally, it is an unusual high stage of water in a stream channel [
The analysis of socio-economic components of flooding adopts long-term risk management strategies grounded in an understanding of exposure to the flood, hazard characteristics and pattern of vulnerability and the relationship between different stakeholders in the perception of food risk [
Floods, although a natural disaster, could also be caused by anthropogenic activities and human interventions in natural processes, such as increase in settlement areas, population growth located in areas prone to flooding [
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Strategies for mitigating against flood risks, include amongst others; development of Flood Early Warning System (FEWS) [
Nigeria has had its own fair share of flooding and has recorded some of the highest death tolls in the West African Region. In the northern parts of the country, entire villages and huge spaces of agricultural land have been destroyed by flooding [
Notably, Odubo (2014) has carried out a study of the socio-cultural effects of flooding in Southern Ijaw, Bayelsa State, Nigeria. He noted that in Nigeria, flood has been documented to have affected and displaced more people than any other disaster [
Since the effect of flooding on movement and invariably the ease of doing trading business at various market locations, based on gender differences, as well as its socio-economic implication on household income is the main interest of this study, there is a considerably departure from the widespread issues examined by Odubo (2014). Consequently, the problem which this present study examines is the socio-economic implication of re-current flooding on the income of female traders in southern Ijaw Local Government Area, Bayelsa State. This study of female traders’ income is juxtaposed against that of the income earned by male traders for meaningful comparative analyses.
The impact of such intense flooding patterns and processes in an environment noted for frequent crude oil exploitation operational accidents, as well as induced crude oil spillages due to vandalization and sabotage activities, and widespread local crude oil refining could be more devastating on the marine environment, especially in such a vulnerable ecological area.
The aim of this study is to examine the implication of recurrent flooding on women development in Southern Ijaw Local Government Area, in the heart of the Niger Delta Area of Nigeria. The study is aimed at comparing the level of vulnerability of male and female traders during flood and non-flood days, with major emphasis on incomes from trading transactions. Thus this study specifically focuses on the socio-economic implication of flood events on trading activities viewed from a gender perspective. A knowledge of this will help in gaining an integrated perception in comparing the possibly existing gap between the socio-economic growth of male and female traders and consider how this type of occurrences, if negative, poses a threat to the development of women in this region. Consequently, the objectives of the study are to: 1) identify the causes of re-current flooding in southern Ijaw L.G.A, Bayelsa State; 2) assess the comparative effect of flooding on the income of male and female marketers in the study area; 3) identify the more vulnerable gender group to consequences of flood events on personal income 4 make relevant suggestions on how to prevent and control future occurrences.
Thus, for this study it could be assumed that during flood days the movement of traders and buyers from house to business premises is hindered. However, a transect walk through business premises shows that there seems to be a pattern, where male traders could afford non-easily flooded business premises, while women traders, who tend to have limited trading resources, usually rent or acquire premises which are less developed infrastructural, more likely to be flooded and as such less accessible, within the same area.
There is also the usual concentration of traders selling the same products in a particular area. Most often accessibility to the area may be almost uniform. There may be gender sensitivity in types of items sold, in some areas of the market, while in some areas it is not. Sometimes both a man and his wife may co-own a trading outlet. A comparative study of both female and male respondents will also assist in determining if women are more affected by flood events, through increase or decrease in patronage.
In this study the following null (Ho) hypotheses were tested:-
Hypothesis I: Ho: “There is no statistically significant difference in the income earned by men and women traders from marketing activities on flood days and non-flood days in Southern Ijaw Local Government Area, Bayelsa State”.
Hypothesis II: Ho: “There is no statistically significant difference in the income earned by women traders from marketing activities on flood and non-flood days in Southern Ijaw Local Government Area, Bayelsa State”.
The study area is Southern Ijaw Local Government Area of Bayelsa State. Its headquarters is in the town of Oporoma. It is located on Latitude 44˚48'17"N and Longitude 6˚04"E. The area has a coastline of approximately 60km on the Bight of Benin. It is the largest local government in Nigeria. The people and their language are known as Izon.
