Simulation of long-term landscape-level fuel treatment effects on large wildfires

2007 ◽  
Vol 16 (6) ◽  
pp. 712 ◽  
Author(s):  
Mark A. Finney ◽  
Rob C. Seli ◽  
Charles W. McHugh ◽  
Alan A. Ager ◽  
Bernhard Bahro ◽  
...  
Keyword(s):  
Prescribed Burning ◽  
Treatment Strategies ◽  
Dynamics Simulation ◽  
Fire Growth ◽  
Fuel Treatments ◽  
Fuel Treatment ◽  
Blue Mountains ◽  
Fuel Model ◽  
Treatment Optimisation ◽  
Large Fires

A simulation system was developed to explore how fuel treatments placed in topologically random and optimal spatial patterns affect the growth and behaviour of large fires when implemented at different rates over the course of five decades. The system consisted of a forest and fuel dynamics simulation module (Forest Vegetation Simulator, FVS), logic for deriving fuel model dynamics from FVS output, a spatial fuel treatment optimisation program, and a spatial fire growth and behaviour model to evaluate the performance of the treatments in modifying large fire growth. Simulations were performed for three study areas: Sanders County in western Montana, the Stanislaus National Forest in California, and the Blue Mountains in south-eastern Washington. For different spatial treatment strategies, the results illustrated that the rate of fuel treatment (percentage of land area treated per decade) competes against the rates of fuel recovery to determine how fuel treatments contribute to multidecade cumulative impacts on the response variables. Using fuel treatment prescriptions that simulate thinning and prescribed burning, fuel treatment arrangements that are optimal in disrupting the growth of large fires require at least 1 to 2% of the landscape to be treated each year. Randomly arranged units with the same treatment prescriptions require about twice that rate to produce the same fire growth reduction. The results also show that the topological fuel treatment optimisation tends to balance maintenance of previous units with treatment of new units. For example, with 2% landscape treatment annually, fewer than 5% of the units received three or more treatments in five decades with most being treated only once or twice and ~35% remaining untreated after five decades.

A computational method for optimising fuel treatment locations

2007 ◽  
Vol 16 (6) ◽  
pp. 702 ◽  
Author(s):  
Mark A. Finney
Keyword(s):  
Fire Spread ◽  
Time Algorithm ◽  
Computational Method ◽  
Fire Growth ◽  
Spread Rate ◽  
Fuel Treatment ◽  
Large Fires ◽  
Random Patterns ◽  
In Fire ◽  
Weather Scenario

Modelling and experiments have suggested that spatial fuel treatment patterns can influence the movement of large fires. On simple theoretical landscapes consisting of two fuel types (treated and untreated), optimal patterns can be analytically derived that disrupt fire growth efficiently (i.e. with less area treated than random patterns). Although conceptually simple, the application of these theories to actual landscapes is made difficult by heterogeneity (fuels, weather, and topography). Here a computational method is described for heterogeneous landscapes that identifies efficient fuel treatment units and patterns for a selected fire weather scenario. The method requires input of two sets of spatial input data: (1) the current fuel conditions; and (2) the potential fuel conditions after a treatment is conducted (if treatment is permitted in a particular location). The contrast in fire spread rate between the two landscapes under the weather scenario conditions indicates where treatments are effective at delaying the growth of fires. Fire growth from the upwind edge of the landscape is then computed using a minimum travel time algorithm. This identifies major fire travel routes (areas needing treatment) and their intersections with the areas where treatments occurred and reduced the spread rate (opportunity for treatment). These zones of treatment ‘need and opportunity’ are iteratively delineated by contiguous patches of raster cells up to a user-supplied constraint on percentage of land area to be treated. This algorithm is demonstrated for simple and for complex landscapes.

scholarly journals Understanding the Impact of Different Landscape-Level Fuel Management Strategies on Wildfire Hazard in Central Portugal

