Consequence-Based Prioritization for Texas Short-Line Rail Resilience
Executive Summary
Texas should formalize consequence-of-disruption and network-dependency analysis when
prioritizing investments in short-line bridges, interchange connections, industrial leads, and
access tracks. Physical condition, load capacity, and traffic volume remain important, but they do not fully measure the consequences of losing an asset. A stronger framework should also
consider alternate rail access, highway capacity, shipper dependence, hazard exposure, and
restoration time.1,2,4,5,6,7
This proposal would expand earlier Texas rail-planning recommendations. A 2002 TxDOT-
sponsored report proposed evaluating rail lines according to statewide importance, interchange opportunities, distance to alternate rail service, highway alternatives, truck-related costs, economic-development effects, funding, and local support. Those recommendations focused on rail preservation but provide a foundation for resilience decisions.
The Limitations of Traditional Metrics
Traffic, load, and structural-condition measures identify deterioration and capacity needs, but
they do not show what would happen if a connection failed. A lightly used bridge or industrial
lead may still provide the only practical rail access for a rail-dependent business. Without a
nearby alternative, loss of service may force freight onto highways, raise costs, or weaken
industrial development.
A 2003 survey reported that 616 miles of Texas short-line track used rail lighter than 90 pounds per yard and estimated that 47 percent of surveyed route miles required upgrades for 286,000-pound railcars. These historical figures are not a current inventory, but they show how bridge, rail, tie, and ballast needs can exceed the financial capacity of smaller railroads.²
The 2006 Texas study found that low-density lines accounted for a large share of estimated
investment needs but a smaller share of measurable pavement savings. It concluded that funding decisions should also consider increased shipping costs and effects on rural economies.²
Network Dependency and Cascading Effects
Railways, highways, waterways, ports, and intermodal terminals form an interconnected system. When one link fails, freight may shift to other links or modes. Those alternatives can experience higher loads, congestion, or capacity problems, creating indirect or cascading effects. Houston freight-network research shows that vulnerability analysis should account for both direct hazard damage and redistributed traffic.4,5Loss of short-line service does not always cause truck diversion. Freight may move by another railroad, transfer to water transportation, or shift to highways. Where practical alternatives are unavailable, however, displaced freight may shift to highways, increasing shipping costs, pavement damage, congestion, collision risk, emissions, and noise.²
For its pavement analysis, the 2006 study assumed that one railcar would be replaced by three five-axle, 80,000-pound trucks. This was a planning assumption, not a universal conversion.² A later evaluation of 14 Texas short lines estimated that, compared with an all truck scenario, their 2015 operations avoided the equivalent of 417,177 truck movements and produced savings in shipping, maintenance, congestion, safety, and emissions.³
Texas ports also depend on railroads, highways, waterways, pipelines, energy, and
communications. Failure of access facilities can delay imports and exports, while failures of
supporting infrastructure, such as energy or communications systems, can partially shut down
port operations and create losses for dependent industries.⁵ A single rail failure will not
necessarily close a port, but loss of a critical connection can worsen disruption when other routes are constrained. 4,5
Consequence of Disruption and Time to Restore
Statewide modeling projects that Texas land susceptible to flooding will expand by about 10 to 12 percent by 2100 and that exposure of existing transportation assets could increase by 10.5 to 15.4 percent. About 95 percent of newly forecast susceptible land lies outside the Gulf Coast region, indicating greater inland risk.⁶
The same study found that almost half of the statewide rail network was already in moderate to-very-high flood-susceptibility zones, with substantial exposure among business and industrial leads. Because the study does not isolate short-line ownership, applying these results specifically to short lines is a policy inference.⁶
Restoration time should affect prioritization. The RRTD study found that lost rail service can
force businesses to use costlier trucking, weaken industrial recruitment, or contribute to
relocation.¹ A Texas rail-network model found that advance positioning of maintenance
equipment reduced repair time by an average of 7.23 hours compared with reactive dispatch.
This supports considering repair access, equipment availability, equipment travel time, and
expected outage duration.⁷
Hazardous-material traffic adds another consequence factor. The chlorine study used ALOHA,
GIS, and game theory to estimate population and infrastructure exposure and identify security-critical rail links. It supports considering population density, critical facilities, and release consequences. It did not examine natural-disaster closures or forced diversion from rail to highway.⁸
Implementing a Network-Dependency Framework
A Texas framework should combine asset vulnerability, network dependency, consequence of failure, and restoration capability. Betweenness centrality can identify links used by many shortest paths when detailed freight-flow data are unavailable. It should remain one factor because it does not measure physical condition, flood exposure, sole-source shipper access, economic effects, or repair time. 1,2,4,5,6,7
Texas can build on earlier preservation criteria by combining engineering condition with
alternate routes, interchange access, highway impacts, shipper dependence, hazard exposure, economic consequences, and restoration requirements. This would help prevent low-volume but high-consequence assets from being overlooked. 1,2,4,5,6,7
Conclusion
The supplied sources support the central argument that traffic volume and physical condition
alone are insufficient for short-line resilience prioritization. Texas should formalize a broader
framework that evaluates dependency, alternatives, consequences, and restoration time so that limited resources target assets whose loss would cause the most serious disruption. 1,2,3,4,5,6,7
Endnotes
Morgan, C. A., Roop, S. S., and Warner, J. E. Texas Rural Rail Transportation Districts:
New Roles and Relationships. Texas Transportation Institute, 2002.
Warner, J. E., and Solari Terra, M. Importance of Short Line Railroads to Texas.
Southwest Region University Transportation Center, 2006.
Gao, L., Saldarriaga, D., You, B., Qiao, F., and Li, Q. Evaluation of Transportation and
Economic Impact of Short Line Railroads in Texas. University of Houston and Texas
Southern University, n.d.
Sun, J., Bathgate, K., Pan, S., and Zhang, Z. “Network-Based Method for Assessing
Multi-Modal Transportation Network Vulnerability to Cascading Failures.” Sustainability
Analytics and Modeling 4 (2024): 100034.
Bathgate, K., Sun, J., Pan, S., Balakrishnan, S., Zhang, Z., Murphy, M., Han, Z., and
Loftus-Otway, L. Creating a Resilient Port System in Texas: Assessing and Mitigating
Extreme Weather Events: Final Report. Center for Transportation Research, The
University of Texas at Austin, 2022.
Ahasan, R., Güneralp, İ., Güneralp, B., and Birgisson, B. “The Growing Threat of
Flooding on Transportation Infrastructure Across Texas Through 2100.” Earth’s Future
14 (2026): e2026EF008207.
Wang, J., Zhang, Z., Huang, Y., and Hu, H. “Proactive Dispatch of Rail Maintenance
Equipment Under Weather-Induced Disruptions: An Optimization Framework
Integrating Machine Learning-Driven Risk Assessment.” Advanced Engineering
Informatics 69 (2026): 103990.8.
Khanmohamadi, M., Bagheri, M., Khademi, N., and Ghannadpour, S. F. “A Security Vulnerability Analysis Model for Dangerous Goods Transportation by Rail: Chlorine Transportation in Texas-Illinois.” Safety Science
