# Wildfire SOP
Last updated March 15, 2023 by J. Mehta and M. Ackerson
# Scope
Hazard: Wildfire
Asset types: Buildings
Consequences: Downtime, Repair cost
Region: USA
# Introduction
Wildfires represent a growing risk to buildings due to climate change and urbanization. Buildings constructed in the wildland-urban interface (WUI) are directly exposed to wildfires because of their proximity. Buildings in more urban environments may not be directly exposed to flames, but they may experience spot fires from airborne embers and the consequences of thick smoke.
The risk assessment methodology described herein focuses on wildfire risk in terms of downtime and financial loss. Currently, 3 workflows for wildfire building-level risk assessments are detailed in this SOP – 1) within Iris for a single asset, 2) within Iris for multiple assets, and 3) off-platform analysis. The perusal of this SOP should provide a step-by-step guide to implement any one of the 3 workflows to assess building-level risk to repair costs and downtime from wildfire flames and embers
# Overview of Risk Classes
| Description | Class 1 | Class 2 | Class 3/4 |
|---|---|---|---|
| Hazard data | Wildfire data from FSF | Same as Class 1 | Not yet developed |
| Exposure & Vulnerability data | Building use type Latitude, Longitude | Building use Building replacement value or building area or building footprint area and number of floors Latitude, Longitude Exterior wall material Roof material Compliance with WUI / fire code Time factor Location factor | Not yet developed |
| Time to set up project | Allocate 8hrs for project set-up in Iris | Allocate 8hrs for project set-up in Iris | Not yet developed |
| Time required to review and input exposure data | Assume data has been collected (add time estimate to proposal) Less than 30 sites: 30 min per site More than 30 sites: 15 minutes per site + 8hr batching setup | Assume data has been collected (add time estimate to proposal) Less than 30 sites: 90 min per site More than 30 sites: 60 minutes per site + 8hr batching setup | Not yet developed |
| Time required to review or obtain cost data (location & time factors, replacement value) | Not applicable for Class 1 | Allow 8hrs for cost team to provide regional location factors, appropriate time factor, and replacement value ($/sf) for 2-3 building types | Not yet developed |
| Time required to review hazard data and QA/QC risk results | Allocate 8h for R+R team support for R+R team QA/QC | Allocate maximum of 16h or 8h per 50 sites for R+R team QA/QC support | Not yet developed |
| Output | Qualitative risk ratings (e.g., High, Medium, Low) | Quantitative risk metrics (AAD, AAL) Qualitative risk ratings (e.g., High, Medium, Low) | Not yet developed |
# Class 1 wildfire risk assessment for building downtime and repair cost
Please follow the steps enumerated in this section to obtain the expected downtime and repair costs for a wildfire risk analysis of buildings. This process will determine the hazard experienced at the asset, assign a vulnerability archetype to the building, and perform the risk analysis to get downtime and repair cost estimates on the asset. The hazard data for each site, the building exposure information, and the vulnerability curves will be combined to produce risk results for this Class 1 Assessment. It should be noted that this SOP is only applicable to Class 1 wildfire risk assessments in the U.S., as archetypal vulnerability curves are predicated on the U.S.-only wildfire hazard data provided to Arup’s San Francisco Risk and Resilience team by First Street Foundation. Class 1 wildfire risk assessments outside the U.S. are not supported at this time.
# Hazard
Information about three different wildfire hazard intensity measures are required as inputs to conduct a wildfire risk assessment. Wildfire hazard data is generally provided for specific “pixels” (spatial unit) with a resolution of 30 meters. The three hazard inputs are:
- The return period vs. flame length curve of flame lengths at the pixel in which the building is located (“parcel pixel flame length”).
- The return period vs. flame length curve of flame lengths at all adjacent pixels to the one in which the building is located (“adjacent pixel flame length”).
- The return period vs. ember counts curve of modelled ember counts at the pixel in which the building is located (“parcel pixel ember count”).
Step 1: Obtain Hazard Data
In Iris, for 1 asset
• If conducting an assessment in Iris for a single asset, the Input Hazard tab will lead you to a window where you can make the relevant selections to auto-populate these 3 pieces of hazard data from the FSF wildfire dataset. The dataset provides two time horizons (Present – 2022 and Future – 2052) from which to make a selection. Select the time horizon that best suits your assessment and click “Get Hazard.” This will call HAPI and also take you to a window where you can review and confirm your auto-populated hazard data. You can also download the .json and .csv formats of this hazard data. Once you select “Use Hazards,” you will be able to proceed to the next phase of the assessment.
In Iris, for multiple assets
• If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to autopopulate wildfire hazard data for all assets simultaneously, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching hazard data population for your asset portfolio.
Outside of Iris
• If conducting the assessment outside of Iris, please contact Jinal Mehta (Jinal.mehta@arup.com) and Stevan Gavrilovic (Stevan.gavrilovic@arup.com) to work with you to extract the hazard data you need.
# Exposure
For a C1 risk assessment, this section is not needed. You can move ahead to the ‘Vulnerability’ section.
