Measuring vulnerability to assess households resilience to flood risks in Karonga district, Malawi

Abstract

AbstractMany parts of Malawi are prone to natural hazards with varying degrees of risk and vulnerability. This study aimed at obtaining baseline data for quantifying vulnerability of the households to flood risks in Karonga District in northern Malawi, specifically in Group Village Headman Matani Mwakasangila of Traditional Authority Kilupula. The study used cross-sectional survey, and data were collected using a structured questionnaire. This study applied Flood Vulnerability Index and statistical methods to quantify and analyse vulnerability of households in the aspects of exposure, susceptibility and resilience characteristics. Proportional Odds Model also known as Ordered Logistic Regression was used to identify factors that determine vulnerability of households to flood risks. The results show that households headed by females and elders of age (at least 61 years) were the most vulnerable to floods because of their limited social and livelihood capacities, resulting from being uneconomically active group. Households with houses built of mud, thatched and very old with no protective account for high vulnerability due to the fact that most of them are constructed using substandard materials. The level of vulnerability was increasing with an increase in the number of households exposed and susceptible to floods. With an increase in resilience to floods, vulnerability level was decreasing. The results further revealed a predictive margins of vulnerability levels which were not significantly different among the villages. However, villages with more exposed, susceptible and not resilience households were most vulnerable to floods. This study recommends that vulnerability assessment should be included in Disaster Risk Reduction planning and implementation in order to make DRR more efficient and realistic. This would further strengthen the disaster risk management to be more proactive as well as increase resilience of households to flood risks.