Improved surveillance of antibiotics and antibiotic resistance (AR) throughout the environment is an important aspect of the prevention and control of threats posed to human and ecological health. In response to field investigations often limited by resources and time, this study aims to develop a systematic approach to assess watershed vulnerability to antibiotic pollution and AR by integrating modeling and field studies. The national antibiotic pollution vulnerability index was developed to identify watersheds most impacted by antibiotic sources. The index incorporates multiple metrics representing antibiotic pollution driven by both agricultural activities and municipal wastewater (i.e. outpatient antibiotic prescriptions, wastewater treatment plant effluent flow, stream order and dilution factor of effluent-receiving streams, manure application, and animal facilities), alongside climate change indicators (i.e., temperature, precipitation, and runoff). The pollution index was applied at a state level in North Carolina to identify the most-impacted watersheds and inform site selection for targeted field study quantifying azithromycin, ciprofloxacin, sulfamethoxazole, and trimethoprim concentrations. Modeled-informed sites in NC demonstrated the highest reported concentrations of azithromycin, trimethoprim, and sulfamethoxazole compared to previous NC studies, confirming the index effectiveness in identifying watersheds with higher antibiotic concentrations. At the national scale, watersheds relatively more vulnerable to antibiotic pollution are predominantly located in the Midwest, South, and Northeast regions of the U.S., with Iowa and Indiana being the most impacted states. Climate change is expected to exacerbate watershed vulnerability to agriculture-driven AR in the Midwest and Northeast due to an increase in precipitation and mean temperature coupled with intense agricultural activities. In addition, due to climate change-induced reductions in precipitation and runoff, watersheds in the Midwest, Mid-Atlantic, and South Central are dominantly at higher risk of effluent-driven AR occurrences. We have disseminated the developed indices as open-source online tools to aid in prioritizing strategies to mitigate AR occurrence across the U.S.