Financing Wildfire Resilience in Colorado

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.

Wildfire Risk Assessment Assumptions for Economic Analysis of Denver Water’s From Forests to Faucets (F2F) Wildfire Resilience Partnership

In 2019 Jones et al. (published by the Colorado Forest Restoration Institute) estimated the net economic benefits of Denver Water’s F2F Partnership. Through F2F, partners implement and monitor a series of wildfire risk reduction projects, including forest restoration, biomass removal, and prescribed burning, in areas of high priority for source water protection. To date, F2F partners have treated over 120,000 acres within forested areas that supply water to Denver Water.

Because the primary objective of the F2F treatments was to reduce fire severity, the authors decided to hold the probability of wildfire occurrence constant across baseline (pre-treatment) and post-treatment conditions. While this may underestimate the benefits of the treatments, previous studies have shown that the effect of wildfire risk reduction strategies on the likelihood of fire occurrence is relatively small at the landscape scale.

Jones et al. estimated burn probability across the study area using Large Fire Simulator (FSim). This allowed them to estimate the likelihood of treatments encountering wildfire over their effective lifespan (assumed to be 25 years). The authors assumed two wildfire occurrence scenarios to calculate benefits. The first scenario calculates the benefits of wildfire mitigation treatments assuming treated acres are burned once during the 25-year time frame (conditional occurrence). The second calculates expected benefits based on the modeled probability of the wildfire mitigation treatments encountering wildfire, which varies across the landscape (expected occurrence).

To model fire behavior with and without treatments, the authors used FlamMap 5.0, which spatially predicts fire attributes under different conditions. The authors relied on surface and canopy fuels data from LANDFIRE (2014) to model fire behavior under baseline conditions. Surface fuels are represented by categorical fire behavior fuel models (FBFMs), which characterize common fuel loading and arrangements and their associated flame lengths and rates of spread. Canopy fuels are described in terms of canopy base height, canopy height, canopy bulk density, and canopy cover. To assess post-treatment fire behavior, the authors reclassified surface fuels into new FBFMs and modified the canopy fuel assumptions by treatment type with proportional adjustment factors (reflective of post-treatment conditions).

The authors also estimated treatment effects under two fire behavior scenarios. The first scenario relies on modeled changes to wildfire severity based on changes to canopy and surface fuels and the resulting fire behavior predictions. The second scenario assumes wildfire severity is lowered one level in the treated areas, unless already at low severity. For example, high severity wildfire changes to moderate severity and moderate severity to low severity. The second scenario gives the forest manager the benefit of the doubt that an appropriate treatment to mitigate crown fire hazard was prescribed.

The range of scenarios examined yielded four sets of results based on combinations of assumptions related to burn probability (conditional vs expected fire occurrence) and wildfire behavior following the planned treatments (modeled vs. assumed effectiveness). These assumptions were applied across benefit categories, providing “bookends” to the expected range of total benefits.

Source: Jones, K., Chamberlain, L., Gannon, B., and Wolk, B. 2021. A Cost-Benefit Analysis of Denver’s Forests to Faucets Program, 2011-2019. CFRI-2102.