Key elements of Key elements of the National Fire the National Fire Danger Rating Danger Rating

System for South System for South AfricaAfrica

The nature of a National Fire Danger Rating System

Climate and Risk

Fire danger regions map

Daily data for region: Fuel condition Forecast and actual

weather

Fire danger model

Users in each region

Collect fire occurrence

data

Forecast and actual fire danger rating for regions

Fire danger rating table

Vel

dfire

Info

rmat

ion

Sys

tem

Communicate

Outputindex

Rating

Monitor and improve

Input region data

Monitor and improve

Monitor and improve

Climate and Risk

Fire danger regions map

Daily data for region: Fuel condition Forecast and actual

weather

Fire danger model

Users in each region

Collect fire occurrence

data

Forecast and actual fire danger rating for regions

Fire danger rating table

Vel

dfire

Info

rmat

ion

Sys

tem

Communicate

Outputindex

Rating

Monitor and improve

Input region data

Monitor and improve

Monitor and improve

Adoption of a model: Candidate Models

- McArthur Forest Model- McArthur Grassland Model- US Model- Lowveld Model

United States Model McArthur Grassland Model

McArthur Forest Model Lowveld Model

Design Principles Physical models Empirical models Empirical models Not documented

Model Complexity Complex Simple Simple Simple

Inputs Fuel models and readily available weather data

Requires weather and curing estimates. A range of methods are available

for estimating curing, some expensive, others

subjective.

Only readily available weather

data needed

Only readily available weather

data needed

Degree of User Sophistication Required

High – User needs to have understanding of

all the station parameters that are embedded within the

model

Moderate – User needs to asses curing estimates Low

Low - if applied without rainfall

correction factors, otherwise moderate

Ability to Model Green-up and Curing

Green up and curing based on modelled fuel moisture, and effects

simulated by transfer of herbaceous fuel loads to the dead fuel category

Uses curing estimates directly None None

Similarities and differences between candidate models

United States Model McArthur Grassland Model

McArthur Forest Model

Lowveld Model

Modelling of Fuel Moisture Yes No No No

Ability to deal with Fuel Loads

Yes, but currently limited to 20 standard fuel models No No No

Output Indicator Values

Burning IndexEnergy Release ComponentSpread ComponentIgnition Component

Fire Danger IndexFire Danger

Index Fire Danger Index

Ability to Deal with Daily and Seasonal Planning

High (Daily and Seasonal Planning) Low (Daily Planning only) Low (Daily

Planning only) Low (Daily Planning only)

Potential for Application of Indicator Values to different aspects of

Veldfire Management

High – Many indicator values

Moderate – Long-term simulator of drought through

the estimation of curing

Low – Only a single indicator

value

Low – Only a single indicator value

Available Software Yes – Public Domain Yes – Public Domain Yes – Public Domain

Yes – Available from Lowveld Fire Protection

Association

Use in South AfricaTested in South Africa in the

1980’s, but not currently used

Not used Not used

Lowveld Fire Protection Association, Kwa-Zulu Natal

Midlands Fire Protection Association and South

African Weather Services

Additional features embedded in software KBDI None KBDI None

• McArthur Forest ModelMcArthur Forest Model: Unable to deal with : Unable to deal with green-up and curing.green-up and curing.

• McArthur Grassland ModelMcArthur Grassland Model: Green-up and : Green-up and curing requires estimates. curing requires estimates.

• Lowveld ModelLowveld Model: Unable to deal with green-up : Unable to deal with green-up and curing and has no basis in theory.and curing and has no basis in theory.

• US NFDRS ModelUS NFDRS Model: Ability to model fuel : Ability to model fuel moisture content, model green-up and curing and moisture content, model green-up and curing and provides many indices that address different provides many indices that address different aspects of fire danger.aspects of fire danger.

Selection of a Fire Danger Rating Model

• The Act requires that the model must underpin a system that will assist in the identification of dangerous activities, and of the precautions that should be taken, for for each ratingeach rating

• Model should be able to support a range of activities related to fire management under conditions of low or moderate fire danger (e.g. being able to decide whether or not to initiate prescribed burns based on the risk of a prescribed burn becoming uncontrollable).

Support for Integrated Veldfire Management

Support for Integrated Veldfire Management

• Burning IndexBurning Index• Energy Release ComponentEnergy Release Component• Keetch-Byram Drought IndexKeetch-Byram Drought Index• Spread ComponentSpread Component• Ignition ComponentIgnition Component

Fire Danger Ratings

Classification Description of ClassificationInsignificant The fire danger is so low that no precaution is needed

Low Fires including prescribed burns may be allowed in the open air on thecondition that persons making fires take reasonable precautions against firesspreading

Moderate The fire danger is such that no fires may be allowed in the open air exceptthose that are authorised by the Chief Fire Officer of the local fire service andthose in designated fireplaces; authorised fires may include prescribed burns

High The fire danger is such that no fires may be allowed under any circumstancesin the open air

Extremely High The fire danger is such that no fires may be allowed under any circumstancesin the open air, and special emergency fire preparedness measures must beinvoked

Veldfire Risk Assessment

• A need to identify areas of uniform riskA need to identify areas of uniform risk

• RISK = Likelihood + ConsequenceRISK = Likelihood + Consequence

• Determine vegetation types for the 6 biomes in Determine vegetation types for the 6 biomes in South Africa.South Africa.

