156 - Trigger Boundaries with Harry Mitchell and Nick Kalogeropoulos

Transcript

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With this result, when a fire starts with 34% chance of a dire evacuation, 34% chance of tragedy, you cannot just rely on fire suppression.

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That age has passed.

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You need to look at so much more.

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You need to look at community resilience, you need to look at the fuel condition.

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How did the fire spread at a peak rate of spread of 130 meters a minute?

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This should have been a chance to show that everything went.

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Every layer of fire protection that exists went wrong in Mati and it was the time to assign responsibility when it should have been assigned, to show that there are so many more ways of fighting a fire short term, long term, whatever.

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And with this trigger boundary methodology methodology we want to show that suppressing a fire is not the only option hello everybody, welcome to the fire science show.

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I could record this intro a hundred times, but I don't think I would ever go close to how nick has introduced you into the subject.

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You don't know what it is yet.

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You may guess we're somewhere between engineering and wildfires, and that is true.

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In this episode we will be talking about wildfire preparedness and actually an engineering methodology that was developed in a project called Woonity, a very big project that we will be talking about and this part on imperial legend and under supervision of Guillermo Reyn.

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This is called the trigger boundaries and it's a very nice way to assess when communities should evacuate, when they should leave, when is the last moment they can safely evacuate from a wildfire that is approaching them.

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My guests today are two PhD students from Imperial Well, dr Harry Mitchell you've heard him before in the podcast on the smoldering of timber, and Harry's done a lot of work on trigger boundaries as well and my second guest, nick Algaropouloulos, who you've just heard seconds ago.

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He has a really powerful story behind him doing this job.

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He has firsthand experience with wildfires.

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He's very charismatic and has done a lot of research to take the very first simple model they came up with into a probabilistic simulator.

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So if you're hesitant to stay with us because this is wildfires and you don't do wildfires, oh boy, it's totally worth it, and I'm sure many of us will be doing wildfires in the future.

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Here we are given a tool that we can work with and, as engineers, we have to appreciate that.

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So let's spin the intro and jump into the episode.

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Episode.

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Welcome to the Firesize Show.

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My name is Wojciech Wigrzyński and I will be your host.

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This podcast is brought to you in collaboration with OFR Consultants.

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We confirmed that Kari has not quit, so that's a good one.

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That was a funny one, and first time in the podcast, nikolas Kalogorapus.

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Hello, nik, good to have you in the podcast.

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Hello, thank you for having me Long time listener so far.

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First time speaker.

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Perhaps not a one-time comer.

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We'll see after this episode.

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Great to have you both, and the topic for today is something that you have been both working on in Imperial for many, many years as a part of collaboration called the WNITI, and that is the trigger boundaries.

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In the general theme of wildfire evacuation, I saw Nick's talk on IFSS and that was really, really interesting and I thought that the concept is quite brilliant and could be applied not just to wildfires but in many places like industrial fire safety or perhaps even in some way moved into the world of buildings, so I'm super happy to have listeners learn about it.

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So let's start with the idea what the trigger boundary is and what's the place of that in fire safety is and what's the place of that in fire safety I guess I'll start so trigger boundaries came about when we were looking into how we can use, you know, engineering mindset and mathematics to improve community fire safety.

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One of the things we found from, I think, professor Tom Kova, his team in the US was they used a methodology where they find an imaginary line around the community, to talk in fire safety terms, where R set equals A set.

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I'll explain for people that you know don't have a trying to approve document B.

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So it's a line where the available time to evacuate, dictated by the progression of the fire, is equal to the required time to evacuate for the whole community.

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So when the fire reaches this imaginary line around the landscape, the population has an exact amount of time to evacuate before the fire reaches them.

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If an evacuation happens before that line, then the entire community will have evacuated before the fire reaches them.

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If an evacuation starts after the fire has crossed this boundary, then there is a chance that people will still be in the community when the fire reaches them.

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If an evacuation starts after the fire has crossed this boundary, then there is a chance that people will still be in the community when the fire reaches them.

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It's a sort of line to mark the last chance of safe evacuation.

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Okay, and at what scale is it determined?

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Is it like for a single house, for a single person, for a town, a region?

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It's determined in a per community basis, essentially depending on the evacuation strategy that someone might have.

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They might decide that the best way to evacuate a community is all at once, or they might decide that they can do they can evacuate a bigger parcel of land in stages.

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We take that minimum parcel of land that has been decided on and, with the help of collaborators like Enrico from Lund, we estimate how long it will take for that community to be evacuated and do the analysis for that scope.

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That scale.

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I think the concept is, at the same time, very simple but very powerful.

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So you basically know that if this line is crossed, there is no more chance for safe evacuation and you risk that someone will get hurt in the fire.

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And you also know that if the fire is 10 kilometers from that line, you perhaps can use other strategies to mitigate or, you know, keep, because, like what people do when the fire comes, they would prepare their households or well-being for the incoming fire and then hopefully they would evacuate.

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So perhaps you have more time to prepare or, in terms of industry, perhaps you don't need to shut down the factory.

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That was also an interesting discussion I just had with Eulalia Planas some weeks ago in the podcast.

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So a very simple but yet a very interesting concept.

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What does it mean that the fire crosses the line?

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Like what exactly crosses the line?

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The flames, the smoke, the firebrands?

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So this is actually a really interesting point.

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This is actually a really interesting point.

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So the purpose of the trigger boundary is that it gives adequate time before the quote-unquote fire reach the front of the fire, reaches the community.

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But that isn't necessarily when things will become untenable for the community itself.

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So at the moment, just because it's what is available in terms of modeling capabilities, the trigger time itself is defined by the where the actual wildfire spread front reaches the trigger boundary.