# Vulnerability
For wildfire, three archetypal vulnerability curves are associated with each consequence type:
- Parcel pixel flame length vs. consequence curves, which relate repair costs (in USD) and downtime (in days) to flame lengths given in the hazard dataset for the pixel in which the asset parcel is located.
- Adjacent pixel flame length vs. consequence curves, which relate repair costs (in USD) and downtime (in days) to flame lengths given in the hazard dataset for the pixels adjacent to that in which the asset parcel is located.
- Parcel pixel ember count vs. consequence curves, which relate repair costs (in USD) and downtime (in days) to modelled ember counts given in the hazard dataset for the pixel in which the asset parcel is located.
Building use type, wall material, roof material, year built, and defensible area are required to assign the appropriate archetypal vulnerability curves to the building. More information about the building characteristics can be found in Appendix.
Step 1: Obtain relevant building characteristics and determine their corresponding archetype tag
For a C1 RA, please select the building use type (Residential, Commercial, or Industrial) which most closely resembles your building.
Other building characteristics, such as wall material, roof material, compliance with wildfire codes and standards, and defensible space, are fixed for a C1 RA. Please see below for further explanation on the specific assumptions made.
- Wall material – For a C1 RA, assume conservatively that wall material has high ignition potential (HCW).
- Roof material – For a C1 RA, assume conservatively that the roof material has high ignition potential (HCR).
- Compliance with WUI/wildfire code – For a C1 RA, assume the building was built before fire code applicability and/or that it does not comply with all applicable WUI and/or wildfire codes and standards in the region, including those requiring annual maintenance (BC). Defensible area – For a C1 RA, assume conservatively that there is some vegetation within 50ft (15m) of the building and select the no defensible space tag (ND).
Step 2: Obtain vulnerability curves for each hazard and consequence pair
In total there are six (6) vulnerability curves per archetype:
- Flame length (parcel pixel) vs. repair cost as percent (%) replacement cost
- Flame length (parcel pixel) vs. downtime
- Flame length (adjacent pixel) vs. repair cost as percent (%) replacement cost
- Flame length (adjacent pixel) vs. downtime
- Ember count (parcel pixel) vs. repair cost as percent (%) replacement cost
- Ember count (parcel pixel) vs. downtime
In Iris, for 1 asset
- For a C1 RA, Iris automatically will determine the archetype tags for all 5 building characteristics and select the appropriate flame length and ember count archetypal vulnerability curves from the wildfire vulnerability curve database.
In Iris, for multiple assets
- If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to populate the appropriate assumed building characteristics in batch, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching risk assessment characteristics for your portfolio.
Outside of Iris
- After the archetype tags have been determined for all five building characteristics, please select the appropriate flame length and ember count archetypal vulnerability curves from the wildfire vulnerability curve database. The names of flame length vulnerability curves are given in Section 9.3. and the names of the ember count vulnerability curves are given in Section 9.3.. The curves themselves are located in the Iris Resources SharePoint, under Technical Guidance and Resources, in the folder Wildfire Vulnerability Curves. Please contact the authors of this SOP, Jinal Mehta (Jinal.mehta@arup.com) and Meg Ackerson (meg.ackerson@arup.com) with any questions.
# Risk Determination
Now that the hazard, exposure, and vulnerability data has been collected, the risk can be determined for a given building and all three wildfire hazard intensity measures.
Conceptual
Please see Appendix 4A Determining average annual loss (AAL) from return-period losses for a conceptual overview of going from the hazard data (i.e., hazard intensity vs. return period) and vulnerability curve selected (i.e., hazard intensity vs. consequence) to risk metrics such as average annual loss and average annual downtime.
In Iris, for 1 asset
- In the Run Risk Analysis pop-up, ensure your exposure and vulnerability inputs are correct and press “Run Risk Analysis”
- In the risk metrics output pane,
- For each hazard IM, see the losses, % loss, and time to recover for each return period; AAL, AAD
- See the maximum AAL, AAD across all hazard IMs
In Iris, for multiple assets
- If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to conduct risk assessments in batch, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching risk assessments for your portfolio.
Outside of Iris
- Follow the steps in Appendix 4A Determining average annual loss (AAL) from return-period losses to set up your risk analysis workflow. Please contact the authors of this SOP, Jinal Mehta (Jinal.mehta@arup.com) and Meg Ackerson (meg.ackerson@arup.com) with any questions.
# Iris Interface for a Class 1 Wildfire Risk Assessment
If running a risk assessment in Iris, this section walks through how to input the information and run a Class 1 risk assessment of a single asset through the Iris GUI.
Creating or updating an asset
It is assumed that the reader has logged into Iris and created an appropriate group for this analysis. Please refer to General Iris Guidelines if not and return to this step.
If you have not already, create a new asset by selecting the ‘New Asset’ button in the top righthand corner of the screen (see blue circle in image below).
This button leads to the asset creation page, as seen in the next figures. The following information is needed to run a wildfire risk analysis:
- Location (Latitude, Longitude) ,(1)
- Building Use Type (Primary Occupancy Type) (2)
- Building replacement value or building area or building footprint area and number of floors (3)
- Note that if latitude and longitude is not filled out here, you will also have a chance to edit it in the Input Hazard window after creating a risk assessment on the asset.
