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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Wildfire Risk Support via Satellite-Derived Vegetation Health and Land Surface Model Soil Moisture

Land Surface Model (LSM) and evaporative demand products provide advanced lead time to wildfire conditions that complement traditional fire indices and represent short-term changes that add context to overall, long-term drought conditions. Established fire indices typically use weather indicators (i.e., precipitation, temperature) and estimated dead fuel moisture to indirectly obtain land surface and sub-surface characterization. The convergence of LSM shallow and deep-layer soil moisture output and satellite-derived vegetation health combine to provide a tool for stakeholders to examine trends in the state of land surface conditions that can help assess wildfire threat. Satellite remote sensing data can constrain near-real time vegetation characteristics within the LSM and/or provide a derived stress index in order to help characterize the wildfire risk. In addition, a percentile product of soil moisture is derived from a comparison of current LSM conditions to the historical record of the LSM in order to put the current conditions in perspective relative to the season and geographic region. The 2015 season as well as the 2018 Camp Fire Complex in California were examined in terms of the changes in LSM soil moisture and vegetation states. Satellite vegetation health consistently showed decreases a month prior to wildfire initiation. Additionally, maximum changes in total column soil moisture corresponded with the greatest concentration of fire locations. While soil moisture deficits occurred in the shallow layers across northern California in 2018, significant deficits at all sub-surface levels were seen ahead of the Camp Fire event. This presentation will demonstrate the complementary value of LSM output and satellite measured vegetation health to diagnose short-term deficits in sub-surface soil moisture and the rapid decline in vegetation health which precedes large wildfire events.

Wildfire↗
DOE OSTI2022

Managing Power Systems-Induced Wildfire Risks Using Optimal Scheduled Shutoffs: Preprint

The growing demands for electricity and the increase in extreme weather conditions are putting unprecedented pressure on our electrical grids. Oftentimes, this pressure leads to electrical components failures which might ignite wildfires. This work develops a novel model to balance the reliability of power networks operations and risks of wildfires ignition by optimizing the operational schedule of power transmission networks considering time-varying risk measures that consider exogenous and operational factors. Energy storage systems are considered to deliver power during peak wildfire hours and enable temporal load shifting. The problem is formulated as a mixed-integer linear program that maximizes a weighted sum of the served power demand and the reduction in grid-induced wildfires risk. The results demonstrate the ability of the model to reduce wildfires risks significantly without considerable load shedding.

energy scheduling↗
DOE OSTI2024

Long duration battery sizing, siting, and operation under wildfire risk using progressive hedging

Battery sizing and siting problems are computationally challenging due to the need to make long-term planning decisions that are cognizant of short-term operational decisions. This paper considers sizing, siting, and operating batteries in a power grid to maximize their benefits, including price arbitrage and load shed mitigation, during both normal operations and periods with high wildfire ignition risk. Here we formulate a multi-scenario optimization problem for long duration battery storage while considering the possibility of load shedding during Public Safety Power Shutoff (PSPS) events that de-energize lines to mitigate severe wildfire ignition risk. To enable a computationally scalable solution of this problem with many scenarios of wildfire risk and power injection variability, we develop a customized temporal decomposition method based on a progressive hedging framework. Extending traditional progressive hedging techniques, we consider coupling in both placement variables across all scenarios and state-of-charge variables at temporal boundaries. This enforces consistency across scenarios while enabling parallel computations despite both spatial and temporal coupling. The proposed decomposition facilitates efficient and scalable modeling of a full year of hourly operational decisions to inform the sizing and siting of batteries. With this decomposition, we model a year of hourly operational decisions to inform optimal battery placement for a 240-bus WECC model in under 70 min of wall-clock time.

25 ENERGY STORAGE↗
NASA NTRS2023

Chile Wildland Fires: Augmenting Wildfire Risk Assessment Efforts with Satellite-based Measurements of Soil Moisture and Vegetation Health in Central and South-Central Chile

Since 2010, Central and South-Central Chile have recorded abnormally low annual precipitation, resulting in over a decade-long megadrought. This water deficit has driven more severe wildfires, which begin earlier in the year, last longer, and burn over significantly larger areas. Past studies indicated wildland fires propagate following vegetation stress and under certain soil moisture conditions. Our work further investigated the drivers of the unprecedented wildfire that devastated Central and South-Central Chile in 2017 and 2023. To that end, we leveraged NASA Earth observations from space to explore the link between terrestrial variables and wildland fires. We first delineated the burnt extent using data from Landsat 9 Operational Land Imager 2 (OLI-2), along with the combined information from Terra + Aqua Moderate Resolution Imaging Spectroradiometer (MODIS). Next, we analyzed vegetation health based on the Normalized Difference Vegetation Index (NDVI) and evapotranspiration (ET) products of Terra MODIS. Furthermore, we examined soil moisture data from the Soil Moisture Active Passive (SMAP) mission. As the megadrought continues, we found greater anomalies and stress in vegetation indices across the region. We also identified certain pre-fire conditions in soil moisture and evapotranspiration in the days and months leading to the recent wildfires. We compared these findings against control areas that were not impacted by wildfires. Using satellite-based NASA Earth observations, we were able to provide insights into potential indicators of wildfire risk, which can augment future risk assessment and management efforts.