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But I suppose there would need to be other considerations in reality as well, like when do firebrands pass the trigger boundary?

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When does smoke pass the trigger boundary as well?

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Because, as we're seeing in the larger woundity project, smoke is quite a big consideration in the capacity of a community to evacuate.

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You know, if people driving through smoke where they can barely see in front of themselves, then that's seriously going to impede their capacity to evacuate.

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So there are other considerations that need to come into it when we're getting into more complex models.

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We know that the smoke will affect the evacuation, definitely.

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But in terms of the simplest, visibility affects evacuation speed.

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There's a paper by Rico Ronchi on that.

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There's also the concept of is it safer for people to evacuate or is it safer to stay in place if there is a lot of smoke outside and if their building and community preparation is that that allows them to stay in place?

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All right.

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Now we have some modeling to deal with smoke.

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It can be implemented in the three-year boundary methodology.

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It's not implemented in the models we have so far.

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It of course depends on what fuel might be burning, how the wind might be, if there's a lot of smoldering, because we've seen that the flaming part of the fire produces a lot of smoke but it's very hot and goes up, whereas the smoldering part of the water produces colder smoke, which is what ends up going into the communities.

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So there's a lot of interconnectivity at play that can come into the methodology and the framework of trigger boundaries.

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But to select models that can do everything at once is a bit tricky.

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There's so many components that must go into that first, like two separate trees of modeling.

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First the modeling, the evacuation.

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So you need to know how much time actually people need to escape and all the possible scenarios in which the wildfire approaches the community, which will be dictated by the direction of wind, the speed of wind, if it's slow or not.

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Uh, how dry is the fuel?

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How much the fuel is?

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There must be so much, so much into it.

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We'll we'll try to dig into that.

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But first I need to also understand what's the point of doing this extremely complex modeling task.

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How do you see this, perhaps affecting the safety of communities?

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Or what's the rationale behind developing this complex methodology?

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The overall aim of it is to inform safer and more reliable evacuations.

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So around 2% to 3% of wildfires in the northern US, for example, spread into urban areas.

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And when a wildfire spreads into an urban area, stay put isn't always going to be the most effective method of defending the population.

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There will become a critical point where you might need to evacuate, but currently there aren't many resources or tools beyond firefighter intuition that define when is the time where we actually need to call an evacuation.

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So there's a lot of obviously there's a lot of research into wildfire spread modeling.

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So semi-empirical models like Farsight and Flammat and Prometheus, and the list goes on and on and on.

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And then there's a mountain of research into evacuation modeling as well.

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But the interaction and how to couple and interpret both of those phenomena together is heavily understudied and undercharacterized.

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So essentially, the point of trigger boundaries is to sort of bridge that gap, to try and understand okay, when do we need to evacuate people so that they don't end up evacuating into or towards the fire, or before, how do we evacuate them before fire starts to impede the evacuation route?

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Also?

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the delayed evacuation, especially if you have limited capacity to escape, like if you're in a alpine village with just one road, or I think, nick, you are showing an example from greece of matty fire, where it was also impeded.

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If the evacuation is delayed, it's obvious that the consequences will be there.

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But I would love to understand, like, what could be the consequences?

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Like how does it look when the evacuation is started, after those, let's say, trigger boundaries which were not known are crossed?

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Yeah, this is unfortunate, talking about any.

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You know, delayed evacuation in a wildfire is not a pleasant story.

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In my case, I have family in Matti, which was subject to the Matti fire of 2018, with 104 people dead.

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Thankfully, everyone from my family is safe, but, you know, the house next to us is gone A few hours after that.

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It's gone.

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Thankfully, not many people that we knew that were victims of the fire, but some people adjacent to us on the buildings opposite us did not make it.

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So we've seen the worst that can happen in a delayed evacuation.

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The worst thing that can happen is that people might just not know what is going on In Matti, in that area, as I was like I grew up there Even since you, even since I was eight or nine I was used to seeing the sky turn orange, the firefighting helicopters coming down to the seaside to pick up water, so people were used to seeing smoke.

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And when there's smoke over your area, maybe you don't believe that it's a fire that's headed to your place, and in the case of Malta, so many things went wrong that people realized that they were in danger when trees next to them started catching fire because of firebrands.

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So the worst thing that can happen in delayed evacuation is that people don't know that they're in danger.

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And if you don't know you're in danger, you haven't made evacuation plans, and the architecture of the community such that most buildings have wooden roofs, which means that you cannot make it a safe place to stay in place and avoid for it to pass, then your only option is to try and evacuate.

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And if the road network is subpar and there is no coordination for evacuating cars, what can happen is a blockage, when either a car breaks down or there is too much traffic for the road network to handle, not the moment one person decides to abandon their car and go somewhere else.

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In the case of Mati, run to the beach.

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That's it.

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The entire ingress route is blocked off, and in Mati there was only a north and south route.

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Anyway.

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That can happen.

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Some people decide to stay in their cars because the smoke is way too dense.

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Some people go to the beach, but the smoke is still way too dense.

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So, yeah, delaying an evacuation can lead to tragedy, and most often does.

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We refer to such phenomena as dire evacuations, when people attempt to evacuate without enough time to do so safely, and we see it time and time again.

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We saw it in 2018 in Mati, in the Camp Fire, in 2023 in the La Jaina Fire in Portugal, in the Pedro Gao Fire, in individual cases, in the Black Saturday fires in Australia.

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It happens time and time and time again.

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Circumstances are such that an evacuation either occurs or has to occur when there's not enough time to do so safely, either because of the strength of the winds, the dryness of the fuel or just the delayed process of starting the evacuation.