- Note that if building occupancy type is left blank here, you will also have a chance to select it in the Run Risk Analysis window after creating a risk assessment on the asset.
- Note that if any of these are left blank here, you will also have a chance to edit them in the Run Risk Analysis window after creating a risk assessment on the asset.
At the bottom of the page, select ‘Create’ or ‘Update’ to save the information that has been input.
Creating a risk assessment on an asset
To create a risk assessment on an asset, navigate to the Risk Metrics tab and click on the ‘Create’ button in the top righthand corner.
This button leads to an assessment creation page which asks for some detail about the type of assessment. Fill out the Assessment Name with a description of the assessment (e.g., “Phase 1,” “Site Study”), timeframe (e.g., “Present Day 2020” or “Future 2050”), and hazard type (e.g., “Wildfire – flames and embers”). An example assessment name would be “Phase 1 Present Day 2020 Wildfire C1 Assessment.”
Designate the Hazard Type as “Wildfire” and Risk Class as “2” to capture the analysis details. The Executive Summary can be left blank for now. Finally, click on the ‘Create Assessment’ button at the bottom of this page (circled in teal below).
ADD IMAGE
The assessment should now appear under the ‘Risk Metrics’ tab on the asset page.
ADD IMAGE
Input Risk Parameters
ADD IMAGE
Input Hazard Information
Step 1: Select auto-population option (only option available for wildfire)
ADD IMAGE
Step 2: Specify wildfire hazard model parameters
ADD IMAGE
Step 3: Review and confirm autopopulated data ADD IMAGE
Run Risk Analysis
ADD IMAGE
View risk metrics and optionally publish risk ratings
# Class 2 wildfire risk assessment for building downtime and repair cost
Please follow the steps enumerated in this section to obtain the expected downtime and repair costs for a wildfire risk analysis of buildings. This process will determine the hazard experienced at the asset, assign a vulnerability archetype to the building, and perform the risk analysis to get downtime and repair cost estimates on the asset.
The hazard data for each site, the building exposure information, and the vulnerability curves will be combined to produce risk results for this Class 2 Assessment.
It should be noted that this SOP is only applicable to Class 2 wildfire risk assessments in the U.S., as archetypal vulnerability curves are predicated on the U.S.-only wildfire hazard data provided to Arup’s San Francisco Risk and Resilience team by First Street Foundation. Class 2 wildfire risk assessments outside the U.S. are not supported at this time.
# Hazard
Three pieces of hazard data are required to conduct a wildfire risk assessment. These three hazard inputs are:
- The return period vs. flame length curve of flame lengths at the pixel in which the building is located.
- The return period vs. flame length curve of flame lengths at all adjacent pixels to the one in which the building is located.
- The return period vs. ember counts curve of modelled ember counts at the pixel in which the building is located.
Step 1: Obtain Hazard Data
In Iris, for 1 asset
- If conducting an assessment in Iris for a single asset, the Input Hazard tab will lead you to a window where you can make the relevant selections to auto-populate these 3 pieces of hazard data from the FSF wildfire dataset. The dataset provides two time horizons (Present – 2022 and Future – 2052) from which to make a selection. Select the time horizon that best suits your assessment and click “Get Hazard.” This will call HAPI and also take you to a window where you can review and confirm your auto-populated hazard data. You can also download the .json and .csv formats of this hazard data. Once you select “Use Hazards,” you will be able to proceed to the next phase of the assessment.
In Iris, for multiple assets
- If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to autopopulate wildfire hazard data for all assets simultaneously, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching hazard data population for your asset portfolio.
Outside of Iris
- If conducting the assessment outside of Iris, please contact Jinal Mehta (Jinal.mehta@arup.com) and Stevan Gavrilovic (Stevan.gavrilovic@arup.com) to work with you to extract the hazard data you need.
# Exposure
If only assessing downtime risk, move ahead to the ‘Vulnerability’ section.
If only assessing repair cost risk qualitatively (e.g., High, Med, Low), move ahead to the ‘Vulnerability’ section.
If assessing repair cost risk AND interested in quantitative metrics (i.e., repair cost ($) at a given return period, AAL, etc.), please follow the following steps to obtain total building replacement cost, which is needed to calculate quantitative repair costs.
Step 1: Obtain replacement cost
Conceptual
To determine the $ losses for a given hazard intensity, you will need to adjust the % loss archetypal vulnerability curves to your building’s value. To do this, you will need to obtain the building’s replacement cost. There are 2 ways to obtain this metric.
- Direct – you have the building replacement cost.
- Calculate it from the total building area (in sqft) and the $/sqft cost table in Section 1. . a. Building replacement cost = total building area * cost per square foot b. Note that if you do not have the building’s total area on hand, you can calculate it from the building footprint area and the estimated number of floors of your building. i. Total building area = building footprint area * number of floors
If using Iris to conduct your assessment(s), please follow the steps below to input or obtain building replacement cost depending on the interface you are using to conduct your risk assessment.
