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    <title>Research in Progress (RIP)</title>
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
    </image>
    <item>
      <title>Generating reliable freight disruption measures with freight telematics data</title>
      <link>https://rip.trb.org/View/2684220</link>
      <description><![CDATA[Freight network resilience is critical for economic stability, especially during disasters and infrastructure failures. This study refines disruption measures using Robinsight, COMPASS IOT, and Robinsight telematics data, alongside WAZE crowdsourced data and infrastructure-based instrumentation (TN RDS). Building on prior research, we analyzed freight mobility impacts from events like the Oregon Durkee Fire (2024), Hurricane Helene, and major bridge closures (I-40, I-55, I-84).

Year 3 focuses on validating key disruption indicators, enhancing predictive models, and integrating emerging data sources to assess infrastructure failures and safety risks from freight detours. Aligned with US Department of Transportation priorities, this research provides transportation agencies with actionable insights to improve freight mobility, inform infrastructure investments, and strengthen supply chain resilience. The findings will support data-driven decision-making, ensuring a more adaptive and robust freight transportation system.]]></description>
      <pubDate>Wed, 25 Mar 2026 16:27:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2684220</guid>
    </item>
    <item>
      <title>Legal Aspects of Airport Programs. Topic 18-02. Role of Legal Counsel During an Airport Emergency</title>
      <link>https://rip.trb.org/View/2625812</link>
      <description><![CDATA[All airports face risks from emergencies, whether man-made, mechanical, or natural. While 14 C.F.R. Part 139 Airports are required to establish an Airport Emergency Plan to address at least nine types of emergencies, some airports also create emergency plans to manage and plan for their response. The role of the Airport’s legal counsel in the AEP should be examined at various airports, considering steps airport legal counsel can take preparing, responding, recovering from major emergencies to support prompt emergency response and mitigate liability and risk to the airport.  

The report will provide analysis to explain the legal requirements for an Airport Emergency Plan (AEP) under 14 C.F.R. Part 139, identify other statutes and regulations that create responsibilities for emergency response outside of 14 C.F.R. Part 139, as well as other emergency plans airports implement. Additionally, it should evaluate tools an airport legal counsel can utilize, both in terms of emergency planning and conducting typical airport business to help manage potential risks during an emergency. It should discuss the roles of legal counsel and resources they can utilize during and immediately following the initial response and examine the benefits and drawbacks to these approaches. The report should include two or three case studies that explore whether and how legal counsel supports the Airport in responding to and recovering from an emergency.]]></description>
      <pubDate>Thu, 20 Nov 2025 15:52:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625812</guid>
    </item>
    <item>
      <title>Evaluating isolated areas, alternative routing, and economic impact for resilient transportation in North Carolina</title>
      <link>https://rip.trb.org/View/2604572</link>
      <description><![CDATA[Natural disasters, such as flooding, landslides, storm surge, and wildfire can cause severe impacts to the social, environmental, economic, and transportation systems of North Carolina. At the same time, transportation infrastructure plays a critical role in natural disaster response and recovery efforts during these natural disaster events. Unfortunately, extreme hazard events such as these are occurring with greater frequency and intensity. These events can negatively impact road functionality and lead to the loss of essential services. According to the National Oceanic and Atmospheric Administration (NOAA), weather-related disasters have cost over $1.875 trillion since 1980. The built environment isn’t designed to handle many of the impacts that are happening due to extreme hazard events. For example, stormwater systems, culverts, and tidal pumps were all designed for past events— not current and future conditions. The failure of these systems will impact  communities to a level where they may not be able to return to normal for months or years.

Transportation planners and engineers from North Carolina Department of Transportation (NCDOT), as well as other federal, state, and local agencies across the state, and in close collaboration with emergency managers, are increasingly looking for better ways to address these issues and become more resilient, while simultaneously planning for a more reliable transportation network. Planning for extreme events is about finding ways for systems to bounce back to normal as quickly as possible after the negative impacts of an event. One particular issue that NCDOT faces is the rerouting of traffic during and immediately after natural disaster events. Typical considerations include traffic volumes, current conditions, roadway capacities, and overall safety. However, there are other considerations such as the overall economic impact, including issues like commerce, commute times for individuals traveling between work and home, access to essential services, and disruption to local businesses, that should also be taken into account. These impacts can be further compounded in areas where entire networks of roads, such as a neighborhood or community, become cut-off due and thus isolated. This isolation can be due to such factors as a damaged bridge or road washout. Worse yet, these impacts can often last for days or even months. By identifying these areas ahead of time, and better understanding the potential economic impacts, NCDOT and other agencies can be better equipped when planning for a more resilient and sustainable transportation infrastructure system.