Benjamin D Goffin↗
DOE OSTI2024

Enhanced Pacific Northwest heat extremes and wildfire risks induced by the boreal summer intraseasonal oscillation

The occurrence of extreme hot and dry summer conditions in the Pacific Northwest region of North America (PNW) has been known to be influenced by climate modes of variability such as the El Niño-Southern Oscillation and other variations in tropospheric circulation such as stationary waves and blocking. However, the extent to which the subseasonal remote tropical driver influences summer heat extremes and fire weather conditions across the PNW remains elusive. Our investigation reveals that the occurrence of heat extremes and associated fire-conducive weather conditions in the PNW is significantly heightened during the boreal summer intraseasonal oscillation (BSISO) phases 6-7, by ~50–120% relative to the seasonal probability. The promotion of these heat extremes is primarily attributed to the enhanced diabatic heating over the tropical central-to-eastern North Pacific, which generates a wave train traveling downstream toward North America, resulting in a prominent high-pressure system over the PNW. The ridge, subsequently, promotes surface warming over the region primarily through increased surface radiative heating and enhanced adiabatic warming. The results suggest a potential pathway to improving subseasonal-to-seasonal predictions of heatwaves and wildfire risks in the PNW by improving the representation of BSISO heating over the tropical-to-eastern North Pacific.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Security constrained optimal power shutoff for wildfire risk mitigation

Abstract Electric grid faults are increasingly the source of ignition for major wildfires. To reduce the likelihood of such ignitions in high risk situations, utilities use preemptive de‐energization of power lines, commonly referred to as Public Safety Power Shutoffs (PSPS). Besides raising challenging trade‐offs between power outages and wildfire safety, PSPS removes redundancy from the network at a time when component faults are likely to happen. This may leave the network particularly vulnerable to unexpected line faults that may occur while the PSPS is in place. Previous works have not explicitly considered the impacts of these outages. To address this gap, the Security Constrained Optimal Power Shutoff problem is proposed which uses post‐contingency security constraints to model the impact of unexpected line faults when planning a PSPS. This model enables, for the first time, the exploration of a wide range of trade‐offs between both wildfire risk and pre‐ and post‐contingency load shedding when designing PSPS plans, providing useful insights for utilities and policy makers considering different approaches to PSPS. The efficacy of the model is demonstrated using the EPRI 39‐bus system as a case study. The results highlight the potential risks of not considering security constraints when planning PSPS and show that incorporating security constraints into the PSPS design process improves the resilience of current PSPS plans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Wildfire Risk Reduction and Resilience Applications: A Summary of NASA’s DEVELOP 2022 Wildfire Projects

NASA’s DEVELOP Program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. DEVELOP maintains a balance of projects across nine application areas, one of which is Wildfires. DEVELOP's Wildfires application area supports pre-fire (fuel loading, fire risk), during (active fire detection), and post-fire (fire extent, intensity) monitoring and modeling. In 2022 so far, DEVELOP has conducted six projects with Wildfires as a primary or secondary component across a diverse set of study areas. This presentation introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision-making regarding wildfires.

Wildfire↗
NASA NTRS2022

Chile Wildfires: Utilizing NASA and NOAA Earth Observations to Determine Lightning-ignited Wildfire Risks in Central Chile

