Notes: GIS Applications in Fire Ecology & Management In this - - PDF document

NR406

GIS Applications in Fire Ecology & Management Lesson 4 Fire Risk, Hazard, and Risk Models

Stockwell Fire, 1996 photo from www.wildlandfire.com

Notes:

In this lesson we will cover the concepts of fire risk and hazard, different types of risk and hazard and how we can use GIS and fire behavior models as tools to model risk and hazard. A model is a simplification of the real world. Models are used for better understanding of a system and for prediction. Models can be based on past experiences, research, laws of nature, and expert opinion.

NR406: GIS Applications in Fire Ecology and Management

5 Mile fire in northw estern W I SCONSI N

Look at flam e height relative to tree height

5 Mile fire in northw estern W I SCONSI N

Look at flam e height relative to tree height

Photo from www.wildlandfire.com

Notes:

Reasonably reliable models in the form of computer software exist for modeling surface fires such as Behave, Behave Plus, Farsite, FlamMap, Fofem, Firesum, etc. The fire in the picture above is however not amenable to being modeled – at least not yet. Software for fire modeling is available at no cost via the internet: Public domain software for fire - http://www.fire.org/ Fire Research and Management Exchange System (FRAMES)- http://frames.nbii.gov/portal/server.pt

NR406: GIS Applications in Fire Ecology and Management

http://www.nifc.gov/nicc/predictive/outlooks/OutlookMap.pdf

National W ildland Fire Potential Outlook National W ildland Fire Potential Outlook

Notes:

By September 11 2006, 81,522 fires in the US had burned a total of 8,694,482 acres according to the National Year-to- Data report from NIFC (http://www.nifc.gov/stats/ytd_st.htm). This map is a simple model of fire potential in the USA for a certain time period. What inputs do you think went into creating this map (model)?

NR406: GIS Applications in Fire Ecology and Management

Fire Behavior Triangle Fire Behavior Triangle

• Weather
• Topography
• Fuel

Fire Fire

Notes:

Surely you are all familiar with the fire behavior triangle. Predictive fire behavior models are centered around fuel, topography, and weather.

NR406: GIS Applications in Fire Ecology and Management

Fuel – the stuff that burns Fuel – the stuff that burns

• Fuel load

Dry weight of combustible material per unit area Sometimes categorized according to type – fine woody debris, litter, understory, etc.

Notes:

In a forest, fuel is usually the vegetation and the organic material on the forest floor. Fuel load tells us how much fuel there is – can’t have a fire without fuel

NR406: GIS Applications in Fire Ecology and Management

Fuel Moisture Fuel Moisture

Concepts

• Wet things don’t burn
• Small things dry more quickly than big

things

• Fire start with small fuels
• Fire spread is the fire starting over and
• ver again

Dead fuels

• 1 hour – less than ¼ ” diam eter
• 10 hour – ¼ ” to 1” diam eter
• 100 hour – 1” to 3” diameter
• 1000 hour – 3” to 8” diameter

Notes:

Fuel moisture and particle size are important properties of fuels.

NR406: GIS Applications in Fire Ecology and Management

Fuel Model Fuel Model

• A way to put fuel into categories according to

how it burns

• There are several fuel model systems in use

for wildland fire

• Fire behavior software uses the Fire Behavior

Prediction System models

• Most models of wildland fire fuels initially

classify fuels as grass, shrub, timber, or slash

Notes:

You are probably familiar with the concept of categorizing fuels in ‘Fuel Models’. Fuels are categorized into fuel models according to how they

• burn. There are several fuel model systems in use for wildland
• fire. The Anderson (1982) categorization of fuel model is the

most widely used system. Fire behavior models use fuel models to predict fire behavior. Anderson, Hal E. 1982. Aids to determining fuel models for estimating fire behavior. USDA For. Serv. Gen. Tech. Rep. INT-122, 22p. lntermt. For. and Range Exp. Stn., Ogden, Utah 84401 Available at: http://www.fs.fed.us/rm/pubs_int/int_gtr122.html

NR406: GIS Applications in Fire Ecology and Management

Fuel Model Fuel Model Considerations:

• Fuel load
• Fuel moisture
• Ratio of surface area to volume
• Depth of the fuel bed
• Horizontal/ vertical orientation

Notes:

These are fuel properties that affect how fuels burn We already discussed Fuel load and moisture.

