Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Development and Applications of Fire Danger Rating Systems in Southeast Asia


Published on

Presented by Dr. Michael Brady, CIFOR, 25 July 2019

Published in: Science
  • Be the first to comment

  • Be the first to like this

Development and Applications of Fire Danger Rating Systems in Southeast Asia

  1. 1. Development and Applications of Fire Danger Rating Systems in Southeast Asia Dr. Michael Brady, CIFOR, 25 July 2019
  2. 2. Early Warning Information Data Information Action Analysis & Interpretation -Fuel -Weather -Fire Hot Spot FDRS Decision Making: Analysis & Interpretation -Risk (ignition) -Priority (impacts) -Timing (spread) -Resources (control) -Fuel -Weather -Fire
  3. 3. Fire Danger • A general term used to describe conditions of the fire environment including a) ease of ignition, b) rate of spread, c) difficulty of control and d) fire impact • Indicates the ability of a fire to start, spread and do damage
  4. 4. Canadian Forest Fire Danger Rating System (CFFDRS) • FDR research initiated in 1925 • 5 FDRS versions developed since then, each building on previous System • latest CFFDRS established in 1968
  5. 5. CFFDRS Structure
  6. 6. FIRE WEATHER INDEX Different components measure different aspects of fire potential
  7. 7. Underlying Principle • Each of the behavior indices corresponds to a variable in Byram’s line fire intensity equation: I = HWR where FWI estimates: I = energy output per unit length of fire front (kw/m) BUI estimates: W = weight of available fuel (kg/m2) ISI estimates: R = rate of spread (m/min) and H = heat of combustion, (considered constant) FWI Behavior Indices The most important measure of fire behaviour is fire intensity.Fire intensity (I) represents the heat released per meter of firefront (kW/m of fire front). It is a function of (1) heat yield of fuel (kilojoules/kg), (2) amount of fuel per unit area (kg/m2) and (3) the rate of forward spread of fire front (km/h).
  8. 8. Prevention Measures • Increased public awareness activities • Step-up detection activities • Notification of relevant agencies and companies
  9. 9. Monitoring Measures • Provides daily indicators of fire hazards • Critical for planning aerial surveillance, pre- suppression activities and enforcement
  10. 10. Mitigation Measures • Position resources where more fires are expected • Determine resource requirements based on potential severity of fires • Coordinate resources of relevant agencies and companies
  11. 11. Southeast Asia FDRS Project 1999-2004 + Ongoing Updates • Expanded application of FDRS in fire prone areas of SE Asia • Enhancement of vegetation fire information and management systems in the region, to complement FDRS • Enhanced awareness and capacity of regional networks to provide early warning for anticipated fires and transboundary haze
  12. 12. A. Technical Adaptation B. FDRS Operation C. Practical Application D. Regional Networks Project Organization & Activities
  13. 13. Adaptation Activities • Model development • Calibration: • Hot spot calibration • Fire climate study • Fuel moisture and ignition studies • Definition & adjustment of fire danger class boundary • Fuel type mapping
  14. 14. FDR and Hotspots
  15. 15. 0 0 0 1 0 0 2 0 o m e t s N INTEGRATED WEATHER 01/15/2000 MISSING 01/15/2000 01/15/2000 01/15/2000 $ $ $ $ $ $ $ $ $ $ $ $ $ 1 0 3 0 0 K il e r Drought Code Sumatra, Indonesia 1994-1998 961090-DC 0 200 400 600 800 1000 1200 1400 1 27 53 79 105131 157 183 209235 261 287313 339 365 1994 1995 1996 1997 1998 1999 2000 960350-DC 0 200 400 600 800 1000 1200 1400 1 27 53 79 105 131157 183209235 261287 313339 365 1994 1995 1996 1997 1998 1999 2000 962210-DC 0 200 400 600 800 1000 1200 1400 1 27 53 79 105131 157183209 235261287 313339365 1994 1995 1996 1997 1998 1999 2000 Historical Weather Database Spatial Calculations Analysis Historical Weather Database
  16. 16. Analysis of Historical Weather Data Characterize the fire climate in terms of fire season onset, severity and duration
