Oral Presentation Society for Freshwater Science 2026 Annual Meeting

How, when, and where we measure matters: Study design shapes inferred wildfire impacts on water quality (135685)

Riley Barton 1 , Katie Wampler 1 , David Donahue 2 , Lisa Erkert 2 , Kevin Bladon 1
  1. Forest Ecosystems & Society, Oregon State University, Corvallis, OR, USA
  2. Eugene Water & Electric Board, Eugene, OR, USA

Wildfires can substantially alter landscapes, with consequences for downstream aquatic ecosystems and drinking water sources that vary widely among watersheds. However, our understanding of these impacts may be constrained by limitations in study design and how, when, and where we quantify source water quality. The unpredictability of wildfire complicates systematic investigation because researchers must often rely on opportunistic designs, which are frequently limited by scarce pre-fire data and the absence of suitable unburned reference sites. In our study, we leveraged a rare opportunity to evaluate how study design may influence the detection and interpretation of wildfire effects on key water quality constituents. The 2020 Holiday Farm Fire burned approximately 18% of the McKenzie River sub-basin, a 3,461 km2 watershed in Oregon, USA. Here, we were fortunate to have collected 14 years of pre-fire and five years of post-fire water quality data from burned and unburned sites. We used this data to evaluate wildfire responses in dissolved organic carbon (DOC) and total suspended solids (TSS) using multiple commonly applied study design frameworks. We found that inferred fire effects depended strongly on study design, sampling context (seasonality and tributary versus mainstem locations), and the analyte of interest. DOC responses were particularly sensitive to methodological choices, whereas TSS showed more consistent fire-related signals across designs. These results demonstrate that study design can influence, not only the magnitude, but the apparent presence, of wildfire impacts on water quality, underscoring the need to explicitly account for methodological context when generalizing disturbance responses.