Relations between soil hydraulic properties and burn severity
Title | Relations between soil hydraulic properties and burn severity |
Publication Type | Journal Article |
Year of Publication | 2015 |
Authors | Moody, JA |
Secondary Authors | Ebel, BA |
Tertiary Authors | Nyman, P |
Subsidiary Authors | Martin, DA, Stoof, C, McKinley, R |
Journal | International Journal of Wildland Fire |
Volume | Online early |
Keywords | hydrology, infiltration, technical reports and journal articles |
Abstract | Wildfire can affect soil hydraulic properties, often resulting in reduced infiltration. The magnitude of change in infiltration varies depending on the burn severity. Quantitative approaches to link burn severity with changes in infiltration are lacking. This study uses controlled laboratory measurements to determine relations between a remotely sensed burn severity metric (dNBR, change in normalised burn ratio) and soil hydraulic properties (SHPs). SHPs were measured on soil cores collected from an area burned by the 2013 Black Forest fire in Colorado, USA. Six sites with the same soil type were selected across a range of burn severities, and 10 random soil cores were collected from each site within a 30-m diameter circle. Cumulative infiltration measurements were made in the laboratory using a tension infiltrometer to determine field-saturated hydraulic conductivity, Kfs, and sorptivity, S. These measurements were correlated with dNBR for values ranging from 124 (low severity) to 886 (high severity). SHPs were related to dNBR by inverse functions for specific conditions of water repellency (at the time of sampling) and soil texture. Both functions had a threshold value for dNBR between 124 and 420, where Kfs and S were unchanged and equal to values for soil unaffected by fire. For dNBRs >~420, the Kfs was an exponentially decreasing function of dNBR and S was a linearly decreasing function of dNBR. These initial quantitative empirical relations provide a first step to link SHPs to burn severity, and can be used in quantitative infiltration models to predict post-wildfire infiltration and resulting runoff. |
DOI | 10.1071/WF14062 |