Occurrences of antibiotics and antibiotic resistance have been reported in various environmental settings, posing a global concern due to associated human and ecological risks. Therefore, the main objective of this study is to develop a holistic approach to determine the most-impacted streams and watersheds to antibiotics and antibiotic resistance across the U.S. Wastewater treatment plant (WWTP) effluent is a major point source of antibiotics and antibiotic resistance in the aquatic environment. Thus, WWTPs and receiving streams were integrated into a GIS-based model to assess the impacts of WWTP effluent and influencing factors such as instream flow, WWTP effluent flow rates, and estimated environmental concentrations on antibiotic resistance threats at the national level. Concentrations of commonly detected antibiotics such as ciprofloxacin, erythromycin, and sulfamethoxazole were predicted at WWTP discharge sites. Predicted concentrations were then compared into the antibiotic resistance safety threshold calculated from the predicted no-effect concentrations (PNECs) for selection resistance to determine streams that are susceptible to the potential presence of antibiotic resistance. Then, we examined the geospatial distribution of watershed vulnerability to antibiotic resistance contamination by the development of a multimetric index considering multiple point and nonpoint pollution sources. In addition to WWTPs, other antibiotic point sources (hospitals and total antibiotic prescription) and nonpoint sources (antibiotic use by food-producing animals and manure application) were incorporated into the model as well as dam storage ratio as the hydrologic indicator and projected minimum temperature change as a climate change indicator. Consequently, the index of watershed vulnerability to antibiotic resistance was calculated, which ranks most to least resistance-impacted watersheds. Lastly, outcomes of the previous parts of the study were translated into targeted field analysis quantifying selected antibiotics within NC watersheds that are modeled to be most impacted by antibiotic pollution sources. In addition, we used hot spots analysis to determine counties with intense hot spots of antibiotic-impacted watersheds and investigate the racial and socioeconomic status of identified counties in NC. This study presented a holistic approach to assess spatial hazards of antibiotics and antibiotic resistance, and such information can be used to prioritize watershed management, control, and mitigation strategies in impacted watersheds.