The joint proposal team, consisting of researchers from the University of North Carolina at Asheville’s National Environmental Mapping and Applications Center (NEMAC) and the University of North Carolina at Charlotte, proposes a comprehensive and innovative approach to helping NCDOT better understand the forces behind transportation route and commute pattern disruptions, and their effects on local economies, in the face of an increase in extreme hazard events. Through comprehensive user research and discovery, data analysis, and the development of decision-making workflows, the project team seeks to provide NCDOT with actionable insights to better plan and respond to disruptions related to extreme hazard events, ultimately improving infrastructure reliability and community access.]]></description>
      <pubDate>Tue, 30 Sep 2025 11:13:25 GMT</pubDate>
      <guid>https://rip.trb.org/View/2604572</guid>
    </item>
    <item>
      <title>Guide to Operational Resilience for Disruptive Events at Airports</title>
      <link>https://rip.trb.org/View/2588326</link>
      <description><![CDATA[Airports must deal with an array of challenges caused by infrequent but highly disruptive events, extreme weather, cyberattacks, cascading irregular operations, and other disruptions that can severely impair or halt critical functions and have an impact on facilities, passengers, employees, stakeholders, and the surrounding communities. Airports must be operationally resilient to withstand, adapt to, and continue providing service during any disruptive event. This requires many airport functional areas and stakeholders that may be affected (including operations, safety, emergency management, planning, and tenants) to have a role in the response. 

Research is needed to deliver clear, actionable guidance that enables airports of all sizes to build robust operational resilience plans for disruptive events.

OBJECTIVES: The objectives of this research are to (1) develop a guide to support airports of all sizes building robust operational resilience plans to respond to disruptive events of any type by leveraging existing resources, tools, data, and proven practices, (2) develop a checklist for building operational resilience, and (3) identify funding sources, eligibility criteria, and application guidance for developing operational resilience plans.]]></description>
      <pubDate>Tue, 12 Aug 2025 10:33:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2588326</guid>
    </item>
    <item>
      <title>A Guide for Airport All-Hazard Recovery Planning</title>
      <link>https://rip.trb.org/View/2588320</link>
      <description><![CDATA[Airports face different types of incidents and disasters, each with their own level of severity, which may result in major operational disruption, contributing to financial setbacks and emotional distress among airport employees, tenants, and passengers. Resources such as FAA AC 150-5200-31C, Airport Emergency Plan and the Federal Emergency Management Agency’s National Response Framework, Comprehensive Preparedness Guide 101, and the National Incident Management System provide foundational guidance to prepare U.S. airports to respond to all types of incidents and disasters. However, many airports do not have detailed recovery plans as they are difficult to develop and airport-specific guidance on incident and disaster recovery is limited.

Research is needed to support airports in understanding the recovery process following all-hazard incidents and disasters, whether they are small incidents that cause minimal disruptions or major disasters that cause significant disruptions and require intervention from external stakeholders.

The objective of this research is to develop a guide for airports to plan and execute a recovery from all-hazard incidents and disasters. The guide should be scalable to all types of airports and speak to airport emergency planners and executives. The guide must include an executive summary and a template for an airport recovery plan. The template should be inclusive of everything from initial recovery to back to normal operations and include checklists for short-, medium-, and long-term actions.]]></description>
      <pubDate>Tue, 12 Aug 2025 09:50:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2588320</guid>
    </item>
    <item>
      <title>Analyzing Pre- and Post-Coastal Hazard Pavement Conditions to Optimize Response Strategies for Coastal Infrastructure Resilience</title>
      <link>https://rip.trb.org/View/2427611</link>
      <description><![CDATA[Texas' coastal region stretches over 367 miles along the Gulf of Mexico which is a significant ecological and economic zone encompassing beaches, marshes, estuaries, and barrier islands. This area supports a vibrant tourism industry, international trade, commercial fishing, and energy production, with major ports such as Houston, Corpus Christi, and Galveston playing vital roles. However, Texas' coastline faces increasing risks from natural hazards, necessitating efficient and effective infrastructure response strategies to mitigate impacts and ensure rapid recovery. This research aims to investigate the effects of coastal hazards on pavement conditions and to use network analysis for optimizing pavement infrastructure response, maintenance decisions, and treatment allocation to support coastal communities. The study focuses on Houston which is a key urban center exposed to frequent coastal hazards.  Hurricane Harvey was selected as a case study for in-depth analysis.

