Rural households in Vietnam have been facing various adverse impacts on their livelihoods. By using 28 indicators of sustainable livelihood framework (SLF), this study aims to identify the livelihood vulnerability index (LVI) of the households in the coastal sandy zone in Thua Thien Hue (TTH). Based on the baseline data in 2007-2008, the study conducted a survey of 110 households living in four districts of the region to have a thorough evaluation of LVI. The results showed that excluding the increase in natural capital index (0.194-0.225), the value of LVI reduced in the dimension of human capital (0.365-0.363), social capital (0.081-0.075), physical capital (0.139-0.048) and financial capital (0.405-0.273). In overall, the value of the LVI index scored 0.244 in 2007-2008 and 0.214 in 2017-2018, respectively. The research findings contribute a deeper understanding of the vulnerable context of household communities that support the issuance of policy intervention, a social project as well as impact assessment of the given factors such as change of vulnerable contexts, structure and process.

The key farming communities in Vietnam are generally poor and lack resources to adapt to and mitigate the impacts of climate extreme events (CEEs), but the extent of their adaptation strategies is not well understood. This study aims to analyze the impacts of CEEs, current barriers, and adaptation strategies based on three categories of livelihood strategies. The classification method is first used to divide the livelihood strategy into these three categories, and a multinomial logistic model (MLS) is then applied to determine the set of parameters that affect adaptation options. CEEs result in significant damage in terms of both financial and health dimensions. Various barriers remain, such as the low capacity of relevant staff, lack of local budgets, and outdated methods being used to estimate and mitigate the impacts of CEEs. Notably, there were over 44%, and 28% conducted reactive and proactive adaptations, respectively, while a high percentage of households did not implement at least one adaptation method, around 27%. The MLS model is able to explain about 51.2% of the driving factors that influence adaptation strategies. In addition, the behavior of households in choosing adaptation methods shows the difference between perceptions of CEEs’ impacts and livelihood strategy profiles. There is a need for a package of adaptive solutions to address the impacts of CEEs that cover the many different household perspectives and involve stakeholders at multiple levels.