Transportation Rate Analysis: Gulf Intracoastal Waterway East (GIWW-E), Arkansas River, Red River

Transcription

1 Paper Submittal for Presentation at TRB rd Annual Meeting January 0, Publication in the Compendium of Papers, and Publication in the Transportation Research Record Paper # - Transportation Rate Analysis: Gulf Intracoastal Waterway East (GIWW-E), Arkansas River, Red River By Annie Protopapas, Ph.D., P.E. (Corresponding Author) Associate Research Engineer, Multimodal Freight Transportation Programs Texas A&M Transportation Institute, Texas A&M University System Research Parkway, Gilchrist, College Station, TX - Tel: () -0 Fax: () -0 a-protopapas@ttimail.tamu.edu C. James Kruse Director, Center for Ports & Waterways Texas A&M Transportation Institute, Texas A&M University System 0 N. Post Oak, Suite 0, Houston, TX 0 Tel: () - Ext. 0 Fax: () - j-kruse@tamu.edu Leslie E. Olson Associate Research Scientist, Multimodal Freight Transportation Programs Texas A&M Transportation Institute, Texas A&M University System Research Parkway, Gilchrist, College Station, TX - Tel: () - Fax: () -0 l-olson@tamu.edu Michael B. Donelan Lecturer, Maritime Administration Texas A&M University, Galveston Lazy Lane, The Woodlands, TX 0 Tel: (0) 0- donelanm@tamug.edu Words in Text:,0 (Abstract: ) Tables: (@0) Figures: (@0) Total Words:,0 October 0

2 Protopapas, Kruse, Olson, Donelan 0 0 ABSTRACT This research effort developed transportation rates ($/net ton) from origin to destination including transfer and handling fees for a non-statistically-significant sample of 00 waterborne movements and their alternative least-cost all-overland routings (i.e., rail and/or truck). The sample consisted of originating, terminating, internal, or through movements on waterways: Gulf Intracoastal Waterway East (GIWW-E 00); Arkansas River (0); and Red River (0). Water linehaul rates obtained from two major barge operators and handling rates obtained from terminal operators were compared to the corresponding rates obtained from the Barge Costing Model (BCM). It was found that the BCM underestimates waterborne charges, and that its definitions of cost components are inconsistent with real-world barge operations. Terminal operators interviewed were not aware of any nor could identify any specific offriver origins or destinations, so none were associated with any of the movements. Linehaul rail rates were obtained from the Surface Transportation Board s Carload Waybill Samples 00 and 00 and Uniform Railroad Costing System. Truck rates were obtained from national and interstate motor carriers. In most cases (/00 movements) the least-cost, most practical landonly linehaul alternative to barge was found to be rail. Overall, this research concluded that barge shipment is the least-cost transportation alternative for every commodity group on the GIWW-E and Red, and for the majority of commodity groups on the Arkansas, resulting in annual savings of $.B. Additional field data collection efforts based on larger, statistically significant samples are needed in order to implement improvements in the BCM.

3 Protopapas, Kruse, Olson, Donelan INTRODUCTION The objective of this research was to facilitate the calculations of the National Economic Development (NED) benefits attributable to navigation through the Gulf Intracoastal Waterway- East (GIWW-E) which stretches from New Orleans, Louisiana to St. Marks River, Florida; the Arkansas River; and the Red River (Figure ). To accomplish this objective, the study developed a full range of transportation routings, linehaul rates, and supplemental costs for a sample of 00 movements (originating, terminating, internal, or through) on the waterways: GIWW-E 00; Arkansas 0; and Red 0. All 00 movements were contained in and selected from the 00 Waterborne Commerce Statistics Center s (WCSC) commodity movement data. Previous transportation rate analyses were originally intended to be based on data collected via on-site or remote surveys and interviews with each origin and destination water facility/terminal. However, limitations in collecting confidential financial information in this manner made this approach unfruitful and use of the Barge Costing Model (BCM) was the only alternative to obtain the existing water routing rates. In addition, the previous research efforts concluded that there are only two practical alternatives for gathering accurate, complete, and upto-date field data required to conduct more accurate rate and routing analyses in the Lower Mississippi-GIWW geographic region:. Conduct face-to-face field interviews at the sites in question, an approach that, again, proved to be ineffective on a benefit-cost basis through the previous studies, or. Collect information directly from targeted and selected barge and facility/terminal operators a more promising course of action. This transportation rate analysis implemented the second recommendation and succeeded in procuring actual waterborne charges from targeted selected barge and facility/terminal operators for % of the sampled movements. Freight rates for each sampled movement were developed based on the actual waterinclusive routing and for a competing (least-cost) all-overland alternative. All rates and fees were stated in th Quarter 0 (0Q) U.S. dollars per net ton. Results were documented on a movement-by-movement basis (unique origin/destination/commodity or ODC combination) via a separate rate sheet for each observation. These movement data were also integrated into one data table for each waterway. (Note: All references to movement herein refer to these unique ODC combinations, not individual physical movements.) This document describes the study s scope and guidelines; parameters and data sources; methods employed; findings and results of the transportation rate data collection, research, construction, and analysis; limitations encountered; supporting assumptions; and conclusions and recommendations from this work for future reference.