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You've wrote something that resonates very strongly with me.

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That's that for laymen it's very difficult to tell how dangerous is the fire.

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It's related to risk perception of fires.

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There has been a lot of research on that and even you know, I'm, with my limited experience with fire scientists visiting my, my laboratory, technically, people who are extremely well educated in in terms of fire sometimes seeing those you know, 10 megawatts fire out of nothing feels really scary and you've been to cold dreads and stuff.

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You know how a big fire is.

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And even if you're ready for it, it's still surprising sometimes, and if you're a layman, especially if you've seen those images of orange sky, the orange sky will not be oranger because it's more dangerous.

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Right, it's different things that indicate that you're in danger or not, and as a layman, there's absolutely no chance you can tell.

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There's no way out of your experience you'll be able to just say, oh yeah, this time it's really bad.

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Perhaps in some indigenous communities where this knowledge was passed from generation to generation and they just lived in an area that has burned every three years, perhaps they've built a community intuition, but it's not something we should trust on when designing an evacuation process, right?

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So I guess here the winity and furthermore, the trigger boundaries come in.

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The first iteration of that was called the PERIL model.

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Am I correct, harry?

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Yeah, absolutely so.

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It was the Population Evacuation Trigger Algorithm.

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Okay, the acronym doesn't quite line up, but we'll glaze over that Close enough For a pre-chat GPT times?

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we'll glaze over that.

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Close enough For a pre-ChatGPT times?

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I would say that that's close enough, you could probably get closer.

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I think ChatGPT would have got relatively close to that, though I'm happy with that, but yeah, so basically the idea of Peril was to introduce a simple, robust trigger boundary model to the Woonity engine, which essentially for those who don't know is essentially a software package that's being developed, led by the Fire Protection Research Foundation at the NFPA, along with a few of us at Imperial, lund, movement Strategies, nrc and RMIT.

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But basically the idea is that Peril could take one data from a wildfire spread scenario and an evacuation scenario and then develop a trigger boundary around the community from that.

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And also nice thing about it as well is that it doesn't necessarily have to be a model or it.

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It can actually.

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Peril can actually be supported by data like actual experimental data.

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So, for example, one part of the Woonity project was that our team ran an evacuation drill in a WooWee community called Roxburgh Park, essentially just asking I think it was, I can't remember maybe like 10% of the community to evacuate once evacuation notice was given, and from that we got an approximation of the required evacuation time.

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So, for example, that data could be inputted into Peril and use that to support developing a trigger boundary.

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But there's like infinite ways the fire can grow and spread right.

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If you have no wind, it's going to spread very slowly.

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If there's a strong wind, it's going to be a completely different outcome.

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If it's going uphill, it's going to be different than if it's coming to your village from downhill.

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So how does the model take it into account?

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You perform countless amounts of fire spread simulations and then fuel in and compare that with your evacuation simulation.

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How does it work.

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So the first iteration of the model, the AeroAlp, only took into account a single run of both an evacuation and a wildfire simulation model.

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So you could say it's like a scenario-based trigger boundary Absolutely.

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So you take one case of okay, for example, we had a UK case study called Swinley Forest, which was a wildfire that happened I think in the early 2000s, which was modeled heavily by Tom Smith and the University of Greenwich, where basically they took burn data and then calibrated a wildfire spread model to that.

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So you can take a single scenario and then do it like that or, as nick then developed into the next iteration of the model, you can take multiple evacuation scenarios or multiple wildfire spread scenarios and develop something that's a bit more generic, rather a bit more one-fits-all in terms of what a community could see.

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Because, as we're getting sort of this, climate change is impacting things more and more.

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We are seeing more extreme wildfire spread scenarios, which will obviously make things much more complicated when it comes to evacuation.

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Before I leave.

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Nick, I'll follow up on this earlier because I think on this simpler case it's easier to clear out some ideas.

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So, is the trigger boundary a single number?

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Is it a spectrum?

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Do you put any safety margin in that or you just say, okay, like 17 minutes is the trigger boundary and it's up to you to decide whether you like to evacuate 30 minutes or 10 minutes before.

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So in the first iteration, peril, there was a safety factor implemented in it, but not natively.

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For example, if you wanted to model a specific fire and a specific community evacuation, you could put a safety factor on the community evacuation time.

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That's how you would apply it.

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After that the story goes I joined the Haze Lab and one of my first tasks was to take the work of Harry and try to integrate it into the wider Woonity project, university of Melbourne Movement Strategies, funded by NIST and managed by the National Fire Protection Association in the US, where we are the first to attempt a unified coupled wildfire evacuation model.

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So the first platform, let's say that encompasses both wildfire simulations, pedestrian evacuation simulation and vehicular evacuation simulation, because when you have there's a lot of models that do the three independently, we're the first ones to try and do so in a unified content, and one of the great outcomes of such research is trigger boundaries.

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So when I joined I was tasked with trying to do, you know, the nitty-gritty coding stuff to go from R development to Unity.

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And as I was doing it, enrico asked what would happen if I wanted to test out a fire coming, you know, both from the north starting there and from the south, starting there.

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What if I want a boundary for those two fires and for a third fire that you know happened on a low moisture content day.

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That expanded to what if we test 10,000 fires?

00:22:54.028 --> 00:23:03.875
By the end we realized that instead of studying single scenarios with a specific fire ignition point with quite a drastic evacuation, what if we try and do it probabilistically?

00:23:03.875 --> 00:23:10.523
The way I explained this in presentation is imagine if we had to evacuate this room right now.

00:23:10.523 --> 00:23:14.882
I could time you and take a very specific amount of time to evacuate this left theater.

00:23:14.882 --> 00:23:15.743
But what if I needed to know how specific amount of time to evaluate this lecture?

