Wildfire Risk Analysis Solution

The vendor required to provide wildfire risk analysis software solution that includes wildfire reduction risk modeling, forecasting, and predictive analytics to enhance operational decision-making for safeguarding the community, infrastructure, and electrical grid assets.
- Risk mitigation (wildfire risk reduction modelling)
•    Perform a detailed analysis of risk using weather research forecast model (WRF) re-analysis climatology data combined with wildfire spread simulations and calculating consequence metrics for possible asset ignitions. 
•    Identify the weather scenarios to be used from the WRF re-analysis data. 
•    The WRF re-analysis data will be provided as a separate product deliverable. 
•    The results in a software application that facilitates review, query, filtering, and exporting of the analysis results. 
•    The application will accommodate multiple analysis runs, allowing for the historical tracking of risk over time on a per-asset basis. 
•    Mitigation planning models and risk spend efficiency (RSE) models to properly calculate risk reduction. 
•    The product must support the development of this analysis as part of the probability of ignition (POI) model development. 
•    Contractor staff to work with agency to understand the output metrics and provide guidance on the evaluation of the metrics and best practices. 
•    The primary conditional risk metrics shall include:
o    Fire size potential 
o    Population impacted 
o    Buildings threatened 
o    Estimated buildings destroyed 
o    A set of fire behavior outputs (i.e., rate of spread, flame length, fire behavior index, etc.) 
o    Integration with the POF and POI data to derive expected risk metrics using the conditional risk metrics listed above.
- WRF re-analysis weather data
•    Develop a 20-year historical re-analysis dataset. 
•    2 km resolution, hourly data for every day in the historical period. 
•    Analyze the data to provide the necessary weather variables to support the fire behavior analysis. 
•    Conduct annual updates to add to the re-analysis dataset to ensure current conditions are included. 
•    Integrate the data into the product modeling environment to facilitate the fire modeling runs. 
•    Leverage the historical re-analysis data to provide historical risk percentiles in the operational environment, providing context to daily operational risk forecasts, i.e., percentile relative to historical conditions.
- Surface and canopy fuels data
•    Provide a projected dataset of surface and canopy fuels to support the analysis. 
•    The baseline for this data is the current, up-to-date fuels. 
•    Provide adjustments to reflect future conditions, such as 2030 fuels, for use in risk analysis. 
•    Collaborate with the agency team to determine the appropriate vintage of fuels data that is necessary in consideration of the agency service territory. 
•    This data will be updated regularly to match modeling timelines using the operational fuels data.
•    The GIS datasets will be provided separately to support external agency project usage.
- Herbaceous and woody live and dead fuel moisture (LFM) and (DFM) data
•    The product shall provide the LFM model using remote sensing-derived vegetation indices, extending methods to high resolution (30 m), to create two additional products required for fire behavior modeling (leveraging readily available sentinel imagery and Modis historical data). 
•    The product shall ingest the LFM data into risk analysis software. 
•    The model has also been successfully used to develop historical LFM and DFM for back-casting risk to support historical analysis. 
•    Produce dead fuel moisture (DFM) data along with the LFM model daily.

- Contract Period/Term: 3 years
- Pre-Offer Conference Date: November 18, 2025
- Questions/Inquires Deadline: November 20, 2025