NR406: GIS Applications in Fire Ecology and Management

FM 1 – Short Grass FM 2 – Open Timber Grass Understory FM 5 – Short Brush FM 8 – Closed Short Needle Conifer FM 9 – Closed Long Needle Conifer FM 10 – Closed Timber Heavy DWD FM 11 – Light Logging Slash Fuel m odels (Anderson, 1982) Fuel m odels (Anderson, 1982)

Notes:

A few fuel models are listed here. If you are not familiar with the concept of the Anderson fuel models, please take some time to read: Anderson, Hal E. 1982. Aids to determining fuel models for estimating fire behavior. USDA For. Serv. Gen. Tech. Rep. INT-122, 22p. lntermt. For. and Range Exp. Stn., Ogden, Utah 84401 Available at: http://www.fs.fed.us/rm/pubs_int/int_gtr122.html

NR406: GIS Applications in Fire Ecology and Management

BEHAVE Outputs: Fireline I ntensity BEHAVE Outputs: Fireline I ntensity

Fireline Intensity for Fuel models at 5 mph wind

500 1000 1500 2000 2500 3000 3500 4000 10 20 30 40 50

Slope (degrees) Fireline Intensity (kW/

FuelM 1 FuelM 2 FuelM 5 FuelM 8 FuelM 9 FuelM 10 FuelM 11

Notes:

This graph is an output from the fire behavior model BEHAVE. The model was run at a constant wind (5 miles per hour) for the fuel models described on the last slide. Notice the high fireline intensity for Fuel model 2 (open timber grass understory) and 5 (short brush) and the low fireline intensity for fuel model 8 (closed short needle conifer forest).

NR406: GIS Applications in Fire Ecology and Management

BEHAVE outputs: Flam e length BEHAVE outputs: Flam e length

Flame length for Fuel models at 5 mph winds 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 10 20 30 40 Slope (degrees) Flame length (meters

FuelM 1 FuelM 2 FuelM 5 FuelM 8 FuelM 9 FuelM 10 FuelM 11

Notes:

Similar to the last slide but here you have flame length on the y-axis rather than fireline intensity.

NR406: GIS Applications in Fire Ecology and Management

BEHAVE outputs: Rate of spread BEHAVE outputs: Rate of spread

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0 10 20 30 40

Slope (degrees)

Rate of spread (meters / minute) FuelM 1 FuelM 2 FuelM 5 FuelM 8 FuelM 9 FuelM 10 FuelM 11

Rate of Spread for Fuelmodels at 5 mph wind

Notes:

Here is the rate of spread for different fuel models at varying

• slope. Notice the high rate of spread for FM 1 (short grass).

NR406: GIS Applications in Fire Ecology and Management

Scott, Joseph H.; Burgan, Robert E. 2005. Standard fire behavior fuel m odels: a comprehensive set for use with Rothermel's surface fire spread model.

• Gen. Tech. Rep. RMRS-GTR-153. Fort Collins, CO:

U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station; 72 p. There is a need for m ore refined fuel m odels There is a need for m ore refined fuel m odels

Notes:

According to Scott and Burgan (2005) the Anderson (1982) 13 fire behavior fuel models have worked well for predicting spread rate and intensity of active fires at the peak of fire

• season. However, they have deficiencies in other situations,

including prescribed fire, wildland fire use, simulating the effects of fuel treatments on potential fire behavior, and simulating transition to crown fire using crown fire initiation

• models. There is a need for further developed fuel models.

Scott and Burgan have developed 40 ‘new’ fuel models and the Landfire project (www.Landfire.gov) have created spatial data layers of both the 13 Anderson fuel models and the 40 Scott and Burgan fuel models. We will talk more about the Landfire data and how to access these spatial data layers in Lesson 8.

