From Flames to Flow: Utah Water Research Lab Unraveling Streamflow Changes Post-Wildfire

Wildfires and other watershed disturbances are becoming an increasing concern for natural resource managers.

Since 2000, an average of 7 million acres across the U.S. have burned each year due to wildfires, altering how water moves across the landscape. But watershed dynamics are complex. Naturally variable factors like weather, seasons, rainfall and snowpack make it challenging to determine how fires and other watershed disturbances change streamflow patterns, which is critical to managing natural resources.

A team of researchers led by Associate Professor Belize Lane at USU’s Utah Water Research Laboratory has developed and tested an innovative algorithm called the Rainfall-Runoff Event Detection and Identification toolkit, or RREDI. This toolkit can untangle the effects of watershed disturbances — such as wildfires, droughts, intense flooding, insect infestations, invasive species and human development — from the natural variability in rainfall-runoff.

“Essentially, the automated algorithm takes long-term rainfall and streamflow data and identifies and separates out individual rainfall events and the resulting surges of water in the stream,” says Haley Canham, the graduate student on the team that originally developed the RREDI Toolkit. “Instead of researchers having to painstakingly sift through long-term timeseries data, the RREDI Toolkit’s algorithm does that work automatically.”

The team tested RREDI across nine study watersheds in the western US, including a watershed in Utah, and generated a dataset of more than 5000 rainfall-runoff events across the watersheds. This large data perspective revealed broader patterns that might have been missed when only looking at a few events or study locations.

To determine the effects of a wildfire on streamflow runoff, more information on each rainfall-runoff event is needed, including the climate (wet or dry), season, and the amount of prior rainfall. These factors influence the runoff response and must be accounted for to understand the impact of the burned landscape on the watershed.

Context is crucial because the wetness or dryness of the year and the season-specific timing can amplify or mask the fire’s effects. For example, a fire might reduce soil absorption, leading to increased runoff. However, if the year is dry, the impact on streamflow, erosion or water quality might seem small.

Conversely, if the same fire happens before a wet winter, the runoff and the effects might be amplified.

By sorting the rainfall runoff events based on whether the year was wet or dry and by the season when the wildfire occurred, the researchers could see more distinctly how runoff across those landscapes changed due to the fires.

“It’s not just about the immediate floods or debris flows right after a fire, but also the longer-term recovery,” Lane says. “Dams, reservoirs, water treatment plants, community planning all need to adapt to handle changing streamflow patterns, whether that is from wildfires or other types of disturbances.”

The RREDI Toolkit's ability to sort through big data and separate natural variability from disturbance effects provides valuable insights for natural resource management. Managers can use the algorithm’s outputs to identify broader patterns that can lead to better planning and adaptation strategies and enhanced community resilience to changing watershed conditions.

Canham, H. A., Lane, B., Phillips, C. B., and Murphy, B. P. (2025). Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments. Hydrol. Earth Syst. Sci., 29, 27–43. https://doi.org/10.5194/hess-29-27-2025

RREDI Toolkit is publicly available on HydroShare.