4 Protopapas, Kruse, Olson, Donelan FIGURE Mississippi River System and Gulf Intracoastal Waterway.

5 Protopapas, Kruse, Olson, Donelan 0 0 WATERBORNE MOVEMENT SAMPLE The USACE provided datasets consisting of a total of, waterborne movements:,0 movements routed over the GIWW-E;, over the Arkansas; and over the Red in 00. A total of movements that involved passenger vessels were removed ( from GIWW-E and from Red), resulting in a population of,0 movements (, for GIWW-E,, for Arkansas, and for Red). These movements represented total annual tonnage flows for each specific origin-destination-commodity (ODC) triple; not individual trip tonnages. As directed by USACE and stated in the project scope of work, a sample of 00 movements (00 from GIWW- E, 0 from Arkansas, and 0 from Red) were then selected for inclusion in the sample to mirror the populations as accurately as possible, i.e., such that the distribution of tonnage by WCSC commodity group in each waterway sample mirrored the distribution of tonnage by commodity group in the WCSC population of movements that utilized the respective waterway in 00. This was accomplished by classifying the movements in each waterway s population by commodity group, ranking the movements in each commodity group by descending tonnage, and then selecting movements from each commodity group using a top-down iterative method, until both the tonnage distribution by commodity group and the total number of movements for the specific waterway sample converged to the prescribed specifications. The non-statistically significant sample of 00 movements in the GIWW-E sample corresponded to approximately % of movements and % of tonnage in the GIWW-E population; the 0-movement Arkansas sample corresponded to % of movements and % of tonnage in the Arkansas population; and the 0- movement Red sample corresponded to % of movements and % of tonnage in the Red population. (Table, Table, Table )

6 Protopapas, Kruse, Olson, Donelan TABLE Distribution of Movements and Tonnage by Commodity Group in Population and Sample GIWW-E. WCSC Commodity Group Population Sample Movements % Tons (000s) % Movements % Tons (000s) % Coal,0, Petroleum Products 0,0, Crude Petroleum,0,00 Aggregates 00,, Grain & Grain Products Chemicals,, Non-metallic Ores & Minerals Iron Ore and Iron & Steel Products 00,,0 Others. 0 0, Total,* 00%, 00% 00 00% 0, 00% Sample as % of Population % % * After passenger movements were removed from,0 movements in the original GIWW-E dataset

7 Protopapas, Kruse, Olson, Donelan TABLE Distribution of Movements and Tonnage by Commodity Group in Population and Sample Arkansas. WCSC Commodity Group Population Sample Movements % Tons (000s) % Movements % Tons (000s) % Coal 0 Petroleum Products 0 0 Crude Petroleum Aggregates, Grain & Grain Products 0 0, Chemicals, Non-metallic Ores & Minerals Iron Ore and Iron & Steel Products. 0 Others 0 Total,* 00%,0 00% 0 00%, 00% Sample as % of Population % % * No passenger movements in the original Arkansas dataset

8 Protopapas, Kruse, Olson, Donelan TABLE Distribution of Movements and Tonnage by Commodity Group in Population and Sample Red. WCSC Commodity Group Population Sample Movements % Tons (000s) % Movements % Tons (000s) % Coal Petroleum Products,,0 Crude Petroleum Aggregates 0,, Grain & Grain Products 0 Chemicals 0, 0 0 Non-metallic Ores & Minerals 0 Iron Ore and Iron & Steel Products Others Total * 00%,0 00% 0 00%, 00% Sample as % of Population % % * After passenger movements were removed from movements in the original Red dataset