Initially, the research team will conduct a comprehensive literature review of existing studies focusing on methods used for evaluating pavement conditions before and after coastal hazards. This review aims to identify best practices and effective methodologies for enhancing pavement durability and performance. Following this, the team will analyze historical pavement condition data from Houston before Hurricane Harvey, focusing on different pavement types (ACP, CRCP, JCP) and utilizing statistical models to understand data variability and characteristics. Subsequently, the team will analyze pavement conditions in Houston following Hurricane Harvey. This analysis will involve comparing pre- and post-Harvey data to assess the impact on pavement performance. Statistical methods will be applied to evaluate distress distribution and severity of pavements. Additionally, the research will evaluate the effectiveness of pavement condition analysis models for better maintenance prioritization post-coastal hazards. This step aims to understand how maintenance strategies evolve post-disaster and to enhance decision-making for maintenance planning. The final phase of the research focuses on developing tailored strategies for improving infrastructure durability. This involves reviewing existing strategies including customizing them for Texas' coastal context and assessing their effectiveness through scenario analysis. The expected outcome of this research is to provide valuable insights into pre- and post-coastal hazard pavement conditions in Houston. By leveraging network analysis models, the study aims to inform maintenance decisions that prioritize efficient response measures. The findings will contribute to developing strategies that enhance durability for coastal pavement infrastructure.
]]></description>
      <pubDate>Thu, 12 Sep 2024 15:33:49 GMT</pubDate>
      <guid>https://rip.trb.org/View/2427611</guid>
    </item>
    <item>
      <title>Present and future hazard scenario database for coastal infrastructural 
resilience and maintenance planning</title>
      <link>https://rip.trb.org/View/2425156</link>
      <description><![CDATA[This project seeks to characterize present and future flooding impacts for coastal communities by using a database of historical and synthetic storms to force a suite of hydrodynamic and wave models for a coastal community. Projections of wave, surge, and flooding will be particularly focused on areas near critical infrastructure components (e.g., roads critical for evacuation and recovery; bridge piers, etc.). Synthetic storms have many of the same trends as the historical storms but have random starting and ending locations along established tracks, along with a distribution of hurricane parameters along these tracks. Wind fields from the hurricanes can be calculated from the parameters, and since the parameters have a probability of occurrence associated with them, surge probability and susceptibility can be determined. In addition, upland discharge values will be added to represent flooding from rainfall and riverine sources. The overall product will be a set of maps delineating flooding risk and susceptibility. For selected infrastructural components of particular concern, a phase-resolved wave model, driven by flooding and wave events from hurricanes, can be used to simulate the time-dependent forces from hurricane-driven waves and help pinpoint potentially damaging conditions within hurricane events. Finally, the results will be used to evaluate the impact of flooding on evacuation and traffic flow.]]></description>
      <pubDate>Tue, 03 Sep 2024 19:50:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2425156</guid>
    </item>
    <item>
      <title>Generating reliable freight disruption measures with freight telematics data (Year 2)</title>
      <link>https://rip.trb.org/View/2422948</link>
      <description><![CDATA[In the aftermath of disasters that challenge the resilience of transportation networks, the urgency for planning for rapid mobility and recovery has been underscored. The primary objective of resilience is to enable transportation agencies to prepare more effectively for such events. In this light, resilience measures serve as a critical tool, providing a means to assess the impact of disruptions and inform strategic investments to mitigate these occurrences. The first year of the study team’s research addressed the critical challenges faced by states and agencies in measuring freight network systems: the scarcity of comprehensive data and the inadequacy of analytical methods. While there is substantial data available on the movement of people and passenger vehicles, understanding freight movements—especially under disruptive scenarios—poses distinct challenges. Freight movements, governed by corporate supply chain decisions, are subject to constant change due to various economic conditions and span multiple jurisdictions and transport modes. Moreover, methods to capture and analyze data that encompasses these complex dynamics have been limited. With a focus on these challenges, the study team’s initial research presented a novel framework that leveraged Robinsight telematics data to bridge this gap. In the first year, the study team has delved into the telematics data to explore its capacity for developing robust freight network resiliency measures, with the trucking sector in Tennessee and the Pacific Northwest.]]></description>
      <pubDate>Thu, 29 Aug 2024 17:29:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2422948</guid>
    </item>
    <item>
      <title>Identification of Unprecedented Coastal Flooding Hotspots for Highway Network Durability </title>
      <link>https://rip.trb.org/View/2422886</link>
      <description><![CDATA[The proposed work outlines an innovative approach aimed at constructing a comprehensive framework and toolsets for evaluating unprecedented coastal flood risks while considering the highway network's durability. This approach involves integrating detailed highway network information with an artificial intelligence (AI) based flood model. The intellectual merit of this project resides in leveraging AI algorithms, hydrodynamic numerical simulations, road risk scoring, and remote sensing techniques to (1) develop a super-resolution, physically informed AI algorithm to improve flood hazard mapping on a road network scale and (2) transfer research outputs to operations for public benefits. ]]></description>
      <pubDate>Thu, 29 Aug 2024 14:08:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2422886</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Airport Practices. Topic S03-21. Managing All Phases of a Wild Fire Incident at Airports to Safeguard Critical Infrastructure</title>
      <link>https://rip.trb.org/View/2413912</link>
      <description><![CDATA[Wild fires wreak havoc across the country. In 2022 there were over 7 million acres burned throughout the United States. The devastating effects of the Colorado Marshall Fire in 2021 showcased how fast fires can engulf and destroy infrastructure. Wild fire events have continued to increase in intensity and frequency. These events have necessitated that the national airport community shift focus from strictly aviation related incidents to an all-hazard approach. The infrastructure associated with airports can be vital to continued operations, and any disruption in service could have cascading effects on the National Airspace System. Airports should begin to consider the probability of wild fires and protect infrastructure that keeps the airports operational. Not all infrastructure carries the same criticality, and not all infrastructure will require additional mitigation efforts. 

