This study encompasses 25 kilometers of the Chehalis River in Washington, USA that currently has sections under a Total Maximum Daily Load (TMDL) plan for stream temperature impairments that exceed 18°C, a regulatory standard set at the time of the listing to protect salmonid spawning, rearing, and migration. Using information integrated from stationary data loggers (n=22) that collected stream temperature information from August 4-September 10, 2017, and longitudinal thermal profiling performed on July 29-30, August 4-5, and September 9-10, 2017, this study aimed to quantify the spatial distribution of stream temperature, evaluate relative consistencies of the riverine thermal regime over time, and identify which independent variables (land cover, aspect, canopy cover, impervious surfaces, channel width, discharge and air temperature) are correlated with stream temperature metrics using Spearman's rank correlation and stepwise linear regression modeling. Stream temperature was found to be strongly correlated with all air temperature metrics. The strongest model from stepwise linear regression (R2 = 0.711) found width, shrub/scrub, mixed forest, and cultivated crop land cover to be the strongest explanatory variables with the seven day average of the daily maximum stream temperature (7DADMaxTw) at the 22 sites. Tributaries had overall cooler average maximum stream temperatures than main stem sites. Thermal profiling identified seven cold-water patches (defined as the cumulative stream temperature ≥1°C cooler than the surrounding water). Integrating longitudinal thermal profiling and stationary data loggers allows resource managers to understand spatiotemporal stream temperature trends and influences and can assess more effective mitigation strategies to combat rising stream temperatures.