Integrating fire spread patterns in fire modelling at landscape scale

被引:29
作者
Duane, Andrea [1 ,2 ]
Aquilue, Nuria [1 ,3 ]
Gil-Tena, Assu [1 ,2 ]
Brotons, Lluis [1 ,2 ,4 ]
机构
[1] CSIC CTFC CREAF, CEMFOR CTFC, InForest Joint Res Unit, Solsona 25280, Spain
[2] CREAF, Cerdanyola Del Valles 08193, Spain
[3] Univ Quebec, Ctr Etud Foret, Montreal H2X 3Y7, PQ, Canada
[4] CSIC, Cerdanyola Del Valles 08193, Spain
基金
加拿大自然科学与工程研究理事会;
关键词
Wind-driven fires; Topography-driven fires; Convective fires; Landscape fire succession models; Mediterranean ecosystems; Synoptic weather situations; SOUTHERN CALIFORNIA; WILDLAND FIRES; WILDFIRE; SIMULATION; AGE; REGIMES; DISTURBANCE; SUCCESSION; VEGETATION; DYNAMICS;
D O I
10.1016/j.envsoft.2016.10.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Fire spread modelling in landscape fire succession models needs to improve to handle uncertainty under global change processes and the resulting impact on forest systems. Linking fire spread patterns to synoptic-scale weather situations are a promising approach to simulating fire spread without finegrained weather data. Here we present MedSpread a model that evaluates the weights of five landscape factors in fire spread performance. We readjusted the factor weights for convective, topography driven and wind-driven fires (n = 123) and re-assessed each fire spread group's performance against seven other control simulations. Results show that for each of the three fire spread patterns, some landscape factors exert a higher influence on fire spread simulation than others. We also found strong evidence that separating fires by fire spread pattern improves model performances. This study shows a promising link between relevant fire weather information, fire spread and fire regime simulation under global change processes. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:219 / 231
页数:13
相关论文
共 71 条
  • [1] Simulating wildfire patterns using a small-world network model
    Adou, J. K.
    Billaud, Y.
    Brou, D. A.
    Clerc, J. -P.
    Consalvi, J. -L.
    Fuentes, A.
    Kaiss, A.
    Nmira, F.
    Porterie, B.
    Zekri, L.
    Zekri, N.
    [J]. ECOLOGICAL MODELLING, 2010, 221 (11) : 1463 - 1471
  • [2] AGUADE David M., 1998, Nimbus, V1-2, P93
  • [3] Albini F., 1976, INT30 USDA FOR SERV
  • [4] Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes
    Allen, Craig D.
    [J]. ECOSYSTEMS, 2007, 10 (05) : 797 - 808
  • [5] Anderson H E., 1983, Predicting Wind-Driven Wild Land Fire Size and Shape
  • [6] Fire modeling and information system technology
    Andrews, PL
    Queen, LP
    [J]. INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2001, 10 (3-4) : 343 - 352
  • [7] [Anonymous], 1991, INT438 USDA FOR SERV
  • [8] Forest fire propagation prediction based on overlapping DDDAS forecasts
    Artes, Tomas
    Cardil, Adrian
    Cortes, Ana
    Margalef, Tomas
    Molina, Domingo
    Pelegrin, Lucas
    Ramirez, Joaquin
    [J]. INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2015 COMPUTATIONAL SCIENCE AT THE GATES OF NATURE, 2015, 51 : 1623 - 1632
  • [9] Characterising performance of environmental models
    Bennett, Neil D.
    Croke, Barry F. W.
    Guariso, Giorgio
    Guillaume, Joseph H. A.
    Hamilton, Serena H.
    Jakeman, Anthony J.
    Marsili-Libelli, Stefano
    Newham, Lachlan T. H.
    Norton, John P.
    Perrin, Charles
    Pierce, Suzanne A.
    Robson, Barbara
    Seppelt, Ralf
    Voinov, Alexey A.
    Fath, Brian D.
    Andreassian, Vazken
    [J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2013, 40 : 1 - 20
  • [10] Modelling the effect of spatial scale and correlated fire disturbances on forest age distribution
    Boychuk, D
    Perera, AH
    TerMikaelian, MT
    Martell, DL
    Li, C
    [J]. ECOLOGICAL MODELLING, 1997, 95 (2-3) : 145 - 164