Landscape Hazard Assessment Past Approaches and Current Modeling Tools.

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Presentation transcript:

Landscape Hazard Assessment Past Approaches and Current Modeling Tools

Vegetation/Fuels Information was ground truthed. Rating Included Ignition Likelihood, Values at Risk, and Suppression Difficulty Fuels Hazard based on static evaluation of each location. Not able to evaluate change based on Fuel Treatments

Fire behavior calculated independently for each pixel Used fireline intensity (analog for flame length) No assessment of ignition or spread

Adding Fire Growth Potential FLAMMAP Burn Probability/IFT-DSS RanDig

FLAMMAP 5 is stand alone software, with latest version of the Minimum Travel Time (MTT) fire growth model for Burn Probability and Treatment Optimization calculations. It includes spotting as spread vector Calculation intensive analyses like burn probability can take hours to complete IFT-DSS is online tool, in development. It includes FLAMMAP 3, which does not incorporate spotting spread Calculations made on server, saving local computer resources

Factor Issues for Burn Probability Analysis What are vectors of spread What environmental scenarios are of interest Ignition frequency and distribution What are barriers How are fuel treatments and fire scars represented Are you evaluating individual landscape changes or evaluating hazard in a general sense Size of Analysis Area

Effect of Landscape Classification

LANDFIRE 2008 CWPP 2006 LANDFIRE Landscapes are consistently developed across the entire US. Limited use of local mapping of vegetation. Significant edits are normally required for analysis. Locally produced versions, like this CWPP project map may be more accurate. They are often limited by ownership boundary, image availability, and the time for production.

Is this Masticated Fuel Break a Barrier?

What do you think now?

Fire Behavior in Treatments & Burn Scars

Effect of Ignition Source Random Ignitions And Spatially Explicit Ignitions

Lightning and Human Ignitions 2013 Ignition Cause Human Lightning 2014 Ignition Cause Human Lightning

Lowery, James, "The effect of random and spatially explicit lightning and human-caused ignitions on simulated burn probabilities at small scales" (2012). Theses, Dissertations, Professional Papers. Paper 992

10,000 Random Ignitions 3,500 Human Ignitions

Effect of Environment Factors Fuel Moisture Windspeed Wind Direction

Windspeed Wind Direction

Wind-Driven Surface Fires DMC Driven Cumulative Drought Stage Diurnal Effect Stage

How the FLAMMAP Burn Probability Model Works

10,000 overlapping Fire Perimeters Before Recent Fires

10,000 overlapping Fire Perimeters After Recent Fires The Inputs Matter!

The Results Burn Probability Conditional Flame Length Fire Size Distribution

Burn Probability Output Use enough ignitions to burn entire landscape

Conditional Flame Length Averages all flame length from fires that burned each pixel

Evaluating Treatments Landscape accuracy critical Worst case environment? Multiple wind directions?

Reprocessing Model Outputs Combining burn probabilities from multiple analyses, accounting for – wind direction – Landscape changes Other Examples Ager, Alan A.; Vaillant, Nicole M.; Finney, Mark A.; Preisler, Haiganoush K Analyzing wildfire exposure and source–sink relationships on a fire prone forest landscape. Forest Ecology and Management. 267: 271–283.

Concluding thoughts and questions