Capturing Spatiotemporal Variation in Wildfires for Improving Postwildfire Debris‐Flow Hazard Assessments

Abstract

Wildfires can increase the frequency and magnitude of catastrophic debris flows. Integrated, proactive naturalhazard assessment would therefore characterize landscapes based on the potential for the occurrence and inter actions of wildfires and postwildfire debris flows. This chapter presents a new modeling effort that can quantify the variability surrounding a key input to postwildfire debris-flow modeling, the amount of watershed burned at moderate to high severity, in a prewildfire context. The use of stochastic wildfire simulation captures variabil ity surrounding the timing and location of ignitions, fire weather patterns, and ultimately the spatial patterns of watershed area burned. Model results provide for enhanced estimates of postwildfire debris-flow hazard in a prewildfire context, and multiple hazard metrics are generated to characterize and contrast hazards across watersheds. An area in northern New Mexico, USA, is presented as a case-study location, where postwildfire debris flows are a salient hazard and where land managers are actively pursuing mitigation efforts. Modeling results are described in terms of informing mitigation efforts. Limitations and future directions are presented.

Estimating post-fire debris-flow hazards prior to wildfire using a statistical analysis of historical distributions of fire severity from remote sensing data

“…However, direct prediction of fire severity and associated metrics (i.e. dNBR and soil burn severity) and potential debris-flow hazards for future wildfires is an infrequently explored topic in the scientific literature (Tillery et al 2014;Haas et al 2016;Tillery and Haas 2016).…”

“…Few efforts to estimate potential debris-flow hazards before the occurrence of fire (Stevens et al 2011;Lancaster et al 2014;Tillery et al 2014;Haas et al 2016;Tillery and Haas 2016) have been attempted. Stevens et al (2011) used the presence of vegetation cover as an indicator of fire severity.…”

Prioritising fuels reduction for water supply protection

“…We used CFA (Scott and Reinhardt 2001) modelled with FlamMap 5.0 (Finney et al 2015) as a proxy for burn severity by assuming that surface, passive crown and active crown fire correspond to low, moderate and high burn severity respectively (Tillery et al 2014;Haas et al 2017;Jones et al 2017). Characterising fire effects by burn severity category is consistent with how field-based erosion studies stratified their sampling (e.g.…”

“…CFA is a prediction of fire type in categories of unburned, surface fire, passive crown fire and active crown fire, which has been used as a proxy for burn severity in previous watershed risk assessments (e.g. Tillery et al 2014;Haas et al 2017;Jones et al 2017). Large fires driven by very dry and windy conditions are responsible for most of the area burned in the Colorado Front Range (Graham 2003;Sherriff et al 2014;Haas et al 2015), so we assessed risk using fire behaviour modelled under extreme fire conditions.…”

“…For practical reasons, we used burn probability to represent the spatial and temporal variability in wildfire occurrence (Scott et al 2013), which limits our ability to quantify wildfire consequences that are tied to fire and rainfall event magnitudes, such as exceeding turbidity thresholds for water treatment (Oropeza and Heath 2013;Hohner et al 2017). Simulation-based risk analysis methods (Thompson et al 2016;Haas et al 2017) could be used to better quantify the fuels reduction effects on fire event consequences and probabilities for exceeding thresholds of impact.…”