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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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    <item>
      <title>A two-stage stochastic optimization model for port infrastructure planning</title>
      <link>https://trid.trb.org/View/2382030</link>
      <description><![CDATA[This paper investigates inland port infrastructure investment planning under uncertain commodity (such as coal, petroleum, manufactured products, nonmetallic minerals) demand conditions. A two-stage stochastic optimization is developed to model the impact of demand uncertainty on infrastructure planning and transportation decisions. The model minimizes expected total costs, including capacity expansion costs, associated with handling equipment and storage infrastructure, and the expected transportation costs. To solve the problem, an accelerated Benders decomposition algorithm is implemented. The use of a stochastic approach is justified by comparing the value of stochastic solution with its corresponding deterministic solution. For demonstration, the model is applied to the Arkansas section of the McClellan-Kerr Arkansas River Navigation System (MKARNS). Given data availability, the model is generalizable to other regions. Results show that as investment in port capacities (handling equipment and storage infrastructure) increases by $8 million, the percent of commodity volumes that moves via waterways (in ton-miles) increases by 1%. For the Arkansas application, the model determines nonmetallic minerals as the most affected commodity by investment, and it identifies a cluster of ports at Little Rock where the investment would have the most significant impact. The contribution of the paper is in introducing a stochastic modeling framework to quantify mode shift dependencies on inland waterways port infrastructure (handling equipment and storage). Comparison of a stochastic approach to the state-of-the-literature deterministic approaches, shows that a failure to use a stochastic modeling to capture uncertainty in commodity demand could cost up to $21 M per year. The model serves as a decision-making tool for optimal, distributed allocation of monetary investments, that encourages mode shift to inland waterways.]]></description>
      <pubDate>Fri, 09 Aug 2024 15:31:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2382030</guid>
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    <item>
      <title>Bottleneck squeezes Mississippi</title>
      <link>https://trid.trb.org/View/1734169</link>
      <description><![CDATA[]]></description>
      <pubDate>Fri, 28 Aug 2020 17:29:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/1734169</guid>
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    <item>
      <title>Modeling dynamic behavior of navigable inland waterways</title>
      <link>https://trid.trb.org/View/1721043</link>
      <description><![CDATA[The inland waterway transportation system of the United States links its inland ports with the rest of the world by providing a cost-effective, fuel-efficient, and environmentally friendly mode of freight transportation. For this research study, a maritime transportation simulator (MarTranS) that integrates agent-based modeling, discrete-event simulation, system dynamics, and multiregional input–output analysis was developed to elucidate the relationships between inland waterway transportation system components and their associated economic impacts. An improved understanding of these relationships is critical to the assessment of risk reduction within the system, decisions concerning investment in support infrastructure, and future economic impacts. It is hypothesized that failure to invest in future improvements to the infrastructure that supports the inland waterway transportation system will have negative long-term economic consequences. While the performance of the MarTranS is demonstrated through a case study of the McClellan–Kerr Arkansas River Navigation System, the work is generalizable to other segments of the inland waterway transportation system and can enable maritime transportation stakeholders to better allocate investment budgets and increase the economic benefits of waterway transportation systems.]]></description>
      <pubDate>Mon, 27 Jul 2020 09:39:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/1721043</guid>
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    <item>
      <title>Regional Economic Impact Study for the McClellan Kerr Arkansas River Navigation System</title>
      <link>https://trid.trb.org/View/1373085</link>
