modeling

Comprehensive assessment of ecological change after fires have burned forests and rangelands is important if we are to understand, predict and measure fire effects. We highlight the challenges in effective assessment of fire and burn severity in the field and using both remote sensing and simulation models.

Fire-prone landscapes are not well studied as coupled human and natural systems (CHANS) and present many challengesfor understanding and promoting adaptive behaviors and institutions. Here, we explore how heterogeneity, feedbacks, and externaldrivers in this type of natural hazard system can lead to complexity and can limit the development of more adaptive approaches topolicy and management.

As carbon modeling tools become more comprehensive, spatialdata are needed to improve quantitative maps of carbon emissions from fire.The Wildland Fire Emissions Information System (WFEIS) provides mappedestimates of carbon emissions from historical forest fires in the United Statesthrough a web browser.

Fuel treatment effectiveness is often evaluated with fire behavior modeling systems that use fuel models to generate fire behavior outputs. How surface fuels are assigned,either using one of the 53 stylized fuel models or developing custom fuel models, can affect predicted fire behavior.

Current practices for measuring high heat flux in scenarios such as wildland forest fires use expensive, thermopile-based sensors, coupled with mathematical models based on a semi-infinite-length scale. Although these sensors are acceptable for experimental testing in laboratories, high error rates or the need for water cooling limits their applications in field experiments.

High temporal resolution information on burnt area is needed to improve fire behaviour and emissions models. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) thermal anomaly and active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the timing of burnt area for 16 large wildland fires.

Fuel consumption specifies the amount of vegetative biomass consumed during wildland fire. It is a two-stage process of pyrolysis and combustion that occurs simultaneously and at different rates depending on the characteristics and condition of the fuel, weather, topography, and in the case of prescribed fire, ignition rate and pattern.

Given that resource managers rely on computer simulation models when it is difficult or expensive to obtain vital information directly, it is important to evaluate how well a particular model satisfies applications for which it is designed. The Forest Vegetation Simulator (FVS) is used widely for forest management in the US, and its scope and complexity continue to increase.

Fire behavior modeling and geospatial analyses can provide tremendous insight for land managers as they grapple with the complex problems frequently encountered in wildfire risk assessments and fire and fuels management planning.

The Rothermel surface fire spread model includes a wind speed limit, above which predicted rate of spread is constant. Complete derivation of the wind limit as a function of reaction intensity is given, along with an alternate result based on a changed assumption. Evidence indicates that both the original and the revised wind limits are too restrictive.