This synthesis will describe the practices for managing all phases of a wild fire incident that impact airport critical infrastructure. The audience for this synthesis are airport operators that do not have plans in place for managing all phases of a wild fire incident. 

]]></description>
      <pubDate>Mon, 05 Aug 2024 19:47:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/2413912</guid>
    </item>
    <item>
      <title>Prediction of Bridge Inventory Characteristics using Machine Learning</title>
      <link>https://rip.trb.org/View/2404273</link>
      <description><![CDATA[This project will develop a methodology and machine learning tool for predicting key characteristics of bridges in a bridge inventory. The machine learning tool will use individual bridge information available from the National Bridge Inventory (NBI) to predict other bridge characteristics that are better aligned with predictions of current bridge condition ratings and bridge performance in natural hazards. The methodology will help DOTs better quantify the current state of their bridge infrastructure, identify prioritization for modernization and retrofit, and will enable more realistic emergency planning for natural hazards and disasters. ]]></description>
      <pubDate>Sun, 21 Jul 2024 15:09:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2404273</guid>
    </item>
    <item>
      <title>Assessment of Autonomous Vehicle Sharing for Evacuation and Disaster Relief</title>
      <link>https://rip.trb.org/View/2353428</link>
      <description><![CDATA[Description: This research project begins a new line of inquiry that explores how privately-owned autonomous vehicles may be used in pre-impact assisted evacuation and post-impact relief distribution. The research team starts by investigating whether the public in South Carolina would be willing to share their future autonomous vehicle’s time to assist with evacuation and post-impact relief distribution, in the case where trucks are unable to complete a route. Such a situation may arise when there is some infrastructure damage and height or weight limits are a concern for the operational routes, but it is still safe to use smaller vehicles. The team also identifies and explores the public’s concerns and potential barriers and limits to sharing. This initial exploration will help identify the feasibility of a related future system.

Intellectual Merit: The overall goal of this project is to help prepare transportation and emergency management agencies for the near future when autonomous vehicles are more prevalent.

