To test the hypothesis that wildfire smoke can cool summer river and stream water temperatures by attenuating solar radiation and air temperature, we analyzed data on summer wildfire smoke, solar radiation, air temperatures, precipitation, river discharge, and water temperatures in the lower Klamath River Basin in Northern California. Previous studies have focused on the effect of combustion heat on water temperatures during fires and the effect of riparian vegetation losses on postfire water temperatures, but we know of no studies of the effects of wildfire smoke on river or stream water temperatures. Wildfire smoke is difficult to quantify, but we successfully used a newly available daily high‐resolution (1 km) data set of aerosol optical thickness (AOT) derived from satellite imagery to represent smoke density during 6 years with extensive wildfire activity (2006, 2008, and 2012–2015). Smoke reduced solar radiation by 121 W m−2 per 1.0 AOT relative to clear‐sky conditions. Linear mixed‐effects models showed that on average, smoke cooled daily maximum and mean air temperatures by 0.98 °C and 0.47 °C per 1.0 AOT, respectively, across 19 remote automated weather stations. Smoke had a cooling effect on water temperatures at all 12 river and stream locations analyzed. On average, smoke cooled daily maximum and mean water temperatures by 1.32 °C and 0.74 °C per 1.0 AOT, respectively. This smoke‐induced cooling has the potential to benefit cold‐water adapted species, particularly because wildfires are more likely to occur during the warmest and driest years and seasons.

Using nonparametric Mann‐Kendall tests, we assessed long‐term (1953‐2012) trends in streamflow and precipitation in Northern California and Southern Oregon at 26 sites regulated by dams and 41 “unregulated” sites. Few (9%) sites had significant decreasing trends in annual precipitation, but September precipitation declined at 70% of sites. Site characteristics such as runoff type (groundwater, snow, or rain) and dam regulation influenced streamflow trends. Decreasing streamflow trends outnumbered increasing trends for most months except at regulated sites for May‐September. Summer (July‐September) streamflow declined at many sites, including 73% of unregulated sites in September. Applying a LOESS regression model of antecedent precipitation vs. average monthly streamflow, we evaluated the underlying streamflow trend caused by factors other than precipitation. Decreasing trends in precipitation‐adjusted streamflow substantially outnumbered increasing trends for most months. As with streamflow, groundwater‐dominated sites had a greater percent of declining trends in precipitation‐adjusted streamflow than other runoff types. The most pristine surface‐runoff‐dominated watersheds within the study area showed no decreases in precipitation‐adjusted streamflow during the summer months. These results suggest that streamflow decreases at other sites were likely due to more increased human withdrawals and vegetation changes than to climate factors other than precipitation quantity.

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Low streamflows can increase vulnerability to warming, impacting coldwater fish. Water managers need tools to quantify these impacts and predict future water temperatures. Contrary to most statistical models' assumptions, many seasonally changing factors (e.g., water sources and solar radiation) cause relationships between flow and water temperature to vary throughout the year. Using 21 yr of air temperature and flow data, we modeled daily water temperatures in California's snowmelt‐driven Scott River where agricultural diversions consume most summer surface flows. We used generalized additive models to test time‐varying and nonlinear effects of flow on water temperatures. Models that represented seasonally varying flow effects with intermediate complexity outperformed simpler models assuming constant relationships between water temperature and flow. Cross‐validation error of the selected model was ≤1.2°C. Flow variation had stronger effects on water temperatures in April–July than in other months. We applied the model to predict effects of instream flow scenarios proposed by regulatory agencies. Relative to historic conditions, the higher instream flow scenario would reduce annual maximum temperature from 25.2° to 24.1°C, reduce annual exceedances of 22°C (a cumulative thermal stress metric) from 106 to 51 degree‐days, and delay onset of water temperatures >22°C during some drought years. Testing the same modeling approach at nine additional sites showed similar accuracy and flow effects. These methods can be applied to streams with long‐term flow and water temperature records to fill data gaps, identify periods of flow influence, and predict temperatures under flow management scenarios.

Low streamflows can increase vulnerability to warming, impacting coldwater fish. Water managers need tools to quantify these impacts and predict future water temperatures. Contrary to most statistical models’ assumptions, many seasonally changing factors (e.g., water sources and solar radiation) cause relationships between flow and water temperature to vary throughout the year. Using 21 years of air temperature and flow data, we modeled daily water temperatures in California’s snowmelt-driven Scott River where agricultural diversions consume most summer surface flows. We used generalized additive models to test time-varying and nonlinear effects of flow on water temperatures. Models that represented seasonally varying flow effects with intermediate complexity outperformed simpler models assuming constant relationships between water temperature and flow. Cross-validation error of the selected model was ≤1.2 °C. Flow variation had stronger effects on water temperatures in April–July than in other months. We applied the model to predict effects of instream flow scenarios proposed by regulatory agencies. Relative to historic conditions, the higher instream flow scenario would reduce annual maximum temperature from 25.2 °C to 24.1 °C, reduce annual exceedances of 22 °C (a cumulative thermal stress metric) from 106 to 51 degree-days, and delay onset of water temperatures >22 °C during some drought years. Testing the same modeling approach at nine additional sites showed similar accuracy and flow effects. These methods can be applied to streams with long-term flow and water temperature records to fill data gaps, identify periods of flow influence, and predict temperatures under flow management scenarios.