As part of the planning effort leading up to the development of a statewide FreightPlan, the Oregon Department of Transportation (ODOT) developed a statewidecommodity flow forecast. The methodology used to create this Oregon Commodity FlowForecast (Oregon CFF), aimed to address the limitations of existing forecasts –inconsistent and separate databases for different modes, lack of transparency in dataand assumptions, and data gaps – in a consistent methodology based on national andlocal data sources, and be able to meet the tight timelines. This paper will documentthe work done by the consulting team and the agency to create a statewide forecastthat addressed these limitations.The project team decided to build on the Federal Highway Administration (FHWA)Freight Analysis Framework (FAF2) national commodity flow forecast. The FAF2commodity flow forecast was chosen because FAF2 is national in scope, highly regardedin terms of capturing interstate and international flows, uses a relatively recent baseyear (2002), and provided a quick way to complete a forecast in time for the OregonFreight Plan work.FAF2 provides freight flows in tons or dollar value between 130 FAF2 regionsencompassing the US for the year 2002 plus forecasts from 2010 to 2035 in five yearincrements. The desired final product for the Oregon CFF was a county-county levelflow forecast for truck, rail, marine, air, and pipeline modes. In order to transform thecoarse FAF2 zone flows (2 zones cover Oregon) into counties within Oregon, the datawas disaggregated. Since the FAF2 dataset contains the whole United States, flows withat least one trip ends within Oregon were disaggregated from FAF2 zones to Oregoncounties.Each of the freight modes was disaggregated separately. In the case of truck flows, thiswas done based on county employment and IMPLAN inter-industry coefficients of whatcommodities are made and used by each industry. For rail flows, the FAF2 flows werecompared to the Surface Transportation Board‘s Rail Carload Waybill data set whichcontains county level detail of origin and destinations. The overall numbers were foundto be comparable, so the Waybill data for 2002 was used as the base, and the FAF2iigrowth rates were applied to forecast the future years. The other modes relied on localdata to allocate FAF2 flows to specific Oregon facilities (rail stations, airports, marineports, or pipeline terminals), including US Corps of Engineers Waterborne Commercedata and the Oregon Energy Report. Zones outside of Oregon were aggregated fromFAF2 zones to ―Other Domestic‖ and ―Other International‖ categories. Specialconsideration was made for air mail and fish commodities using the knowledge ofindustry experts. Using the Rail Waybill data and other sources required a conversion incommodity categories, because FAF2 uses the Standard Classification of TransportedGoods (SCTG)TG and other sources used the Standard Transportation Commodity Codeclassification.Once the data was disaggregated to represent county-county commodity flows, theFAF2 future year forecast numbers were adjusted down to account for the economicdownturn that occurred after the forecast was prepared. One of the challenges ofworking with the FAF2 data is the inability to adjust or quantify the FAF2 underlyingeconomic forecasts, particularly the optimistic economic conditions and low fuel priceassumptions. These poses some limitations that must be taken into account.The Oregon CFF 2002 to 2035 forecast provides a basis for understanding the primaryfreight movements today and in the future under existing conditions. In severalinstances circumstances are likely to change, and the detail and transparency providedin Oregon CFF can provide a starting point for evaluating such changes.
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