  17. 17. FDRS Project Office, BPPT Building Jl. M.H. Thamrin 8, Building I, 1st Floor Jakarta 10340 - Indonesia Tel/Fax : (62.21) 3190 1424 2 Monthly Drought Code Distribution - Palembang Month 0 1 2 3 4 5 6 7 8 9 10 11 12 13 DroughtCode 0 200 400 600 800 1000 FIRE CLIMATE ASSESSMENT SUMATERA, INDONESIA Guswanto, R. Field, J. Wigianto, Iqbal, Suwandi, M. Brady and J. Little Climate has been attributed as a major factor in recent fire and haze events in Sumatera Island, and the role of weather in vegetation fires in other parts of the world is well documented. This study assessed the longer-term fire weather characteristics of Sumatera Island by examining seasonal patterns in a variety of fire danger rating (FDR) indices. Components of the fire climate assessment are important to the development of fire management in South East Asia for several reasons. Fire season characterization allows fire managers to compare current FDR values against historical FDR values, improving their ability to assess the severity of the current fire danger situation. In addition, it allows fire managers to assess the expected onset, severity and duration of a fire season. These benefits in turn allow fire managers to more effectively implement smoke-prevention mechanism, such as burning permit restrictions, public warnings, fire patrols, and pre-allocation of fire-fighting resources. Here, fire season refers to a period of climatic conditions where severe burning conditions, or fire weather, are present. The relationship between fire season and large-scale phenomenon such as the El-Nino/Southern Oscillation (ENSO) is was examined. Fire climate was assessed using FDR indices, whose calculation requires a continuous record of daily weather values. An integrated historical daily weather database was constructed using data from BMG and the NCDC. Database integration included reformatting source data and applying temporal interpolation in the case of missing data. The integrated weather database was then used as input to the Spatial Fire Management System (sFMS), which uses interpolated weather surfaces constructed from weather station data to calculate FDR surfaces. Data from the calculated FDR surfaces was extracted by sampling the surfaces at a defined set of locations. Time- series techniques were applied to each sampled location to determine the seasonality of calculated historical FDR values. Based on these analyses, the typical fire climatic regions were identified. The relationship between historical FDR values and historical ENSO indicators was examined using correlation analysis at varying time-lags, with regions of strong and weak correlation being identified. Fire Weather Index System - Drought Code : Drought Code (DC) measures moisture in deep organic soils (peat) and heavier dead fuels on the surface. DC indicates potential for deep, smoldering fires. Daily DC surfaces built using daily weather grids. Cell-wise statistics calculated from daily DC grids, over: • each individual month (e.g., July 1985 Mean DC) • all months, excluding startup (JFM 1973) & 1976, for DC normal. Mean Monthly Maximum DC: • on average, how high does the Drought Code get each month? Grids stratified based on NCEPCPC ENSO classification. START PEAK END Fire Climate Assessments Goals : Determine the existence of a typical fire season or seasons in Sumatra Island and to then characterize their inter-annual and spatial variability with respect to onset, severity, and duration. Build longer-term Fire Weather Index (FWI) database. Look at seasonality, normal & extreme FWI values. Examine relationships between FWI system values and climate. Example Questions: • how does this today’s Drought Code (DC) compare to ’82 or ’97? • how bad does the DC typically get in September? • how severe can the DC get during El Nino and non-El Nino years? Drought Code Sumatera, Indonesia 1973-1998 PEAK Heavy smoke and Haze affecting communities Plantation burning Drought code of Palembang, 1973-1998 NON EL NINO CONDITION EL NINO CONDITION Median Drought Code and First Harmonics for ENSO and non -ENSO years, Palembang Station, 1994 -1998 -200 0 200 400 600 800 1000 1200 1400 0 50 100 150 200 250 300 350 Julian Date D R O U G H T C O D e MEDIAN DC ENSO FIRST HARMONIC- ENSO MEDIAN DC NON-ENSO FIRST HARMONIC-NON ENSO Combusition Threshold Extreme Drought PATTERNS OF DRY PERIODS IN SUMATRA
  18. 18. FUEL CHARACTERIZATION • Fuel Type Classification • Fuel Model Calibration: – Moisture Profile Study – Ignition Study • Fuel Mapping
  19. 19. Fuel Type Mapping
  20. 20. Electronic FDRS Daily Maps, Electronic, Automated, Multiple Stations
  21. 21. Practical Applications • Primary objective to integrate FDRS products with existing fire suppression and mobilization plans • Mobilization can become more anticipatory through early warning, paving the way for better preparedness in serious fire situations
  22. 22. Interpretation of FWI Danger Levels for Difficulty of Control and Practical Applications
  23. 23. Regional FDRS Supports the haze monitoring functions of the Regional Haze Action Plan/ASEAN Agreement on Transboundary Haze Pollution