In Iris, for 1 asset
- If you have the replacement cost on hand, please input it in the Business section of the Create/Edit Asset pop-up.
- If you do not have the replacement cost on hand, Iris can calculate it using the methods described above. Please input the total above ground and below ground floors, and either (a) the areas of each level or (b) the area of the building footprint in the Occupancy section of the Create/Edit Asset pop-up.
In Iris, for multiple assets
- If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to autopopulate replacement cost, number of floors, and/or building floor areas for all assets simultaneously, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching asset data population for your portfolio.
Outside of Iris
- Follow the steps in the Conceptual section above to set up your risk analysis workflow. Please contact the authors of this SOP, Jinal Mehta (Jinal.mehta@arup.com) and Meg Ackerson (meg.ackerson@arup.com) with any questions.
# Vulnerability
For wildfire, three archetypal vulnerability curves are associated with each consequence type:
- Parcel pixel flame length vs. consequence curves, which relate repair costs (in USD) and downtime (in days) to flame lengths given in the hazard dataset for the pixel in which the asset parcel is located.
- Adjacent pixel flame length vs. consequence curves, which relate repair costs (in USD) and downtime (in days) to flame lengths given in the hazard dataset for the pixels adjacent to that in which the asset parcel is located.
- Parcel pixel ember count vs. consequence curves, which relate repair costs (in USD) and downtime (in days) to modelled ember counts given in the hazard dataset for the pixel in which the asset parcel is located.
Building use type, wall material, roof material, year built, and defensible area are required to assign the appropriate archetypal vulnerability curves to the building. See the following table for the options available within each building characteristic category.
Table 1: Table of building characteristics and their respective tags for archetype assignment.
| Building Characteristics | Description | Archetype Tag |
|---|---|---|
| Usage | Residential | RES |
| Commercial | COM | |
| Industrial | IND | |
| Wall Material | High ignition potential, combustible material wall | HCW |
| Low ignition potential, combustible material wall | LCW | |
| Noncombustible material wall | NCW | |
| Roof Material | High ignition potential, combustible material roof | NCW |
| Low ignition potential, combustible material roof | LCR | |
| Noncombustible material roof | NCR | |
| Compliance with applicable WUI or wildfire codes, standards, or guides | Built before WUI/wildfire code was adopted or not compliant with applicable WUI or wildfire codes, standards, and guides | BC |
| Built after WUI/wildfire code was adopted or compliant with applicable WUI or wildfire codes, standards, and guides | AC | |
| Defensible space | No defensible space within 50ft | ND |
| High defensible space within 50ft | HD |
Step 1: Obtain relevant building characteristics and determine their corresponding archetype tag
Usage – Please select the building use type from the table above that most closely resembles your building. If the building has multiple use types, please select the building use type that encompasses most of the building area
Wall material - Please see the Appendix A for a table of common exterior wall types, their ignition potential description, and the most appropriate wall archetype tag to use.
- If the exterior wall type is unknown, assume conservatively that wall material has high ignition potential (HCW).
Roof material - Please see the Appendix B for a table of common roof types, their ignition potential description, and the most appropriate roof archetype tag to use.
- If the roof type is unknown, but the number of stories in a building is available, follow the below logic to assign an ignition potential and archetype tag:
- If the number of stories is less than or equal to three (3), then consider roof type as having high ignition potential (HCR). If the number of stories is greater than three (3), then consider roof type as non-combustible material (NCR).
- If the roof type and number of stories are unknown, assume conservatively that the roof material has high ignition potential (HCR).
- If the roof type is unknown, but the number of stories in a building is available, follow the below logic to assign an ignition potential and archetype tag:
Compliance with WUI/wildfire code – Please select the appropriate code compliance category from the table above. By default, the BC tag should be selected and only in select cases should the AC tag be used. Do not use the AC tag unless it has been confirmed that the building complies with all applicable WUI and/or wildfire codes and standards in the region, including those requiring annual maintenance.
Defensible area - Review satellite imagery to determine if there is any vegetation within 50ft (15m) of the building. If there is no vegetation (i.e., trees or shrubs) within 15m of the building, select the high defensible space (HD) tag. If any vegetation is observed within 50ft (15m) of the building, select the no defensible space (ND) tag. If the building has not been built or satellite imagery is not available, the ND tag should be selected by default.
Step 2 Obtain vulnerability curves for each hazard and consequence pair
In total there are six (6) vulnerability curves per archetype:
- Flame length (parcel pixel) vs. repair cost as percent (%) replacement cost
- Flame length (parcel pixel) vs. downtime
- Flame length (adjacent pixel) vs. repair cost as percent (%) replacement cost
- Flame length (adjacent pixel) vs. downtime
- Ember count (parcel pixel) vs. repair cost as percent (%) replacement cost
- Ember count (parcel pixel) vs. downtime
In Iris, for 1 asset
- After the archetype tags have been determined for all five building characteristics and input into the Assumed Building Characteristics section of the Run Risk Analysis pop-up, Iris will automatically select the appropriate flame length and ember count archetypal vulnerability curves from the wildfire vulnerability curve database.