00:23:15.743 --> 00:23:23.888
But what if I needed to know how long it will take to evaluate this room tomorrow or with another class or in a year from now?

00:23:23.888 --> 00:23:30.023
At that point you can't have a precise number, but what you can do is you can have a range of possible numbers.

00:23:30.023 --> 00:23:42.061
It might be slow, it might be fast, it might be a slow day after lunch, it might be a day where it's only first year undergraduates, so they're very speedy to go, so on.

00:23:42.061 --> 00:23:44.250
We took trigger boundaries to the same direction, so we can model a single fire and a single evacuation.

00:23:44.250 --> 00:23:52.880
But what if we want to study what will happen on any possible fire that might threaten this community for any realistic evacuation time.

00:23:53.482 --> 00:24:01.722
What we're doing now is we are stimulating single fires again, yes, but we're doing so in an assembled fashion as you described.

00:24:01.722 --> 00:24:05.621
We're doing hundreds of simulations until convergence is achieved.

00:24:05.621 --> 00:24:06.384
What does that mean?

00:24:06.384 --> 00:24:07.559
I'll leave it as a question mark.

00:24:07.619 --> 00:24:36.929
But until we're satisfied with the result, we run individual peri-studies and bundle them all together in the end, by the end, instead of the fictional line that we were talking about before, where it evaluated before the parity line, you say if after there's a bit of a problem, now we have this sort of band, I'd say, around the community, by that evaluation, completely outside of the band, you have a 100% chance of evacuating on time.

00:24:37.335 --> 00:24:41.255
100% chance when it comes to the model input parameter you selected.

00:24:41.255 --> 00:24:52.185
And as you delay your evacuation and the fire progresses towards the community and into this band, your probability of evacuating safely decreases.

00:24:52.185 --> 00:24:56.432
You might delay your evacuation by a bit and you might decrease it so that now you have an 80% chance of evacuating safely decreases.

00:24:56.432 --> 00:25:00.405
You might delay your evacuation by a bit and you might decrease it so that now you have an 80% chance of evacuating safely.

00:25:00.405 --> 00:25:04.118
You might delay it more and now you have a 40% chance of evacuating safely.

00:25:04.118 --> 00:25:11.118
This percentage the way we do it now comes from doing repeat simulations based on the historic wind.

00:25:11.118 --> 00:25:23.423
So we would look at the weather station data for the last 20 years, find what's the average daily maximum wind, that's the average daily minimum humidity, and how does that vary within a month?

00:25:23.674 --> 00:25:29.742
But the percentage is related to all fires that can expect, so it's not like you have a 40% chance.

00:25:29.742 --> 00:25:36.784
It's that in 40% of fires you would escape and in 60% fires you would escape and in 60% fires you would not.

00:25:36.784 --> 00:25:42.625
Based on your inputs, because for every single fire the trigger boundary will be in some different place, right?

00:25:43.287 --> 00:26:03.862
Yes, the percent chance tries to relay the fact that, based on historic wind, if you start an evacuation when the fire is at this point, the wind temperature, humidity, fuel moisture content is such that on the 60th decile of wind you will not have enough time and on the 40th decile you'll have time.

00:26:03.862 --> 00:26:08.605
But it's not just wind, it's all those parameters that dictate fire behavior bundled together.

00:26:09.095 --> 00:26:39.604
It's really interesting because, at one hand, it's a scenario-based tool which tells you the location of the boundary in a single scenario, and what you're doing here is an extremely difficult task and I know that because we were doing similar things with winds and fire to just create a number, one output out of hundreds of possible scenarios, each with a very, very small probability, because the probability of each individual wind is very low.

00:26:39.604 --> 00:26:43.425
There's like 2% of Western wind with five meters per second.

00:26:43.425 --> 00:26:54.005
These are very low probabilities, right, but the fun part about wind is that, even though it's a collection of low probability events like each wind has its very low probability, you always have one.

00:26:54.005 --> 00:27:00.939
So, like the probability you will have one of them is 100 percent, because that's the windrows, that's all the historical wind, very, very interesting.

00:27:00.939 --> 00:27:08.384
One more thing that I need to clear so you said it was the first coupled approach Is the coupling bi-directional?

00:27:08.384 --> 00:27:15.040
Does it mean that your fire simulation influences the evacuation simulation?

00:27:15.040 --> 00:27:17.688
Do people move differently in different fire scenarios?

00:27:17.688 --> 00:27:20.323
Like you block roads and stuff like that?

00:27:20.916 --> 00:27:26.744
As far as I know last time we talked with the team, parts of fire do increase the evacuation.

00:27:26.744 --> 00:27:34.261
So the fire progressing might block off a road and make it inaccessible will change the evacuation dynamics.

00:27:34.261 --> 00:27:36.003
The fire will produce smoke of some visibility.

00:27:36.003 --> 00:27:36.868
That will change the evacuation dynamics.

00:27:36.868 --> 00:27:37.835
The fire will produce smoke of some visibility.

00:27:37.835 --> 00:27:39.942
That will affect the evacuation speed.

00:27:39.942 --> 00:27:44.605
There is no difference from the evacuation model to the fire model.

00:27:44.605 --> 00:28:06.184
I don't know how that happened, but one important thing to mention is that as of now we can but do not model firefighter intervention, because we want to model the worst case scenario, the worst case conditions, because we know that the fire will spread but we do not know that firefighting actually will happen like in Máté.

00:28:06.204 --> 00:28:08.906
This model- to some extent show the weak spots of the community.