Broader Impacts: if such a system were developed, the government’s cost of assisted evacuation could be lowered and humanitarian relief distribution could also be facilitated. Benefits to society include additional resources for evacuation and obtaining relief supplies and active citizen engagement in helping their “neighbors.”

Technology Transfer Plan: The project findings will be disseminated through a webinar for practitioners, the research community, and the public.]]></description>
      <pubDate>Mon, 25 Mar 2024 15:43:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/2353428</guid>
    </item>
    <item>
      <title>Flood Assessment System for TxDOT (FAST)</title>
      <link>https://rip.trb.org/View/2359105</link>
      <description><![CDATA[The Texas Department of Transportation (TxDOT) wishes to move from a reactive to a proactive response during flood emergency operations. Real-time flood map services provide valuable information for TxDOT flood decision making. The National Weather Service initiated the operation of real-time flood inundation maps for Texas in October 2023. The research team will create a Flood Assessment System for TxDOT as an additional set of real-time flood maps to describe flood impact on the road and bridge system. These maps will be distributed to TxDOT's Maintenance Division staff as web services and tested in large scale flood emergency response exercises conducted with TxDOT Districts. The research team will operate and maintain 80 RQ-30 stream gages to support flood forecasting and decision making. Researchers will refine the targeted approach for RQ-30 velocity sensor calibrations to support timely rating development using velocimetry. As many of the 80 RQ-30 gauges as possible will be added to the Interagency Flood Risk Management (InFRM) Flood Decision Support Toolbox. Combining novel gauging techniques with inundation mapping provides real-time streamflow information and transportation flood impacts that enable scenario planning and proactive actions to flood events. This project will be a continuation of Project 0-7095 "Evaluating Improved Streamflow Measurement at TxDOT Bridges."]]></description>
      <pubDate>Mon, 25 Mar 2024 10:40:52 GMT</pubDate>
      <guid>https://rip.trb.org/View/2359105</guid>
    </item>
    <item>
      <title>Analyzing Transit-based Evacuation Demand in Hurricanes</title>
      <link>https://rip.trb.org/View/2292741</link>
      <description><![CDATA[Large-scale evacuation events have become the norm in the Gulf of Mexico Region due to
the impacts of climate change. Meanwhile, population growth has pushed more residents into flood-prone areas. Previous hurricane evacuations have seen massive congestion on primary evacuation routes. Additionally, many historically- disadvantaged populations, such as minority, low-English-proficiency, low-income, carless, senior, and/or disabled individuals, have faced difficulties in evacuations. Mass transit and rail have the potential to serve their travel needs during evacuations. What is needed is an accurate estimation of transit-based evacuation demand in hurricanes, so that public transit can be appropriately used to reach those at-risk populations.
To tackle this problem, the researchers propose to leverage the anonymized GPS trajectory data
(generated from mobile devices such as smartphones and smartwatches), the General Transit Feed Specification (GTFS) and/or GTFS Realtime data, the survey data collected from the disadvantaged populations, and public comments on unmet transit needs to estimate the transit-based evacuation demand during hurricanes. The goal of this research is to study transit vehicles and their use during hurricane evacuation events by collecting, analyzing, and integrating multi-source datasets, particularly focusing on understanding the travel needs of disadvantaged populations. Estimating transit-based evacuation demand (i.e., existing transit use and unmet travel needs) during hurricanes will be a focal point. This proposed research aims to improve understanding of hurricane evacuation process and enhance emergency 
planning and management with equity prioritized. This research will also help determine how transit services may be improved during such events to facilitate safe, efficient, and effective evacuations, particularly the evacuations of disadvantaged populations. The proposed research will be accomplished via five tasks:
• Task 1 - Meeting with local stakeholders (state/local DOT, city managers and planners,
NGOs, among others) to seek their inputs and feedback for our research design, results,
and products;
• Task 2 - Transit-based evacuation trip inference using GPS and GTFS data, where the researchers will use the individual-level movement data generated from mobile devices (i.e., GPS data) along with the bus schedules from GTFS data to infer which trips are transit travel during evacuations;
• Task 3 - Survey data collection and analysis, where the survey will be widely distributed
through multiple channels to ensure the representativeness of the sample. Particularly, the PIs will collaborate with the established contacts to reach marginalized communities, and Qualtrics survey panel will also be leveraged to help collect a representative sample;
• Task 4 - Transit-based evacuation demand estimation by integrating the transit trip
inference results from Task 2 and the reported unmet demand from Task 3; and
• Task 5 - Final report and policy brief.
The researchers will use Lee County, FL and New Orleans, LA as the study areas, as they have been frequently impacted by hurricanes and ordered large-scale evacuations in the past decade. Particularly, Lee County experienced significant human loss and damage in the 2022 Hurricane Ian, while New Orleans was severely impacted by the 2021 Hurricane Ida and 2005 Hurricane Katrina. Zhao has ongoing research focusing on Hurricane Ian evacuation analysis and she has established local contacts in Lee County, FL, and Tian has ongoing working relationships with stakeholders in New Orleans, LA. Furthermore, Zhao and Tian are physically located in FL and LA, who are well positioned to conduct local community engagement activities to reach marginalized populations.]]></description>
      <pubDate>Mon, 20 Nov 2023 16:07:42 GMT</pubDate>
      <guid>https://rip.trb.org/View/2292741</guid>
    </item>
    <item>
      <title>Proactive Planning Tool to Reduce Wildfire Sedimentation Risks</title>
      <link>https://rip.trb.org/View/2286653</link>
      <description><![CDATA[Wildfire has increased 20-fold in the past four decades in the western US and projected warming is expected to further increase wildfire activity for the foreseeable future. After a wildfire, burned hillslopes exhibit profoundly altered hydrology, dramatically increasing erosion rates and under some conditions delivering large amounts of wood to nearby stream channels. Increased flood flows, as well as excessive amounts of sediment and wood delivered to the stream pose considerable risk to transportation infrastructure within and downstream from burned areas. Just two of hundreds of examples, post-wildfire flooding and sedimentation caused extensive damage to Highway 143 in Parowan Canyon in 2017 and US 89 near Birdseye, Utah in 2019. Given the recent and expected future increases in wildfire and related risks to transportation infrastructure, there is an urgent need to determine if, how, and where forest, fire, and infrastructure management practices could be most effective in reducing high severity fire, erosion, and downstream impacts to high-value transportation resources. 