      <description><![CDATA[The McClellan-Kerr Arkansas River Navigation System (MKARNS), located in Oklahoma and Arkansas, contains 440 miles of waterway and is a crucial part of the United States’ transportation system. The MKARNS strategically connects the heartland of the United States with the rest of the world via the Mississippi River and Port of New Orleans. The authors investigate the regional economic impacts of the MKARNS in order to inform waterway stakeholders of the system’s value. The study considers regional economic impacts from hydropower energy generation, U.S. Army Corps of Engineers (USACE) operations and maintenance (O&M) expenditures, private sector investment expenditures, port activities, shippers’ activities, transportation cost savings, and recreation benefits related to the MKARNS. The findings show the MKARNS contributes total impacts of $8.5 billion in sales, $4.3 billion in gross domestic product (GDP), and 55,872 jobs to the national economy. The findings of this study will inform future MKARNS investment decisions which can result in sustainable growth in the regional and national economy.]]></description>
      <pubDate>Mon, 02 Nov 2015 09:18:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/1373085</guid>
    </item>
    <item>
      <title>Inherent Costs and Interdependent Impacts of Infrastructure Network Resilience</title>
      <link>https://trid.trb.org/View/1357410</link>
      <description><![CDATA[This article describes a metric that offers a quantitative treatment of resilience, focusing specifically on measuring resilience in infrastructure networks.  The authors frame “resilience” as the ability of systems to recover from a disruptive event.  Their model includes inherent cost metrics: loss of service cost and total network restoration cost.  In addition to this quantitative data, the model includes a more-qualitative perspective that integrates data describing the regional, multi-industry impacts of a disruptive event.  These data combine to measure the interdependent impacts of network resilience. The authors use an illustrative case study of an inland waterway transportation network, the Mississippi River Navigation System, to demonstrate how their approach would be implemented.  The authors conclude by reiterating that incorporating resilience in an interdependency model increases accuracy in determining the assessment of patterns in cost metrics over time (as the system is recovering).]]></description>
      <pubDate>Tue, 30 Jun 2015 09:28:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1357410</guid>
    </item>
    <item>
      <title>Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows</title>
      <link>https://trid.trb.org/View/1317704</link>
      <description><![CDATA[This article describes the application of stochastic measures of network resilience to waterway commodity flows.  The authors define network resilience along dimensions of reliability, vulnerability, survivability, and recoverability; they quantify network resilience as a function of component and network performance.  They describe a means to optimize network resilience strategies by adapting the Copeland Score for nonparametric stochastic ranking. They next present a case study of the Mississippi River Navigation System to demonstrate the use of these stochastic measures in a real-world setting that has national economic impact.  The National Waterway Network (NWN) is composed of links, which represent either a shipping lane or simply a path in open water, and nodes, which are facilities such as a port, lock, dam, or an intermodal terminal.  A subset of the nation’s entire waterway network of 6,906 links, the Mississippi River Navigation System includes 3,046 links and 1,545 nodes. The case study analyzes the resilience of a known number of links that might go completely inoperable due to a disruptive event, such as a drought, flood, or hurricane. The authors conclude that their methodologies can be useful for the decision-making authorities and risk managers overseeing the reliability and resilience of critical infrastructures to disruptive events.  They stress that minimizing the time to full recovery can decrease the economic losses incurred by the closure of a few sections in the waterway network.]]></description>
      <pubDate>Wed, 26 Nov 2014 15:07:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1317704</guid>
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    <item>
      <title>River shippers forced to lighten loads as Mississippi nears record low water</title>
      <link>https://trid.trb.org/View/1213015</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 11 Sep 2012 09:52:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1213015</guid>
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    <item>
      <title>Great Lakes and Ohio River Navigation Systems Statistical Supplement 2010</title>
      <link>https://trid.trb.org/View/1101269</link>
      <description><![CDATA[This report, prepared by the Great Lakes and Ohio River Division's Navigation Planning Center, includes statistics pertaining to the Great Lakes Navigation System and the Ohio River Navigation System.  Data covered include those describing commodity traffic, state tonnage, commodity shipments, ports, performance characteristics, and commercial vessels.]]></description>
