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Environmental Modeling Integration of GIS with Env Models

Discover how GIS data and meteorological models can predict fire potential in San Jacinto Mountain, Southern California, by integrating topographic and weather databases. Implement diagnostic wind and slope-wind interaction fire models for accurate predictions.

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Environmental Modeling Integration of GIS with Env Models

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  1. Environmental Modeling Integration of GIS with Env Models

  2. 1. Issue • Predict fire potential in San Jacinto Mountain, Southern California • using GIS data and meteorological data and • meteorological models Zack, J.A. and R.A. Minnich, 1991. Integration of geographic information systems with a diagnostic wind field model for fire management. Forest Science, 37(2): 560-573.

  3. 1. Causal factors of wildfire • Hot and dry weather - high temperature and low humidity • Windy - high wind speed and certain wind direction • Fuels - dry grasses and shrubs

  4. 2. Tasks • Find topographic and weather databases • Use GIS and weather data as input for a diagnostic wind model to estimate surface wind field • Combine output of the wind model and slope as input for a slope-wind interaction fire model to estimate fire potential • Use GIS to display model results

  5. 3. Model I A diagnostic wind field model: KRISSY Input (1) 3D topography, (2) vertical profile of horizontal wind speed and direction, (3) synoptic-scale pressure gradient, and (4) inverse distance squared interpolation To estimate wind direction and speed for surface grids and above surface grids

  6. 4. Data • Surface: wind speed wind direction temperature (21 sites) 1:24,000 DEM • Upper air: 1 vertical profile of wind and temperature

  7. 5. GIS Processes • Re-sample DEM to 150m resolution • Attach locations to elevation and weather data for KRISSY

  8. 6. Model I Again Model constraints: - Concordance with surface and upper air observations - Laws of physics

  9. 6. Model I .. • Output • Convert model output in GIS: elevation, wind direction, wind speed, E-W, N-S, and vertical component of wind • Prepare slope angle and aspect for the second model

  10. 7. Model II • Slope-Wind Interaction Fire Model (SWIF) • Fire spread rates increase up-slopes and change with slope aspect • SWIFi,j = Vi,j {1+[(sin Si,j)0.5* (cos (i,j-i,j))]} Vi,j -wind speed (estimated by KRISSY) Si,j -slope angle (degree) i,j - wind direction (estimated by KRISSY) i,j -slope aspect

  11. 7. Model II.. 45~1350(e) vs. 2250~3150(w) -450~450(n) vs.1350~2250(s) Sin0 = 0 Cos0 = 1 Sin270 = -1 Cos270 = 0 Sin90 = 1 Cos90 = 0 3. 4. Aspect is a circular variable. To differentiate its circular values, divide it into e-w|n-s, or use sin or cos. Sin180 = 0 Cos180 = -1

  12. 7. GIS Process II • Display fire potential using a set of graduated point symbols

  13. 8. Possible Error Sources • Resampling terrain data • Surface wind observation • Spatial distribution of the wind observation

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