116 resultados para road weather information system


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Researchers should continuously ask how to improve the models we rely on to make financial decisions in terms of the planning, design, construction, and maintenance of roadways. This project presents an alternative tool that will supplement local decision making but maintain a full appreciation of the complexity and sophistication of today’s regional model and local traffic impact study methodologies. This alternative method is tailored to the desires of local agencies, which requested a better, faster, and easier way to evaluate land uses and their impact on future traffic demands at the sub-area or project corridor levels. A particular emphasis was placed on scenario planning for currently undeveloped areas. The scenario planning tool was developed using actual land use and roadway information for the communities of Johnston and West Des Moines, Iowa. Both communities used the output from this process to make regular decisions regarding infrastructure investment, design, and land use planning. The City of Johnston case study included forecasting future traffic for the western portion of the city within a 2,600-acre area, which included 42 intersections. The City of West Des Moines case study included forecasting future traffic for the city’s western growth area covering over 30,000 acres and 331 intersections. Both studies included forecasting a.m. and p.m. peak-hour traffic volumes based upon a variety of different land use scenarios. The tool developed took goegraphic information system (GIS)-based parcel and roadway information, converted the data into a graphical spreadsheet tool, allowed the user to conduct trip generation, distribution, and assignment, and then to automatically convert the data into a Synchro roadway network which allows for capacity analysis and visualization. The operational delay outputs were converted back into a GIS thematic format for contrast and further scenario planning. This project has laid the groundwork for improving both planning and civil transportation decision making at the sub-regional, super-project level.

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Stream channel erosion in the deep loess soils region of western Iowa causes severe damage along hundreds of miles of streams in twenty-two counties. The goal of this project was to develop information, systems, and procedures for use in making resource allocation decisions related to the protection of transportation facilities and farmland from damages caused by stream channel erosion. Section one of this report provides an introduction. Section two presents an assessment of stream channel conditions from aerial and field reconnaissance conducted in 1993 and 1994 and a classification of the streams based on a six stage model of stream channel evolution. A Geographic Information System is discussed that has been developed to store and analyze data on the stream conditions and affected infrastructure and assist in the planning of stabilization measures. Section three presents an evaluation of two methods for predicting the extent of channel degradation. Section four presents an estimate of costs associated with damages from stream channel erosion since the time of channelization until 1992. Damage to highway bridges represent the highest costs associated with channel erosion, followed by railroad bridges and right-of-way; loss of agricultural land represents the third highest cost. An estimate of costs associated with future channel erosion on western Iowa streams is also presented in section four. Section four also presents a procedure to estimate the benefits and costs of implementing stream stabilization measures. The final section of this report, section five, presents information on the development of the organizational structure and administrative procedures which are being used to plan, coordinate, and implement stream stabilization projects and programs in western Iowa.

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The Rathbun Land and Water Alliance and partners have undertaken a highly effective approach to water quality protection through the Rathbun Lake Special Project. This approach is achieving a significant reduction in the sediment and phosphorus that impair water quality in Rathbun Lake and its tributaries as a result of the targeted application of best management practices (BMPs) for priority land in the watershed. This project application proposes to assist landowners to apply BMPs that will reduce sediment and phosphorus delivery from priority land in one targeted sub-watershed as part of the Rathbun Lake Special Project. Features of this project are: (1) use of geographic information system (GIS) analysis to identify priority land that requires BMPs; (2) assistance for landowners to apply BMPs on 1,450 acres that will reduce the annual delivery of sediment by 2,160 tons and phosphorus by 8,210 pounds; (3) evaluation of the benefits from BMP application using GIS analysis and water quality monitoring; and (4) watershed outreach activities that encourage landowners to apply BMPs for priority land to protect water quality.

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This research project covered a wide range of activities that allowed researchers to understand the relationship between stability, pavement distress, and recycled portland cement concrete (RPCC) subbase aggregate materials. Detailed laboratory and field tests, including pavement distress surveys, were conducted at 26 sites in Iowa. Findings show that specific gravities of RPCC are lower than those of crushed limestone. RPCC aggregate material varies from poorly or well-graded sand to gravel. A modified Micro-Deval test procedure showed that abrasion losses of virgin aggregate materials were within the maximum Micro-Deval abrasion loss of 30% recommended by ASTM D6028-06. Micro-Deval abrasion loss of RPCC aggregate materials, however, was much higher than that of virgin materials and exceeded 30% loss. Modulus of elasticity of RPCC subbase materials is high but variable. RPCC subbase layers normally have low permeability. The pavement surfaces for both virgin and RPCC subbase across Iowa were evaluated to fulfill the objectives of this study related to field evaluation. Visual distress surveys were conducted to gather the detailed current pavement condition information including the type, extent, and severity of the pavement distresses. The historical pavement condition information for the surveyed field sections was extracted from the Iowa DOT's Pavement Management Information System (PMIS). The current surface condition of existing field pavements with RPCC subbase was compared with the virgin aggregate subbase sections using two different approaches. The changes in pavement condition indices (PCI and IRI) with time for both types of pavements (subbases) were compared.