      <pubDate>Wed, 18 May 2011 13:23:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1101269</guid>
    </item>
    <item>
      <title>Short-Term Lock Traffic Forecasts on Ohio River System</title>
      <link>https://trid.trb.org/View/1091993</link>
      <description><![CDATA[With over 2,800 miles of navigable waterways, the Ohio River System (ORS) plays a vital role in the nation's freight movement. Locks and dams have been key elements of traffic movements by influencing the capacity of the waterway system, efficiency of barge movements, and time and costs of commodity shipments. This paper provides short-term traffic forecasts for individual locks along the ORS to assist in the planning of the regional investment plan. Using monthly lock traffic data from 1998 through 2008, the paper employs three forecasting methods: four-point moving average, Holt-Winters method, and trend and seasonal components. The results show greater similarity between the forecasting techniques on locks that have a more stable traffic pattern. The three methods show a tendency to predict similar traffic volumes for locks that have high seasonal and time trends. For example, Ohio River Lock No. 52, the most heavily used lock with an average of over 90 million tons each year from 1998 to 2008, is predicted for traffic to remain steady at current levels. However, for those locks that do not have stable seasonal and time trends (e.g., locks along Kanawha and Monongahela Rivers), the three forecasting methods show traffic patterns that deviate from each other. The findings indicate that more stable traffic patterns may allow more accurate forecasting.]]></description>
      <pubDate>Wed, 18 May 2011 11:43:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1091993</guid>
    </item>
    <item>
      <title>ECONOMIC FOUNDATIONS OF OHIO RIVER NAVIGATION INVESTMENT MODEL</title>
      <link>https://trid.trb.org/View/742419</link>
      <description><![CDATA[The Ohio River Navigation Investment Model (ORNIM) estimates the benefits of navigation improvements and balances those estimated benefits against the estimated costs of improvements.  The economic assumptions within ORNIM are identified; the rationale for these assumptions is provided; and how these assumptions alter the estimates of inland-water navigation benefits, as compared with those of the theoretical model, are addressed. ORNIM is a spatially detailed partial equilibrium model that incorporates the following assumptions: (a) demand for individual movements, provided exogenously, is perfectly inelastic; (b) willingness to pay (WTP) for individual river movements is equal to the exogenously given least-cost alternative rail rate; and (c) the supply of rail for individual movements is perfectly elastic at the exogenously given rail rate.  The first assumption biases upward estimates of with-project benefits.  However, empirical evidence on demand elasticity and WTP suggests that these assumptions are reasonable in the short run.  In the long run, decisions to move cargo by water depend only in part on river rates, with environmental and energy policies also being critical.  The demand for waterway movements is determined exogenously to ORNIM, and the U.S. Army Corps of Engineers' recent scenario-based approach to demand projection is laudable.  The third assumption unequivocally biases downward ORNIM's estimate of with-project benefits.  Future ORNIM enhancements include improvements in analyzing congestion fees, environmental externalities, traffic management, and system reliability as well as improvements in data quantity and quality.  ORNIM, like other navigation models, is data constrained.  Without significant data improvements, attempts to relax economic assumptions within ORNIM are of questionable value.]]></description>
      <pubDate>Thu, 14 Oct 2004 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/742419</guid>
    </item>
    <item>
      <title>FUTURE UTILIZATION AND OPTIMAL INVESTMENT STRATEGY FOR INLAND WATERWAYS: NEW MODEL FROM U.S. ARMY CORPS OF ENGINEERS TO ASSIST POLICY MAKERS</title>
      <link>https://trid.trb.org/View/742421</link>
      <description><![CDATA[For nearly three decades, the U.S. Army Corps of Engineers (the Corps) has been measuring incremental system navigation transportation costs for proposed infrastructure investments in search of the National Economic Development (NED) plan: local optimization in a system-level evaluation.  The increasingly complex and sophisticated analysis requires the development of additional modeling modules.  The traditional analysis assumed a most-likely traffic forecast and a set investment timing. Cost-benefit analyses on various alternatives were compared to determine the without-project condition and the recommended with-project NED plan.  Sensitivity analyses of traffic forecasts and investment timing were done on the with-project plan.  The second generation of analysis factored in the impacts of scheduled chamber closure differences between alternatives, and the third generation of analysis factored in the impacts of unscheduled ones.  