In 2020, Colorado experienced the most severe wildfire season in recorded history, with wildfires burning 625 357 acres across the state. Two of the largest fires burned parts of Rocky Mountain National Park (RMNP), and a study was initiated to address concerns about potential effects on drinking water quality from mobilization of ash and sediment. The study took advantage of a wealth of pre-fire data from adjacent burned and unburned basins in western RMNP. Pre- and post-fire data collection included discrete sample collection and high-frequency water-quality measurements using in-stream sensors. Kruskal–Wallis tests on discrete data indicated that specific conductance, base cations, sulphate, chloride, nitrate, and total dissolved nitrogen concentrations increased post-fire, whereas silica and dissolved organic carbon (DOC) did not (p ≤ 0.05). In-stream sensors captured large spikes in concentrations of nutrients, turbidity, and DOC in the burned basin that were missed by discrete sampling. Sensor data indicated nitrate and turbidity increased by up to one and two orders of magnitude, respectively, from pre-event concentrations during storms, and DOC increased up to 3.5×. Empirical regression equations were developed using pre-fire data and applied to the post-fire period to estimate expected stream chemistry in the absence of fire (a ‘no-fire’ scenario). Overlays of actual post-fire chemistry showed the timing and magnitude of differences between observed and ‘estimated’ chemistry. For most solutes, observed post-fire concentrations were notably greater than expected under the ‘no-fire’ scenario, and differences were greatest during storm events. Comparison of data from the burned and unburned basins indicated DOC concentrations were affected by climate as well as fire. Results from this study demonstrate the importance of both pre-fire data and high-frequency data for characterizing dynamic hydrochemical responses in wildfire-affected areas.