In recent years, Central Chile has experienced wildfires of increasing frequency and intensity which threaten natural resources and communities. The Corporación Nacional Forestal (CONAF) responds to wildfires caused by a variety of ignitions, including lightning, but it is difficult to determine the prevalence of lightning-ignited wildfires based solely on ground observations. In collaboration with CONAF and the Embassy of Chile, Agricultural Office, the team used Earth observations to map coincidence of lightning strikes and wildfire ignitions. The Active Fire Product of Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) identified wildfires as thermal anomalies, which the team compared to the lightning events detected by NOAA’s GOES-16 Geostationary Lightning Mapper (GLM). Next, the team mapped lightning strike frequency and lightning related wildfires across the study area. Finally, the team calculated and mapped a relative estimate of lightning-ignited wildfire vulnerability across the year, fire season (December – March), and off-season (April – November) by summing the following factors: lightning frequency, the Normalized Difference Moisture Index (NDMI) and land surface temperature (LST). These risks were then weighted by fuel availability. Preliminary analysis of the lightning fire relationship showed a spatiotemporal coincidence, primarily in the South-central region of study, near Temuco, and isolated areas on the Andean front. The team identified areas at risk of lightning-induced wildfires, predominantly in the northern third of the study area and along the Andean front. Adjusting the relative weight of risk factors and improving the lightning and fire coincidence map by clustering VIIRS thermal anomalies into fire events could reduce discrepancies and improve risk assessments for future work.

Christopher Matechik↗
DOE OSTI2024

Five Year Wildfire Risk Reduction Action Plan for the Electric Power Industry

The U.S. DOE and the Electric Power Research Institute convened a wildfire advisory group to bring together knowledge of ignition risks, electric utility needs, the applicability of available technology, and existing technology gaps. The outcome is a five-year action plan, containing recommendations on RD&D projects, that if completed by the year 2030, may accelerate the power industry’s ability to substantially reduce wildfire ignition risks. When reviewing this document please consider it is a snapshot in time for the years 2023 and 2024, could be obsolete by the end of the decade. The following list comprises the titles and topics for the proposed follow-on demonstrations: 1. Hybrid Undergrounding RD&D, 2. Live Downed Conductor Detection RD&D, 3. Fault Energy Reduction RD&D, 4. Advanced Inspection and Response Drone, 5. Fault and PQ Event Signature Repository, 6. Advanced and Intelligent Sensor Nodes, 7. Fire Friendly Asset Coatings and Coverings, and 8. Environmental Monitoring Action Plan.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2022

Idaho Wildfires II: Assessing the Relationship Between Drought Indicators and Wildfire Risk to Enhance Hazard Modeling and Inform Mitigation Planning

The western United States has experienced twenty years of increased and prolonged drought which have exacerbated wildfire hazards. These jeopardize population centers through increased risks to ecosystem services, local economies, and livelihoods. The Idaho Office of Emergency Management, Water Resources, and Department of Lands are seeking methods to dynamically monitor these conditions and update models that inform hazard mitigation planning and resource allocation. Towards this, these agencies partnered with NASA DEVELOP to produce drought-enhanced wildfire hazard models. Part of a two-term project, the two teams revised the state’s static wildfire hazard model with refined data layers and remotely-sensed data to reflect dynamic ecosystem responses to drought conditions and wildfire potential. Our team distinguished between rangeland and forestland ecosystems, and investigated relationships between drought metrics and vegetation condition using TerrSet Earth Trends Modeler. This analysis determined that total precipitation at a 5-month lag interval (r 2 = 0.72) along with the Evaporative Stress Index (r 2 = 0.69); and precipitation at a 5-month interval (r 2 = 0.42) were important drivers in rangeland and forestland, respectively. These driver variables were incorporated into a temporally dynamic wildfire hazard map. Our team used linear regression to correlate hazard ratings with wildfire frequency. For the year 2020, neither the enhanced hazard model (p < 0.10, r 2 = 0.01) nor the state’s static model (p < 0.05, r 2 = 0.03) were strongly correlated with actual wildfire frequency as they expressed an inverse relationship between wildfire hazard and frequency. This suggests wildfire occurrence is complex and not necessarily driven by the variables used.

Wildfire↗
DOE OSTI2024

Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk

Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.

Science & Technology - Other Topics↗
DOE OSTI2023

Wildfires Risk Evaluation of the System (WiRES) Framework Tool

The invention is a set of algorithms and calculations for a performance-based model to translate wildfire burn potential to actual transmission line outages in real-time in an interactive application that uses geospatial data sets on the wildfire burn potential as well as detailed grid topographical datasets.

Chalishazar, Vishvas↗
NASA NTRS2007

A Rapidly Prototyped Vegetation Dryness Index Evaluated for Wildfire Risk Assessment at Stennis Space Center

MVDI, which effectively involves the differencing of NDMI and NDVI, appears to display increased noise that is consistent with a differencing technique. This effect masks finer variations in vegetation moisture, preventing MVDI from fulfilling the requirement of giving decision makers insight into spatial variation of fire risk. MVDI shows dependencies on land cover and phenology which also argue against its use as a fire risk proxy in an area of diverse and fragmented land covers. The conclusion of the rapid prototyping effort is that MVDI should not be implemented for SSC decision support.

Ross, Kenton↗