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 or 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 demographics 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. We present case studies for select subbasins in the UYPD where especially vulnerable communities overlap with areas projected to experience the highest increases in 10-yr and extreme flows. Compared to using either alone, our results show that coupling SWAT outputs and ACS data provides integrated sociohydrological information that can better inform climate change adaptation planning.