Fuels and fire behavior

1
Fuels and fire behavior in the Central Hardwoods
Fire Behavior and Effects in the Central
Hardwoods
Matthew Dickinson Ecologist
Anthony Bova Physical Scientist
Northern Research Station US Forest Service
Forestry Sciences Lab Delaware, Ohio 43015 Tele
740-368-0100
2
Central Hardwoods
Major US Forest type characterized by
oak dominance Created/maintained by cultural
burning 75 years with limited fires
USFS and USGS, 2003
3
(Recent) number of fires in North Central and
Northeastern US (modified from Haines 1975)
HIAWATHA
HURON-MANISTEE
SUPERIOR
OTTAWA
WHITE MOUNTAIN
CHIPPEWA
CHEQUAMEGON
GREEN MOUNTAIN
50
10
ALLEGHENY
NICOLET
50
10
REGION
MARK TWAIN
50
50
10
10
MONONGAHELA
WAYNE-HOOSIER
SHAWNEE
CLARK
Current fire Dormant season (esp. spring) fires
dominate numerically/area burned Historical fire
More growing season burning?
4
Forest Change in the Central Hardwoods After Fire
Suppression Eastern greater canopy closure,
transition from oak/hickory to mesic
spp. Western greater canopy closure, pine to
oak transition
From Sutherland and Yaussy
5
Fire Behavior and Effects

• General themes
• Fire behavior and effects in Central Hardwoods
  forests
• Process-response approach wherein mechanistic
  models are used as much as possible so that
  generality of resulting tools (e.g., geographic,
  taxonomic) is maximized.

Fire behavior on hilly, hardwood
landscapes Inputs to fire models (fuel
loading/moisture) Landscape hydrological/ecosystem
process modeling Regional fuel moisture
modeling Fire monitoring technology Remote
sensing In-fire sensors
Process
Fire Effects Tree injury and mortality FIRESTEM
development Stem heating Thermal
tolerance Effects of smoke on Indiana
bats Emissions, transport, behavior, and
toxicology Smoke Data-based training Smoke
Mgmt Plans for OH and KY
Process
6
Fire Model Inputs HydroEcological Process
Modeling
Uniform
Maximum variance
Modeled 10-day litter dry-down
Problem Modeling fire behavior over central
hardwoods landscapes for research management
requires model inputs over Appalachian
topography, information that are limiting.
Solution We have focused on fuel loading and
fuel moisture dynamics driven by hydrologic and
ecosystem processes, adding a fire module to
RHESSys (the Regional HydroEcological Simulation
System). Outcome RHESSys is widely used and the
fire module will open new avenues for
application. Next step is to apply over large
landscapes (// processing). Cooperators FFS,
University of North Carolina
Uniform
Tony Randolph, UNC
7
Fuel Moisture (cont.) need a hardwoods fuel
moisture model

• Modified Canadian fine fuel moisture (FFM) model
• Fuel bed temperature and RH affected by wind and
  radiation (important in dormant-season forest)
• FFM OK for L-layer (upper litter layer) but
  F-layer (gt1 yr old) dries more slowly problem
  for smoke modeling

8
Fuel production Targets for modeling A
productivity (site) index based on soil
moisture and energy
Leaf Area Index (? litter fall)
9
EAMC fuel moisture and fire spread predictions
Fall dry-down (Canadian FFM)
OH
WV
KY
VA
Problem Fire managers have limited access to
fuel moisture predictions (and other fire model
input data) for short-range planning and for
running models. Solution As an interim step,
we have worked with EAMC to add a fuel moisture
module to their suite of products. Outcome
Hourly, 3-day Web-based predictions are available
for use/feedback by managers through EAMC.
Enhancements spot WX predictions, FarSite
layers. Cooperator Eastern Area Modeling
Consortium
10
Calibration
Monitoring Fires

• Remote Sensing from the Air
• WASP Wildfire Airborne Sensor Program from
  Rochester Institute of Technology (RIT)
• 3-band infrared (IR) camera Visible camera
• Image (right) indicates surface fire
  intensity/severity of VFEF burn in 2004. Image is
  time-integration of 10 flyovers. Highest
  intensities (bright areas) are near ignition
  lines.
• WASP output will improve fire-spread and
  fire-effects models used by land managers.