The US Geological Survey provides maps of probable debris flows after a wildfire occurs, but this information falls far short of what is needed for long-term, proactive planning to minimize wildfire related risks to infrastructure. The research group has recently developed the only predictive tool to (1) determine possible debris flow risks prior to a wildfire occurring and (2) estimate how far downstream post-wildfire sedimentation risks may occur. The model is also designed to be run iteratively to explore implications of the full range of plausible fire and rainfall scenarios for each location. Adapting the existing post-wildfire sedimentation model to predict risks to transportation infrastructure will enable Utah Department of Transportation (UDOT) to identify potential risks prior to wildfires occurring. Further, the team's work with a broader stakeholder group will facilitate communication and partnerships between UDOT and other relevant state and federal agencies to take proactive forest, fire, and infrastructure management measures that reduce wildfire-related risks to transportation infrastructure.

The existing post-wildfire sedimentation prediction model was developed, and has already been applied, to predict risks to water resource infrastructure. This model represents the most advanced and comprehensive approach available for predicting post-wildfire sedimentation risks at the watershed scale. Thus, adapting the model is the most straight-forward and robust way to evaluate wildfire-related risks to transportation infrastructure throughout the State. Given the limited amount of funding available to the UDOT Research & Innovation Division, this project represents a pilot study in which the research team will adapt the model for use with transportation infrastructure and make predictions in a few targeted locations, determined to be high-priority by the stakeholder group. Following this successful pilot study, the team would work with UDOT and other relevant state or federal agencies to obtain funding needed to predict risks to transportation infrastructure statewide.

This long-term planning toolkit is complementary to the rapid assessment toolkit the team has outlined in another proposal. Specifically, this toolkit will simulate hypothetical wildfires to identify where the greatest risks exist throughout the State, so proactive measures can be taken prior to a wildfire occurring in those locations. In contrast, the rapid assessment toolkit would be designed for risk assessment immediately after a fire has occurred to inform Burned Area Emergency Response efforts.
]]></description>
      <pubDate>Mon, 06 Nov 2023 17:04:44 GMT</pubDate>
      <guid>https://rip.trb.org/View/2286653</guid>
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