9 Protopapas, Kruse, Olson, Donelan EXISTING WATER ROUTING Through examination of the individual ports/docks and telephone discussions with selected terminals and facilities it was discovered that off-river origins and/or destinations were either nonexistent, unidentifiable, infinite, or unknown. In many instances privately owned and operated docks serve as holding docks for adjoining/nearby industrial facilities; midstream holding docks between sibling facilities of the same corporation; import/export docks; or receiving/distribution points to an infinite number of off-river origins/destinations, e.g., grain elevators. Loading/unloading of barges is typically performed via pump, conveyor belt, crane with clamshell, etc. directly from/to the port/dock. In summation, there was inadequate information to confidently support inclusion of origin or destination leg land movements beyond the water origins/destinations. The researchers concluded that since no land movement per se beyond a facility port/dock could be isolated and identified, the water origin/destination had to be assumed to be the ultimate origin/destination in both the existing water routing and the least-cost all-overland routing. Two major barge operators provided estimated water linehaul rates in 00 dollars for of the 00 movements (%). Rates for the remaining movements, i.e. Coal movements on GIWW-E and Aggregates movements on Arkansas, were obtained from movements in the same commodity groups on the remaining waterways, as applicable (please see footnotes in corresponding tables). The operator rates were compared to the rates produced by the Barge Costing Model (BCM) in order to investigate the model s ability to reflect the real world and to identify areas in which it could be improved. The BCM was originally developed by the Tennessee Valley Authority (TVA) over 0 years ago and has been updated and used continuously, extensively, and successfully for USACE s study and analysis purposes; thus it can be described as a legacy model. The BCM is designed to provide shipper cost information on the linehaul movement of commodities between points on the Inland Waterway System. Additionally, the model calculates transfer costs to and from barge, i.e., the barge operator s cost of time to load or unload a barge for the routing being analyzed. The model utilizes information obtained from a variety of sources: USACE s Lock Performance Monitoring System (LPMS) and WCSC databases, Inland River Record (barge and towboat characteristics) (), Shallow Draft Vessel Costs (fixed and variable cost data) (), Shippers and receivers, and Barge and Towing industry. The latest update of the model took place in 0Q. The BCM was used to obtain rates for all 00 movements for comparison purposes and statistically significant differences were found between the BCM rates and the operator rates. First, the F-test Two-Sample for Variances (the operator rate vs. the BCM rate for each movement) was conducted for each waterway. Overall, the F-tests concluded that the variances were unequal. Specifically, the variance of operator rates was greater than the variance of BCM rates for GIWW-E and Red, while for Arkansas the variance of BCM rates was greater/equal than the variance of operator rates, at a % level of confidence. Hence, the T-test Two-Sample Assuming Unequal Variances was conducted for each waterway. The T-tests concluded that the mean of operator rates was greater than the mean of BCM rates for GIWW-E and Red, while for

10 Protopapas, Kruse, Olson, Donelan Arkansas the mean of BCM rates was greater/equal than the mean of operator rates, at a % level of confidence. The statistical analysis based on this small and non-statistically significant sample can help indicate possible population trends. However, greater confidence could be acquired in future research efforts through additional statistical analyses based on larger, statistically significant movement samples. The rates for movements were not provided by the operators so these had to be inferred from rates for comparable movements that were provided. The researchers decided it was wiser to report the operator rate, whether it was direct or inferred, for all movements due to greater confidence than the rate output by the BCM. Water linehaul distances and times, load/unload times, and any supplemental times were reported as calculated by the BCM. All movement data were presented in individual rate sheets. Water handling (loading/unloading) costs for dry bulk movements (for liquid bulk see discussion below) in 0Q dollars were obtained from additional industrial facilities and barge and terminal operators on a confidential basis by a member of the research team who is a retired barge company executive with years of experience in barge transportation contracting. To be precise, it was discovered that no separate and distinct handling charge exists where liquid bulk is concerned (commodity groups (Petroleum Products), (Crude Petroleum), and (Chemicals)). In contrast to dry bulk, liquid bulk terminals have a completely different cost structure for cargo transfers involving marine vessels, including barges. Generally, cargo handling costs are included in rental charges for liquid storage tanks paid by the shipper, with a maximum number of tank turnovers per rental period; in other words, a certain number of cargo transfers are built into the rates. The logistics calculation performed by shippers is not as simple as adding several dollars per ton to the barge freight rate to account for cargo handling costs. Using hypothetical numbers, a storage tank with volumetric capacity of 00,000 barrels ( barrel = gallons) suitable to store petroleum or petrochemicals could be rented for perhaps $0,000 per year in a major port. Such a tank might cost $ million to build. The rental cost includes a specific volume of total throughput per year. As a working rule, petroleum cargoes may be allowed inventory turnovers annually, while petrochemicals are typically allowed turnovers. Excess throughput is charged at rates on the order of $0.0 per gallon. Depending on vessel size, a certain amount of free time ( to hours) is allowed to accomplish cargo sampling and testing, line flushing and so on, in addition to normal cargo pumping time. Thereafter, marine delay charges are assessed for use of the dock ($00-00 per hour). Accessorial charges such as tank cleaning, cargo heating, vapor recovery and excess manpower are additional. The operators linehaul rates were adjusted to 0Q dollars using the Association of American Railroads (AAR) Rail Cost Adjustment Factor (RCAF) since cost escalation in the rail and barge industry is similar (). All costs output by the BCM were in 0Q dollars and were subsequently adjusted to 0Q dollars as well, through the AAR s All-Inclusive Index Less Fuel (All-LF). This index provides a parallel measure of the RCAF without the influence of the fuel cost component. The fuel price was adjusted within the model by using the Energy Information Administration s (EIA) latest (April 0) published Refiner Petroleum Product Price for Ultra Low Sulfur Diesel Fuel (). The fuel price used was $./gallon plus federal tax of $0.0/gallon (barge operators pay federal tax only).

