Performance Evaluation of Concrete Pavement Granular Subbase - Pavement Surface Condition Evaluation, TR-554, 2008

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.

Performance Measurement for Highway Winter Maintenance Operations, TR-491, 2009

The goal of this research project was to develop a method to measure the performance of a winter maintenance program with respect to the task of providing safety and mobility to the travelling public. Developing these measures required a number of steps, each of which was accomplished. First, the impact of winter weather on safety (crash rates) and mobility (average vehicle speeds were measured by a combination of literature reviews and analysis of Iowa Department of Transportation traffic and Road Weather Information System data. Second, because not all winter storms are the same in their effects on safety and mobility, a method had to be developed to determine how much the various factors that describe a winter storm actually change safety and mobility. As part of this effort a storm severity index was developed, which ranks each winter storm on a scale between 0 (a very benign storm) and 1 (the worst imaginable storm). Additionally a number of methods of modeling the relationships between weather, winter maintenance actions and road surface conditions were developed and tested. The end result of this study was a performance measure based on average vehicle speed. For a given class of road, a maximum expected average speed reduction has been identified. For a given storm, this maximum expected average speed reduction is modified by the storm severity index to give a target average speed reduction. Thus, if for a given road the maximum expected average speed reduction is 20 mph, and the storm severity for a particular storm is 0.6, then the target average speed reduction for that road in that storm is 0.6 x 20 mph or 12 mph. If the average speed on that road during and after the storm is only 12 mph or less than the average speed on that road in good weather conditions, then the winter maintenance performance goal has been met.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

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.

Iowa's Renewable Energy and Infrastructure Impacts, TR-593, 2010

The federal government is aggressively promoting biofuels as an answer to global climate change and dependence on imported sources of energy. Iowa has quickly become a leader in the bioeconomy and wind energy production, but meeting the United States Department of Energy’s goal having 20% of U.S. transportation fuels come from biologically based sources by 2030 will require a dramatic increase in ethanol and biodiesel production and distribution. At the same time, much of Iowa’s rural transportation infrastructure is near or beyond its original design life. As Iowa’s rural roadway structures, pavements, and unpaved roadways become structurally deficient or functionally obsolete, public sector maintenance and rehabilitation costs rapidly increase. More importantly, costs to move all farm products will rapidly increase if infrastructure components are allowed to fail; longer hauls, slower turnaround times, and smaller loads result. When these results occur on a large scale, Iowa will start to lose its economic competitive edge in the rapidly developing bioeconomy. The primary objective of this study was to document the current physical and fiscal impacts of Iowa’s existing biofuels and wind power industries. A four-county cluster in north-central Iowa and a two-county cluster in southeast Iowa were identified through a local agency survey as having a large number of diverse facilities and were selected for the traffic and physical impact analysis. The research team investigated the large truck traffic patterns on Iowa’s secondary and local roads from 2002 to 2008 and associated those with the pavement condition and county maintenance expenditures. The impacts were quantified to the extent possible and visualized using geographic information system (GIS) tools. In addition, a traffic and fiscal assessment tool was developed to understand the impact of the development of the biofuels on Iowa’s secondary road system. Recommended changes in public policies relating to the local government and to the administration of those policies included standardizing the reporting and format of all county expenditures, conducting regular pavement evaluations on a county’s system, cooperating and communicating with cities (adjacent to a plant site), considering utilization of tax increment financing (TIF) districts as a short-term tool to produce revenues, and considering alternative ways to tax the industry.

Risk analysis of climate change on coffee nematodes and leaf miner in Brazil

The objective of this work was to assess the potential impact of climate change on the spatial distribution of coffee nematodes (races of Meloidogyne incognita) and leaf miner (Leucoptera coffeella), using a Geographic Information System. Assessment of the impacts of climate change on pest infestations and disease epidemics in crops is needed as a basis for revising management practices to minimize crop losses as climatic conditions shift. Future scenarios focused on the decades of the 2020's, 2050's, and 2080's (scenarios A2 and B2) were obtained from five General Circulation Models available on Data Distribution Centre from Intergovernmental Panel on Climate Change. Geographic distribution maps were prepared using models to predict the number of generations of the nematodes and leaf miner. Maps obtained in scenario A2 allowed prediction of an increased infestation of the nematode and of the pest, due to greater number of generations per month, than occurred under the climatological normal from 1961-1990. The number of generations also increased in the B2 scenario, but was lower than in the A2 scenario for both organisms.

GeoTools-Android: eines geogràfiques per Android

Aquest treball tracta de l'estat actual de les aplicacions sobre sistemes d'informació geogràfica per Android.

Iowa Community Colleges High School Enrollment Report, February 2006

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.

Third Annual Iowa Community Colleges High School Enrollment Report, January 2007

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.

Iowa Community Colleges High School Enrollment Report, July 2008

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.

Second Annual Iowa Community Colleges High School Enrollment Report, February 2006

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.

Joint Enrollment 2012

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.

Joint Enrollment 2008

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.

Joint Enrollment Report, 2009

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.

Joint Enrollment 2010

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.

Joint Enrollment 2013

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.