Antibiotic resistance (AR) is a global healthcare issue driven by the overuse of antibiotics in clinical, agriculture, and aquaculture applications. Urban and agricultural runoff introduce antibiotic-resistant bacteria and antibiotic contamination to recipient environments. Antibiotics change microbial community compositions in favor of resistant species and can trigger the exchange of AR genes. Mapping the changes in microbial community compositions and AR gene abundance has yet to be elucidated in response to rainstorm runoff. Sampling at the Batiquitos lagoon outlet in California occurred over 14 days; before, during, and after the first two rainstorms of the 2019-2020 season. Coastal water was captured on-site on a 0.22 µm mixed cellulose ester membrane filter. We performed total DNA isolation and shotgun library preparation on the isolated microbiomes followed by 2 x 150 base paired-end sequencing. Microbial composition and AR gene identification was performed on the resulting metagenomes, to determine a time course profile of relative microbial abundance and antibiotic resistance profiles. Additionally, we performed meta-SourceTracker analysis on the time course metagenomes to investigate proportions of exogenous and endogenous microbial community members throughout and following rainstorms, as well as to explore possible sources of exogenous taxa. We observed an overall bimodal increase in alpha diversity and AR gene counts in the 24-72-hour period following each rainstorm. Taxonomic changes are reflected by a relative depletion of Cyanobacteria and relative increase in Proteobacteria and Bacteroidetes. The microbial community profile returned to a pre-storm composition after approximately six days contrary to the three-day recovery time commonly referenced.​