Every year a vast majority of 30–46 million km2 of the global land surface burn due to wildfire, approximately 4% of the global land surface. Recently in North America the area burnt by wildfires has increased sharply, while regions like Southeast Asia and South America have seen a rise in the number of land-clearing fires and other escaped wildfires in equatorial forests. In 1997, Malaysia, for example, spent $8.2 million to put out fires that resulted in major evacuations.
The extraordinary costs of fire suppression activities are matched only by the damages to property and ecosystems these fires wreak – in South America, this loss is estimated at $1.6 billion annually. In the US, damages from major fires were found to account for as much as 95% of total costs from fire.
In emerging economies, the default mode of fighting wildfires is reactive – to tackle fires as they arise using whatever resources are available. This approach is both costly and dangerous.
Advances have been made through the use of basic weather data from meteorological stations. In years past, fire agencies used this data to develop fire danger rating systems that helped them predict, prevent and suppress fires. However, there is a mismatch between the specialized, comprehensive data needed for effective fire management today and what is available from rudimentary meteorology networks. This leads to inaccuracy that can cause dangerous errors in decision-making.
Fire Weather Data Adds Critical Insight to Fire Management
A wildfire moves at speeds of up to 14 miles an hour (23 kilometers an hour), consuming everything – trees, brush, homes, even humans – in its path. Modern fire agencies use fire weather data to make decisions about how many people to send to a fire, where to send them, and how quickly they must arrive. Should the focus be on ground operations, or is aerial support needed? Operations are constantly adapting to fire weather information: imminent rainfall may make fire suppression activities unnecessary; an expected change in the wind direction may inform a shift towards protection of a nearby town; windy conditions may make it too dangerous for a helicopter. By understanding the weather’s effect on a fire’s behaviour, decision-makers can make the most effective use of available resources while prioritizing the safety of their firefighters.
Fire danger rating systems: the key to fact-based decision-making
A reliable fire danger rating system is acknowledged worldwide as the keystone of effective wildfire management. A fire danger rating system removes reliance on experience and intuition, and instead allows decisions to be based on consistent, science-based criteria. An early study of Canada’s fire danger rating system found that over an eleven-year period the system saved more than $750 million in firefighting expenditures. In China, implementation of a national fire danger rating system has reduced area burned by 90% since 1987.
Fire weather data reduces risks during prescribed burns
An excess buildup of fuel caused by ongoing fire suppression can lead to extreme fire conditions. Fire weather data and danger rating systems allow land managers to reduce fire risk by doing prescribed burns during times when the fire will achieve its objective but the probability of escape is low.
The importance of proactive resource allocation
It is not feasible to have 100% of staff ready to go at all times, nor is it feasible to have enough equipment and staff to deal with the most extreme fire season. Instead, fire danger ratings can help determine the level of preparedness and resource prioritization on any given day.
Fire weather data helps post-fire analysis
Fire weather data allows fire investigators to trace a fire’s path to its source, while fire danger ratings can help inform whether a fire was the result of natural or human causes – a low ignition risk, for example, could suggest arson.
Accurate Fire Weather Data = Accurate Fire Decisions
To be useful, fire weather data must be accurate. Likewise, fire danger ratings and fire behaviour prediction systems will produce significantly different results when weather inputs are changed.
Small weather changes have big consequences
In some situations, an underestimation of wind speed by 9 km/hr would result in an underestimation of the rate of fire spread by half. Even a 2 km/hr error in wind speed could produce a difference in the rate of spread that would cover the transition from surface fire to crown fire.
The Fire Weather Index can be thrown off by 20%–a significant difference in terms of expected fire weather – by a single day’s error of 10% in relative humidity, or a 2-degree error in air temperature. Add in a 6 km/hr error in wind speed and the index will be 30% off.
Gaps in fire weather data invalidate historical analysis
Similarly, a gap in the weather data caused, for example, by equipment failure creates inconsistencies. Since fuel moisture content is established over the course of years, a fire danger rating cannot be properly calculated without a continuous record of fire weather data.
Late fire weather data is useless data
Fire danger rating systems are intended to predict the worst-case scenario, which for fire is the afternoon when heating peaks. Weather observations must be taken at noon and reported quickly so that ratings reflect today’s fire danger, not tomorrow’s. Hourly data is even more useful, particularly during fire suppression when sudden shifts in weather can jeopardize a crew’s safety.
Simply put, poor data leads to poor decision-making.
Inaccurate danger ratings rack up unnecessary expenses
A fire danger rating that has been mistakenly set too high will incur significant costs as a consequence. In the US, higher fire danger ratings trigger a lengthening of staff hours, resulting in overtime pay of 50%. Given the average crew cost of $3,000 per day, this will quickly add up. Aerial resources are even more expensive: In South Africa, it costs $23,000 a month to keep a helicopter on standby. In Australia, a heli-tanker is $20,000 per day on standby. And in Italy and France, the average cost for water bombers on standby is $13,000 per hour. Public funds are too scarce to be wasted on being ready for fires that may never happen.
Inaccurate danger ratings lead to escaped fires
Fire danger ratings are used to determine crew readiness and resource availability. A delayed or insufficient initial attack will lead to more escaped fires. According to an Australian study, on a bad day, a fire crew delay of just one hour will reduce the probability of containment within 8 hours by 60%.
In the US, just 1% of fires account for 94% of suppression expenditure. The damages from an escaped fire can be enormous. In India, a single fire in a Sandalwood Forest in 1997 generated $43 million in damages.
Poor prediction of fire behaviour endangers lives and property
Once a fire gets going, an accurate prediction of its behaviour is needed to safely and effectively allocate firefighting resources and defend lives and property. Weather conditions dictate whether it is safe for aerial resources to come in, where ground crews should be set-up, and whether nearby settlements need to be evacuated or not.
Proper resource allocation is a large factor in cost. A study of large fires in the US found that geospatial technologies (which are often informed by fire weather data) reduce cost inefficiency by 44%, suggesting there is significant scope for improvement in even sophisticated operations like those found in the US.
Reducing the impact of wildfires with a dedicated fire weather is not only critical in saving lives and reducing damage to property, but it also reduces unnecessary wildfire expenses. Having critical fire weather data insight into fire management arms decision-makers with accurate information to prioritize resources and reduce risk to their firefighters. But, how do you achieve fire weather data accuracy? Find out next issue.
For more information, go to www.ftsinc.com
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