@article {bnh-8335, title = {Investigating the suitability of aviation tracking data for use in bushfire suppression effectiveness research}, year = {2022}, month = {04/2022}, institution = {Bushfire and Natural Hazards CRC}, address = {Melbourne}, abstract = {

Aircraft are an important part of bushfire suppression and their use is increasing. They were used heavily during the 2019/20 {\textquotedblleft}Black Summer{\textquotedblright} bushfire season in NSW and several inquiries have highlighted the need for research into their effectiveness.

Tracking equipment is becoming routinely deployed on aircraft and there is increasing availability of high-quality ancillary data such as aerial imagery and fire severity mapping. These allow detailed analyses of aircraft activities. However, the usefulness of the data needs to be evaluated, and the analysis needs to be informed by information about the tasking objectives of the aircraft and whether those objectives were met.

This project provides an initial investigation into the process of evaluating aerial suppression using these new data sources and interviews with personnel involved in the suppression activities.

Firebombing event data (drops/fills) from the 2019/2020 bushfire season in NSW from the National Aerial Firefighting Centre (NAFC){\textquoteright}s Arena database was provided by the NSW Rural Fire Service. This data included ~70000 aircraft suppression drop locations and times from aircraft that included helicopters (mainly large and medium helitaks), Single-Engine Air Tankers and Large Air Tankers. As an initial step, we examined the data for completeness, accuracy and errors, and described the data contents. This data was missing for most of the aircraft known to be dropping on the fires, especially the smaller ones. The type of drop (gel, water, retardant) was unknown in most cases, the quantity dropped was unknown in 45\% of cases, and the location for the end of drops was often unreliable.

We then tested methods to identify drop objectives based on relationships between drops data and other spatial data including building locations and weather. Using a combination of automated pattern matching and manual checking, the data can be used to identify cases where the objective was initial attack, extinguishing spot fires, asset protection, pre-emptive laying of retardant lines and direct attack. There were a few cases where the success or failure of the objective could be assessed purely with the spatial data. We also explored two particular analytical methods for determining objectives. First, we compared the distribution of Forest Fire Danger Index (FFDI, fire weather) during a fire and for the drops within that fire. This identified several fires for which a large proportion of the drops were more likely to be during extreme fire weather even though extreme weather was rare in that fire. Second, we compared the distribution of distance to houses between all parts of the fire and the drops at that fire. Here we found many fires where the drops were clustered closer to houses than if the drops were (hypothetically) spread evenly across the fire ground. These analyses are preliminary but show great potential.

We conducted 10 interviews with personnel who worked as Air Attack Supervisors during the 2019/20 season. Interviewees were knowledgeable and experienced, and expressed the view that the aerial program could be improved with further knowledge sharing and training. They provided a lot of general information about objectives, how they learned during the season, their views on limitations in aerial suppression, and their own capacity to document the process.

The interviews also highlighted several operational issues that warrant more investigation using a large number of aviation specialists and more specific questions. Chief among these are:

We conducted eight detailed case studies where there were interesting features in the drop data and insightful comments from the interviewees. These were particular days at a particular part of a fire. They included one example with multiple objectives playing out as one failed and the fire spread changed, several where property protection was the dominant objective (largely successful), one on spot fires, and two initial attacks, of which one succeeded and the other failed.\  The case studies demonstrate the power of the approach where spatial data and interview interpretation are combined.

The air drop data has the potential to enable deep analyses of aircraft use and effectiveness during real bushfire responses, especially when combined with other contextual information, such as objectives and environmental conditions. This will require more matching of the data to interviews to determine whether the drop data can be used in this way. We have started this process in this report, identifying clear clusters of activity related to weather and distance to houses, and cross-checking with interviews in the case study, and in some of these cases, the success could be judged. In order to realise the full potential of this approach, the completeness and accuracy of the drop data should be improved and interviews should become a routine part of the seasonal review process.

}, issn = {725}, author = {Heather Simpson and Michael Storey and Matt P Plucinski and Owen Price} } @article {bnh-6109, title = {A Temporal Framework of Large Wildfire Suppression in Practice, a Qualitative Descriptive Study}, journal = {Forests}, volume = {10}, year = {2019}, month = {10/2019}, pages = {884}, abstract = {

Suppression activities on large wildfires are complicated. Existing suppression literature does not take into account this complexity which leaves existing suppression models and measures of resource productivity incomplete. A qualitative descriptive analysis was performed on the suppression activities described in operational documents of 10 large wildfires in Victoria, Australia. A five-stage classification system summarises suppression in the everyday terms of wildfire management. Suppression can be heterogeneous across different sectors with different stages occurring across sectors on the same day. The stages and the underlying 20 suppression tasks identified provide a fundamental description of how suppression resources are being used on large wildfires. We estimate that at least 57\% of resource use on our sample of 10 large wildfires falls outside of current suppression modelling and productivity research.

}, keywords = {wildfire; suppression; fire management; resource use}, doi = {https://doi.org/10.3390/f10100884}, url = {https://www.mdpi.com/1999-4907/10/10/884}, author = {Heather Simpson and Ross Bradstock and Owen Price} }