00:28:08.906 --> 00:28:29.542
Like you know that if the fire is approaching from the west and your biggest road will be very soon cut off, you suddenly have the trigger boundary way, way further away than if it's approaching, let's say, from the south, when it's not going to cut your evacuation.

00:28:29.542 --> 00:28:31.742
Does the model show that Exactly that?

00:28:31.863 --> 00:28:36.646
Yeah, we can take the result of the trigger boundary model, which usually is a map.

00:28:36.646 --> 00:29:01.007
If we produce a map centered with a community and draw a line or a boundary around it, we can then use that as evidence-based decision making and say that if you have a fire coming from the west, your trigger boundary extends so far out because your main means of egress might be compromised, because it is dry shrubbery, which means that the fire is going to come in extremely quickly.

00:29:01.007 --> 00:29:19.964
Now you have a visual indication of your weakest points of entry from the fire and you can have a discussion with the community, with managers, with landscapers, of we need to do something about this direction, because this is a very high fire and truth direction.

00:29:19.964 --> 00:29:22.140
This is something that we take pride in.

00:29:22.140 --> 00:29:31.888
The model that we now have, we have produced a way of having numbers and evidence-based decision-making for community resilience.

00:29:32.734 --> 00:29:44.961
But still, I'm still wondering to what extent you could just run a parallel simulation while having a fire, because I'm not sure to what extent the wildfire modeling is used during wildfire events.

00:29:44.961 --> 00:29:59.902
But seeing the amount of development and interest in this area and knowing that there are a lot of tools to, for example, take the real-time wind data and put them into wildfire models, you perhaps could run it on the side to take decisions.

00:29:59.902 --> 00:30:06.246
Is this also something you have expected out of this software or it's just fully preparedness?

00:30:06.286 --> 00:30:06.666
based.

00:30:06.666 --> 00:30:14.402
Considering the computational time that it takes to develop a trigger boundary, I think it's something that is feasible, feasible.

00:30:14.402 --> 00:30:26.604
I think the only thing that is worth highlighting is that your trigger boundary is only going to be as reliable or accurate as the wildfire spread and the evacuation model and or data itself.

00:30:26.604 --> 00:30:41.425
So you know, if you're in in a rush to develop a wildfire model and get your fuel moisture content massively off, then that's going to have implications for your wildfire spread data and likewise with the evacuation.

00:30:41.425 --> 00:30:52.240
So I think it's something that could be used immediately as a um like, for example, for common operating pictures while a wildfire scenario is happening.

00:30:52.240 --> 00:31:04.578
But I do like the other option as well of being able to use it as a more long-term community planning tool, and that allows a bit more fine-tuning and playing with the model to try and work out okay.

00:31:04.940 --> 00:31:11.282
For example, what would happen if we, like carried out some prescribed burns on this area of wild land?

00:31:11.282 --> 00:31:13.567
How would that affect your trigger boundary?

00:31:13.567 --> 00:31:14.969
How about if we added a road here?

00:31:14.969 --> 00:31:15.631
How would that affect the evacuation time?

00:31:15.631 --> 00:31:16.201
And how would that affect your trigger boundary?

00:31:16.201 --> 00:31:16.510
How about if we added a road here?

00:31:16.510 --> 00:31:17.948
How would that affect the evacuation time?

00:31:17.948 --> 00:31:19.578
How would that alter the trigger boundary?

00:31:19.578 --> 00:31:22.855
So I think, long story short, there's a lot of ways to boil an egg.

00:31:23.218 --> 00:31:25.038
Well, I think you're spot on.

00:31:25.038 --> 00:31:29.820
I think you highlighted upgrade versus the current models very clearly.

00:31:29.820 --> 00:31:40.869
I mean, today you can also run the farsight model of where the fire will go and you can run some simulations of where the smoke will go and you can take an informed decision based on the outcomes.

00:31:40.869 --> 00:31:43.416
You don't have to have a trigger boundary.

00:31:43.416 --> 00:31:48.768
Of course, the added value is having an informed number on the evacuation time.

00:31:48.768 --> 00:31:53.467
Let's talk about the modeling, because that's also very interesting for me.

00:31:53.467 --> 00:31:56.019
The modeling, because that's also very interesting for me.

00:31:56.019 --> 00:32:03.182
So, when you do those models that feed the trigger boundary analysis for a community, what goes into such a model?

00:32:03.182 --> 00:32:10.884
You've already mentioned historical wind, but perhaps you can tell me a little bit more about how you define them and perhaps what fire model you use.

00:32:10.904 --> 00:32:19.641
Let's start with that, so we will not discuss the evacuation side of it because we understand how it works, but we are by no means experts.

00:32:19.641 --> 00:32:23.068
We work with the FHIR model primarily.

00:32:23.555 --> 00:32:25.781
And Enrico can feel invited to cover that gap.

00:32:25.781 --> 00:32:36.195
I'll make sure that happens in the podcast and Enrico Very good idea Right now we can talk about the FHIR model and what happens there idea Right now.

00:32:36.215 --> 00:32:38.481
We can talk about the FHIR model and what happens there Right now.

00:32:38.481 --> 00:32:46.411
The FHIR model that we have selected is Farsight, which was developed by the US Department of Agriculture, both because we have learned how to use it for our first case studies.

00:32:46.411 --> 00:32:53.561
The first case studies that we used for KEREL and KPEREL was the test community evacuation of Roxborough in the US the test community evacuation of Roxborough in the US.

00:32:53.561 --> 00:32:57.567
After that we learned how it works.

00:32:57.567 --> 00:33:09.327
We learned its capabilities, assumptions and limitations and we appreciate the fact that it is generalizable in that they provide some ready-made fuel models.

00:33:09.327 --> 00:33:17.487
In this case fuel models, they bunch up all the variables that affect fire spread depending on the vegetation.