The goal is to be able to optimize investments simultaneously across a system (not just investments at one site) under a series of forecast scenarios while capturing structural reliability differences (scheduled and unscheduled closures).  As the demands of the analysis increased, there was a need to consolidate and dynamically link the various models and techniques developed over the years and to develop new techniques to simultaneously manage investment permutations and automatically select optimal investment plans; the desire was to perform system optimization in a system-level evaluation.  The innovative analysis techniques and relational database management structure of the new Ohio River Navigation Investment Model are introduced, as is a set of flexible, integrated analysis modules that move the Corps closer to these ideals.]]></description>
      <pubDate>Thu, 14 Oct 2004 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/742421</guid>
    </item>
    <item>
      <title>RIVER AND HARBOR AID TO NAVIGATION SYSTEM (RIHANS) PHASE 1-C; SYSTEM DEFINITION. VOLUME I. SYSTEM DESCRIPTION</title>
      <link>https://trid.trb.org/View/17762</link>
      <description><![CDATA[The Coast Guard has initiated development of the River and Harbor Aid to Navigation System (RIHANS), an all-weather, short-range precision navigation system for use in harbors and harbor entrances. This report covers the results of the Collins-proposed RIHANS Phase 1, System Refinement Analysis and Technical Definition. The results provide equipment configuration, deployment configuration, cost projection, and accuracy analysis of the approach proposed to meet RIHANS requirements. The system described in this report is basically a short pulse microwave beacon system. Hyperbolic lines of position are generated by these beacons in a manner similar to the LORAN Systems. (Author) Portions of this document are not fully legible.]]></description>
      <pubDate>Thu, 06 Nov 2003 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/17762</guid>
    </item>
    <item>
      <title>RIVER AND HARBOR AID TO NAVIGATION SYSTEM (RIHANS), PHASE 1-R, SYSTEM DEFINITION. VOLUME 1. SYSTEM AND EQUIPMENT DESCRIPTION</title>
      <link>https://trid.trb.org/View/15801</link>
      <description><![CDATA[The Coast Guard has initiated development of the River and Harbor Aid to Navigation System (RIHANS), an all-weather, short-range precision navigation system for use in harbor and harbor entrances. The report covers the results of the proposed RIHANS Phase-1, System Refinement Analysis and Technical Definition. The results provide equipment configuration, deployment configuration, cost projections, and accuracy analysis of the approach proposed to meet RIHANS requirements. The approach uses active ranging from ship equipments to transponders on fixed shore-based stations. Data communication is superimposed on the ranging function and this can support a port information dissemination function. (Author)]]></description>
      <pubDate>Wed, 07 May 2003 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/15801</guid>
    </item>
    <item>
      <title>BRINGING THE OCEAN TO OKLAHOMA: WATERWAY IS ECONOMIC ENGINE FOR REGION</title>
      <link>https://trid.trb.org/View/722808</link>
      <description><![CDATA[This article briefly describes the McClellan-Kerr Arkansas River Navigation System, which begins at the confluence of the White and Mississippi Rivers and extends to the Tulsa Port of Catoosa. Navigation has attracted industrial investments exceeding the $1.3 billion to build the waterway.  The area between and including the Port of Muskogee and the Tulsa Port of Catoosa has gained more than $5 billion in industrial investments and 5,000 new jobs since the waterway opened.]]></description>
      <pubDate>Mon, 26 Aug 2002 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/722808</guid>
    </item>
    <item>
      <title>DIRECTORY OF PUBLIC AND PRIVATE PORTS AND TERMINALS ON THE MCCLELLAN-KERR ARKANSAS RIVER NAVIGATION SYSTEM IN ARKANSAS AND OKLAHOMA</title>
      <link>https://trid.trb.org/View/681315</link>
      <description><![CDATA[This is the second edition of the directory of ports and terminals on the McClellan-Kerr Arkansas River navigation system.  It contains information relating to the Arkansas and Oklahoma sections of the United States' inland waterway system. The entire inland waterway system connects diverse cities such as New Orleans, Houston, Pittsburgh, and Minneapolis with both Europe and the Far East.  The directory includes information about locks, dams, shipping requirements, barge and towing companies, trucking companies and railroads serving the ports, shipping by waterway, foreign trade zones, ports, and terminals, to name a few of the many topics covered.]]></description>
      <pubDate>Fri, 12 Jul 2002 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/681315</guid>
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