11 Protopapas, Kruse, Olson, Donelan LEAST-COST ALL-OVERLAND ROUTING As described in the previous section, the researchers concluded that since no land movement per se beyond a facility port/dock could be isolated and identified, the water origin/destination had to be assumed to be the ultimate origin/destination in both the existing water routing and the least-cost all-overland routing. It is possible that in the absence of waterway transportation some ODCs may be able to be routed all-overland from the ultimate land origin to the ultimate land destination without going through the existing water origin and/or destination. This could reduce the all-overland routing costs and hence could reduce the savings due to the existing water routing. However there was inadequate information about land origins or destinations beyond the water origins/destinations to support an analysis to this level for individual ODCs. A close examination of each origin/destination via online photography and satellite images (), the 0 National Transportation Atlas Database (NTAD) (), and the USACE s Port Series Reports () showed that the majority of docks were attached to facilities with on-site access to/from a rail mainline (rail connector or spur). Given the bulk, low-end value per unit of weight nature of the commodities involved, it stands to reason that the least-cost linehaul alternative would likely be rail in the absence of barge transportation. In cases where either or both the origin and/or destination facility did not have on-site rail access to a rail mainline, the nearest railhead with transloading capabilities was identified. A short truck haul, miles on average, was estimated to be required between each such facility and the nearest railhead. The requisite truck charges were added to the rail linehaul charges as applicable in order to obtain the cost of the all-overland routing. Please see below for further truck details. For a total of movements ( GIWW-E, 0 Arkansas, and Red), rail mileage and rate (revenue per net ton) were obtained from the Surface Transportation Board s (STB) Carload Waybill Samples 00 (latest available) and 00 (confidential files) which were provided through USACE for purposes of this work (). Each Waybill was analyzed for movements of similar origin-destination-commodity (ODC) triples at two geographic levels, the county Federal Information Processing Standard (FIPS) level and the Business Economic Area (BEA) level, and at the -digit or -digit Standard Transportation Commodity Code (STCC) system used by railroads () due to the absence of waybills for ODC triples identical or similar to waterborne movements in terms of geographical as well as commodity detail. A BEA typically includes one or more counties. Differences between the WCSC commodity classification system and the STCC system sometimes only permitted matching the -digit WCSC code to the -digit STCC code. For example, the closest match to Benzene, Pure (WCSC code ) at the -digit STCC level was STCC Crude Products From Coal Tar, Natural Gas. However, an equivalent ODC triple combination could only be found at the -digit STCC level ( Chemicals and Allied Products). Waybills did not exist for many ODC triples. The absence of waybills for ODC triples identical or similar to waterborne movements is not surprising since waterborne transportation competes effectively with rail, especially for the movements included in this sample. Hence, for a total of movements ( GIWW-E, Arkansas, and Red) the STB s Uniform Railroad Costing System (URCS) program, whose latest update was based on the 00 Waybill Sample, was used to obtain rail linehaul rates per ton (0). The term cost in the URCS documentation is used to refer to the rail shipment cost, i.e. what shippers pay to the railroads, which is precisely the same thing as railroad revenue. Hence, these two terms can be used interchangeably. The URCS only allows for commodity matching at an aggregate -digit