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A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

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In the preparation of this compilation of drainage laws of Iowa, an attempt has been made to include those sections of the Code to which reference is frequently required by the State Highway Commission, Boards of Supervisors and County Engineers in the conduct of highway and road administration as it is affected by the Iowa drainage laws. Of necessity some Code provisions which have a bearing on the principal subject were omitted. Enactments of the 56th General Assembly which modify existing code sections have been included as part of the regular text of the Code sections included in this publication. THE USER IS CAUTIONED THAT THESE CODE SECTIONS, AS MODIFIED BY THE 56th GENERAL ASSEMBLY, ARE NOT A PART OF THE 1954 CODE OF IOWA AND ARE OFFICIAL ONLY INSOFAR AS THEY ARE PRINTED IN THE OFFICIAL PUBLICATION ACTS OF THE 56TH GENERAL ASSEMBLY. SINCE THE 57TH GENERAL ASSEMBLY IS IN SESSION DURING THE PRINTING OF THIS PUBLICATION, ENACTMENTS OF THAT BODY WHICH AMEND OR REPEAL SECTIONS SET OUT HEREIN ARE INCLUDED IN THE BACK OF THIS VOLUME ON THE PINK-COLORED PAPER. THE USER IS CAUTIONED IN USING THIS VOLUME TO REFER TO THE TABLE OF SECTIONS REPEALED OR AMENDED, ON THE PINK-COLORED PAPER AT THE BACK OF THIS VOLUME. This publication is offered with the hope and belief that it will prove to be of value and assistance to those concerned with the problems of administering a highway, road and drainage system.

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Community Colleges of Iowa transmit fiscal year enrollment data to the Department of Education. All data included in this report, except where noted, are taken from the Management Information System (MIS) electronic data files and are confirmed by the community college.

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Community Colleges of Iowa transmit fiscal year enrollment data to the Department of Education. All data included in this report, except where noted, are taken from the Management Information System (MIS) electronic data files and are confirmed by the community college.

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Community Colleges of Iowa transmit fiscal year enrollment data to the Department of Education. All data included in this report, except where noted, are taken from the Management Information System (MIS) electronic data files and are confirmed by the community college.

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Community Colleges of Iowa transmit fiscal year enrollment data to the Department of Education. All data included in this report, except where noted, are taken from the Management Information System (MIS) electronic data files and are confirmed by the community college.

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This report summarizes joint enrollment in Iowa's community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. This report contains fiscal year data for the state's 15 community colleges reported through the Community College Management Information System (MIS) and confirmed by each college.

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This report summarizes joint enrollment in Iowa's community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. This report contains fiscal year data for the state's 15 community colleges reported through the Community College Management Information System (MIS) and confirmed by each college.

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The Iowa Department of Education collects information on joint enrollment in Iowa’s 15 community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. Most jointly enrolled students enroll through Senior Year Plus programs such as PSEO (Postsecondary Enrollment Options) and concurrent enrollment. Others enroll independently by paying tuition or enrolling in courses delivered through contractual agreements that do not meet the definition of concurrent enrollment. For more information about Senior Year Plus programs, please refer to the department’s website. This report consists of fiscal year and trend data on joint enrollment including headcount enrollment, credit hours, student demographics, and enrollment by program type and offering arrangement. All data included in this report is taken from the Community College Management Information System (MIS) and confirmed by each college, unless otherwise noted.

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This report summarizes joint enrollment in Iowa's community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. This report contains fiscal year data for the state's 15 community colleges reported through the Community College Management Information System (MIS) and confirmed by each college.

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This report summarizes joint enrollment in Iowa's community colleges. Jointly enrolled students are high school students enrolled in community college credit coursework. This report contains fiscal year data for the state's 15 community colleges reported through the Community College Management Information System (MIS) and confirmed by each college.