In response to the 2010 Fourmile Canyon fire near Boulder, Colorado, the U.S. Geological Survey collected data to support investigations into the magnitude and critical drivers of water-quality impairment after wildfire. We analyzed chemistry of stream water, sediment, wildfire ash, soil, dust, and mine waste for metals and other parameters in order to evaluate the effects of legacy mining and wildfire on stream chemistry in the Colorado Front Range, USA. This data release includes data that were published earlier (McCleskey et al., 2012; Murphy et al., 2018).

This data repository documents the input files, output files, and RStudio scripts used to quantify changes in water-quality concentrations after the 2020 Cameron Peak Fire in the North Fork Big Thompson River and Buckhorn Creek watersheds using the Weighted Regressions on Time, Discharge, and Season (WRTDS) method. A WRTDS model was developed using 12 years of pre-fire data (2008-August 13, 2020) and used to make predictions of what water-quality concentrations could have been on post-fire (August 13, 2020-2023) sample days had there not been a fire. This method may be a useful tool for post-fire water-quality assessments in the western United States.

Extreme climate events– such as hurricanes, droughts, ice storms, extreme precipitation, and wildfires– have the potential to cause large changes in watershed processes, response, and function. A five-year post-wildfire study of stream chemistry in the Colorado Front Range USA, enabled the analysis of the effects these events have water quality, which is published in the journal article Murphy, S.F., McCleskey, R.B., Martin, D.A., Writer, J.H., and Ebel, B.A., in review, Fire, flood, and drought: Extreme climate events alter flowpaths and stream chemistry: JGR-Biogeosciences. That article describes how extreme climate events altered concentration-discharge relations in ways that elucidate hydrologic flow paths and the role of material connectivity in stream water chemistry. The datasets provided here contain the data used in that analysis.

After wildfires occurred in the western United States during 2020, in-stream water quality monitors and automatic samplers were deployed in four burned watersheds and one unburned watershed. In-stream water temperature, turbidity, and fluorescent dissolved organic matter (fDOM) were measured at high frequency, and the fDOM data were corrected for temperature and turbidity effects. Automatic samplers were triggered during storm events, which captured turbid conditions in the wildfire affected streams. Laboratory experiments with storm event samples informed site-specific turbidity correction coefficients for fDOM data. An iterative solver approach also was developed to verify turbidity correction coefficients. This data release contains laboratory experiment data, as well as in-stream water temperature, turbidity, uncorrected fDOM, temperature-corrected fDOM, and temperature- and turbidity-corrected fDOM data. An example of the iterative solver code is also provided.

After wildfires occurred in the western United States during 2020, in-stream water quality monitors and automatic samplers were deployed in four burned watersheds and one unburned watershed. In-stream water temperature, turbidity, and fluorescent dissolved organic matter (fDOM) were measured at high frequency, and the fDOM data were corrected for temperature and turbidity effects. Automatic samplers were triggered during storm events, which captured turbid conditions in the wildfire affected streams. Laboratory experiments with storm event samples informed site-specific turbidity correction coefficients for fDOM data. An iterative solver approach also was developed to verify turbidity correction coefficients. This data release contains laboratory experiment data, as well as in-stream water temperature, turbidity, uncorrected fDOM, temperature-corrected fDOM, and temperature- and turbidity-corrected fDOM data. An example of the iterative solver code is also provided.

These data are comprised of measurements of elements (e.g., uranium, cobalt, nickel, copper, zinc, cadmium, lead, etc.) in Canyon Mine containment pond vegetation samples collected in calendar year 2018, plus mercury in vegetation samples collected in 2017 and 2018.

These data are comprised of measurements of elements (e.g., uranium, cobalt, nickel, copper, zinc, cadmium, lead, etc.) in Canyon Mine containment pond vegetation samples collected in calendar year 2018, plus mercury in vegetation samples collected in 2017 and 2018.

These data are comprised of measurements of elements (e.g., uranium, cobalt, nickel, copper, zinc, cadmium, lead, etc.), major anions (chloride, nitrite+nitrate as nitrogen, sulfate, etc.), dissolved organic carbon, and general water quality characteristics in Canyon Mine containment pond water samples collected in calendar year 2018.

These data are comprised of measurements of elements (e.g., uranium, cobalt, nickel, copper, zinc, cadmium, lead, etc.), major anions (chloride, nitrite+nitrate as nitrogen, sulfate, etc.), dissolved organic carbon, and general water quality characteristics in Canyon Mine containment pond water samples collected in calendar year 2018.

Spatially-referenced data used in the study "Evaluating the Factors Responsible for Post-Fire Water Quality Response in Forests of the Western USA"