• Classified veldfire risk for each vegetation type. Classified veldfire risk for each vegetation type.

• Overlay municipality boundaries over Overlay municipality boundaries over vegetation type map.vegetation type map.

Likelihood of FireVegetation Type Vegetation Type Likelihood of FireLikelihood of Fire

ForestForest Rare: 1 in 100 yearsRare: 1 in 100 years

ThicketThicket Rare: 1 in 100 yearRare: 1 in 100 year

Arid WoodlandArid Woodland Possible: 1 in 10 yearsPossible: 1 in 10 yearsMoist WoodlandMoist Woodland Likely: 1 in 5 yearsLikely: 1 in 5 yearsSparse Arid WoodlandSparse Arid Woodland Rare: 1 in 100 yearsRare: 1 in 100 years

Succulent KarooSucculent Karoo Rare: 1 in 100 yearsRare: 1 in 100 years

Nama KarooNama Karoo Unlikely: 1 in 20 yearsUnlikely: 1 in 20 years

Grassy Nama KarooGrassy Nama Karoo Possible: 1 in 10 yearsPossible: 1 in 10 years

Coastal GrasslandCoastal Grassland Likely: 1 in 5 yearsLikely: 1 in 5 years

Sour GrasslandSour Grassland Almost certain: 1 in 2 yearsAlmost certain: 1 in 2 years

Consequence of Fire (Australian Std. 1999)

Level of Consequence Social, Economic & Environmental Vulnerability Criteria

1. Catastrophic Death, depressed economy, permanent loss of species or habitats

2. Major Extensive injuries, serious financial loss, habitat destruction

3. Moderate Require medical treatment, damage to property, serious impact on the environment

4. Minor Minor injuries, minor financial loss, discernable environmental impacts

5. Insignificant No injuries, no damage to property, minor impact on the environment

Levels of Risk (Australian Std. 1999)

 

Likelihood Rating

Insignificant

H

M HRare L L L

H E

Unlikely L L M H E

Possible L M H

E

Likely L M H E E

Almost certain M M E

Consequence Rating

Minor Moderate Major Catastrophic

Risk Classification of MunicipalitiesFire danger

regionName of

municipalityWildland Fire Risk

Level

Cannon Rocks to Kei River

Ndlambe H

Great Kei E

Buffalo City E

Ngqushwa E

Plettenberg Bay to Cannon Rocks

Sunday's River Valley L

Kouga H

Kou-Kamma H

Fire Danger Regions of South Africa

• The Act requires the country to be The Act requires the country to be divided into fire danger regions. divided into fire danger regions.

• 53 weather forecasting districts collapsed 53 weather forecasting districts collapsed into 42 fire danger regions on the basis of into 42 fire danger regions on the basis of similar levels of risk.similar levels of risk.

• Each region is to be such that the fire Each region is to be such that the fire danger is sufficiently uniform to allow for danger is sufficiently uniform to allow for a single rating which is meaningful for the a single rating which is meaningful for the entire region.entire region.

Fuel models to be used in each region

Fuel model B - California Chaparral:Fuel model B - California Chaparral: MMany of the any of the fuel model properties embedded within the fuel fuel model properties embedded within the fuel model adequately represent the fynbos vegetation model adequately represent the fynbos vegetation characteristics found in South Africa.characteristics found in South Africa.

Fuel Model C - Pine-Grass Savanna:Fuel Model C - Pine-Grass Savanna: GGrasslands rasslands are a predominant fuel complex in South Africa, are a predominant fuel complex in South Africa, and these grasses experience cycles of green-up and these grasses experience cycles of green-up and curing. Fuel model C has a significant load of and curing. Fuel model C has a significant load of fine dead and live herbaceous (grass) fuel, and as fine dead and live herbaceous (grass) fuel, and as such it should simulate green-up and curing such it should simulate green-up and curing through the year.through the year.

Fuel model allocation to fire danger regions

Fire Danger Region Dominant Vegetation Type

US Fuel Model

Cannon Rocks to Kei River Moist Woodland Pine-Grass Savanna

Eastern Midlands Sour Grassland Pine-Grass Savanna

Northern Interior Grassland Pine-Grass Savanna

Plettenberg Bay to Cannon Rocks

Fynbos California Chaparral

South East Karoo Fynbos California Chaparral

South Interior Midlands Sour Grassland Pine-Grass Savanna