Southern Ijaw has a land area of 2682 km2 approximated and a population of 319,413 persons (NPC Census, 2006) [
The study area lies in the heaviest rainfall area in Nigeria with heavy rainfall almost all year round and a short dry season. The area’s climate supports the cultivation of oil palm, cocoa rice, banana, yam, cocoyam, coconut, cassava, sugarcane etc. The amount of rainfall is adequate for a year round crop production. The vegetation of Southern Ijaw is composed of ecological zones which include coastal barrier Island forests, mangrove forest, and fresh water swamp. The difference with various soil units in the area and they constitute part of the eco-systems.
The socio-economic activities of the people in Southern Ijaw may be considered under three main headings namely, primary occupations, secondary occupations and tertiary occupations. The major traditional primary
occupations include fishing, commerce and water transportation. However, crude oil exportation by multinational companies and the local crude oil refining, have since become the major sources of socio-economic activities in the area. The area also has higher educational institutions like the Niger Delta University (NDU) in Amassoma and Federal Polytechnic Ekowe, amongst others.
This section contains the method of study adopted for this research. The presentation is sub-divided into types of data, sampling population, and data collection methods and data analysis techniques.
Data types obtained by the researcher during this study were generated from two (2) sources, which include primary and secondary data. Both of these were relevant to the assessment of the implications of flooding on the socio-economic activities of female (and male) traders in southern Ijaw, Bayelsa State.
The primary data obtained include data on causes of re-current flooding in the study area, the level of the effect of flooding on the income of male and female traders in the area, identification of the most vulnerable groups to flooding,
1) Questionnaire: Items on the distributed questionnaire was arranged in an orderly form that helped the researchers to obtain relevant data and information aimed at achieving the study objectives. Questionnaire copies were largely distributed to household heads in order to collect unrepeated data.
The questionnaire was an open-ended questionnaire, and it was divided into two sections. Sections A contains questions on the respondent’s personal data, while section B contains items meant to obtain data relevant to stipulated research objectives.
2) Oral interviews: These interviews were conducted in form of Focus Group Discussions (FGDs) and Key Informant Interviews (KII) with groups of key informants, household heads, farmers, traders, fishermen and women and so on.
3) Direct observation: Here, the researchers’ observations were carried out through visual assessment of field objects, people, facilities and processes. Observations were carried out on markets and trading activities, non-flood days, movement of buyers on rainy and non-rainy days, flood situations, transportation activities and other relevant processes. Observed are also flooded farmlands, houses/compounds, schools and roads affected by flooding.
The sample population consisted of 4952 persons. The estimated number of households is 868. Only four (4) communities within the sample population of communities were selected for several reasons which include low research budget, the wide expanse of the area and time. Also not all the members of the population were engaged in trading. Thus thirty-one (31) males and thirty-one (31) female traders, with trading outlets within Obololi, Emete, Lobia and Azama communities were purposively selected, due to their engagement in trading activities and willingness to participate in the study. These latter selected respondents were monitored for the actual amount of total sales on three (3) flood days, and three (3) non-flood days, (in this case beginning from the day after flood and invariably rainfall had ceased).
Stratified random sampling and simple random sampling techniques were adopted in this study. Firstly selection of 4 communities was done, followed by simple random sampling which was employed in selecting 83 respondents/household heads to which the questionnaires were administered. A total of 80 questionnaires were retrieved. However only 75 questionnaires were properly filled and thus used in data analyses. Also
S/N | Villages | S/N | Villages |
---|---|---|---|
1 | Abagbene | 33 | Ekowe |
2 | Agidigbene | 34 | Emete |
3 | Agoubin | 35 | Eniwari |
4 | Amassana | 36 | Ezetu |
5 | Amatoro | 37 | Ekeni |
6 | Angiama | 38 | Eniwari |
7 | Apoi | 39 | Ezetu |
8 | Ayama | 40 | Fonibri |
9 | Ayougbene | 41 | Furupah |
10 | Azuzuamma | 42 | Gabaran |
11 | Baberegbene | 43 | Idirigbene |
12 | Diebu | 44 | Igbomotoru |
13 | Ikeingbenbiri | 45 | Igboibiri |
14 | Kainyanbiri | 46 | Ikebiri |
15 | Kemiegbene | 47 | Ikeinbiri |
16 | Kolokologbene | 48 | Ikoromogbene |
17 | Korokorosei | 49 | Kassama |
18 | Lobia | 50 | Kemebiama |
19 | Nangebene | 51 | Koluama |
