A field-parameterised model for quantifying the reduced probability of post fire debris flows in response to hillslope surface wood shred treatments

Post-fire debris flows (DF) pose a substantial threat to life, property, infrastructure, and water supplies of major cities. For example, post-fire DF resulted in 23 deaths in Montecito, California following the 2018 Thomas fires (Kean et al., 2019). Major fires this year at the wildland-urban interface in Los Angeles have again primed the region for major potential post-fire hydro-geomorphic risks.  In Australia, post-fire DF in 2003 resulted in the closure of the capital city’s major water supply for several months (White et al., 2006), and modelling shows that Melbourne’s water supply is at high risk of contamination for up to a year if (or when) its forested water supply catchments are burned by wildfire (Nyman et al., 2020). One of the few feasible mitigation strategies to protect communities, infrastructure and high-value catchments from these devastating impacts is the broadscale application of surface mulches to burned hillslopes.  However, while multiple studies have investigated the effectiveness of these treatments in reducing post-fire erosion and runoff, very few have evaluated its effectiveness specifically in the context of DF risk mitigation, and none (to the authors knowledge) have empirically (i.e., using field experiments)  linked the effectiveness of these treatments to DF initiation likelihood and risk to assets. As a result, any meaningful cost-benefit analysis (CBA) of hillslope treatments is currently not possible. This knowledge gap is particularly important because, while the post-fire risks to life and property are substantial, the costs of broadscale hillslope treatments in difficult terrain are also substantial (~$5,000USD hectare^-1 (Robichaud et al, 2013)). The aim of this research was to quantify the effectiveness of surface mulch (wood shred) treatments in reducing the likelihood of DF initiation in recently burnt landscapes, and to integrate these observations within a purpose-built modelling framework that can be used for rapid CBA of DF risk mitigation.   

We combine experimental field data from 12-months of monitoring (natural and simulated rainfall events) at twelve 30m² runoff plots, treated at varying wood shred application rates, with a DF initiation model to estimate the reduction in DF risk using a novel approach. The protection of water reservoirs is used as a case-study to illustrate how altering DF risk through surface mulch application has direct and substantial impacts on critical infrastructure, using a hydrodynamics model to quantify reductions in water contamination risk. Risk reductions are presented in applied terms (dollars per headwater treated vs. number of debris flows prevented in the landscape) to enable rapid CBA for land managers. Initial results indicate wood shred treatment increases soil infiltration capacity by 50% in high-intensity rainfall events which translates to substantial reductions in DF and water contamination risk. While we use water contamination as a case study to illustrate the impact to assets, this approach can be used to enable CBA for the protection of other critical infrastructure. With huge costs associated with both debris flow damage and with mitigation techniques, the need to undertake empirically based CBA is paramount to both management agencies and communities.