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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Water Management and Systems Research » Research » Publications at this Location » Publication #408836

Research Project: Improving Resiliency of Semi-Arid Agroecosystems and Watersheds to Change and Disturbance through Data-Driven Research, AI, and Integrated Models

Location: Water Management and Systems Research

Title: Estimating changes in streamflow attributable to wildfire in multiple watersheds using a conceptual watershed model

Author
item WELLS, RYAN - Colorado State University
item Mankin, Kyle
item NIEMANN, JEFFREY - Colorado State University
item KIPKA, HOLM - Colorado State University
item Green, Timothy
item Barnard, David

Submitted to: Ecohydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/5/2024
Publication Date: 8/5/2024
Citation: Wells, R., Mankin, K.R., Niemann, J.D., Kipka, H., Green, T.R., Barnard, D.M. 2024. Estimating changes in streamflow attributable to wildfire in multiple watersheds using a conceptual watershed model. Ecohydrology. Article e2697. http://doi.org/10.1002/eco.2697.
DOI: https://doi.org/10.1002/eco.2697

Interpretive Summary: Wildfire in the western U.S. has major impacts on water supply. Planning for how water supply changes after fire is critical, and new approaches are needed to quantify these changes. We developed a method to isolate the daily effects of fire and tested the method in six burned watersheds across the western U.S.: North Eagle Creek, NM (2012 Little Bear Fire), Lopez Creek, CA (1985 Las Pilitas Fire), and City Creek, Devil Canyon Creek, East Twin Creek, and Plunge Creek, CA (2003 Old Fire). Streamflow increased after fire in all six watersheds. The most consistent changes occurred during periods of low streamflow. Several specific results emerged for each watershed. Lopex Creek had 6 years of increased streamflow followed by 6 years of reduced streamflow before returning to pre-fire streamflow behavior 12 years after the Las Pilitas Fire. We didn’t see streamflow recover to pre-fire conditions in either North Eagle Creek 9 years after the Little Bear Fire or the four San Bernadino, CA watersheds 18 years after the Old Fire. This study used a new method to quantify specific, daily changes in flow after wildfire that would not be quantifiable otherwise. Researchers could use this method in other watersheds to describe the effects of fire on streamflow and better understand the streamflow conditions that are most affected by fire.

Technical Abstract: Over half of western U.S. water supply is sourced from forested lands that are increasingly under wildfire risk. Studies have begun to isolate the effects of wildfire on streamflow, but they have used coarse temporal resolutions that cannot account for the numerous, interconnected watershed processes that control the responses to rainfall events. To address these concerns, we developed a method to isolate fine-scale (daily) effects of fire from climate. Wildfire effects were represented by the difference between measured post-fire daily streamflow and unburned scenarios of post-fire daily streamflow simulated by a hydrologic model calibrated to pre-fire conditions. The method was applied to track hydrologic recovery after wildfires in six burned watersheds across the western U.S.: North Eagle Creek, NM (2012 Little Bear Fire), Lopez Creek, CA (1985 Las Pilitas Fire), and City Creek, Devil Canyon Creek, East Twin Creek, and Plunge Creek, CA (2003 Old Fire). All six watersheds experienced prolonged increases of post-fire streamflow, with the most consistent changes occurring during periods of low streamflow. Following 6 years of increased streamflow, Lopez Creek experienced 6 years of reduced streamflow, before returning to pre-fire streamflow behavior 12 years after the fire. North Eagle Creek and the four watersheds affected by the Old Fire continued to demonstrate elevated streamflow 9 and 18 years post-fire, respectively. This study demonstrates the utility of examining post-fire streamflow at daily resolution over multiple years. In particular, these results captured the variability of change across flow frequencies during recovery periods that would not be quantifiable otherwise.