Bangladesh is one of the most disaster-prone countries in the world. In particular, its riverine dwellers face continuous riverbank erosion, frequent flooding, and other adverse effects of climate change which makes the life of people more vulnerable. In order to assess adaptive capacity, understanding of how different households comprehend climate change is crucial. This paper aims to measure the determinants of adaptive capacityto understand the vulnerability risk among the riverbank erosion affected households. An integrated model was proposed with the constructs derived from Awareness-Ability-Action (AAA) and Socioeconomic-Sociopolitical and Institutional-Socioecological (SSS) model. A structured questionnaire survey was used to collect data from 300 participants who were affected by natural disaster specifically river erosion. The proposed research model was tested using the partial least-squares (PLS) method, a statistical analysis technique based upon structural equation modeling (SEM).The results show that the loss of farming land and all levels of riparian households impacted severely by riverbank erosion and forced into a low livelihood status, strong adaptive capacity would reduce vulnerability risk in the affected areas, community-level vulnerability measurement enhances communities understandings, build capacity, make aware, and allow them to identify appropriate locally adaptation strategies, and local level adaptation strategies may reduce the impact of such hazards on all sorts of vulnerability risk among rural households. The nature of this study may restrict its generalizability to other research settings. Future research may be necessary to validate the findings by applying this model in the vulnerability context in other developing countries. This research method and results would generate new insights with respect to planning the sustainable development goal and provide a reference for decision-making.