Date of Award:

8-2022

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Civil and Environmental Engineering

Committee Chair(s)

Belize A. Lane

Committee

Belize A. Lane

Committee

Colin B. Phillips

Committee

Brendan P. Murphy

Abstract

Wildfires can contribute to enhanced flooding, erosion, debris flows, sediment transport, and water quality changes that impact downstream infrastructure, water users, and aquatic habitat. With increasing wildfire risk in the western U.S. due to a changing climate, understanding post-wildfire rainfall-runoff patterns and controls is critical for continued water resources security. To improve understanding of post-wildfire rainfall-runoff patterns and controls, we developed a transparent, repeatable analysis framework to collect precipitation and streamflow data, identify paired rainfall-runoff events, and analyze these events to evaluate post-wildfire rainfall-runoff patterns and controls. To automate the rainfall-runoff event identification, the Rainfall-Runoff Event Detection and Identification (RREDI) algorithm was developed.

Flow and precipitation data were collected through a hydrologic monitoring network installed in the area burned by the Grizzly Creek Fire (Aug 2020) in Glenwood Canyon, Colorado, USA in five burned watersheds and two nearby unburned watersheds. The North American monsoon drove the precipitation regime during the monitoring period (summer 2021) resulting in highly localized, intense thunderstorm events. The observed rainfall-runoff patterns were highly variable, indicating a number of complex controls including precipitation variability, watershed and burn characteristics, seasonality, and prior storm events may influence rainfall-runoff response. This study investigates post-wildfire rainfall-runoff events across space and time scales to reveal hydrologic patterns and potential controls.

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