The Wildland–Urban Interface (WUI): From Simple Models to Mitigating Fire Risk Michael Ghil Ecole Normale Supérieure, Paris, and University of California, Los Angeles V. Spyratos, ENS & ENGREF; P. Bourgeron, INSTAAR, CU, Boulder; and C. Lampin & M. Jappiot, CEMAGREF, Aix-en-Provence Please see these sites for further details:

Motivation The WUI occupies about 10% of the surface and contains about 40% of the houses in the conterminous U.S. Fires have caused huge damages in the WUI in the Western U.S., as well as Southern Europe this past summer and fall. Further spreading of construction into (semi-)pristine vegetated areas. Global change seems to increase dryness in the areas of interest. Actual joint, interactive modeling of housing and vegetation seems to be novel and interesting. Simple, “toy” models can provide useful ideas. The hierarchical modeling approach allows one to go back-and-forth between “toy” (conceptual) and detailed (“realistic”) models, and between models and data. The WUI occupies about 10% of the surface and contains about 40% of the houses in the conterminous U.S. Fires have caused huge damages in the WUI in the Western U.S., as well as Southern Europe this past summer and fall. Further spreading of construction into (semi-)pristine vegetated areas. Global change seems to increase dryness in the areas of interest. Actual joint, interactive modeling of housing and vegetation seems to be novel and interesting. Simple, “toy” models can provide useful ideas. The hierarchical modeling approach allows one to go back-and-forth between “toy” (conceptual) and detailed (“realistic”) models, and between models and data.

Some spectacular WUI fires A house is threatened by a wall of flames from a wild fire west of the Missionary Ridge fire, north of Durango, Colorado (AP/Charlie Riedel). As Colorado burns in the summer of 2002, flames from a new fire loom menacingly behind a mountain home near Durango (Barry Gutierrez)

A toy model of the WUI Panels (a, b, c) – the central cell is ignited: (a)it’s a tree stand; (b)it’s a flammable house; or (c)It’s a fireproofed house. Panels (a, b, c) – the central cell is ignited: (a)it’s a tree stand; (b)it’s a flammable house; or (c)It’s a fireproofed house. A lattice model with nearest-neighbor interactions, already used in forest-fire modeling: novelty is including the houses. Panels (d, e) – example of fire spreading over the landscape: red cells are on fire, black cells are burnt; green and yellow cells are unburnt trees and houses.

Fire-spread probability Mean fire size S as a function of p, the vegetation’s probability of fire spread, for different house densities d: d 0 indicates fireproofed houses only, d 1 flammable houses only. Mean fire size S as a function of p, the vegetation’s probability of fire spread, for different house densities d: d 0 indicates fireproofed houses only, d 1 flammable houses only.

Fire proofing vs. Fuel treatment Regime diagram of mean fire size S as a function of p and d (d 0 or d 1 ): (a) note narrow transition zone between widespread and limited fire size; and (b) higher efficiency of fireproofing of houses.

Application to Mediterranean landscapes Fire distribution over 2 days in Europe: GIS tool

Contexte (6/8) Urbanization in a forested area, in the South of France Motivations are similar to Western U.S.

Methodology : Combine 2 criteria Clustered Isolated Diffuse Structure of habitat Structure of vegetation Continuous, dense Discontinuous, sparse Absent, other

Density of fire outbreaks per 1000 ha over the period 1997–2006 Cemagref photos C. Lampin, Ph. D. Thesis 2007 Site of Aix Source: fire data ONF

Some conclusions &/or questions What do we know? It’s getting warmer and drier, which favors forest fires. Houses spread, which puts more people & goods at risk. So, we should try to improve fire protection. Fire proofing entire communities seems to help, both the community and the vegetation in which it is immersed. What do we know? It’s getting warmer and drier, which favors forest fires. Houses spread, which puts more people & goods at risk. So, we should try to improve fire protection. Fire proofing entire communities seems to help, both the community and the vegetation in which it is immersed. What do we know less well? How, exactly, do houses interact with forest fires? How does climatic change affect this interaction? What to do? Better understand the system and its forcings. Use a full hierarchy of forest-fire and climate models to do so.

Some references  Malamud, B.D., G. Morein, D. L. Turcotte, 1998: Forest fires: An example of self-organized critical behavior, Science, 281, 1840–1842.  Hargrove, W.W., R.H. Gardner, M.G. Turner, W.H. Romme, D.G. Despain, 2000: Simulating fire pattern in heterogeneous landscapes, Ecological Modelling, 135, pp 243–263.  Spyratos, V., P. Bourgeron, and M. Ghil, 2007: Development at the wildland–urban interface and the mitigation of forest-fire risks, Proc. Natl. Acad. Sci. USA, 104: 14272–14276; doi: /pnas  Malamud, B.D., G. Morein, D. L. Turcotte, 1998: Forest fires: An example of self-organized critical behavior, Science, 281, 1840–1842.  Hargrove, W.W., R.H. Gardner, M.G. Turner, W.H. Romme, D.G. Despain, 2000: Simulating fire pattern in heterogeneous landscapes, Ecological Modelling, 135, pp 243–263.  Spyratos, V., P. Bourgeron, and M. Ghil, 2007: Development at the wildland–urban interface and the mitigation of forest-fire risks, Proc. Natl. Acad. Sci. USA, 104: 14272–14276; doi: /pnas