Determinants of flood risk mitigation strategies at household level: a case of Khyber Pakhtunkhwa (KP) province, Pakistan

Pakistan is one of the most adversely affected countries by climate-related extreme events such as floods owing to its geographical and climatic conditions. Over the last two decades, frequency and severity of flood events have been increased and has adversely affected the livelihood and well-being of millions of people in Pakistan. The development of effective mitigation policies requires a clear understanding of the impacts and local responses to extreme events, which is quite limited in Pakistan. This study used a dataset of 600 households collected through face-to-face interviews from two districts of Khyber Pakhtunkhwa province that were severely affected from 2010 floods. The correlation and probit model methods are used to assess the study objectives. The findings of the study revealed that elevated ground floor, foundation strengthening, construction of house with reinforced material and precautionary savings were the main adaptation measures adopted at household level. The results from the probit model showed that gender, age, location, monthly income, family size, house ownership, disability, and education influence the households’ choices of mitigation strategies. The study further indicated that adoption of mitigation strategies at household level is constrained by several factors, i.e., financial constraint, lack of early warning system, lack of land use planning and inadequate resources. Further mitigation strategies also varied across different groups of households based on education, age, and income. Additionally the study discovered that the local policies on disaster management need to be improved to address the barriers to the adoption of advanced level adaptation measures at the household level such as advanced level early warning system, flood forecasting and dissemination of updated information and support, house building codes, infrastructure building practices, and adequate spatial planning.