NR406: GIS Applications in Fire Ecology and Management

• improve the accuracy of fire behavior predictions outside of the peak

fire season, such as encountered in prescribed fire and fire use

• applications. For example, the original grass models 1 (short grass)

and 3 (tall grass) are fully cured. Applying those models to situations in which the grass fuelbed is not fully cured leads to over-prediction.

• increase the num ber of fuel models applicable in high-extinction-

moisture areas. Only a few of the original 13 fuel models are appropriate for fuelbeds that burn well at relatively high dead fuel moistures.

• increase the num ber of fuel models for forest litter and litter with

grass or shrub understory. Predicted surface fire behavior drives crown fire models (Van Wagner 1977, Alexander 1988), so increased precision in surface fire intensity prediction will lead to increased precision in crown fire behavior and hazard assessment.

• increase the ability to simulate fuel treatments by offering more fuel

model choices.

• Scott and Burgan (2005)

Suggestions for fuel m odel im provem ents Suggestions for fuel m odel im provem ents

Notes:

These are a few suggestions from Scott and Burgan (2005) regarding the improvements needed http://www.fire.org/index.php?option=com_content&task=view &id=27&Itemid=27

NR406: GIS Applications in Fire Ecology and Management

Federal Funding for Mitigation Federal Funding for Mitigation

Notes:

Communities all over the country are currently interested in modeling fuels, fires, and risk. National fire plan, healthy forest initiative provide incentives for communities to mitigate, or reduce their exposure to, fire hazard. Communities need to develop mitigation plans to qualify for funding

NR406: GIS Applications in Fire Ecology and Management

Fuels Reduction Fuels Reduction

Photo from Scott Roberts http://www.forestryimages.org

Notes:

Mitigation can take form of fuel reduction, which could be the trees……

NR406: GIS Applications in Fire Ecology and Management

Fuels Reduction Fuels Reduction

Notes:

…..or human structures

NR406: GIS Applications in Fire Ecology and Management

Hazard and Risk Hazard and Risk Hazard

• A source of potential danger or adverse condition.
• A natural event is a hazard when it has the

potential to harm people or property.

Hazard Identification

• The process of identifying hazards that threaten an

area.

Hazard Mitigation

• Sustained actions taken to reduce or

elim inate long-term risk from hazards and their effects.

Notes:

What is the difference between hazard and risk? Hazard is the source of a potential danger, for example a natural event is a hazard when it has the potential to harm people or property.

NR406: GIS Applications in Fire Ecology and Management

Risk Risk The estimated impact that a hazard would have on people, services, facilities, and structures in a community; the likelihood of a hazard event resulting in an adverse condition that causes injury or damage.

(hazard and risk definitions after FEMA 386-2)

Notes:

Risk is the estimated impact that the hazard would have on people or properties. The risk is the likelihood that the hazard event will result in adverse conditions.

NR406: GIS Applications in Fire Ecology and Management

• Risk of ignition?
• Risk of fast spread?
• Risk of high fire severity?
• Risk to structures?

Risk of w hat? Risk of w hat?

Notes:

Mapping fire risk can mean many things! The risk of ignition? The risk of fast spread? The risk of high fire severity? The risk to human properties? Heavy fuels is a hazard with a high risk of resulting in a high severity fire. Tall grass prairie and savannas with high and dry fuel loads are hazards with a high risk in resulting in a fire with a high rate of spread. Heavy fuels near development are hazards with a high risk of resulting in loss of human values in a fire.

NR406: GIS Applications in Fire Ecology and Management

Xeric cover types

• South & west aspects
• Ramp of yellow to red on

a slope gradient Latah County Plan

• “The risk rating presented

here serves to identify where certain constant variables are present that aid in identifying where fires typically spread the fastest across the landscape.”

Risk of fast fire spread Risk of fast fire spread

Notes:

This map was developed as part of the Latah county fire plan. The map was developed in a GIS simply by selecting areas of xeric cover types, south and west aspects, and steep slopes. The map was presented as a map showing areas with a high risk of developing fires with fast spread. Rather this map represents fire prone areas. No fire behavior calculations were incorporated when this map was created and its value has been questioned. Maps such as this one are often misinterpreted by decision makers and the general public. Risk of fast spread is not the same as risk of a severe fire, risk to development or risk of

• ignition. Always be specific when using the words fire hazard

and fire risk.

