The National Research Council critiqued the U.S. EPA's Environmental Monitoring and Assessment Program (EMAP) for its coarse spatial sampling, and recommended that EMAP work to increase the precision of population estimates. This thesis argues that augme nting EMAP monitoring of aquatic resources with data from existing, or auxiliary, monitoring programs will heighten estimate precision. In the first chapter the theoretical basis for EMAP data augmentation is developed. Development includes: examination of how the monitoring stations contributing to the STORET, BIOS, and ODES databases can provide EMAP with auxiliary data; introduction to Overton's statistical algorithm for combining probability and quasi-probability data; presentation of the federal initiatives promotingdata augmentation; and discussion of the computational tools and georeferencing procedures required for data augmentation. In the second chapter a methodology to augment EMAP-Surface Waters-Streams (EMAP-SWS) with STORET monitoring stati on data is presented. This methodology calculates the separate and augmented EMAP-SWS estimates of a computer simulated pollution event, and then quantifies the change in estimate precision as well as the auxiliary data bias. The computer tools, programs, and electronic data, as well as the procedure for simulating, monitoring, and estimating pollution are assembled into a decision support system (DSS). The DSS is tested on a case study within North Carolina's Neuse and Pamlico River Basins, and the results demonstrate that data augmentation increased estimat e precision.