In Iris, for multiple assets
- If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to populate the appropriate assumed building characteristics in batch, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching risk assessment characteristics for your portfolio.
Outside of Iris
- After the archetype tags have been determined for all five building characteristics, please select the appropriate flame length and ember count archetypal vulnerability curves from the wildfire vulnerability curve database. The names of flame length vulnerability curves are given in Section 9.3. and the names of the ember count vulnerability curves are given in Section 9.3.. The curves themselves are located in the Iris Resources SharePoint, under Technical Guidance and Resources, in the folder Wildfire Vulnerability Curves. Please contact the authors of this SOP, Jinal Mehta (Jinal.mehta@arup.com) and Meg Ackerson (meg.ackerson@arup.com) with any questions.
# Risk Determination
Now that the hazard, exposure, and vulnerability data has been collected, the risk can be determined for a given building and all three wildfire hazard intensity measures.
Conceptual
Please see Appendix D1 Determining average annual loss (AAL) from return-period losses for a conceptual overview of going from the hazard data (i.e., hazard intensity vs. return period) and vulnerability curve selected (i.e., hazard intensity vs. consequence) to risk metrics such as average annual loss and average annual downtime.
In Iris, for 1 asset
- In the Run Risk Analysis pop-up, ensure your exposure and vulnerability inputs are correct and press “Run Risk Analysis”
- In the risk metrics output pane, - For each hazard IM, see the losses, % loss, and time to recover for each return period; AAL, AAD - See the maximum AAL, AAD across all hazard IMs
In Iris, for multiple assets
- If conducting an assessment in Iris for multiple assets, you can repeat the process described above for all assets within the Iris GUI. Alternatively, if you have a large number of assets and want to conduct risk assessments in batch, please email Jinal Mehta (Jinal.mehta@arup.com) and Tamika Bassman (Tamika.bassman@arup.com) to assist you with batching risk assessments for your portfolio.
Outside of Iris
- Follow the steps in the Conceptual section above to set up your risk analysis workflow. Please contact the authors of this SOP, Jinal Mehta (Jinal.mehta@arup.com) and Meg Ackerson (meg.ackerson@arup.com) with any questions.
# Iris Interface for a Class 2 Wildfire Risk Assessment
If running a risk assessment in Iris, this section walks through how to input the information and run a Class 2 risk assessment of a single asset through the Iris GUI.
Creating or updating an asset
It is assumed that the reader has logged into Iris and created an appropriate group for this analysis. Please refer to General Iris Guidelines if not and return to this step. If you have not already, create a new asset by selecting the ‘New Asset’ button in the top righthand corner of the screen (see blue circle in image below).
This button leads to the asset creation page, as seen in the next figures. The following information is needed to run a wildfire risk analysis:
- Location (Latitude, Longitude) , (5)
- Building Use Type (Primary Occupancy Type) (6)
- Building replacement value or building area or building footprint area and number of floors (7)
(5) Note that if latitude and longitude is not filled out here, you will also have a chance to edit it in the Input Hazard window after creating a risk assessment on the asset. (6) Note that if building occupancy type is left blank here, you will also have a chance to select it in the Run Risk Analysis window after creating a risk assessment on the asset. (7) Note that if any of these are left blank here, you will also have a chance to edit them in the Run Risk Analysis window after creating a risk assessment on the asset.
ADD IMAGE
At the bottom of the page, select ‘Create’ or ‘Update’ to save the information that has been input.
Creating a risk assessment on an asset
To create a risk assessment on an asset, navigate to the Risk Metrics tab and click on the ‘Create’ button in the top righthand corner.
This button leads to an assessment creation page which asks for some detail about the type of assessment. Fill out the Assessment Name with a description of the assessment (e.g., “Phase 1,” “Site Study”), timeframe (e.g., “Present Day 2020” or “Future 2050”), and hazard type (e.g., “Wildfire – flames and embers”). An example assessment name would be “Phase 1 Present Day 2020 Wildfire C2 Assessment.” Designate the Hazard Type as “Wildfire” and Risk Class as “2” to capture the analysis details. The Executive Summary can be left blank for now. Finally, click on the ‘Create Assessment’ button at the bottom of this page (circled in teal below).
ADD IMAGE
The assessment should now appear under the ‘Risk Metrics’ tab on the asset page.