00:33:17.487 --> 00:33:20.003
Sorry to interrupt you, but how does it work?

00:33:20.234 --> 00:33:28.403
So I assume that the audience of the Fire Science Show would be most familiar with FDS and CFD modeling, or perhaps CFAST as a zone model.

00:33:28.403 --> 00:33:31.222
What kind of model is Fonsite?

00:33:31.222 --> 00:33:32.601
Is it an equation?

00:33:32.601 --> 00:33:35.781
Is it like a bunch of cells, automata?

00:33:35.781 --> 00:33:37.164
What's the magic inside?

00:33:37.645 --> 00:33:38.407
Very good question.

00:33:38.407 --> 00:33:40.446
You sort of forget that.

00:33:40.446 --> 00:33:45.563
You know there's listeners that may not have FDS, you know, but have never heard of welfare modeling.

00:33:45.563 --> 00:33:49.625
So in FDS it's a very high fidelity model.

00:33:49.625 --> 00:34:03.307
Let's call it a very physical model, in that most of it background mathematics relies on physical knowledge, be it Navier-Stokes equation, diffusion equations, mass conservation equations.

00:34:03.307 --> 00:34:08.286
They are very accurate but take a very long time to produce a result.

00:34:08.286 --> 00:34:12.302
You know you can wait for a week for an FDS study.

00:34:12.302 --> 00:34:13.163
We have fidelity.

00:34:13.163 --> 00:34:24.048
In our case, in Wildfires we have such programs Like FDS has a subroutine, subzoner, submodel called WFDS for Wildfire.

00:34:24.675 --> 00:34:28.186
But we want models that can run in the minutes.

00:34:28.186 --> 00:34:38.599
We want operational models, ones that we can either run now and get a result in five minutes, or one that we can run hundreds of and get a result in five minutes, or one that we can run hundreds of and get a probabilistic outcome within the hour.

00:34:38.599 --> 00:34:43.858
So the way that is usually done is either empirically or semi-empirically.

00:34:43.858 --> 00:35:09.809
So either you use slide rules and linear relations and regressions to know that, to find a relationship between how fast the wind is blowing and how fast your fire will be, or you start from a physical basis, say, for example, studying how heat transfer between cylinders might occur and build that up to a model where you might find that at some point you need a constant that you have to find experimentally.

00:35:10.235 --> 00:35:10.818
Farsight does the second part.

00:35:10.818 --> 00:35:12.351
It is based on a mathematical principle called the Rothenberg model.

00:35:12.351 --> 00:35:12.914
It does the second part.

00:35:12.914 --> 00:35:22.434
It is based on a mathematical principle called the Rotherman model, which essentially its foundation is that there's going to be so many listeners that you know there's going to be Mark listening.

00:35:22.434 --> 00:35:24.802
That has made this model I'm going to be explaining.

00:35:24.822 --> 00:35:30.501
He's going to email me saying no, you got it all wrong, but anyway that's going to happen, no matter what you say.

00:35:30.501 --> 00:35:35.367
So yeah, like take the least blow, go on Nick Rothenberg model, it's yours go.

00:35:45.795 --> 00:35:46.918
Rothenberg model.

00:35:46.918 --> 00:35:52.112
Its main foundation is that how fast the fire goes is a relation of how much energy your fuel provides versus how much energy it needs to combust.

00:35:52.112 --> 00:35:52.655
It's a physical principle.

00:35:52.655 --> 00:35:59.048
And then to find how much energy the fuel provides and how much energy it requires branches out to relations that are found experimentally.

00:35:59.048 --> 00:36:16.985
Like de Rochemaier was a very smart man, along with Andersen and Albini and anyone else I'm forgetting from the Missoula Fire Lab, and you know they extrapolated and said from this main equation how do we find, for example, how much energy a unit of fuel puts out?

00:36:16.985 --> 00:36:25.125
And they do the math, extrapolate, and they come up and say that, oh, the value that dictates this is the surface area to volume ratio, for example.

00:36:25.954 --> 00:36:32.889
You can find that experiment, you can define it, or it comes down to the bulk fuel moisture.

00:36:32.889 --> 00:36:39.583
You can use FDS to model, or you can do a few experiments, see how the fuel moisture varies with time and so on.

00:36:39.583 --> 00:36:41.802
So this is what the model does.

00:36:41.802 --> 00:37:05.670
You give it these bulk values that represent the fuel moisture, the topography, the wind, the fuel structure, and in it it has some empirical relations, meaning Excel, linear regressions of how each variable affects the fire itself, plugs them all together and tells you how fast the fire will spread at any given point.

00:37:05.670 --> 00:37:08.684
So the output is flame spreads velocity.

00:37:09.815 --> 00:37:12.737
Let's say level one output would be the speed of the fire, its rate of spread.

00:37:12.737 --> 00:37:14.420
One output would be the speed of the fire, its rate of spread.

00:37:14.420 --> 00:37:20.766
The level two output would be starting from some sort of ignition, how might it spread over time?

00:37:20.766 --> 00:37:25.650
And at that point you get to not in Firesight but in general you get to choose.

00:37:25.650 --> 00:37:27.391
What methodology do I want to use?

00:37:27.391 --> 00:37:39.505
It might be, as you pointed out, cellular automata where you sort of have a rule set of spread, like maybe a cell is, maybe a point in space, is burning for 10 minutes and then spreads to its neighbor, or something like that.

00:37:40.155 --> 00:37:43.963
It's all discrete in time, so you just say, okay, let's start at time zero.

00:37:43.963 --> 00:37:46.143
After 10 minutes, the fire is here.