12 Protopapas, Kruse, Olson, Donelan STCC level. In addition, the Waybill-reported rail rates were all-inclusive but URCS calculates shipper costs based on mileage and switching by railroad, hence it requires the user to enter mileage by railroad for each rail route. NTAD was used to trace rail routes and determine mileage on individual railroads networks in order for URCS to account for linehaul and switching charges. The URCS cost in dollars per carload was converted to dollars per net ton based on a carload weight of 0 tons. Costs obtained from the Waybill Samples and the URCS were then adjusted to 0Q dollars via the AAR s Rail Cost Adjustment Factor (RCAF) (), which measures the rate of inflation in all seven railroad inputs: labor, fuel, materials and supplies, equipment rents, depreciation, interest, and other expenses. Based on the researchers experience, the reported system average speed of. mph for Union Pacific Railroad, the largest of the Class I railroads, was reduced to mph in order to reflect en-route terminal dwell times and was used to calculate the mainline rail trip time in days (). Two days were added to origin legs and one day to destination legs with on-site or nearby rail line access to account for the rail load/unload time, travel time, and dwell/switch time required for local rail service between mainline railheads and individual facilities or transload terminals. It was assumed that a total of movements ( GIWW-E, Arkansas, and Red) movements with about 00 rail miles or less between origin and destination would take place solely by truck at an average speed of 0 mph. This hypothesis was supported by the fact that no waybills with even remotely similar combinations of ODC triples or even distancecommodity doubles were found in either Waybill Sample for such movements. Short truck hauls between facilities without on-site rail access and the nearest railhead with transloading capability were estimated to be miles on average at an average speed of 0 mph. Truck trip times either for linehaul or short haul to the nearest railhead were reported in days, to enable comparison with rail and water trip times. Short haul truck miles, time, and rates were added to linehaul rail miles, time, and rates, as applicable, in order to obtain the all-overland routing figures. Truck rates per net ton-mile for dry and liquid bulk were obtained through telephone and communication with 0 national interstate and local motor carriers and individual facilities. The rates consisted of a base rate and a fuel surcharge expressed in dollars per pound, gallon, day, truckload, representative commodity, or fixed miles/route. They also stated that they did allow for typical load/unload time but that there was no separate and distinct cost figure attached to it. A truckload net cargo weight of tons (0,000 lbs), densities of representative commodities, and trip distances and durations were taken into consideration in order to calculate a truck cost in dollars per ton-mile for all commodities on a nationwide basis. All calculations included requisite handling costs (load/unload and transfer) as applicable. Load/unload costs at facilities to/from rail or truck, as well as transfer costs at transload terminals, in terms of dollars per net ton, were assumed to be equal to the load/unload costs obtained from facilities and operators for the water routing. Separate and distinct load/unload costs were applied to dry bulk only; rail and truck rates for liquid bulk were assumed to include built-in load/unload costs on the premise that the same shipper-facility contracts would likely apply independently of the mode of transportation used. Load/unload times involving rail or truck are likely to be different than barge but it is not possible to estimate them without knowing the size of individual shipments, truck or railcar availability, or facility/terminal load/unload capacity etc. Hence, rule-of-thumb figures of half a day for truck or rail loading at the origin facility and truck-rail transfer at the transload terminal,