20 | Ofonigbene | 52 | Lasukogbene |
21 | Olugboiri | 53 | Luduan |
22 | Omomobiri | 54 | Obololi |
23 | Onyema | 55 | Okpotuwari |
24 | Opuama | 56 | Olugbobro |
25 | Owelkorogha | 57 | Ondewari |
26 | Peremabiri | 58 | Oporoma |
27 | Sampou | 59 | Otuan |
28 | Togogbene | 60 | Oyereghene |
29 | Ukparatibu | 61 | Poloubou |
30 | Umbugbene | 62 | Ukubie |
31 | Tebidada | 63 | Torubobougbene |
32 | Ekeni |
S/N | Names of Sample Villages | Estimated Study Population | Estimated Average House-Hold Size | Estimated House-Hold Number | % of Sampled House-Hold | No. of Sampled Households | No. of Retrieved Questionnaires Properly Filled | % of Returned Questionnaire |
---|---|---|---|---|---|---|---|---|
1 | Obololi | 1577 | 7 | 225 | 10 | 23 | 22 | 95.7 |
2 | Emete | 864 | 6 | 144 | 10 | 14 | 12 | 85.7 |
3 | Lobia | 1203 | 5 | 241 | 10 | 24 | 21 | 87.5 |
4 | Azama | 1306 | 6 | 218 | 10 | 22 | 20 | 90.9 |
Total | 4952 | 6 (average) | 828 | - | 83 | 75 | 90.4 |
shows the four (4) major communities that were randomly selected for questionnaire distribution and analysis. These include; Obololi, Emete, Lobia and Azama communities. Results in
In an attempt to satisfy the above stated objectives, solve the research problems and test the hypothesis of the study, the data collected were presented in tables and analyzed using, simple averages, percentages and frequencies.
Also the statistical technique used in testing the hypotheses of the research is the Analysis of variance (ANOVA). The ANOVA statistical model is useful in the determination of statistical differences between two or among more variables. The “F-Value” indicates the ratio of two mean squares, when the F-value is large and the significance level is small (typically smaller than 0.05 or 0.01) the null hypothesis can be rejected in order words, a small significance level indicates that the results probably are not due to random chance. Also the “Sig value” shows the conditional probability that a relationship as strong as the one observed in the data would be present, if the null hypothesis were true. It is often called the P-value. Typically a value of less than 0.05 is considered significant. “The Sum of squares” highlights the sum of the squared deviations about some quality, while “Df” shows the value associated with a test statistic that is used in determine the observed significance level. From the “Mean square”, it is possible to know the sum of square divided by the degrees of freedom.
The findings of the study are presented below. Plates 1-4 show different scenarios of flooding in the study area.
Plate 1. A Half-submerged residential building in the study area as a result of flood.
Plate 2. A school affected by flooding in Obololi community, Bayelsa state.
Plate 3. A flooded street in the study area.
Plate 4. Azama community, Bayelsa state during flooding.
Causes of Flood in the Study AreaData were collected on earnings from customers’ patronage of women and men engaged in trading activities in open and locked-up shops in Obololi, Emete, Lobia and Azama communities.
ANOVA results in
S/N | Causes of flood | Frequency | % |
---|---|---|---|
1 | Excessive rainfall | 10 | 13.33 |
2 | Blockage of drainage channel | 11 | 14.67 |
3 | Construction of residences on floodable areas | 3 | 4.00 |
4 | Lack of adequate drainage system | 8 | 10.67 |
5 | Increase in sea level | 7 | 9.33 |
6 | All of the above | 29 | 38.67 |
7 | Others (specify) | 1 | 1.33 |
Total | 75 | 100 |
ANOVA | ||||||
---|---|---|---|---|---|---|
Summary | ||||||
Groups | Count | Sum | Average | Variance | ||
Day 1 men flood | 33 | 676,008 | 20,485.09091 | 490,177,139.5 | ||
Day 2 men flood | 33 | 446,116 | 13,518.66667 | 304,571,888.4 | ||
Day 3 men flood | 33 | 294,085 | 8911.666667 | 144,368,552.5 | ||
Day 1 no flood men | 33 | 556,467 | 16,862.63636 | 447,516,285.7 | ||
Day 2 no flood men | 33 | 750,201 | 22,733.36364 | 564,632,626.4 | ||
Day 3 no flood men | 33 | 718,404 | 21,769.81818 | 245,302,790 | ||
Day 1 women flood day | 33 | 454,739 | 13,779.9697 | 279,667,857.2 | ||
Day 2 women flood day | 33 | 229,380 | 6950.909091 | 70,710,713.65 | ||
Day 3 women flood day | 33 | 158,859 | 4813.909091 | 14,714,488.96 | ||
Day 1 women no flood | 33 | 293,148 | 8883.272727 | 61,229,525.14 | ||
Day 2 women no flood | 33 | 314,034 | 9516.181818 | 27,835,708.65 | ||
Day 3 women no flood | 33 | 552,114 | 16,730.72727 | 1,064,112,895 | ||
ANOVA | ||||||
Source of Variation | SS | Df | MS | F | P-value | F crit |
Between Groups | 13,203,574,800 | 11 | 1,200,324,982 | 3.8773939 | 2.4944E−05 | 1.813615 |
Within Groups | 1.18875E+11 | 384 | 309,570,039.2 | |||
Total | 1.32078E+11 | 395 |
(47.73%) to N292,085 (20.77%) for male traders during flood days. The same observation of increase from day one to day three is true for marketing sales by women during flood days from N454,739 (53.94%) to N158,859 (18.84%). The reverse is observed for both men and women on non-flood days, where sales tend to surge from the first days of study towards the last days. Notably the data for non-flood days were collected a day after flood had receded and rain had stopped.