ADD IMAGE
Input Risk parameters
ADD IMAGE
Input Hazard Information
Step 1: Select auto-population option (only option available for wildfire)
ADD IMAGE
Step 2: Specify wildfire hazard model parameters
ADD IMAGE
Step 3: Review and confirm autopopulated data
ADD IMAGE
Run Risk Analysis
ADD IMAGE
View risk metrics and optionally publish risk ratings
ADD IMAGE
# Supplemental References
| Source (location) | Link |
|---|---|
# Reference Projects
| Project Name | Job Number | Brief Description of Wildfire Risk Analysis (Class, Assest) | Analyst Contact(s) |
|---|---|---|---|
| First Street Foundation Wildfire Risk | Class 2 risk analysis to develop component-level building models and produce the vulnerability curves now standard for Class 2 wildfire risk assessments. Note that only two building components were modelled: wall and roof. | Meg Ackerson Kenny Buyco | |
# Glossary
Burn Probability - The annualized likelihood of burning at a site
Flame Length – a measure of fire intensity; in this SOP, the maximum flame length (measured in ft) conditional on fire occurrence
Ember Count – a measure of fire intensity; in this SOP, the sum of modelled pseudo-embers that enter the site’s pixel
Parcel Pixel – the pixel in which the building parcel is located
Adjacent Pixel – Out of the 8 adjacent pixels to the parcel, the pixel with the highest burn probability
# Appendix
# Appendix A - Data Collection Templates
Class 1 template: Wildfire C1 RA Vulnerability Data Template.xlsx
Class 2 template: Wildfire C2 RA Vulnerability Data Template.xlsx
# Appendix B - Exposure
# Appendix B1 - $/SF costs for residential, commercial, and industrial building types
| Type | Stories | Description | $/SF |
|---|---|---|---|
| Residential - Single Family House | 2 Stories | $340 | |
| Residential - High Rise | 8-24 Stories | Precast concrete / Reinforced | $470 |
| Residential - Medium Rise | 4-7 Stories | Precast concrete / Reinforced | $410 |
| Residential - Low Rise | 1-3 Stories | Stone Veneer / Wood Frame | $380 |
| Commercial - Office | 1-20 Stories | Office, with Brick Veneer / Reinforced Concrete | $440 |
| Commercial - Restaurant, bakery, Bar, Nightclub | 1 Story | Restaurant with Brick Veneer / Wood Frame | $420 |
| Commercial - Retail, Dept Stores etc. | 1 Story | Store, Retail with Brick Veneer / Reinforced Concrete | $330 |
| Commercial - Convenience Store | 1 Story | Store, Convenience with Face Brick / Wood Frame | $280 |
| Commercial - Hotel High Rise | 8-24 Stories | Hotel, 8-24 Story with Precast Concrete / Reinforced Concrete | $440 |
| Commercial - Hotel Medium Rise | 4-7 Stories | Hotel, 4-7 Story with Precast Concrete / Reinforced Concrete | $400 |
| Commercial - Motel | 2-3 Stories | Motel, 2-3 Story with Stucco & Concrete Block / Wood Joists | $370 |
| Commercial - Supermarket | 1 Story | Supermarket with Brick Veneer / Reinforced Concrete | $320 |
| Commercial - Carwash | 1 Story | Car Wash with Concrete Block / Bearing Walls | $600 |
| Commercial - Parking Structure | 5 Story | Garage, Parking with Cast in Place Concrete / Reinforced Concrete | $190 |
| Commercial - Laundromat | 1 Story | Laundromat with Decorative Concrete Block / Bearing Walls | $480 |
| Commercial - Veterinary hospital | 1 Story | Veterinary Hospital with Brick Veneer / Wood Truss | $360 |
| Industrial | 1 Story | Warehouse | $380 |
Key Assumptions
All costs are in 2021 4th Quarter USD.
Location: Sacramento, CA.
Sources: RSMeans and other internal project data
# Appendix C - Vulnerability
# Appendix C1 - Building characteristics and their respective tags for archetype assignment
| Building Characteristics | Description | Archetype Tag |
|---|---|---|
| Usage | Residential | RES |
| Commercial | COM | |
| Industrial | IND | |
| Wall Material | High ignition potential, combustible material wall | HCW |
| Low ignition potential, combustible material wall | LCW | |
| Noncombustible material wall | NCW | |
| Roof Material | High ignition potential, combustible material roof | NCW |
| Low ignition potential, combustible material roof | LCR | |
| Noncombustible material roof | NCR | |
