Global Journal of Human-Social Science, B: Geography, Environmental Science and Disaster Management, Volume 22 Issue 3

Frequency of Flood occurrence Frequency of Flood occurrence in a year The higher the extent of coverage/magnitude, the higher the vulnerability Period of flood occurrence in a year Number of months with flood in a year Severity Extent of coverage Flood perception Pre-flood awareness % of population with pre-flood awareness Flood experience Past flood experience % population who had experience flood Exposure Proximity to water body Average Distance from River The average distance to flood prone areas The shorter the average distance to water body, the higher the vulnerability The longer it takes for flood to recede the higher the vulnerability Flood duration Number of days it takes for flood to recede Number of days with flood water Source: Adapted from Ali, 2018, Ali, Onah, Mage, Yiyeh, Tarzoho, and Iorhuna, (2022). III. R esults and D iscussion a) Flooding Vulnerability Level at Oweto Community The results of the flooding vulnerability level as shown by PCA and composite vulnerability index for study area are presented in Tables 2 and 3. The result of the PCA is presented in Table 2. The shows that first principal component explained most of the variation in the flood vulnerability indicators with an eigen value of 10.450 and the percentage variance explanation of 38.705%. This component shows high loadings on the adaptive capacity indicators such as nature of source of assistance; impact on businesses and sensitivity indicators such as pre-flood awareness, past flood experience and flood duration. Since more factors loaded were on adaptive capacity indicators, the first component is named Adaptive Capacity Component, which is an indication that the study has relatively moderate to high resilience capacity to cope with flood disaster. The second component which has an eigen value of 6.154 with percentage explanation of 22.793% is named Socio-economic Component . This is because the second component is highly loaded on socio- economic variables such as nature of business, annual income, sex and educational attainment which are part of adaptive capacity factors. The third component with an eigen value of 4.139 accounted for 15.328% explanation in the variation in the flood vulnerability indicator. The component is highly loaded in the period of flood occurrence and frequency of flood occurrence. Therefore the component is named Sensitivity Indicators Component. This suggests that even though the study area has relatively highly adaptive capacity, the sensitivity factor is relatively high thereby making households highly vulnerable. In the same vein, the fourth component with an eigen value of 3.048 and 11.290% explanation is highly loaded on variables such as relocation, flood losses and other source of income. Therefore the component is called flood adaption and impact component. Overall, the total percentage explanation of 88.117% substantially accounted for the variation in the vulnerability indicators of adaptive capacity, sensitivity and exposure factors. Table 2: Rotated Component Matrix Variable Component 1 2 3 4 Sex .162 .879 .162 .130 Length of stay .862 .444 .021 .001 Ethnic group .700 .176 .460 .418 Age .508 .451 .324 .587 Educational qualification .513 .774 .255 .189 Occupation .831 .409 .132 .224 Marital status .461 .398 .566 .492 Distance from river .493 .758 .269 .330 Volume XXII Issue III Version I 40 ( ) Global Journal of Human Social Science - Year 2022 © 2022 Global Journals B Assessment Household Vulnerability to Flood Disaster: A Study of Oweto Community in Agatu Local Government Area of Benue State, Nigeria