It appears that trading tends to build up gradually, and appears to peak as traders and invariably buyers gain confidence, that the markets will be more operational. Generally incomes earned by women traders were noticed to be often lower than those of men traders during flood days and non-flood days. The nature of goods sold, quantities and the differences in their prices may have caused this difference. For instance a male or female
ANOVA | ||||||
---|---|---|---|---|---|---|
SUMMARY | ||||||
Groups | Count | Sum | Average | Variance | ||
Day 1 women flood day | 33 | 454,739 | 13,779.97 | 2.8E+08 | ||
Day 2 women flood day | 33 | 229,380 | 6950.909 | 70,710,714 | ||
Day 3 women flood day | 33 | 158,859 | 4813.909 | 14,714,489 | ||
Day 1 women no flood | 33 | 293,148 | 8883.273 | 61,229,525 | ||
Day 2 women no flood | 33 | 314,034 | 9516.182 | 27,835,709 | ||
Day 3 women no flood | 33 | 552,114 | 16730.73 | 1.06E+09 | ||
ANOVA | ||||||
Source of Variation | SS | Df | MS | F | P-value | F crit |
Between Groups | 3.21E+09 | 5 | 6.41E+08 | 2.534902 | 0.030069 | 2.261137581 |
Within Groups | 4.86E+10 | 192 | 2.53E+08 | |||
Total | 5.18E+10 | 197 |
Flood Days | Men (Flood Days) | % | Men (Non-Flood Days) | % | Women (Flood Days) | % | Women (Non-Flood Days_ | % |
---|---|---|---|---|---|---|---|---|
1 | N676,008 | 47.73% | 556,467 | 27.48% | 454,739 | 53.94% | 293,148 | 25.29% |
2 | N446,116 | 31.50% | 750,201 | 37.05% | 229,380 | 27.21% | 314,034 | 27.09% |
3 | N294,085 | 20.77% | 718,404 | 35.48% | 158,859 | 18.84% | 552,114 | 47.62% |
N1,416,209 | 100.00% | 2,025,072 | 100.00% | 842,978 | 100.00% | 1,159,296 | 100.00% |
trader selling a particular product in retail may not make as much income as a male or female trader selling the same product in wholesale transactions, although depending on the frequency of transactions too.
It is therefore appropriate in this chapter to highlight some policy consideration which, if implemented could play an important role in flood risk management. The following policy consideration is recommended:
1) Government and key stakeholders should encourage communities to relocate permanently to higher
S/N | Control measures | Frequency | % |
---|---|---|---|
1 | Construction of more Drainage | 12 | 16 |
2 | Early monitoring and warning | 11 | 14.7 |
3 | Widening of existing drainage channels | 8 | 10.6 |
4 | Enactment of policies that restrict dumping of waste in drainage channels | 6 | 8.0 |
5 | Avoidance of construction on flood plains | 5 | 6.7 |
6 | All of the above | 33 | 44.0 |
Total | 75 | 100 |
Source: Fieldwork, 2015.
grounds and non-floodable areas. The relocation should go with the provision of all necessary socio-infrastruc- tural amenities such as schools, hospitals, infrastructure, pipe-borne water and agriculture inputs for a period not lesser than three (3) years to enable the household members to settle down. Efforts should also be made to introduce alternative livelihood strategies in the new areas of settlement.