| Compliance with applicable WUI or wildfire codes, standards, or guides | Built before WUI/wildfire code was adopted or not compliant with applicable WUI or wildfire codes, standards, and guides | BC |
| Built after WUI/wildfire code was adopted or compliant with applicable WUI or wildfire codes, standards, and guides | AC | |
| Defensible space | No defensible space within 50ft | ND |
| High defensible space within 50ft | HD |
# Appendix C2. Common exterior wall types, their ignition potential and archetypal labels
| Ext Wall Type | Ignition Potential | Archetypal Label |
|---|---|---|
| Asbestos Shingle | non-combustible | NCW |
| Brick | non-combustible | NCW |
| Brick Veneer | non-combustible | NCW |
| Block | non-combustible | NCW |
| Composition | high ignition potential | HCW |
| Concrete | non-combustible | NCW |
| Concrete Block | non-combustible | NCW |
| Glass | non-combustible | NCW |
| Log | low ignition potential | NCW |
| Metal | non-combustible | NCW |
| Rock, Stone | non-combustible | NCW |
| Stucco | non-combustible | NCW |
| Tile | non-combustible | NCW |
| Tilt-up (pre-cast concrete) | non-combustible | NCW |
| Other | high ignition potential | HCW |
| Wood Shingle | high ignition potential | HCW |
| Wood | high ignition potential | HCW |
| Wood Siding | high ignition potential | HCW |
| Siding (Alum/ Vinyl) | low ignitioin potential | LCW |
| Adobe | non-combustible | NCW |
| Shingle (Not Wood) | low ignition potential | LCW |
| Marble | non combustible | NCW |
| Combination | high ignition potential | HCW |
| Masonry | non-combustible | NCW |
# Appendix C3 - Common roof types, their ignition potential and archetypal labels
| Ext Roof Type | Ignition Potential | Archetype Tag |
|---|---|---|
| Asbestos | non-combustible | NCR |
| Built-Up | high ignition potential | HCR |
| Composition Shingle | high ignition potential | HCR |
| Concrete | non-combustible | NCR |
| Metal | non-combustible | NCR |
| Slate | non-combustible | NCR |
| Gravel/Rock | non-combustible | NCR |
| Tar & Gravel | high ignition potential | HCR |
| Bermuda | non-combustible | NCR |
| Masonite/ Cement Shake | high ignition potential | HCR |
| Fiberglass | low ignition potential | LCR |
| Aluminum | non-combustible | NCR |
| Wood Shake/ Shingles | high ignition potential | HCR |
| Other | high ignition potential | HCR |
| Asphalt | high ignition potential | HCR |
| Roll Composition | high ignition potential | HCR |
| Steel | non-combustible | NCR |
| Tile | non-combustible | NCR |
| Urethane | high ignition potential | HCR |
| Shingle (Not Wood) | high ignition potential | HCR |
| Wood | high ignition potential | HCR |
| Gypsum | low ignition potential | LCR |
# Appendix C4 - List of flame length vulnerability curves
| List of FL Archetypes | |||
|---|---|---|---|
| FL_p_COM_HCW_HCR_HD | FL_p_COM_HCW_HCR_ND | FL_a_COM_HCW_HCR_HD | FL_a_COM_HCW_HCR_ND |
| FL_p_COM_HCW_LCR_HD | FL_p_COM_HCW_LCR_ND | FL_a_COM_HCW_LCR_HD | FL_a_COM_HCW_LCR_ND |
| FL_p_COM_HCW_NCR_HD | FL_p_COM_HCW_NCR_ND | FL_a_COM_HCW_NCR_HD | FL_a_COM_HCW_NCR_ND |
| FL_p_COM_LCW_HCR_HD | FL_p_COM_LCW_HCR_ND | FL_a_COM_LCW_HCR_HD | FL_a_COM_LCW_HCR_ND |
| FL_p_COM_LCW_LCR_HD | FL_p_COM_LCW_LCR_ND | FL_a_COM_LCW_LCR_HD | FL_a_COM_LCW_LCR_ND |
| FL_p_COM_LCW_NCR_HD | FL_p_COM_LCW_NCR_ND | FL_a_COM_LCW_NCR_HD | FL_a_COM_LCW_NCR_ND |
| FL_p_COM_NCW_HCR_HD | FL_p_COM_NCW_HCR_ND | FL_a_COM_NCW_HCR_HD | FL_a_COM_NCW_HCR_ND |
| FL_p_COM_NCW_LCR_HD | FL_p_COM_NCW_LCR_ND | FL_a_COM_NCW_LCR_HD | FL_a_COM_NCW_LCR_ND |
| FL_p_COM_NCW_NCR_HD | FL_p_COM_NCW_NCR_ND | FL_a_COM_NCW_NCR_HD | FL_a_COM_NCW_NCR_ND |
| FL_p_RES_HCW_HCR_HD | FL_p_RES_HCW_HCR_ND | FL_a_RES_HCW_HCR_HD | FL_a_RES_HCW_HCR_ND |
| FL_p_RES_HCW_LCR_HD | FL_p_RES_HCW_LCR_ND | FL_a_RES_HCW_LCR_HD | FL_a_RES_HCW_LCR_ND |
| FL_p_RES_HCW_NCR_HD | FL_p_RES_HCW_NCR_ND | FL_a_RES_HCW_NCR_HD | FL_a_RES_HCW_NCR_ND |
| FL_p_RES_LCW_HCR_HD | FL_p_RES_LCW_HCR_ND | FL_a_RES_LCW_HCR_HD | FL_a_RES_LCW_HCR_ND |
| FL_p_RES_LCW_LCR_HD | FL_p_RES_LCW_LCR_ND | FL_a_RES_LCW_LCR_HD | FL_a_RES_LCW_LCR_ND |
| FL_p_RES_LCW_NCR_HD | FL_p_RES_LCW_NCR_ND | FL_a_RES_LCW_NCR_HD | FL_a_RES_LCW_NCR_ND |