Forests ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 522
Author(s):  
Akli Benali ◽  
Ana C. L. Sá ◽  
João Pinho ◽  
Paulo M. Fernandes ◽  
José M. C. Pereira
Keyword(s):  
Management Strategies ◽  
Treatment Strategies ◽  
Fire Season ◽  
Burned Area ◽  
Treatment Area ◽  
Fuel Treatment ◽  
The North ◽  
Wildfire Hazard ◽  
Central Portugal ◽  
The Impact

The extreme 2017 fire season in Portugal led to widespread recognition of the need for a paradigm shift in forest and wildfire management. We focused our study on Alvares, a parish in central Portugal located in a fire-prone area, which had 60% of its area burned in 2017. We evaluated how different fuel treatment strategies may reduce wildfire hazard in Alvares through (i) a fuel break network with different extents corresponding to different levels of priority and (ii) random fuel treatments resulting from a potential increase in stand-level management intensity. To assess this, we developed a stochastic wildfire simulation system (FUNC-SIM) that integrates uncertainties in fuel distribution over the landscape. If the landscape remains unchanged, Alvares will have large burn probabilities in the north, northeast and center-east areas of the parish that are very often associated with high fireline intensities. The different fuel treatment scenarios decreased burned area between 12.1–31.2%, resulting from 1–4.6% increases in the annual treatment area and reduced the likelihood of wildfires larger than 5000 ha by 10–40%. On average, simulated burned area decreased 0.22% per each ha treated, and cost-effectiveness decreased with increasing area treated. Overall, both fuel treatment strategies effectively reduced wildfire hazard and should be part of a larger, holistic and integrated plan to reduce the vulnerability of the Alvares parish to wildfires.

scholarly journals Fuel Treatment Longevity in Ponderosa Pine-Dominated Forest 24 Years After Cutting and Prescribed Burning

2020 ◽  
Vol 3 ◽  
Author(s):  
Sharon M. Hood ◽  
Christopher R. Keyes ◽  
Katelynn J. Bowen ◽  
Duncan C. Lutes ◽  
Carl Seielstad
Keyword(s):  
Ponderosa Pine ◽  
Prescribed Burning ◽  
Fuel Treatment

scholarly journals Comparing Modeled Emissions from Wildfire and Prescribed Burning of Post-Thinning Fuel: A Case Study of the 2016 Pioneer Fire

Fire ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 22
Author(s):  
Josh Hyde ◽  
Eva K. Strand
Keyword(s):  
Air Quality ◽  
Prescribed Fire ◽  
Prescribed Burning ◽  
Effective Means ◽  
National Forest ◽  
Conifer Forest ◽  
Mixed Conifer ◽  
Fuel Treatments ◽  
Mixed Conifer Forest

Prescribed fire is often used by land managers as an effective means of implementing fuel treatments to achieve a variety of goals. Smoke generated from these activities can put them at odds with air quality regulations. We set out to characterize the emission tradeoff between wildfire and prescribed fire in activity fuels from thinning in a case study of mixed conifer forest within the Boise National Forest in central Idaho. Custom fuelbeds were developed using information from the forest and emissions were modeled and compared for four scenarios, as follows: Untreated fuels burned in wildfire (UNW), prescribed fire in activity fuels left from thinning (TRX), a wildfire ignited on the post-treatment landscape (PTW), and the combined emissions from TRX followed by PTW (COM). The modeled mean total emissions from TRX were approximately 5% lower, compared to UNW, and between 2–46% lower for individual pollutants. The modeled emissions from PTW were approximately 70% lower than UNW. For the COM scenario, emissions were not significantly different from the UNW scenario for any pollutants, but for CO2. However, for the COM scenario, cumulative emissions would have been comprised of two events occurring at separate times, each with lower emissions than if they occurred at once.

