Per- and polyfluoroalkyl substances (PFASs) are synthetic chemicals that are ubiquitous in environmental and biological systems, including human serum. PFASs are used in many products and industrial processes and are tied to numerous health effects. Due to multiple sources and exposure pathways, methods are needed to identify PFAS sources in communities to develop targeted interventions. We assessed effectiveness of three source apportionment methods (UNMIX, positive matrix factorization [PMF], and principal component analysis - multiple linear regression [PCAMLR]) for identifying contributors to human serum PFAS concentrations in two highly exposed populations in Colorado and North Carolina where drinking water was contaminated via upstream sources, including a Space Force base and a fluorochemical manufacturing plant. UNMIX and PMF models extracted three to four potential PFAS exposure sources in the Colorado and North Carolina cohorts while PCA-MLR classified two in each cohort. No sources were characterized in NHANES (National Health and Nutrition Examination Study). Results suggest that these three methods can successfully identify sources in highly exposed populations. Future PFAS exposure research should focus on analyzing serum for an expanded PFAS panel, identifying cohorts with other distinct point source exposures, and combining biological and environmental data to better understand source apportionment results in the context of PFAS toxicokinetic behavior.