Linking hydraulic properties of fire-affected soils to infiltration and water repellency

Heat from wildfires can produce a two-layer system composed of extremely dry soil covered by a layer of ash, which when subjected to rainfall, may produce extreme floods. To understand the soil physics controlling runoff for these initial conditions, we used a small, portable disk infiltrometer to measure two hydraulic properties: (1) near-saturated hydraulic conductivity, K-f and (2) sorptivity, S(theta(i)), as a function of initial soil moisture content, theta(i), ranging from extremely dry conditions (theta(i) < 0.02 cm(3) cm(-3)) to near saturation. In the field and in the laboratory replicate measurements were made of ash, reference soils, soils unaffected by fire, and fire-affected soils. Each has a different degrees of water repellency that influences K-f and S(theta(i)). Values of K-f ranged from 4.5 x 10(-3) to 53 x 10(-3) cm s(-1) for ash; from 0.93 x 10(-3) to 130 x 10(-3) cm s(-1) for reference soils; and from 0.86 x 10(-3) to 3.0 x 10(-3) cm s(-1), for soil unaffected by fire, which had the lowest values of K-f. Measurements indicated that S(theta(i)) could be represented by an empirical non-linear function of theta(i) with a sorptivity maximum of 0.18-0.20 cm s(-0.5), between 0.03 and 0.08 cm(3) cm(-3). This functional form differs from the monotonically decreasing non-linear functions often used to represent S(theta(i)) for rainfall-runoff modeling. The sorptivity maximum may represent the combined effects of gravity, capillarity, and adsorption in a transitional domain corresponding to extremely dry soil, and moreover, it may explain the observed non-linear behavior, and the critical soil-moisture threshold of water repellent soils. Laboratory measurements of K-f and S(theta(i)) are the first for ash and fire-affected soil, but additional measurements are needed of these hydraulic properties for in situ fire-affected soils. They provide insight into water repellency behavior and infiltration under extremely dry conditions. Most importantly, they indicate how existing rainfall-runoff models can be modified to accommodate a possible two-layer system in extremely dry conditions. These modified models can be used to predict floods from burned watersheds under these initial conditions. Published by Elsevier B.V.