Elsevier

Journal of Hydrology

Volume 513, 26 May 2014, Pages 301-313
Journal of Hydrology

Modeling the effects of surface storage, macropore flow and water repellency on infiltration after wildfire

https://doi.org/10.1016/j.jhydrol.2014.02.044Get rights and content

Highlights

  • Infiltration after wildfire is initially controlled by storage in wettable surface material.

  • Steady state infiltration is controlled by the hydraulic conductivity of ash or the soil.

  • Soil hydraulic conductivity is restricted by repellency and macropore availability.

  • The maximum strength of repellency in the soil is a function of monthly weather.

  • Macropore flow is initially low after wildfire but increases during recovery.

Summary

Wildfires can reduce infiltration capacity of hillslopes by causing (i) extreme soil drying, (ii) increased water repellency and (iii) reduced soil structure. High severity wildfire often results in a non-repellent layer of loose ash and burned soil overlying a water repellent soil matrix. In these conditions the hydraulic parameters vary across discrete layers in the soil profile, making the infiltration process difficult to measure and model. The difficulty is often exacerbated by the discrepancy between actual infiltration processes and the assumptions that underlie commonly used infiltration models, most of which stem from controlled laboratory experiments or agricultural environments, where soils are homogeneous and less variable in space and time than forest soils. This study uses a simple two-layered infiltration model consisting of surface storage (H), macropore flow (Kmac) and matrix flow (Kmat) in order to identify and analyze spatial–temporal infiltration patterns in forest soils recovering from the 2009 Black Saturday wildfires in Victoria, southeast Australia. Infiltration experiments on intact soil cores showed that the soil profile contained a region of strong water repellency that was slow to take on water and inactive in the infiltration process, thus restricting flow through the matrix. The flow resistance due to water repellent soil was represented by the minimum critical surface tension (CSTmin) within the top 10 cm of the soil profile. Under field conditions in small headwaters, the CSTmin remained in a water repellent domain throughout a 3-year recovery period, but the strength of water repellency diminished exponentially during wet conditions, resulting in some weather induced temporal variation in steady-state infiltration capacity (Kp). An increasing trend in macropore availability during recovery was the main source of temporal variability in Kp during the study period, indicating (in accordance with previous studies) that macropore flow dominates infiltration processes in these forest soils. Storage in ash and burned surface soil after wildfire was initially high (∼4 mm), then declined exponentially with time since fire. Overall the study showed that the two layered soil can be represented and parameterized by partitioning the infiltration process into surface storage and flow through a partially saturated and restrictive soil layer. Ash, water repellency and macropore flow are key characteristics of burned forest soils in general, and the proposed model may therefore be a useful tool for characterizing fire impact and recovery in other systems.

Introduction

Fire can increase overland flow by reducing interception, infiltration and surface roughness (Martin and Moody, 2001, Robichaud, 2000, Shakesby and Doerr, 2006, Sheridan et al., 2007). Increased production of overland flow can in turn lead to increased erosion rates (Cerda and Lasanta, 2005, Lane et al., 2006a, Moody and Martin, 2001, Robichaud et al., 2008a, Shin et al., 2013, Smith et al., 2011, Wagenbrenner and Robichaud, 2013) and increased frequency of threshold driven responses such as flash floods and debris flows (Cannon, 2001, Cawson et al., 2012; Kean et al., 2013; Nyman et al., 2011). High severity wildfire (i.e. crown fire) removes vegetation, burns the topsoil and deposits ash on hillslopes. Under these conditions the surface roughness and the rates of interception are low and relatively homogenous across hillslopes, irrespective of the catchment conditions prior to burning (Johansen et al., 2001). Infiltration however can be highly variable due to a strong dependency on pre-fire soil properties. Soil properties such as porosity, pore-size distribution, macroporosity and water repellency are therefore important controls on variation in hydrological responses across burned landscapes (Larsen et al., 2009, Nyman et al., 2011, Robichaud et al., 2007, Shakesby and Doerr, 2006).

Infiltration models use theory of flow in porous media to estimate the rate at which water enters the soil. Essentially the infiltration rate is modeled as a function of (i) the pore-size distribution of the soil matrix, (ii) the initial soil moisture and (iii) the rate at which water is supplied at the surface (Green and Ampt, 1911, Philip, 1957). Hydraulic conductivity (mm h−1), sorptivity (mm h−0.5), or the suction at the wetting front (mm) are infiltration parameters that reflect the combined effects of these properties on flow and retention of water within the soil (Smith et al., 2002). These infiltration parameters can be obtained from laboratory studies, field experiments or pedotransfer functions (Cook, 2007, Moody et al., 2009, Rawls et al., 1983, Risse et al., 1994, Robichaud, 2000). Models of infiltration are process-based and represent the physical processes contributing to flow and storage of water in the soil. However, the models are highly idealized and there remain large gaps in their capacity to represent the actual infiltration processes in forest soils, where infiltration is characterized by preferential flow and non-uniform wetting fronts (Beven and Germann, 2013).

