In 2013, the Regional Stream Quality Assessment (RSQA) study was started as part of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) project. One of the objectives of the RSQA is to characterize the relationships between water-quality stressors and stream ecology and subsequently determine the relative effects of these stressors on aquatic biota within the streams (Garrett and others, 2017; Journey and others, 2015; Coles and others, 2019; Sheibley and others, 2017; May and others, 2020). The study was implemented in five regions across the United States (U.S.); the Midwest (MSQA) in 2013, the southeast (SESQA) in 2014, the Pacific Northwest (PNSQA) in 2015, the northeast (NESQA) in 2016, and California (CSQA) in 2017. To meet this objective (correlations with and effects of stressors), a framework of fundamental geospatial data was required to develop physical and anthropogenic characteristics of each study region for the watersheds and riparian zones associated with each sampling location. This dataset includes 150 selected environmental characteristics for the 483 sites sampled across all regions of the study. The characteristics were derived over the five years (2013 to 2017) using geospatial summary techniques where spatial information is summarized based on spatial extents such as watersheds. The characteristics were developed using the geospatial data for the location of the water-quality sites, delineations of areas draining to the sites (watershed boundaries, including the boundaries of the lower 5 kilometers [km] of watershed [Lower Basin] for the NESQA and CSQA study regions), and riparian-zone boundaries defined from buffers along digitized riparian reaches (Qi and Nakagaki, 2020). This dataset consists of 3 tables: 1) the main data file containing the environmental characteristics of sites, watersheds (including the boundaries of the lower 5 km of watershed for the NESQA and CSQA study regions), and riparian zones, 2) the data dictionary that describes the variables in the data file, and 3) the full citations associated with the references cited in the data dictionary.