2) Government and private investors should provide conducive buildings and areas for business operations, and avoid flood prone areas, while giving better consideration to the female gender.
3) The relevant authorities should delineate both the non-flood areas and flood areas. These should be reflected in widely distributed documents.
4) Construction of dams should be considered to trap excess water. This could be used for irrigation in other areas where water is scarce and also for hydroelectricity. However careless release of dam water could be disastrous.
5) Community based flood-early-warning-systems should be developed.
6) Community initiated mitigation measures should be promoted, so as to build community resilience. Indigenous knowledge should also be identifies and applied in managing flood events
7) Although the consequences of flood may be assumed to be limited to reduced total household income, the implication of reduced household income on family food security and nutrition, as well as the implications of rainy days and resultant cold related ailments caused by chilly weather on human health, exposure to germs saturated flood water, and resultant mosquito breeding in stagnant water, needs to be adequately researched and appropriate management strategies adopted. These are of public health importance.
8) Revolving, low collateral requiring loans should be made available to women to begin or enlarge their trading businesses by governments at different levels for woman development purposes.
This study examined the socio-economic implication of flooding on the incomes of female and male traders in southern Ijaw Local Government Area, Bayelsa State. The objective was focused on knowing the level to which flooding affected women development ranging from their personal income to the pattern of patronage and was aimed at establishing the more vulnerable gender group in the study area. Flooding is generally a temporary condition of partial or complete inundation of normally dry area of land, due to over flow of inland or tidal waters, or from unusual and rapid accumulation or run-off [
The study reveals that although there is no statistically significant difference in the personal income earned by business men and women on flood days and non-flood days, female traders are adversely affected by flooding in terms of their livelihood patterns. Women traders were shown to be earning lesser income during flood and non- flood days than men. Surprisingly, there is a statistical significant difference in the personal income earned among business women on flood and non-flood days.
Candidly, it was expected before the study that this would be the other way round. This finding could be because there is a very wide divide in the level of trading activities of women traders and the investments involved. Respondents during oral interviews, unanimously pointed out that a woman trader, with her own business, could be engaged in the sales of minor products, such as China manufactured Padlocks and Ball pens in a tiny locked-up shop sandwiched between other shops in a respectable trading neighborhood. It’s difficult to imagine how such a female trader is able to afford the monthly or annual shop rents, given the paltry profits she must have been making. She may daily collect her wares on loan, sell and return the costs of the goods, minus her profits to a wholesaler. However, another woman may be a textile goods trader that visits Yenagoa regularly, and sells at wholesale prices.
Oral interviews further revealed that many of the prosperous women traders belonging to the latter group had businesses buoyed by investment funding by their male spouses. Sometimes it’s also difficult to identify a dichotomy in the income flow and savings between a so called “prosperous” female trader’s business stocks and those of the husband’s business. All such trading shops are most likely extensions of the same expanding business, sometimes with the same or different registered names. Thus there is observed disparity in the earnings of female traders with own business and usually those with funds from spouse’s business. Marriage and not bank loans tend to be a major cushion of poverty amongst women.
Painfully, the general situation of low income and independent women traders in the study area is extremely pathetic. Large proportions are hawkers, and are major household income earners, who in their day to day lives are grossly marginalized by poverty, from achieving their well-deserved dreams of good education for their children, social well-being and comfort. A situation of total and draconian government clamp-down like that, which is presently being enforced in Lagos state [
Bayelsa state is a region which is prone to flooding due to high rainfall and long rainy days. This poses considerable problems for socio-economic activities, human settlements and land-use. Almost every part of the area is under water at one time of the year or another. The research recommends that government should provide non-floodable and conducive areas for building business premises with gender consideration.
Oluyemi Ayorinde Akintoye,Abiodun Komomo Eyong,Devine Offiong Effiong,Peter Okpe Agada,Opaminola Nicholas Digha, (2016) Socio-Economic Implications of Recurrent Flooding on Women Development in Southern Ijaw Local Government Area, Bayelsa State, Niger Delta Area of Nigeria. Journal of Geoscience and Environment Protection,04,33-46. doi: 10.4236/gep.2016.48004