The measurement of fuel moisture content is time consuming and labour intensive. Direct measures are often not readily available to fire agencies and operations in timeframes suitable for planned burns or in fighting wildfires. However, it is possible to use indirect measures if they are closely related to fuel moisture content and it makes sense to do so if these surrogates are accurate, timely, inexpensive and relatively easy to obtain (Purvis 1995).
In the case of grasslands, fuel moisture content is dependent on the
simultaneous moisture contents of both live and dead material within the sward. A relationship between fuel moisture content and curing values in grasslands has been developed (Parrott and Donald 1970b; Luke and McArthur 1978). Low curing percentage is associated with high fuel moisture while high curing percentage is associated with very low fuel moisture content (Figure 1.7).
Curing percentages less than 100 are a surrogate indicator for the moisture content of live fuel (Catchpole 2002). Accurate curing assessments are required for grassfire danger ratings to ensure the readiness of the general public and appropriate suppression forces when extreme fire weather is anticipated, and to calculate the rate of spread of fire in grasslands.
Curing percentages between 70 and 90% have the greatest influence on rate of spread of fire and are incorporated into the rate of spread models for grassfires using a curing coefficient (Figure 1.6) (Cheney and Gould 1995b; Cheney et al.
1998). Curing values in the 50 – 75% range provide an opportunity to use fire for planned burning of grasslands (Anderson 2007), as in suitable weather conditions such fires should have a reduced rate of spread and be more easily extinguishable. Importantly, these curing conditions occur earlier in the spring and summer fire season in southern Australia, coinciding with milder weather conditions, which also mediate the fire behaviour and increase the likelihood of suppression (McCarthy 1989).
Figure 1.7. Relationship between percentage of dead grass (grass curing index) and fuel moisture content (after Barber 1990) (Dilley et al. 2004).
Curing values greater than 90% indicate there is insufficient fuel moisture to dampen ignition or sustainability of fire. Grasslands with high proportions of dead fuel will become flammable as residual moisture is driven off by low humidity and high temperature associated with fire weather conditions.
Grasslands with curing values below 50% are generally considered unable to sustain fire (Cheney et al. 1998; Cheney and Sullivan 2008). However, Parrott and Donald (1970b) found that ignition rates for two annual grasses, Hordeum
leporinum Link (barley grass) and Lolium rigidum Gaudich. (Wimmera annual ryegrass), approached 100% when curing was only around 40%. In contrast, when 80% cured, another annual grass (Bromus mollis L., or soft brome grass), could sustain ignition only 50% of the time. The potential of fire to spread at curing values below 50% has been reflected in revisions to the Canadian grass fire spread models (Anderson et al. 2011).
1.5.1 Current curing measurements and their limitations Oven drying is used as a benchmark for determination of fuel moisture content in grass samples (Matthews 2010). Although it is a simple method, variation in drying temperature can affect the fuel moisture content (Matthews 2010) and the 24-hour drying cycle render the technique too time-consuming to provide fuel moisture content values in real-time for fire agency use. The method cannot account for spatial variability in fuel moisture content unless samples are collected over the entire landscape which may not always be practical. Hence, alternatives to oven drying are required.
Obtaining timely and accurate measures of curing across the landscape has proved problematic. Destructively-harvested and oven-dried grass samples can be physically separated into live (green) and dead (dry) fractions and this is the most accurate method for determining a curing percentage (Anderson et al. 2011). This separation is both labour and time-intensive, compounding the disadvantages of the oven drying technique (Anderson et al. 2011). Capturing variability across landscapes remains a limitation.
Visual guides to estimate grass curing have been developed to allow field operators to align grass colour (from green to bleached straw) and physiological stage, with a curing percentage (Garvey and Millie 1999; Flavelle 2002; Anderson
et al. 2011). Fire agencies in most Australian states use field observers to visually assess curing percentages and relay this to a central point, where state-wide information is collated and hand-drawn maps are generated to display the rate of curing at a given time. Figure 1.4 shows the progress of curing across Victoria at monthly intervals in summer 2007/8 established from visual curing estimates.
Visual estimation has been the cornerstone of grass curing assessment in much grassfire research but there has been concern about variation between operators in conducting this task (Cheney et al. 1998). Visual estimates are often poorly correlated with the destructive sampling technique (Millie 1999; Anderson
et al. 2011; Newnham et al. 2011) and the low frequency and partial coverage of observations is a constraint (Newnham et al. 2011).
Comparison of field assessment techniques for curing has shown that a modified Levy Rod technique (Levy and Madden 1933) whereby curing percentage calculated from counts of live and dead leaves touching a metal rod placed vertically into the sward (Anderson et al. 2011), yielded comparable results to the destructive sampling benchmarks (Anderson et al. 2011; Newnham
et al. 2011). It was quick and easy to carry out, and overcame the subjectivity of the visual observation technique (Anderson et al. 2011). The accuracy of the Levy Rod method in tall grasslands under windy conditions has been questioned (Carter and Cochrane 1992), however Anderson et al. (2011) found that windy conditions did not influence their observations. The Levy Rod technique remains labour- intensive and does not overcome the challenges of capturing landscape variability. While it was recently recommended for field assessment (Anderson et al. 2011) it has not yet widely replaced visual assessment (e.g. Callaghan 2010; Anderson et al. 2011).
Remote sensing is also used to estimate curing (Barber 1990; Chladil and Nunez 1995; Dilley et al. 2004; Anderson and Botha 2007; Martin et al. 2007). Vegetation characteristics are assessed using Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors orbiting the Earth daily on satellites operated by the US National Oceanic and Atmospheric Administration. Red and near-infrared reflectance bands are used to calculate the Normalised Difference Vegetation Index (NDVI) which has been related to curing through visual assessments and fuel moisture content. Maps of curing changes have been produced by the Bureau of Meteorology for Victoria and south-eastern Australia using these technologies since the 2002-3 fire season (Newnham et al. 2010). Remotely sensed imaging operates at a coarse spatial scale and is subject to distortion or disruption by cloud, smoke or haze, tree presence, bare ground, etc. (Anderson and Pearce 2003). Development of a Relative Greenness Index may overcome particular problems with NVDI such as bare ground caused by landscape change, and tree presence (Newnham et al. 2011). Recent research funded by the Bushfire Cooperative Research Centre aims to enhance the utility of satellite products (Martin et al.
2007).