1. \(1984\) The 1978 National Fire-Danger Rating System: technical documentation

  2. \(1985\) The national fire-danger rating system: basic equations

  3. \(1988\) 1988 Revisions to the 1978 National Fire-Danger Rating System

  4. \(1989\) Canadian Forest Fire Danger Rating System: An Overview

  5. \(1998\) Bushfire risk at the urban interface estimated from historical weather records: consequences for the use of prescribed fire in the Sydney region of south-eastern Australia

    Applies the McArthur FFWI to bushfires in Australia. Applied corrective terms for slope and windspeed. There is a strong focus on WUI. Evidence shows that results might be highly variable. Tradeoff between prescribed burning and florisitc diversity.

  6. \(1999\) incorporating a gis model of ecological need into fire management planning

    Applied the FRID to measure the chance that a fire comes to the location. It is a balancing of the time since last fire and theaverage return interval for the vegetation class. This gives a conservative estimate about the percentable of the average interval that has been considered. Assumes that a conservative estimate is the most use and that the return time for a vegetation class is homogeneous.

  7. \(2002\) Information systems in support of wildland fire management decision making in Canada

  8. \(2002\) Introducing wildfire into forest management planning: towards a conceptual approach

    Provides a hierarchical structure of importance to features (connection to graded approach?).

    1. Classification into homogeneous information groups/levels
    2. Accumulative "means-to-objectives" relationshipos
    3. Interdependencies among factors
    4. Hierarchical evaluation starting from the more-detailsed to the less-detailed factors, and eventual evaluation of the whole function
    5. Open-ended strucutre, since additional factors can be included as needed
    • Level 1: where an ultimate evaluation is based
    • Level 2: Entities of homogeneous information
    • Level 3: Primary factors of analysis

    Gives the basis of information system, mathematical modeling, DSS (via cost-benefit analysis)

  9. \(2006\) Prescribed burn documentation and fire danger ratings: A case study

    The 1983 Ram Mountain prescribed fire was reassessed with modern (for their time) FWI methodology and historical data. They demonstate that various data input errors lead to differences in calculation. Not a very impressive paper, but it shows validation of some of the oldest examples of the FWI.

  10. \(2009\) A simple index for assessing fire danger rating

    Inspired by FFWI and GFDI, this paper introduces another index F. This measure takign the ratio of the windspeed over a moisture measure. between 0.87-0.98 correlation with the standard measures.

  11. \(2011\) Wildfires and the Canadian Forest Fire Weather Index system for the Daxing'anling region of China

    The application of the FWI system to a specific region of China. The reasoning for this is a lack of traing for local fire personale. This work shows that the work in Canada is easily translatable to the work done in other countries. They do comment, however, that they do need to localize some of the data.

  12. \(2017\) cffdrs: an R package for the Canadian Forest Fire Danger Rating System

  13. \(2017\) A ranking system for prescribed burn prioritization in Table Mountain National Park, South Africa

    Created a ranking of locations to prioritize off a purely heirarchical rating. Purely a recommendation paper; and I guess showing off a way of classifying.

    1. Ecological: Veld age, Vegetation type status, Area susceptible
    2. Management: Access, Water availability, Fire breaks
    3. Infrastructure: Infrastructure flammability
    4. Tourism: Human safety and impacts to income
    5. Invasive Alien species: Alien plant management, Alien plant biomass
    6. WUI: Urban Edge
    7. Heritage: Heritage sites

  14. \(2024\) Live trial performance of the Australian Fire Danger Rating System – Research Prototype

    Fire danger started in 1930s with 'hazard sticks`. This paper provides notes on a live pres of the AFDRS. Their results are compared to expert opinions. The system is make up of eight parts:

    1. Forest
    2. Grassland
    3. Northern Grassland (Savanna)
    4. Spinifex
    5. Mallee-Heath
    6. Shrubland
    7. Buttongrass
    8. Pine

    This most recent rendition had difficulties with complexity, as data collection for the sources and analysis were very time consuming and multi-faceted.

  15. \(2023\) Introduction to the Australian Fire Danger Rating System

    AFDRS was launched in 2022, after about three decades of no substantial work. Most work from 1974-2022 was based (and still is based) on the McArthur metrics. Changes were made to the system in 2009, but it did not stand up to the substantial shift needed with changing landscapes.

    Requirement for an improved fire danger rating system in Australia

    1. Rating definitions are based on operational response, potential for impact and observable characteristics of fire incidents
    2. Modular and supports continuous improvement
    3. Supports incremental investment to address weakness
    4. Based on fire behaviour calculations
    5. Uses the best available weather and fuel data
    6. Suitable for use at a variety of time and space scales
    7. Suitable for consistent and standardised use across the country
    8. Communicates messages to users in a clear and actionable way
    9. Simple to use but makes detail available when it is needed
    10. Includes fire behaviour, ignition likelihood, suppression capacity and potential impacts.

Writing

In the world of wildfire risk assessment, there three main players, Canada, the US, and Australia.

The Canadian Forest Fire Danger Rating System (CFFDRS) was developed in 1989, which built off the FWI system form the 1987. A full history can be seen in [19, 89]{.spurious-link target=“19, 89”}. The CFFDRS includes the subsystems of FWI and FBP. The FWI is further made up of moisture, wind, and drought information to create a numerical rating of fire intensity, and itself is touted as a stand-alone general index of fire danger. The FWI information is fed into FBP to predict how fire will spread. Similarly, FWI information is passed to the Fire Occurrence Prediction System to say where fires will start. This information is gathered together to form a fundamental rating system that is suitable to be injested into larger systems. One such system that serves a front end DSS for CFFDRS is the W.I.S.E. project, previously the Prometheus project, hosted by the REDapp development team with the endorsement of the Canadian Interagency Forest Fire Centre.