Corrigendum to: Prioritising fuels reduction for water supply protection

2020 ◽  
Vol 29 (11) ◽  
pp. 1054
Author(s):  
Benjamin M. Gannon ◽  
Yu Wei ◽  
Lee H. MacDonald ◽  
Stephanie K. Kampf ◽  
Kelly W. Jones ◽  
...  
Keyword(s):  
Water Supply ◽  
Risk Mitigation ◽  
Cost Savings ◽  
Cost Effective ◽  
Fuel Treatments ◽  
Water Supplies ◽  
Fuel Treatment ◽  
Fuels Reduction ◽  
Forest Fuels ◽  
Multiple Resources

Concerns over wildfire impacts to water supplies have motivated efforts to mitigate risk by reducing forest fuels. Methods to assess fuel treatment effects and prioritise their placement are needed to guide risk mitigation efforts. We present a fuel treatment optimisation model to minimise risk to multiple water supplies based on constraints for treatment feasibility and cost. Risk is quantified as the expected sediment impact costs to water supplies by combining measures of fire likelihood and behaviour, erosion, sediment transport and water supply vulnerability. We demonstrate the model's utility for prioritising fuel treatments in two large watersheds in Colorado, USA, that are critical for municipal water supply. Our results indicate that wildfire risk to water supplies can be substantially reduced by treating a small portion of the watersheds that have dense, fire-prone forests on steep slopes that drain to water supply infrastructure. Our results also show that the cost of fuel treatments outweighs the expected cost savings from reduced sediment inputs owing to the low probability of fuel treatments encountering wildfire and the high cost of thinning forests. This highlights the need to expand use of more cost-effective treatments, like prescribed fire, and to identify fuel treatment projects that benefit multiple resources.

Comparing landscape-based decision rules for placement of fuel treatments in the boreal mixedwood of western Canada

2007 ◽  
Vol 16 (6) ◽  
pp. 664 ◽  
Author(s):  
Marc-André Parisien ◽  
David R. Junor ◽  
Victor G. Kafka
Keyword(s):  
Large Scale ◽  
Decision Rules ◽  
Limited Area ◽  
Western Canada ◽  
Fuel Treatments ◽  
Fuel Treatment ◽  
Landscape Features ◽  
Burn Probability ◽  
Rule Sets ◽  
Rule Based Approach

The present study used a rule-based approach to prioritise locations of fuel treatments in the boreal mixedwood forest of western Canada. The analysis, which was conducted in and around Prince Albert National Park, Saskatchewan, was based on burn probability (BP) mapping using the Burn-P3 (Probability, Prediction, and Planning) model. Fuel treatment locations were determined according to three rule-sets and five fuel treatment intensities. Fuel treatments were located according to BP only; jurisdictional boundaries and BP; and non-flammable landscape features, BP, and fuel treatment orientation. First, a baseline BP map was created from the original (i.e. unmodified) fuels grid. Fuel treatments were then added to the selected areas and BP maps produced for each combination of rule-set and treatment intensity. BP values for the treated landscapes were compared with those of the baseline BP map. Results varied substantially among scenarios. Locating fuel treatments as a function of the jurisdictional boundaries and BP yielded the lowest reduction in BP. Results suggest that clumping fuel treatments within a limited area or using landscape features to maximise the large-scale spatial benefits of the fuel treatments can significantly reduce landscape-level BP. Although these two strategies may produce similar overall reductions in BP, their appropriateness and utility depend on management objectives.

Calculation of fire spread rates across random landscapes

2003 ◽  
Vol 12 (2) ◽  
pp. 167 ◽  
Author(s):  
Mark A. Finney
Keyword(s):  
Travel Time ◽  
Growth Rates ◽  
Fire Spread ◽  
Harmonic Mean ◽  
Fire Growth ◽  
Fire Size ◽  
Spread Rate ◽  
Fuel Treatments ◽  
Fuel Mixtures

An approach is presented for approximating the expected spread rate of fires that burn across 2-dimensional landscapes with random fuel patterns. The method calculates a harmonic mean spread rate across a small 2-dimensional grid that allows the fire to move forward and laterally. Within this sample grid, all possible spatial fuel arrangements are enumerated and the spread rate of an elliptical fire moving through the cells is found by searching for the minimum travel time. More columns in the sample grid are required for accurately calculating expected spread rates where very slow-burning fuels are present, because the fire must be allowed to move farther laterally around slow patches. This calculation can be used to estimate fire spread rates across spatial fuel mixtures provided that the fire shape was determined from wind and slope. Results suggest that fire spread rates on random landscapes should increase with fire size and that random locations of fuel treatments would be inefficient in changing overall fire growth rates.