00:37:46.143 --> 00:37:52.297
The new weather is this Calculate the next 10 minutes Okay, after 20 minutes, the fire is now here.

00:37:52.297 --> 00:37:53.219
Here's the weather.

00:37:53.219 --> 00:37:54.320
Okay, okay, 20 minutes.

00:37:54.320 --> 00:37:54.760
The fire is now here.

00:37:54.780 --> 00:37:55.161
Here's the weather.

00:37:55.161 --> 00:37:55.961
Okay, okay, okay, exactly so.

00:37:55.961 --> 00:38:05.777
It gives you the location of the fire at every time interval, let's say 15 minutes, and, yeah, it can use any number of ways.

00:38:05.777 --> 00:38:13.264
What Farsight does is something called the Huygens propagation, which is fancy math, to say that it has its current boundary.

00:38:13.264 --> 00:38:30.786
It applies a rule for how it's going to spread, it applies that rule, and then you have the next 15 minutes and this basically provides you with the location of your fire front Exactly and how you decide when it is too late to evacuate.

00:38:30.894 --> 00:38:41.907
So you know the evacuation time, so you know how much time it takes to evacuate and you know, let's say, from this type of modeling, for every single simulation that is coming.

00:38:41.907 --> 00:38:47.487
When it's too late, what do you look for to say, okay, the evacuation is no longer possible.

00:38:47.487 --> 00:38:53.947
Or you just simply look at the time, you simply look at the spread time of evacuation and when this is reached, that's it.

00:38:54.454 --> 00:39:14.820
So I'll let Harry speak for a bit, but first I will say that right now, the models that we use, be it Farsight, be it Prometheus, which is a boreal forest fire simulation, be it whatever model you want to use, that does the job we want it to do, which is tell you where the fire is going to be in space and time, quickly, within five minutes.

00:39:14.820 --> 00:39:20.286
These models have not been developed to deal with fire entering a community.

00:39:20.286 --> 00:39:27.056
We have been dealt with large fires out in the forests of I don't know, idaho, I don't even know if that has forest.

00:39:27.056 --> 00:39:38.739
But that means that we are very reserved in modeling the fire reaching and entering a community, in modeling the fire reaching and entering a community.

00:39:38.739 --> 00:39:46.697
So, both for limitations in what we can do and for optimizing for safety, we say that the fire has entered the community and it's now the ultimate time.

00:39:47.239 --> 00:40:01.226
When the fire reaches the first boundary, the first, let's say, houses that border the forest, we do not model the fire going into the community, spreading through it, because we cannot do that with any degree that we know is accurate.

00:40:01.226 --> 00:40:04.525
So with that in mind, we say that let's say time is zero.

00:40:04.525 --> 00:40:15.791
When the fire reaches the first houses of the community, we go back and see where the fire is, let's say, 120 minutes before, because we know that our community takes 120 minutes to evacuate.

00:40:15.791 --> 00:40:18.804
That's when we know if it's too early or too late.

00:40:18.804 --> 00:40:28.635
If you know how long the fire will take to reach you, then that's how you can determine if it's too early or too late and that's why you need fire modeling.

00:40:28.635 --> 00:40:41.523
With that you can backtrack, which is what we did in Peril and JPeril and you can know that, with the fire approaching, I have this much time left before it reaches the first house that borders the forest.

00:40:42.416 --> 00:40:48.139
There's a bunch of good wildfire scientists at the University of Idaho, so I guess the safe assumption is they have forests.

00:40:48.139 --> 00:40:54.784
Have you attempted to run a real-life case study of application of those trigger boundaries?

00:40:54.784 --> 00:41:00.822
Have you applied this for a real community to see what happens, and if so, how was it?

00:41:00.822 --> 00:41:01.846
How was the experience?

00:41:01.846 --> 00:41:03.943
What have you learned from applying this tool?

00:41:04.355 --> 00:41:10.014
So I would say, to be honest, that's probably the next step in terms of practical implementation of trigger boundaries.

00:41:10.014 --> 00:41:21.925
So at the moment, all of our development of trigger boundaries for these community case studies is hypothetical in nature, is haven't been used in practice.

00:41:21.925 --> 00:41:48.280
But the next step in order to validate or at least benchmark them, is to conduct a evacuation case study, like we did at roxburgh, where you have a hypothetical fire line approaching a community and a trigger boundary that you've developed using peril or k peril or whichever trigger boundary model of your choice you want, and then evacuating the community at that point.

00:41:48.280 --> 00:42:09.945
So I think the next step in terms of practical implementation because fundamentally it's a very visual and very practical coupling method and we'd want it to be able to be used along with the Woonity engine in a practical sense for communities, rather than just this tool package that just sits on a server completely unused.

00:42:09.945 --> 00:42:13.760
Because we want to benefit communities, we want to make them safer.

00:42:15.856 --> 00:42:20.407
Roxbro is the case study, nick you've shown in the IFSS, I guess.

00:42:20.934 --> 00:42:22.922
Yes, there is one.

00:42:22.922 --> 00:42:24.802
Well, we have submitted a paper.

00:42:25.195 --> 00:42:26.822
Good luck crossing fingers.

00:42:26.822 --> 00:42:29.282
A good interview can certainly help there.

00:42:30.637 --> 00:42:37.615
If you happen to be reviewing a paper, something about probabilistic trigger boundaries, you're a very wonderful person and please get on with it Anyway.

00:42:37.615 --> 00:42:41.983
So we have submitted the paper, again, using probabilistic trigger boundaries.

00:42:41.983 --> 00:42:57.266
This time, this paper is, I'd say, a personal achievement of mine, because we apply the probabilistic trigger boundary methodology to the Matic community with the pretense of doing this before the 2018 fire.