| FL_p_RES_NCW_HCR_HD | FL_p_RES_NCW_HCR_ND | FL_a_RES_NCW_HCR_HD | FL_a_RES_NCW_HCR_ND |
| FL_p_RES_NCW_LCR_HD | FL_p_RES_NCW_LCR_ND | FL_a_RES_NCW_LCR_HD | FL_a_RES_NCW_LCR_ND |
| FL_p_RES_NCW_NCR_HD | FL_p_RES_NCW_NCR_ND | FL_a_RES_NCW_NCR_HD | FL_a_RES_NCW_NCR_ND |
| FL_p_IND_HCW_HCR_HD | FL_p_IND_HCW_HCR_ND | FL_a_IND_HCW_HCR_HD | FL_a_IND_HCW_HCR_ND |
| FL_p_IND_HCW_LCR_HD | FL_p_IND_HCW_LCR_ND | FL_a_IND_HCW_LCR_HD | FL_a_IND_HCW_LCR_ND |
| FL_p_IND_HCW_NCR_HD | FL_p_IND_HCW_NCR_ND | FL_a_IND_HCW_NCR_HD | FL_a_IND_HCW_NCR_ND |
| FL_p_IND_LCW_HCR_HD | FL_p_IND_LCW_HCR_ND | FL_a_IND_LCW_HCR_HD | FL_a_IND_LCW_HCR_ND |
| FL_p_IND_LCW_LCR_HD | FL_p_IND_LCW_LCR_ND | FL_a_IND_LCW_LCR_HD | FL_a_IND_LCW_LCR_ND |
| FL_p_IND_LCW_NCR_HD | FL_p_IND_LCW_NCR_ND | FL_a_IND_LCW_NCR_HD | FL_a_IND_LCW_NCR_ND |
| FL_p_IND_NCW_HCR_HD | FL_p_IND_NCW_HCR_ND | FL_a_IND_NCW_HCR_HD | FL_a_IND_NCW_HCR_ND |
| FL_p_IND_NCW_LCR_HD | FL_p_IND_NCW_LCR_ND | FL_a_IND_NCW_LCR_HD | FL_a_IND_NCW_LCR_ND |
| FL_p_IND_NCW_NCR_HD | FL_p_IND_NCW_NCR_ND | FL_a_IND_NCW_NCR_HD | FL_a_IND_NCW_NCR_ND |
# Appendix C5 - List of ember count vulnerability curves
| List of EC archetypes |
|---|
| EC_COM_HCR_BC |
| EC_COM_LCR_BC |
| EC_COM_NCR_BC |
| EC_RES_HCR_BC |
| EC_RES_LCR_BC |
| EC_RES_NCR_BC |
| EC_IND_HCR_BC |
| EC_IND_LCR_BC |
| EC_IND_NCR_BC |
| EC_COM_HCR_AC |
| EC_COM_LCR_AC |
| EC_COM_NCR_AC |
| EC_RES_HCR_AC |
| EC_RES_LCR_AC |
| EC_RES_NCR_AC |
| EC_IND_HCR_AC |
| EC_IND_LCR_AC |
| EC_IND_NCR_AC |
# Appendix D - Risk
# Appendix D1 - Determining Average Annual Loss (AAL) from return-period losses
Step 1: For each consequence of interest and for each of the three wildfire hazard IMs (parcel pixel flame length, adjacent pixel flame length, and parcel pixel ember count), get estimated loss for each return period.
- For each return period, determine the hazard value from the hazard curve (return period vs. hazard) and look up the corresponding loss value from the vulnerability curve (hazard vs. loss)
***Step 2: For each consequence of interest, across all three wildfire hazard IMs, get average annual loss from the return period losses. ***
To get the average annual loss (AAL), calculate the area under the return period vs. loss curve, mathematically represented by the following equation
where r = return period, L = consequence of interest, and Fe = exceedance probability (Fe=1/r).
In practice, there are several ways to approximate this integral from discrete return period losses. Iris uses trapezoidal integration under the exceedance probability vs. consequence curve, with an inclusion of upper tail losses and exclusion of lower tail losses (as shown in the figure below). The exact method of estimating the area under the curve and whether to include upper tail and/or lower tail losses will depend on the project / client use case. In absence of a clear project direction, we recommend using the same assumptions as Iris for your off-platform calculations.
Step 4: For each consequence of interest, assign the asset AAL by taking the maximum of the three hazard AALs
The AAL assigned to the asset will depend on which hazard (flame length at the parcel pixel, flame length at an adjacent pixel, or ember count at the parcel pixel) controls the risk.
Step 5: Use the AAL to qualitative risk rating tables in the Risk Matrices spreadsheet (linked in Section 9.) to determine the corresponding qualitative ratings for your building’s AALs for each consequence assessed (e.g., AAL, AAD)
- First, determine your client’s risk appetite – risk tolerant, risk neutral, or risk averse. If you do not know your client’s risk appetite, assume your client is risk neutral.
- For each consequence considered, select the appropriate risk matrix for your client’s risk appetite. The risk matrices for all risk appetites and consequences of interest are located at the following SharePoint link: Risk Matrices.xlsx
- Based on your calculated AAL or AAD, determine your risk rating.
# Appendix D2 - AAL to Risk Rating Matrices
Link to shared location (view-only): Risk Matrices.xlsx
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