The growing threat of antimicrobial resistance (AMR) poses a significant global challenge, undermining advancements in healthcare, agriculture, and life expectancy. Despite its critical importance, data on population-level AMR trends, including seasonal and temporal variations, remain scarce. In this study, we conducted metagenomic analysis on 190 wastewater samples collected monthly from December 2022 to December 2023 in Pune, India, to assess the diversity, dynamics, and co-occurrence of AMR determinants. Using nanopore shotgun sequencing, we generated 87.86 Gbp of data, enabling the taxonomic classification of 157 bacterial phyla and 3291 genera. Proteobacteria dominated the microbial community, with notable seasonal shifts, including increased Streptococcus abundance correlating with SARS-CoV-2 viral surges in March 2023. We identified 637 distinct antimicrobial resistance genes (ARGs) associated with 29 antibiotic classes, with multidrug, macrolide-lincosamide-streptogramin, beta-lactams, and tetracyclines genes being the most prevalent, particularly within WHO priority pathogens such as Enterobacteriaceae and Pseudomonas. Temporal normalization of ARG abundance revealed significant seasonal variability, peaking during winter, potentially driven by increased antibiotic use for respiratory infections. The integration of viral load data with AMR trends highlighted complex interactions between viral outbreaks and AMR dissemination. This study demonstrates the potential of wastewater surveillance as an early warning system for AMR, providing valuable insights into environmental and community resistance dynamics. Our results underscore the importance of integrated AMR surveillance to inform public health strategies aimed at mitigating the global AMR threat.