Fire Behavior and Effects Model Evaluation and Demonstration across Innovation Landscapes.
U.S. Geological Survey (USGS) scientists are working with the U.S. Department of Defense (DoD) Environmental Security Technology Certification Program (ESTCP) to demonstrate and improve how next generation fire behavior models inform land management decision-making for partners within the National Innovation Landscape Network (Innovation Landscapes Network). Specifically, this project looks to evaluate and advance the utility of powerful physics-based fire behavior models for adaptive management in southwestern ecosystems.
Background
Wildfire and the cascading hazards that it causes, including the loss and damage of natural and built infrastructure, present key challenges for partners of the National Innovation Landscape Network (NILN). Current commonly employed tools for assessing wildfire risk and behaviors were developed decades ago and have not kept up with the pace of recent technological and methodological developments. Next generation fire behavior models, advancements in fire science, and other emerging technologies together have potential to address critical land management concerns, but the full range of possible management applications – including across different areas of the United States – has yet to be explored and evaluated.
To provide southwestern land managers the best technology and science for predicting wildland fire behaviors and effects, the USGS has partnered with the DoD ESTCP, Los Alamos National Laboratory (LANL), the U.S. Forest Service Rocky Mountain Research Station (USFS-RMRS), Colorado State University (CSU), and a variety of land management partners and stakeholders within the NILN to expand the utility of next generation fire behavior modeling to southwestern ecosystems. With these partners, the USGS is working to adapt and evaluate current fire and fuel modeling tools, including QUIC-Fire (Linn et al., 2020) and FIRETEC (Linn et al., 2002), to perform on southwestern landscapes.
Objectives and Methods
The USGS is using a three-pronged approach to evaluate and advance next generation fire behavior modeling within southwest ecosystems.
1. Collaborate with the Fort Huachuca Military Installation in Arizona to demonstrate how next generation fire behavior models and existing landscape datasets can be leveraged to inform land management decision making within Fort Huachuca Sentinel Landscape. Land managers have identified wildfire as a major concern to military readiness and operations within the installation and have requested evaluation of the effectiveness of their fuel treatments at mitigating severe wildfire behavior, particularly on land inhabited by the federally protected Mexican Spotted Owl (Strix occidentalis lucida).
2. Design and automate a process to derive high-fidelity 3-dimensional canopy structure and bulk properties from aerial LiDAR for use in fire behavior models including the Fire Dynamics Simulator (FDS), FIRETEC, the Forest Vegetation Simulator (FVS), and QUIC-Fire. This work relies on close collaboration with LANL, CSU, and the USFS-RMRS, and has culminated in a publicly available R-package (GitHub - Cloud2Trees).
3. Global scientific review jointly led by the USGS and CSU assessing the various applications of fire behavior models within the scientific literature. By reviewing the uses of fire behavior models, this review project will help researchers and land managers understand how models are used within the research community and encourage greater thoughtfulness into future model selection and application.
U.S. Geological Survey (USGS) scientists are working with the U.S. Department of Defense (DoD) Environmental Security Technology Certification Program (ESTCP) to demonstrate and improve how next generation fire behavior models inform land management decision-making for partners within the National Innovation Landscape Network (Innovation Landscapes Network). Specifically, this project looks to evaluate and advance the utility of powerful physics-based fire behavior models for adaptive management in southwestern ecosystems.
Background
Wildfire and the cascading hazards that it causes, including the loss and damage of natural and built infrastructure, present key challenges for partners of the National Innovation Landscape Network (NILN). Current commonly employed tools for assessing wildfire risk and behaviors were developed decades ago and have not kept up with the pace of recent technological and methodological developments. Next generation fire behavior models, advancements in fire science, and other emerging technologies together have potential to address critical land management concerns, but the full range of possible management applications – including across different areas of the United States – has yet to be explored and evaluated.
To provide southwestern land managers the best technology and science for predicting wildland fire behaviors and effects, the USGS has partnered with the DoD ESTCP, Los Alamos National Laboratory (LANL), the U.S. Forest Service Rocky Mountain Research Station (USFS-RMRS), Colorado State University (CSU), and a variety of land management partners and stakeholders within the NILN to expand the utility of next generation fire behavior modeling to southwestern ecosystems. With these partners, the USGS is working to adapt and evaluate current fire and fuel modeling tools, including QUIC-Fire (Linn et al., 2020) and FIRETEC (Linn et al., 2002), to perform on southwestern landscapes.
Objectives and Methods
The USGS is using a three-pronged approach to evaluate and advance next generation fire behavior modeling within southwest ecosystems.
1. Collaborate with the Fort Huachuca Military Installation in Arizona to demonstrate how next generation fire behavior models and existing landscape datasets can be leveraged to inform land management decision making within Fort Huachuca Sentinel Landscape. Land managers have identified wildfire as a major concern to military readiness and operations within the installation and have requested evaluation of the effectiveness of their fuel treatments at mitigating severe wildfire behavior, particularly on land inhabited by the federally protected Mexican Spotted Owl (Strix occidentalis lucida).
2. Design and automate a process to derive high-fidelity 3-dimensional canopy structure and bulk properties from aerial LiDAR for use in fire behavior models including the Fire Dynamics Simulator (FDS), FIRETEC, the Forest Vegetation Simulator (FVS), and QUIC-Fire. This work relies on close collaboration with LANL, CSU, and the USFS-RMRS, and has culminated in a publicly available R-package (GitHub - Cloud2Trees).
3. Global scientific review jointly led by the USGS and CSU assessing the various applications of fire behavior models within the scientific literature. By reviewing the uses of fire behavior models, this review project will help researchers and land managers understand how models are used within the research community and encourage greater thoughtfulness into future model selection and application.