2 resultados para Forecasting model

em Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States


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A network of 25 sonic stage sensors were deployed in the Squaw Creek basin upstream from Ames Iowa to determine if the state-of-the-art distributed hydrological model CUENCAS can produce reliable information for all road crossings including those that cross small creeks draining basins as small as 1 sq. mile. A hydraulic model was implemented for the major tributaries of the Squaw Creek where IFC sonic instruments were deployed and it was coupled to CUENCAS to validate the predictions made at small tributaries in the basin. This study demonstrates that the predictions made by the hydrological model at internal locations in the basins are as accurate as the predictions made at the outlet of the basin. Final rating curves based on surveyed cross sections were developed for the 22 IFC-bridge sites that are currently operating, and routine forecast is provided at those locations (see IFIS). Rating curves were developed for 60 additional bridge locations in the basin, however, we do not use those rating curves for routine forecast because the lack of accuracy of LiDAR derived cross sections is not optimal. The results of our work form the basis for two papers that have been submitted for publication to the Journal of Hydrological Engineering. Peer review of our work will gives a strong footing to our ability to expand our results from the pilot Squaw Creek basin to all basins in Iowa.

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The purpose of this project is to develop an investment analysis model that integrates the capabilities of four types of analysis for use in evaluating interurban transportation system improvements. The project will also explore the use of new data warehousing and mining techniques to design the types of databases required for supporting such a comprehensive transportation model. The project consists of four phases. The first phase, which is documented in this report, involves development of the conceptual foundation for the model. Prior research is reviewed in Chapter 1, which is composed of three major sections providing demand modeling background information for passenger transportation, transportation of freight (manufactured products and supplies), and transportation of natural resources and agricultural commodities. Material from the literature on geographic information systems makes up Chapter 2. Database models for the national and regional economies and for the transportation and logistics network are conceptualized in Chapter 3. Demand forecasting of transportation service requirements is introduced in Chapter 4, with separate sections for passenger transportation, freight transportation, and transportation of natural resources and commodities. Characteristics and capacities of the different modes, modal choices, and route assignments are discussed in Chapter 5. Chapter 6 concludes with a general discussion of the economic impacts and feedback of multimodal transportation activities and facilities.