NR406: GIS Applications in Fire Ecology and Management

Flam Map : W hat is it? Flam Map : W hat is it?

• FlamMap software creates raster maps of potential fire

behavior characteristics (ROS, flame length, crown fire activity, etc.) and environmental conditions (dead fuel moistures, mid-flame wind speeds, & solar irradiance)

• ver an entire FARSITE landscape.
• It is not a replacement for FARSITE or a fire growth

simulation model. There is no temporal component or contagion process in FlamMap. It uses spatial information on topography and fuels to calculate fire behavior characteristics at one instant for each pixel.

• It uses the same spatial and tabular data as FARSITE; a

Landscape (.LCP) File, Initial Fuel Moistures (.FMS) File, as well as optional Custom Fuel Model (.FMD), Conversion (.CNV), Weather (.WTR), and Wind (.WND) Files.

Notes:

Rather than simply selecting fire prone areas and presenting this as a fire risk map we could use available fire behavior models to create maps that show rate of spread, flame length, crown fire activity etc. under certain fuel and weather conditions across a landscape. FlamMap (http://www.fire.org/index.php?option=content&task=category &sectionid=2&id=9&Itemid=30) is a software which can compute such potential fire characteristics across a landscape.

NR406: GIS Applications in Fire Ecology and Management

Flam Map Flam Map

• It incorporates the following fire behavior models;
• Rothermel's 1972 surface fire model,
• Van Wagner's 1977 crown fire initiation model,
• Rothermel's 1991 crown fire spread model,
• Nelson's 2000 dead fuel moisture model.
• Runs under Microsoft Windows operating systems

(Windows 95, 98, me, NT, 2000, and XP) and features a graphical user interface.

Notes:

Listed here are a few characteristics of FlamMap

NR406: GIS Applications in Fire Ecology and Management

Flam Map - Landscape Them es Flam Map - Landscape Them es

Elevation Slope Aspect Fuel Model Canopy Cover Canopy Height Canopy Base Height Crown Bulk Density

Required Optional

Notes:

FlamMap uses GIS data layers such as elevation, slope, aspect, fuel model, canopy cover, canopy height, canopy base height, and crown bulk density for the computation of potential fire behavior characteristics across the landscape.

NR406: GIS Applications in Fire Ecology and Management

Hazard Areas Hazard Areas

Notes:

These are two GIS maps representing hazard areas for the same landscape. The map above shows fire prone areas (xeric cover types, south and west facing aspects and steep slopes) (the simple GIS map discussed in previous slides) and the map below shows areas that are likely to have a flame length over 4 ft under certain weather and fuel moisture

• conditions. The map below is based on fire behavior modeling

in FlamMap while the map above is simply a selection of certain landscape characteristics in a GIS. Notice that the maps highlight entirely different areas. Decision makers often have a difficult time understanding how such maps are created and may be miss-led by the red color apparently representing hazard. But what hazard? How was the model created? Always question how a map was created before basing decisions on colors!

NR406: GIS Applications in Fire Ecology and Management

Hazard areas w ith structures overlay Hazard areas w ith structures overlay

Elementary Risk Map

Notes:

If the hazard of interest is risk to human development it would be appropriate to add buildings to the map – each yellow dot is a building. Maps are powerful – what do you want to show?

NR406: GIS Applications in Fire Ecology and Management

W hen producing hazard m aps: W hen producing hazard m aps:

• Correct classification of fuels is im portant for inputs

in fire behavior models

• Fuel model 8 (Closed Short Needle Conifer ) and 10

(Closed Timber Heavy DWD ) may be difficult to differentiate on imagery and on the ground, but result in very different fuel behavior

• Much information is lost when classifying detailed

land cover and structure information into broad fuel models

• Development of more detailed fuel models will

require finer scale fuel layers

Notes: