Monitoring is an essential component in ecosystem management, and leveraging existing data sources for multiple species of interest can be one effective way to enhance information for management agencies. Here, we analyzed juvenile Chinook Salmon (Oncorhynchus tshawytscha) bycatch data that has been collected by the recently established Enhanced Delta Smelt Monitoring program (EDSM), a survey designed to estimate the abundance and distribution of the San Francisco Estuary’s (estuary) endangered Delta Smelt (Hypomesus transpacificus). Two key aspects of the EDSM program distinguish it from other fish surveys in the estuary: a stratified random sampling design and the spatial scale of its sampling effort. We integrated the EDSM data set with other existing surveys in the estuary, and used an occupancy model to assess differences in the probability of detecting Delta Smelt across gear types. We saw no large-scale differences in size selectivity, and while detection probability varied among gear types, cumulative detection probability for EDSM was comparable to other surveys because of the program’s use of replicate tows. Based on our occupancy model and sampling effort in the estuary during spring of 2017 and 2018, we highlighted under-sampled regions that saw improvements in monitoring coverage from EDSM. Our analysis also revealed that each sampling method has its own benefits and constraints. Although the use of random sites with replicates, as conducted by EDSM, can provide more statistically robust abundance estimates relative to traditional methods, the use of fixed stations and simple methods such as beach seining may provide a more cost-effective way to monitor salmon occurrence in certain regions of the estuary. Leveraging the strengths of each survey’s method can enable stronger inferences on salmon abundance and distribution. Careful consideration of these trade-offs is crucial as the management agencies of the estuary continue to adapt and improve their monitoring programs.