Version: dev

FireContainment

Statistical fire containment probability model

.esm schema
1.0.0
Source
components/wildland_fire/fsim/fire_containment.esm

Description

Statistical fire containment probability model

Reference

_Statistical fire containment probability model.

This model estimates the probability of fire containment based on fire growth rate characteristics and fire duration. It represents the influence of modern fire management policy on large fire patterns.

The containment probability increases with:

  1. Lower fire growth rates (low spread intervals)
  2. Longer fire duration (more previous intervals)
  3. Non-timber fuel types (easier to suppress)

The model uses a logistic-type function: P_contain = 1 / (1 + exp(-(α₀ + α₁ × NPI + α₂ × is_high_spread + α₃ × is_timber)))

References:

  • Finney, M.A., McHugh, C.W., Grenfell, I.C., Riley, K.L., Short, K.C. (2011). A simulation of probabilistic wildfire risk components for the continental United States. Stochastic Environmental Research and Risk Assessment, 25:973–1000. DOI: 10.1007/s00477-011-0462-z (Section 2.4, Fig. 6)
  • Finney, M.A., Grenfell, I.C., McHugh, C.W. (2009). Modeling large fire containment using generalized linear mixed model analysis. For Sci 55(3):249–255.

source_ref: WildlandFire.jl@126976f2508ceacca6c486b21ae6da5b168c6f46:src/fsim.jl:139_

Parameters

NameUnitsDefaultDescription
α₀Containment model intercept (dimensionless)
α₁Containment model NPI coefficient (dimensionless)
α₂Containment model high-spread coefficient (dimensionless)
α₃Containment model timber fuel coefficient (dimensionless)
NPINumber of previous spread intervals (dimensionless)
is_high_spreadHigh spread interval indicator, 0 or 1 (dimensionless)
is_timberTimber fuel type indicator, 0 or 1 (dimensionless)
one1.0Dimensionless unity (dimensionless)

Observed

NameUnitsDefaultDescription
P_containProbability of fire containment (dimensionless)

Observed expressions

$$ P_{contain} = \frac{one}{one + e^{\left(-1\right) \cdot \left(α₀ \cdot one + α₁ \cdot NPI + α₂ \cdot is_{high\,spread} + α₃ \cdot is_{timber}\right)}} $$

Probability of fire containment (dimensionless)

Raw .esm

Raw .esm JSON (this component)
{
  "variables": {
    "α₀": {
      "type": "parameter",
      "description": "Containment model intercept (dimensionless)"
    },
    "α₁": {
      "type": "parameter",
      "description": "Containment model NPI coefficient (dimensionless)"
    },
    "α₂": {
      "type": "parameter",
      "description": "Containment model high-spread coefficient (dimensionless)"
    },
    "α₃": {
      "type": "parameter",
      "description": "Containment model timber fuel coefficient (dimensionless)"
    },
    "NPI": {
      "type": "parameter",
      "description": "Number of previous spread intervals (dimensionless)"
    },
    "is_high_spread": {
      "type": "parameter",
      "description": "High spread interval indicator, 0 or 1 (dimensionless)"
    },
    "is_timber": {
      "type": "parameter",
      "description": "Timber fuel type indicator, 0 or 1 (dimensionless)"
    },
    "one": {
      "default": 1.0,
      "type": "parameter",
      "description": "Dimensionless unity (dimensionless)"
    },
    "P_contain": {
      "type": "unknown",
      "description": "Probability of fire containment (dimensionless)"
    }
  },
  "reference": {
    "notes": "Statistical fire containment probability model.\n\nThis model estimates the probability of fire containment based on fire growth rate characteristics and fire duration. It represents the influence of modern fire management policy on large fire patterns.\n\nThe containment probability increases with:\n1. Lower fire growth rates (low spread intervals)\n2. Longer fire duration (more previous intervals)\n3. Non-timber fuel types (easier to suppress)\n\nThe model uses a logistic-type function:\n  P_contain = 1 / (1 + exp(-(α₀ + α₁ × NPI + α₂ × is_high_spread + α₃ × is_timber)))\n\nReferences:\n- Finney, M.A., McHugh, C.W., Grenfell, I.C., Riley, K.L., Short, K.C. (2011). A simulation of probabilistic wildfire risk components for the continental United States. Stochastic Environmental Research and Risk Assessment, 25:973–1000. DOI: 10.1007/s00477-011-0462-z (Section 2.4, Fig. 6)\n- Finney, M.A., Grenfell, I.C., McHugh, C.W. (2009). Modeling large fire containment using generalized linear mixed model analysis. For Sci 55(3):249–255.\n\nsource_ref: WildlandFire.jl@126976f2508ceacca6c486b21ae6da5b168c6f46:src/fsim.jl:139"
  },
  "tolerance": {
    "rel": 1e-14
  },
  "equations": [
    {
      "lhs": "P_contain",
      "rhs": {
        "op": "/",
        "args": [
          "one",
          {
            "op": "+",
            "args": [
              "one",
              {
                "op": "exp",
                "args": [
                  {
                    "op": "*",
                    "args": [
                      -1,
                      {
                        "op": "+",
                        "args": [
                          {
                            "op": "*",
                            "args": [
                              "α₀",
                              "one"
                            ]
                          },
                          {
                            "op": "*",
                            "args": [
                              "α₁",
                              "NPI"
                            ]
                          },
                          {
                            "op": "*",
                            "args": [
                              "α₂",
                              "is_high_spread"
                            ]
                          },
                          {
                            "op": "*",
                            "args": [
                              "α₃",
                              "is_timber"
                            ]
                          }
                        ]
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    }
  ],
  "tests": [],
  "analyses": []
}