Improving Long-term Post-wildfire hydrologic simulations using ParFlow

Abstract:

Wildfires alter the natural hydrologic processes within a watershed. After vegetation is burned, the combustion of organic material and debris settles into the soil creating a hydrophobic layer beneath the soil surface with varying degree of thickness and depth. Vegetation regrowth rates vary as a function of radiative exposure, burn severity, and precipitation patterns. Hydrologic models used by the Burned Area Emergency Response (BAER) teams use input data and model calibration constraints that are generally either one-dimensional, empirically-based models, or two-dimensional, conceptually-based models with lumped parameter distributions. These models estimate runoff measurements at the watershed outlet; however, do not provide a distributed hydrologic simulation at each point within the watershed. This work uses ParFlow, a three-dimensional, distributed hydrologic model to (1) correlate burn severity with hydrophobicity, (2) evaluate vegetation recovery rate on water components, and (3) improve flood prediction for managers to help with resource allocation and management operations in burned watersheds. ParFlow is applied to Devil Canyon (43 km²) in San Bernardino, California, which was 97% burned in the 2003 Old Fire. The model set-up uses a 30m-cell size resolution over a 6.7 km by 6.4 km lateral extent. The subsurface reaches 30 m and is assigned a variable cell thickness. Variable subsurface thickness allows users to explicitly consider the degree of recovery throughout the stages of regrowth. Burn severity maps from remotely sensed imagery are used to assign initial hydrophobic layer parameters and thickness. Vegetation regrowth is represented with satellite an Enhanced Vegetation Index. Pre and post-fire hydrologic response is evaluated using runoff measurements at the watershed outlet, and using water component (overland flow, lateral flow, baseflow) measurements.