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

was determined using Yamane (1967) formula. The study sampled 400 households using simple random sampling technique. Respondents were selected based on the criteria of being household members of the community and on their ability to respond to questions put to them appropriately. In doing this priority was given to the heads of the households in responding to questions as contained in the questionnaire, however, where the household head was indisposed, the most elderly with the ability to respond to questions was selected. ii. Computation of Flood Vulnerability index (FVI) Using PCA The following steps were followed in determining FVI using PCA. Step I: In computing FVI, the first step was to quantify the various vulnerability indices as specified on Table 1. Step II: The weights of these indicators were determined using PCA and the component loading of the first component was used. This was consistent with the method used by Akukwe and Ogbodo (2015) Ali 2018 and Ali, Onah, Mage, Yiyeh, Tarzoho, and Iorhuna (2022). In their studies, PCA was run on the variables, and the weights were attached to the indicators using the first principal component scores of the indicators. The reason for assigning the weights determined by PCA to indicators was to avoid the uncertainty of equal weighting given the diversity of indicators used (Akukwe and Ogbodo, 2015; and Deressa, Hassan and Ringler, 2008; Ali, 2018, Ali, Onah, Mage, Yiyeh, Tarzoho, and Iorhuna, 2022). Thus, for the determination of the vulnerability indices, the selected indicators of sensitivity and exposure were negatively associated with their first principal component because it was assumed that areas with higher frequencies of flooding were subjected to higher sensitivity due to the adverse effects of flooding as well as being more exposed (Ali, Onah, Mage, Yiyeh, Tarzoho, and Iorhuna, 2022). On the other hand, adaptive capacity was positively associated with the first principal components because it is assumed that people with higher adaptive capacity were less sensitive to damages caused by flooding, holding exposure level constant. Thus, higher values of the vulnerability indices show less vulnerability and vice versa (Akukwe and Ogbodo, 2015; Deressa et al., 2008; and Madu, 2011; Ali, Onah, Mage, Yiyeh, Tarzoho, and Iorhuna, 2022). Step III: Consequently, vulnerability to flood was computed according to Deressa et al., (2008); and Akukwe and Ogbodo, (2015) as follow: FVI = /Adaptive Capacity/ - / Sensitivity + Exposure/ (1) Ali, 2018, Ali, Onah, Mage, Yiyeh, Tarzoho, and Iorhuna, (2022) explained the adoption of this formula, maintaining that this equation was adopted because flooding is one of the consequences of climate. Equation (1) was expanded as follows: FVI = (wAC 1 + wAC 2 + wAC 3 + … wAC n ) – (wS 1 + wS 2 + wS 3 + … wS n ) + (wE 1 + wE 2 + wE 3 + … wE n ) (2) Where FVI is vulnerability index, w are weights of first components scores, AC 1 …. AC n are adaptive capacity variables, S 1 …. S n are sensitivity Variables, and E 1 …. E n are the exposure variables. Note: AC = Adaptive Capacity; S = Sensitivity; and E = Exposure Table 1: Vulnerability, Units of Measurement, and Their Relationship Vulnerability Determinant of vulnerability Vulnerability indicator Description of each indicator Units of Measurement Relationship between indicator and Vulnerability Adaptive or Resilience Capacity Wealth Average Annual income Receipt of assistance/relief % of total population who earned more than N500,000.00 per annum % of population who received assistance The higher the % of total population more than N500,000.00 per annum, who receive, who are educated, who are employed outside primary production sector like farming, the lesser the vulnerability. Literacy rate Educational qualification % population who are educated Employment status Occupation % of population that are less vulnerable Sensitivity or Susceptibility Flood characteristics Length of stay - The number of years of residence % of population that have stayed longer than 10 years The higher the frequency, the more the vulnerability. The higher the numbers the higher the vulnerability. © 2022 Global Journals Volume XXII Issue III Version I 39 ( ) Global Journal of Human Social Science - Year 2022 B Assessment Household Vulnerability to Flood Disaster: A Study of Oweto Community in Agatu Local Government Area of Benue State, Nigeria