Problem Ecologists and Forest Managers need
various and better devices and methods to monitor
fires. Solution Remote sensing via Wildfire
Airborne Sensing Project (WASP) In-fire
deployment of inexpensive weather/fire monitoring
stations and thermocouple probes. Outcome WASP
images allow us to quantify and visualize fire
behavior and fuel consumption (above right).
In-fire devices can be calibrated to fire
characteristics, such as fuel consumption (right)
and intensity. These calibrations can be used by
anyone using these devices to quantify surface
fire behavior. Cooperators Rochester Institute
of Technology, US Fish Wildlife, USFS Southern
Research Station.
and on the Ground

• Thermocouple probes positioned vertically in
  prescribed and experimental fires.
• Time-integrated thermocouple probe temperatures
  can be calibrated to consumed fuel loading in
  surface fires (see plot on right).
• Rate of temperature change can be calibrated to
  fire line intensity.
• Inexpensive weather stations w/ IR sensors (RIT)
  stationed in prescribed burns, giving wind speed
  and direction, air temperature and heat release
  per unit area.
• Both devices allow inexpensive monitoring of
  surface fires and calibration of airborne images.
  Fore example, there was 100 agreement between
  airborne images (above right) and ground
  monitoring of unburned areas.

WASP image indicating surface fire
intensity/severity of VFEF burn in 2004. Image is
time-integration of 10 flyovers. Highest
intensities (bright areas) are near ignition
lines.
11
Burn fraction Ohio hardwood forest
12
Calibrating Aerial IR Imagery for Fuel
Consumption and Heat Release (?Flame
Lengths) (for Indiana bat and smoke studies,
below) Goal map fuel consumption and heat
release rates for landscape-scale prescribed
fires. Method Calibrate IR flux leaving ground
with fire behavior data (fuel consumption and
heat release rates per unit fireline and area)
both in test burns and prescribed fires.
13
Rapid Deploy probe
Monitoring Fires

• Remote Sensing from the Air
• WASP Wildfire Airborne Sensor Program from
  Rochester Institute of Technology (RIT)
• 3-band infrared (IR) camera Visible camera
• Image (right) indicates surface fire
  intensity/severity of VFEF burn in 2004. Image is
  time-integration of 10 flyovers. Highest
  intensities (bright areas) are near ignition
  lines.
• WASP output will improve fire-spread and
  fire-effects models used by land managers.

Problem Ecologists and Forest Managers need
various and better devices and methods to monitor
fires. Solution Remote sensing via Wildfire
Airborne Sensing Project (WASP) In-fire
deployment of inexpensive weather/fire monitoring
stations and thermocouple probes. Outcome WASP
images allow us to quantify and visualize fire
behavior and fuel consumption (above right).
In-fire devices can be calibrated to fire
characteristics, such as fuel consumption (right)
and intensity. These calibrations can be used by
anyone using these devices to quantify surface
fire behavior. Cooperators Rochester Institute
of Technology, US Fish Wildlife (Tim Hepola),
USFS Southern Research Station.
Thermocouple probe and shielded logger.
and on the Ground

• Thermocouple probes positioned vertically in
  prescribed and experimental fires.
• Time-integrated thermocouple probe temperatures
  can be calibrated to consumed fuel loading in
  surface fires (see plot on right).
• Rate of temperature change can be calibrated to
  fire line intensity.
• Inexpensive weather stations w/ IR sensors (RIT)
  stationed in prescribed burns, giving wind speed
  and direction, air temperature and heat release
  per unit area.
• Both devices allow inexpensive monitoring of
  surface fires and calibration of airborne images.
  Fore example, there was 100 agreement between
  airborne images (above right) and ground
  monitoring of unburned areas.