00:42:57.266 --> 00:43:04.025
If you were to do this trigger boundary study for 2018, what could you have predicted?

00:43:04.025 --> 00:43:09.123
How could have this been used to avoid the tragedy, and what does it teach us about the tragedy itself?

00:43:09.123 --> 00:43:38.568
Without spoiling much of the paper and this is something that, again, I can talk for hours but the primary outcome of the paper for me not maybe not so much for science, but for me as someone that has to live with the consequences of the mighty fire is that, even upon fire ignition, if the whole of the community at once decided to evacuate when the fire started, there was a 34% chance of tragedy.

00:43:39.735 --> 00:43:42.083
Okay, so the fire started within your trigger boundary.

00:43:42.083 --> 00:43:43.467
Let's say Exactly.

00:43:43.974 --> 00:44:08.518
The fire started so close, the wind was so strong and not to blame the evacuation time being high, but the condition of the roads, the emergency alertness system were inadequately set up that even if everyone, even if evacuated up not not even upon detection, upon ignition of the fire there was still a very realistic chance of something going wrong.

00:44:08.518 --> 00:44:34.170
And I say this because the legal trial regarding the Mati fire has just ended, maybe a month ago, and it resulted in six sentences one for the person that started the fire, who's going away for 500,000 years probably, and the other people that were sentenced as doing something wrong on the fire were six officers of the fire service.

00:44:34.170 --> 00:44:44.150
I think one of them was the aerial means supervisor, who should have moved the firefighting airplane from one airfield to the other, or a few other officers.

00:44:44.150 --> 00:44:47.945
If they did something wrong, they need to be punished for it.

00:44:47.945 --> 00:45:03.949
But the fact that only people from the fire service were sentenced is a message to the Greek community, both the firefighting community and the general public, that the only means of fighting a fire we have available is firefighting.

00:45:04.494 --> 00:45:15.342
With these results and with three-year boundaries in general, we want to show that no, when a fire starts with 34% chance of a dire evacuation 34% chance of tragedy.

00:45:15.342 --> 00:45:18.664
You cannot just rely on fire suppression.

00:45:18.664 --> 00:45:20.141
That age has passed.

00:45:20.141 --> 00:45:22.161
You need to look at so much more.

00:45:22.161 --> 00:45:26.563
You need to look at community resilience, you need to look at the fuel condition.

00:45:26.563 --> 00:45:32.443
How did the fire spread at a peak rate of spread of 130 meters a minute?

00:45:32.443 --> 00:45:36.168
This should have been a chance to show that everything went.

00:45:36.168 --> 00:45:49.599
Every layer of fire protection that exists went wrong in Mati, and it was the time to assign responsibility, when it should have been assigned, to show that there are so many more ways of fighting a fire short-term, long-term, whatever.

00:45:49.619 --> 00:45:55.025
And with this trigger boundary methodology, we want to show that suppressing a fire is not the only option.

00:45:55.025 --> 00:46:03.902
And if we maintain this mentality of the only thing we can do is wait for a fire to start and then send people to fight it, it's not enough anymore.

00:46:03.902 --> 00:46:09.164
Fires are so strong, people are moving back to rural communities.

00:46:09.164 --> 00:46:12.003
You need a new approach to this.

00:46:12.003 --> 00:46:16.072
And now you know we're not just saying it because we have studied or something.

00:46:16.072 --> 00:46:16.333
We know.

00:46:16.333 --> 00:46:17.757
We're saying this because we have the numbers.

00:46:17.757 --> 00:46:21.356
We can put them on a map and show you that this approach is not enough.

00:46:21.356 --> 00:46:24.322
You start off with a realistic chance of death.

00:46:24.322 --> 00:46:27.047
You need to start doing something about it.

00:46:27.047 --> 00:46:33.726
That's not, you know, putting another 20 million into getting a helicopter, which you should, but you should also consider.

00:46:33.726 --> 00:46:39.867
Maybe start to try and prescribe fires, maybe start doing fuel conditioning, maybe start planning evacuation.

00:46:39.867 --> 00:46:45.047
Maybe start fire resilient landscaping, maybe start invading wall breaks.

00:46:45.534 --> 00:46:52.009
You know I could build a new road for a start, like so you relieved the evacuation, perhaps right Exactly.

00:46:52.556 --> 00:46:55.505
This methodology gives you the tools to say what do we need?

00:46:55.505 --> 00:46:56.800
Is what we have enough?

00:46:56.800 --> 00:46:58.922
Are we okay with this level of risk?

00:46:58.922 --> 00:47:01.041
There was no such tool before.

00:47:01.041 --> 00:47:01.784
Trigger boundaries.

00:47:01.996 --> 00:47:07.739
This is such a powerful message, actually, and you know what the world of wildfires?

00:47:07.739 --> 00:47:19.193
First, it's a world of the most devastating losses in terms of money, like there are single fires that have been attributed with more than $50 billion losses.

00:47:19.193 --> 00:47:20.519
Right, a single fire.

00:47:20.519 --> 00:47:29.840
You could fund the fire science until the sun blows up with this amount of money Seriously, and we would be very happy if you did.

00:47:29.840 --> 00:47:44.123
Sun blows up with this amount of money Seriously, like, and we would be very happy if you did, and, on the other hand, you would have I'm not sure which country, but I'm very sure I've read the news that some countries, like gonna spend $2 billion for new airplanes, you know, strengthened their aerial firefighting team.

00:47:44.483 --> 00:47:45.505
Wow, that's that I mean.

00:47:45.505 --> 00:47:48.496

156 - Trigger Boundaries with Harry Mitchell and Nick Kalogeropoulos

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