Comprehensive Open Source Development of Next Generation Wildfire Models for Grid Resiliency

The development of next-generation wildfire risk forecasting models to inform effective near-term management and long-term planning decisions.

Spatial Informatics Group, LLC


Pleasanton, CA

Recipient Location


Senate District


Assembly District



Amount Spent



Project Status

Project Update

A beta version of the near-term fire risk forecast tool became available in May 2020 ( and continues to be tested and refined with user input. The tool displays forecasts for active fires and fire risk at a five-day horizon. An API allows for flexible integration with an organization's unique and existing workflows to assist in tactical fire and ignition risk decision-making. The research team also developed beta versions of experimental fire size distribution and fractional fire severity class models covering all of California. They utilized a sample of the beta version fractional fire severity models with observed historical fire sizes to begin testing and validating a bootstrapping procedure for expressing spatial autocorrelation in the clustering of high severity burn patches within fire perimeters.

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The Issue

Many aspects of wildfires in California have changed in the past several decades, including climate patterns and the development of human infrastructure near wildlands. The impacts of wildfire on the electric grid have resulted in increased costs and reduced safety and reliability. Understanding the risks associated with wildfire remains challenging. Operational wildfire behavior models are empirical and not well suited for predicting extreme fire behavior. Therefore, key stakeholders responsible for managing the grid -- including IOUs and state agencies -- lack tools and information that could improve near-term management and long-term planning decisions.

Project Innovation

The project is advancing wildfire science by incorporating the interaction of tree mortality and extreme fire weather into next-generation fire models. The project is developing zero-to-five-day risk forecasts for the grid with predictive capabilities, and computational efficiency and scalability. To support planning, the team is developing long-term fire projections using a coupled fire-climate-vegetation statistical and dynamical model to integrate the latest climate projections, tree mortality, development in the wildland-urban interface, and adaptation strategies. To integrate the models into electric utility management and planning, the team is facilitating workshops with IOUs. To support the California's Fifth Climate Change Assessment, the team is developing a web-based scenario analysis tool to visualize and explore the impacts of climate change and adaptation strategies on the grid.

Project Goals

Develop methodology to optimize weather station configuration.
Improve understanding of the relationship of extreme weather conditions and wildfire.
Improve understanding of fuels, fire behavior and how it is distributed across California.
Develop near-term fire risk and spread forecasts models at a 0-to-5-day temporal scale and at a fine spatial scale.
Develop coupled statistical/dynamical fire-climate-vegetation models to run long-term wildfire risk projections.

Project Benefits

The project will aid regulators and stakeholders in meeting statutory goals by addressing critical fire science gaps and applying the science to provide advanced forecasting capability. Specifically, the project will: 1) advance the science of measuring, modeling, and analyzing extreme weather events, tree mortality, and fire spread at scale; 2) advance risk modeling frameworks to include wind extrema, statewide maps of fuel loads, updated parameterizations, and indicators of where risk forecasting may underestimate fire risk due to gaps in science; and 3) advance the integration of science relating to vegetation dynamics, the wildland-urban interface, land-use, climate, and adaptation strategies, by building on existing models and comparing approaches.

Lower Costs


The project seeks to improve IOU planning and decision-making related to wildfire risk, improving grid reliability and safety and lowering costs.

Greater Reliability


With the use of more granular, dynamic fire-spread models, mitigation activities can be more targeted, and damages associated with fire and outages can be reduced.

Increase Safety


Safety will be improved as IOUs can better plan for maintenance cycles to avoid areas of elevated fire risk, reducing the risk of injury and loss of life.

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