Time-integrated thermocouple probe temperatures
can be experimentally calibrated to consumed
fuel loading in surface fires.
14
Fire Behavior and Effects
Fire behavior on hilly, hardwood
landscapes Inputs to fire models Landscape
hydrological/ecosystem process modeling
Regional fuel moisture modeling Fire monitoring
technology Remote sensing In-fire sensors
Fire Effects Tree injury and mortality FIRESTEM
development Stem heating Thermal
tolerance Effects of smoke on Indiana
bats Emissions, transport, behavior, and
toxicology Smoke Data-based training Smoke
Mgmt Plans for OH and KY
15
Tree Injury Mortality

• Problem Statistical models for a handful of
  species are all that are available for predicting
  tree injury and mortality. Hinders prescribed
  burn planning.
• Solution Develop general approaches to injury
  and mortality based on the processes by which
  trees are injured and die.
• Experiments relating fire behavior to necrosis in
  tree tissues were performed from 2002-2004.
• Quantification of thermal tolerance of live
  tissues.
• Outcome Results have been incorporated into
  FIRESTEM, a physically based mortality model
  (www.firelab.org), under development for
  management applications (looking for more funding
  to add species).
• Cooperators Missoula Fires Sciences Laboratory,
  University of Utah

Total thermal energy imparted to tree boles
correlates closely with area (depth) of necrosis
in stem (Bova and Dickinson 2005 Canadian Journal
Forest Resreach).
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Tree Injury Mortality (cont).

• Problem Statistical models for a handful of
  species are all that are available for predicting
  tree injury and mortality. Hinders prescribed
  burn planning.
• Solution Develop general approaches to injury
  and mortality based on the processes by which
  trees are injured and die.
• Experiments relating fire behavior to necrosis in
  tree tissues were performed from 2002-2004.
• Quantification of thermal tolerance of live
  tissues.
• Outcome Results have been incorporated into
  FIRESTEM, a physically based mortality model
  (www.firelab.org), under development for
  management applications. Windows-based version
  available including red maple and chestnut oak.
• Cooperators Missoula Fires Sciences Laboratory,
  University of Utah

Example application knowing fire behavior and
bark thickness, one can predict injury.
17

• Fire Effects on Endangered Indiana Bats
• Problem Endangered bats constrain state and
  federal burn programs yet there is next to
  nothing known about direct effects of burning on
  bats.
• Solution Model injury and mortality in typical
  prescribed burns and monitor bat behavior during
  and after landscape-scale fires.
• Outcomes
• Better understanding of risks of burning for
  endangered Indiana bats.
• Fuel consumption and smoke production data for
  regional Smoke Management Plans
• Workshops for state and federal managers

Roost characteristics (Mike Lacki, UK)
Smoke production and transport model and
data (Val Young, OU Bob Kremens, RIT EAMC and
collaborators)
Bat behavior (Mike Lacki, UK)
Mixing of smoke Into roosts (Tony Bova, USFS)
Bat physiology and toxicology (Jim Norris, Norris
Consulting)
Predicted bat injury mortality over
fire scenarios
18

• Fuel Consumption and Smoke Emissions From
  Landscape-Scale Burns in Eastern Hardwoods
• (linked with Indiana bat project)
• Problem Smoke management is becoming a central
  issue in developing and maintaining burning
  programs in the eastern US, yet smoke production
  models for hardwoods are based on few to no data
  and are highly biased (Mike Bowden, personal
  communication).
• Solutions and Outcomes
• Develop tools for estimating fuel consumption and
  smoke production from landscape-scale prescribed
  burns (and collect preliminary data for model
  development).
• Data-based training on emissions and smoke
  management
• Develop Smoke Management Plans for Ohio and
  Kentucky (part of a national, mandated process).
• Customers Ohio EPA, Ohio Department of Natural
  Resources, Daniel Boone NF, Wayne NF, Fire and
  Aviation Management (R8 R9).
• Cooperators Rochester Institute of Technology,
  Pacific NW Research Station, Smoke Management
  Staff for R8 and R9.