An optimization model for locating fuel treatments across a landscape to reduce expected fire losses

2008 ◽  
Vol 38 (4) ◽  
pp. 868-877 ◽  
Author(s):  
Yu Wei ◽  
Douglas Rideout ◽  
Andy Kirsch
Keyword(s):  
Spatial Information ◽  
Solution Process ◽  
Fire Risk ◽  
Simulation Models ◽  
Mixed Integer ◽  
Fire Intensity ◽  
Fuel Treatments ◽  
Fuel Treatment ◽  
Mip Model ◽  
Fire Ignition

Locating fuel treatments with scarce resources is an important consideration in landscape-level fuel management. This paper developed a mixed integer programming (MIP) model for allocating fuel treatments across a landscape based on spatial information for fire ignition risk, conditional probabilities of fire spread between raster cells, fire intensity levels, and values at risk. The fire ignition risk in each raster cell is defined as the probability of fire burning a cell because of the ignition within that cell. The conditional probability that fire would spread between adjacent cells A and B is defined as the probability of a fire spreading into cell B after burning in cell A. This model locates fuel treatments by using a fire risk distribution map calculated through fire simulation models. Fire risk is assumed to accumulate across a landscape following major wind directions and the MIP model locates fuel treatments to efficiently break this pattern of fire risk accumulation. Fuel treatment resources are scarce and such scarcity is introduced through a budget constraint. A test case is designed based on a portion of the landscape (15 552 ha) within the Southern Sierra fire planning unit to demonstrate the data requirements, solution process, and model results. Fuel treatment schedules, based upon single and dual wind directions, are compared.

Simulating fuel treatment effects in dry forests of the western United States: testing the principles of a fire-safe forest

2011 ◽  
Vol 41 (5) ◽  
pp. 1018-1030 ◽  
Author(s):  
Morris C. Johnson ◽  
Maureen C. Kennedy ◽  
David L. Peterson
Keyword(s):  
United States ◽  
Treatment Effects ◽  
Fire Hazard ◽  
Fire Behavior ◽  
Post Treatment ◽  
Western United States ◽  
Crown Fire ◽  
Fuel Treatments ◽  
Dry Forests ◽  
Fuel Treatment

We used the Fire and Fuels Extension to the Forest Vegetation Simulator (FFE-FVS) to simulate fuel treatment effects on 45 162 stands in low- to midelevation dry forests (e.g., ponderosa pine ( Pinus ponderosa Dougl. ex. P. & C. Laws.) and Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) of the western United States. We evaluated treatment effects on predicted post-treatment fire behavior (fire type) and fire hazard (torching index). FFE-FVS predicts that thinning and surface fuel treatments reduced crown fire behavior relative to no treatment; a large proportion of stands were predicted to transition from active crown fire pre-treatment to surface fire post-treatment. Intense thinning treatments (125 and 250 residual trees·ha–1) were predicted to be more effective than light thinning treatments (500 and 750 residual trees·ha–1). Prescribed fire was predicted to be the most effective surface fuel treatment, whereas FFE-FVS predicted no difference between no surface fuel treatment and extraction of fuels. This inability to discriminate the effects of certain fuel treatments illuminates the consequence of a documented limitation in how FFE-FVS incorporates fuel models and we suggest improvements. The concurrence of results from modeling and empirical studies provides quantitative support for “fire-safe” principles of forest fuel reduction (sensu Agee and Skinner 2005. For. Ecol. Manag. 211: 83–96).

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