13 Protopapas, Kruse, Olson, Donelan and a quarter day for truck or rail unloading at the destination facility and rail-truck transfer at the transload terminal were adopted, as applicable. In the case of rail loading, unloading, and transloading, these were a subset of the above-mentioned two days for origin rail legs and one day for destination rail legs. In the case of facilities without on-site rail access, an additional half day for truck loading at the origin facility and an additional quarter day for truck unloading at the destination facility were assumed. It must be noted that the logistics involved in a theoretical modal shift from barge to rail or truck are likely to be prohibitive in reality, considering the significant capacity advantage of barges: one dry cargo barge is equivalent to railcars or 0 trucks while one tank barge is equivalent to railcars or trucks (, ). RESEARCH RESULTS The method applied in selecting the movement sample from the population of each waterway was based on tonnage distribution by WCSC commodity group on that waterway and was nonstatistically significant. However, the rates in dollars per net ton-mile obtained for the movements in each commodity group in each waterway sample served as a proxy for extrapolation to obtain rates associated with all movements of the same commodity group in each waterway s movement population. The rates in dollars per net ton-mile obtained for the existing water routing, the least-cost all-overland routing, and the ratio of least-cost all-overland route miles to existing water route miles obtained for each movement were averaged by commodity group for each waterway (Table, Table, Table ). Findings that appear to be irregular e.g., the water rate being higher than the least-cost all-overland rate for a commodity group on the whole or for individual movements within a commodity group may be attributed to the limited, non-statistically significant sample size (in total number of movements and in particular in the number of movements for Arkansas and Red); limited availability and capability of supporting data and tools; or special characteristics associated with the individual movements. It is quite possible that a desire to constrain moving the waterborne commodities by means of company-owned equipment, the lack of good connecting infrastructure, the lack of power units (e.g., locomotives or tractors), or a number of other factors could cause such anomalies. Overall, however, this research concluded that barge shipment is the least-cost transportation alternative for every commodity group on the GIWW-E and Red, and for the majority of commodity groups on the Arkansas.

14 Protopapas, Kruse, Olson, Donelan TABLE Transportation Rates per Net Ton-Mile by Commodity Group GIWW-E. WCSC Commodity Group Average Transportation Rate ($/net ton-mile) Existing Water Routing Least-Cost All-Overland Routing Coal* $0.0 $0. 0. Petroleum Products $0.0 $0.. Crude Petroleum $0.0 $ Aggregates $0.0 $ Grain & Grain Products Chemicals $0.0 $0.. Non-metallic Ores & Minerals $0. $0. 0. Iron Ore and Iron & Steel Products $0.0 $0. 0. Others $0.0 $0..0 = No Movements in this commodity group in the sample * Water routing rates inferred from Coal commodity group in Arkansas TABLE Transportation Rates per Net Ton-Mile by Commodity Group Arkansas. WCSC Commodity Group Average Transportation Rate ($/net ton-mile) Existing Water Routing Least-Cost All-Overland Routing Coal $0.0 $ Petroleum Products $0.0 $ Crude Petroleum Aggregates* $. $0.0. Grain & Grain Products $0.0 $ Chemicals $0.0 $ Non-metallic Ores & Minerals $0.0 $0. 0. Iron Ore and Iron & Steel Products $0.0 $ Others $0.0 $ = No Movements in this commodity group in the sample * Water routing rates inferred from Aggregates commodity group in GIWW-E and Red Average Ratio Land/Water Miles Average Ratio Land/Water Miles

15 Protopapas, Kruse, Olson, Donelan 0 0 TABLE Transportation Rates per Net Ton-Mile by Commodity Group Red. WCSC Commodity Group Average Transportation Rate ($/net ton-mile) Existing Water Routing Least-Cost All-Overland Routing Coal Petroleum Products $0.0 $0. 0. Crude Petroleum $0. $0.. Aggregates $0.0 $ Grain & Grain Products $0.0 $0. 0. Chemicals $0.0 $ Non-metallic Ores & Minerals $0. $0. 0. Iron Ore and Iron & Steel Products Others $0.0 $0. 0. = No Movements in this commodity group in the sample Average Ratio Land/Water Miles The actual transportation rates obtained from the research were applied to the 00 sampled movements. The average transportation rates per net ton-mile and ratio of land miles to water miles by commodity group were applied to the unsampled movements in the same commodity group in each waterway (total of,0 unsampled movements) in order to calculate the total existing water routing cost, the total least-cost all-overland routing cost, and the annual savings (in 0Q dollars) realized by each movement due to the utilization of the water mode. Naturally, extrapolation could only be supported if there was at least one sampled movement for that commodity group for that waterway. Commodity groups with minimal percent tonnage of the waterway population s tonnage were not sampled. The following equations were applied to each unsampled movement in each sampled commodity group in each waterway s population: Total Cost of Existing Water Routing = Average Transportation Rate of Existing Water Routing ($/net ton-mile) x Existing Water Routing Miles x Annual Tons Total Cost of Least-Cost All-Overland Routing = Average Transportation Rate of Least- Cost All-Overland Routing ($/net ton-mile) x Existing Water Routing Miles x Average Ratio Land/Water Miles x Annual Tons Annual Savings due to Utilization of Water Routing = Total Cost of Least-Cost All- Overland Routing Total Cost of Least-Cost All-Overland Routing This methodology was applied to every movement in the population and the results in 0Q dollars are summarized below (Table ).