The effect of burning on infiltration rates is well documented in the literature. Fire impacts on infiltration parameters by (i) adding surface storage capacity as deposits of fine ash and burned soil (Bodí et al., 2012, Cerdà and Doerr, 2008, Woods and Balfour, 2008, Woods and Balfour, 2010), (ii) reducing soil structure and macropore flow (Nyman et al., 2010, Onda et al., 2008) and (iii) reducing pore-space availability and wettability due to water repellent soils (Cerdà and Doerr, 2007, Doerr and Moody, 2004, Moody and Ebel, 2012, Nyman et al., 2010). Soil profiles on fire affected hillslopes typically consist of heated and burned soil that is sandwiched between ash at the surface and an underlying soil matrix that is unaffected by the fire. The layered soil profile means that there is often strong variability with depth for soil properties such as porosity, particle size distribution and water repellency (Bodí et al., 2012, Ebel, 2012, Ebel et al., 2012, MacDonald and Huffman, 2004, Moody and Ebel, 2012, Moody et al., 2009, Stoof et al., 2010, Woods et al., 2007). Characterizing soil hydrological properties and their effects on the infiltration process in these systems is challenging because it requires simultaneous examination of flow processes in soil layers with different media properties (Ebel and Moody, 2013, Moody et al., 2013).

The properties that dominate infiltration change depending on the spatial and temporal scales at which processes are measured. Water repellency for instance can be quantified as a spatial distribution of a point-based measurement of water drop penetration times (Doerr et al., 1998, Robichaud et al., 2008b, Woods et al., 2007). The water repellency has strong effect on the behavior of water drops, reducing the ability of the soil to absorb water (Doerr et al., 2000). However, the strength or persistence of water repellency at points may not translate to large impacts on infiltration if water bypasses the matrix as preferential flow through wettable patches, cracks, and macropores and along roots and rocks (Burch et al., 1989, Doerr and Moody, 2004, Granged et al., 2011, Imeson et al., 1992, Nyman et al., 2010, Shakesby and Doerr, 2006, Urbanek and Shakesby, 2009). Similarly, the temporal scale of measurement is important. Moisture-induced changes to water repellency for instance is important when infiltration is modeled across different seasons, but it might be negligible within rain storms since the time scale of imbibition in water repellent soil may be in the order of several hours to days (Crockford et al., 1991, Ebel et al., 2012, Moody and Ebel, 2012).

Representing the interactions between macropore flow, matrix flow and imbibition is important for understanding and predicting fire-impacts on infiltration processes. Most infiltration models, however, are based on theory and data from systems where the dominant processes and key properties are different from what is typically observed in fire-affected soils, particularly with regards to wetting behavior (imbibition) and macropore flow (Ebel and Moody, 2013, Nyman et al., 2010). In this paper we therefore aim to develop a model for hydraulic conductivity which incorporates moisture dependent water repellency dynamics and which accounts for changes in macropore flow during recovery from wildfire. The study combines field campaigns and laboratory measurements to:

  • 1.

    Model the interactions between imbibition and hydraulic conductivity of intact soil cores that were water repellent.

  • 2.

    Quantify the effects of seasonal weather, water repellency, surface storage and macropore flow on storage and steady-state infiltration in catchments recovering from wildfire.

The study was conducted at sites in Victoria, southeast Australia, burned by the 2009 Black Saturday wildfires and the 2006 Great Divide Wildfires. Previous work from the region shows that macropore flow and water repellency are important controls on infiltration (Burch et al., 1989, Crockford et al., 1991, Lane et al., 2006b, Nyman et al., 2010, Prosser and Williams, 1998, Shakesby et al., 2003, Sheridan et al., 2007, Smith et al., 2011).

Section snippets

Infiltration model

A large proportion of post-fire erosion tends to occur in response to high intensity rainfall events (Ebel et al., 2012, Kean et al., 2011, Nyman et al., 2011, Smith et al., 2011). This study assumes that infiltration during these types of events is determined by storage of water in surface material and the flow of water out of this storage and into the soil matrix. Once storage is depleted, the maximum infiltration capacity (Kp) occurs under ponded conditions and is either controlled by (i)

Laboratory study: Flow and imbibition in water repellent soil

The soils were water repellent at all sites under air dry conditions (Fig. 4). The critical surface tension (CST) was highly variable at each sampling depth apart from the lowest depth interval (7.5–10) were the CST was usually close to 72 (i.e. non-repellent). The spatial variability in CST within the most hydrophobic region of the soil was more strongly skewed at Ella Creek (Fig. 4c) than at the other two sites (Fig. 4a and b). The different patterns of variability essentially show that water

Contribution of the soil matrix to infiltration in burned soils

The effective hydraulic conductivity of the soil matrix, Kmat, was strongly dependent on the availability of actively conducting pore-space. Laboratory experiments on intact cores showed that Kmat remained at <40% of Ks while the relative soil moisture (θi/θs) in the top 10 cm of the soil profile was <0.8. The magnitude of the water repellency effect on hydraulic conductivity (Kmat/Ks) is similar to the 60–70% reduction measured in wet eucalyptus forest (Nyman et al., 2010, Sheridan et al., 2007

Conclusion

The overall objective of the study was to identify key properties contributing to variability in infiltration during recovery from wildfire and to quantify their effect. A storage-based infiltration model was used as framework for analyzing infiltration data. The model fitted the data well and could be used effectively to partition the infiltration process into its key components of storage, matrix flow and macropore flow. Infiltration on intact cores showed that a water repellent layer acted

Acknowledgments

Field work was carried out with assistance from Philip Noske and Chris Sherwin at the University of Melbourne. Randy McKinley (US Geological Survey) kindly provided calculations of the change in normalized burn ratio (dNBR) for areas in Victoria that were burned by the 2009 wildfires. Research funding was provided by Melbourne Water and the eWater Cooperative Research Centre. The authors are grateful for comments and suggestions from two anonymous reviewers.

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