Modelling ignition probability for human- and lightning-caused wildfires in Victoria, Australia

Abstract

Abstract. Wildfires pose a significant risk to people and property, which is expected to grow with urban expansion into fire-prone landscapes and climate change causing increases in fire extent, severity and frequency. Identifying spatial patterns associated with wildfire activity is important for assessing the potential impacts of wildfires on human life, property and other values. Here, we model the probability of fire ignitions in vegetation across Victoria, Australia, to determine the key drivers of human- and lightning-caused wildfire ignitions. In particular, we extend previous research to consider the role that fuel moisture has in predicting ignition probability while accounting for environmental and local conditions previously identified as important. We used Random Forests to test the effect of variables measuring infrastructure, topography, climate, fuel and soil moisture, fire history, and local weather conditions to investigate what factors drove ignition probability for human- and lightning-caused ignitions. Human-caused ignitions were predominantly influenced by measures of infrastructure and local weather. Lightning-sourced ignitions were driven by fuel moisture, average annual rainfall and local weather. Both human- and lightning-caused ignitions were influenced by dead fuel moisture with ignitions more likely to occur when dead fuel moisture dropped below 20 %. In future, these models of ignition probability may be used to produce spatial likelihood maps, which will improve our models of future wildfire risk and enable land managers to better allocate resources to areas of increased fire risk during the fire season.

Dry Live Fuels Increase the Likelihood of Lightning‐Caused Fires

“…When LFMC is dry, the probability of a fire given a lightning strike is 2.25%, compared to 1.27% when LFMC is wet (Figure 4d). These low probabilities of lightning ignitions are consistent with previous research (Abatzoglou et al, 2016;Dorph et al, 2022;Nampak et al, 2021).…”

“…Each lightning pair consists of a dry‐LFMC strike and a wet‐LFMC strike, with land cover being identical and all other wildfire‐related properties being as similar as possible. As covariates, we consider latitude and longitude, above‐ground biomass (AGB) and dead biomass to control for fuel availability (Hessilt, 2022; Safford et al., 2022), wind speed on the lightning day (Goss et al., 2020), cumulative precipitation 12 months before the lightning day, average vapor pressure deficit (VPD) over the 4 months before the lightning day to control for soil moisture (Dadap et al., 2019), and litter moisture effects (Dorph et al., 2022) (Table S1 in Supporting Information ). We use lagged aggregates for precipitation and VPD rather than instantaneous values because soil moisture and litter moisture have memory (McColl et al., 2017).…”

“…Understanding the precise causes of these intensifying effects is challenged by the fact that wildfires are complex phenomena driven by many factors. For example, vegetation density (Hessilt, 2022), dead fuel moisture (Dorph et al., 2022), winds (Keeley & Syphard, 2019; Kolden & Abatzoglou, 2018), and extreme fire weather (Goss et al., 2020; He et al., 2022) all affect fire likelihood in complex and non‐linear ways.…”

Lightning-Induced Wildfires: An Overview

“…Bates et al [138] used the Bayesian network as a framework to assess climate variability in lightning-induced wildfires, and unlike the lightning ignitions, the climate modes were allied to the fire weather conditions. Dorph et al's [139] study in Victoria, Australia, also indicated that lightning-caused wildfires are steered by weather conditions. Clarke et al [140] developed fire models to investigate lightning-induced wildfires in southeastern Australia, specifically Victoria, South Australia, and Tasmania.…”

A global database on holdover time of lightning-ignited wildfires

“…There are still important knowledge gaps about LIWs. Although LIWs are often studied in boreal and temperate ecosystems of North America (e.g., Abatzoglou et al, 2016;Veraverbeke et al, 2017), in other regions, such as Europe and Australia, LIWs receive less attention because of their lower occurrence or burned area in comparison with human-caused fires (Conedera et al, 2006;Ganteaume et al, 2013;Ganteaume and Syphard, 2018;Dorph et al, 2022). Similarly, LIWs are less studied in South America, Asia and Africa (e.g., Manry and Knight, 1986;Kharyutkina et al, 2022;Menezes et al, 2022).…”