16 Protopapas, Kruse, Olson, Donelan TABLE Transportation Costs and Savings by Waterway. Waterway Existing Water Routing Least-Cost All-Overland Routing Annual Savings GIWW-E $.M $,.0M $,.M Arkansas $,.0M $,.M $.M Red $.M $.M $.M Total $,.M $,.M $,0.0M CONCLUSIONS AND RECOMMENDATIONS This transportation rate analysis for the GIWW-E, Arkansas river, and Red river succeeded in procuring actual charges for % of the sampled movements from targeted selected barge and facility/terminal operators. It therefore became possible to validate the rates output by the BCM and it was found that the BCM significantly underestimates real-world water shipping charges and that some of its definitions are inconsistent with real-world barge operations. Overall, this research concluded that barge shipment is the least-cost transportation alternative for every commodity group on the GIWW-E and Red, and for the majority of commodity groups on the Arkansas. The analysis estimated that annual savings of $.B (over 00%) were realized in 00 due to the utilization of the water mode over the least-cost alloverland alternative mode for the population of barge movements on the GIWW-E, Arkansas, and Red in other words, the least-cost all-overland alternative would cost more than twice as much as the water routing. In most cases the least-cost, most practical land-only linehaul alternative was found to be rail: movements for the GIWW-E, for Arkansas, and for Red. External or supplementary datasets and models, information from rail and motor carriers, and the researchers experience were used to develop the least-cost overland transportation rates. Published data issues and limitations encountered in previous studies that still remain include: The port/dock information included in the WCSC is in need of thorough updating. The port/dock information included in USACE s Port Series Reports is in similar need. The different commodity classification systems used by different modes and government agencies should either be integrated into a single, one-size-fits-all classification scheme or a dictionary that translates among the various modal commodity classification systems should be developed. This study concluded that additional research efforts based on larger, statistically significant samples, using similar methods should be conducted in order to obtain additional field data and compare them to the corresponding BCM output. This will help identify areas in which the BCM could be improved through modification of its code, the base data it uses, and its cost definitions so that it reflects actual barge operations more accurately. Future research efforts should incorporate these improvements in order to ultimately increase confidence in the BCM output. These additional research efforts should also provide for expanded data collection efforts related to ultimate land origins and destinations thereby allowing for development of more

17 Protopapas, Kruse, Olson, Donelan 0 accurate least-cost all-overland routings, commensurate costs, and ultimately savings due to the existing water routing. ACKNOWLEDGEMENTS This study was conducted for the U.S. Army Corps of Engineers Huntington District under contract with Nick J. Rahall, II Appalachian Transportation Institute at Marshall University. The authors would like to thank the barge and terminal/facility operators; and Mr. Chris Dager of the Center for Transportation Research at the University of Tennessee, Knoxville for their assistance in this work. REFERENCES The Waterways Journal. Inland River Record. Accessed December 0. U.S. Army Corps of Engineers, Economic Guidance Memo #0-0: Shallow Draft Vessels Operating Costs FY 00 Accessed November 0. Association of American Railroads (AAR). Rail Cost Indexes. Accessed December 0 Energy Information Administration (EIA). Refiner Petroleum Product Prices by Sales Type. Accessed December 0. Google Earth. Accessed December 0. U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation Statistics. National Transportation Atlas Database 0. Accessed December 0. U.S. Army Corps of Engineers, Navigation Data Center. Port Series Reports. Accessed December 0. Surface Transportation Board. Carload Waybill Sample. Accessed December 0. Railinc Corporation Standard Transportation Commodity Code. Accessed December 0. 0 Uniform Railroad Costing System (URCS). Accessed December 0. Union Pacific AAR and STB Reports, AAR-UP Monthly Performance Measures, Current 0. Accessed December 0. Kruse, J., Protopapas, A., and Olson, L. A Modal Comparison of Domestic Freight Transportation Effects on the General Public National Waterways Foundation. Texas Transportation Institute, College Station, TX, February 0. Accessed December 0. Protopapas, A., Kruse, J., and Olson, L. Modal Comparison of Domestic Freight Transportation Effects on the General Public. In Transportation Research Record: Journal of the Transportation Research Board, No. 0, Transportation Research Board of the

18 Protopapas, Kruse, Olson, Donelan National Academies, Washington, D.C., 0, pp Accessed October 0.