General Circulation Models (GCMs) project an increase in the frequency and magnitude of storm events in the Southeastern United States over the next several decades. Additionally, urban development in this region is expected to double by 2060. Communities unable to mitigate and adapt to climate- and land use-change induced impacts on water resources may experience adverse social and economic impacts. Hydrologic model outputs, such as those from the Soil and Water Assessment Tool (SWAT), are helpful at predicting changing hydrologic processes but do not directly incorporate community demographics that are required to assess vulnerability. Therefore, there is a need to couple hydrologic model outputs with socioeconomic data to identify vulnerable communities and support associated climate change adaptation planning efforts. To address these needs, we use a risk matrix framework to couple changes in SWAT simulated streamflow from 1992-2002 (baseline) to 2050-2070 (GCM scenario projections) with census tract social vulnerability index (SoVI) estimates derived from 2010-2014 American Community Survey (ACS) data for the Upper Yadkin-Pee Dee (UYPD) Watershed in North Carolina, USA. To evaluate our results, we compare the spatial distribution of subbasins in urgent need of climate change adaptation planning based on three approaches using: SWAT results only, SoVI results only, and the spatial intersection of SWAT and SoVI results using the risk matrix framework. 10-yr and extreme events increased and were more variable between the baseline and projection SWAT streamflow datasets with especially large increases in the middle and lower parts of the YPD. Socially vulnerable communities were heterogeneously distributed throughout the YPD. The spatial intersection of SWAT and SoVI results integrated biophysical and socioeconomic factors and can be used to inform the first of several steps (i.e., community surveying, stakeholder visioning, and action taking) associated with effective climate change adaptation planning.