Historical Development and Applications of the EPIC and APEX Models, June 2005

The development of the field-scale Erosion Productivity Impact Calculator (EPIC) model was initiated in 1981 to support assessments of soil erosion impacts on soil productivity for soil, climate, and cropping conditions representative of a broad spectrum of U.S. agricultural production regions. The first major application of EPIC was a national analysis performed in support of the 1985 Resources Conservation Act (RCA) assessment. The model has continuously evolved since that time and has been applied for a wide range of field, regional, and national studies both in the U.S. and in other countries. The range of EPIC applications has also expanded greatly over that time, including studies of (1) surface runoff and leaching estimates of nitrogen and phosphorus losses from fertilizer and manure applications, (2) leaching and runoff from simulated pesticide applications, (3) soil erosion losses from wind erosion, (4) climate change impacts on crop yield and erosion, and (5) soil carbon sequestration assessments. The EPIC acronym now stands for Erosion Policy Impact Climate, to reflect the greater diversity of problems to which the model is currently applied. The Agricultural Policy EXtender (APEX) model is essentially a multi-field version of EPIC that was developed in the late 1990s to address environmental problems associated with livestock and other agricultural production systems on a whole-farm or small watershed basis. The APEX model also continues to evolve and to be utilized for a wide variety of environmental assessments. The historical development for both models will be presented, as well as example applications on several different scales.

Epidemic: Responding to America's Prescription Drug Abuse Crisis, 2011

Prescription drug abuse is the Nation’s fastest-growing drug problem. While there has been a marked decrease in the use of some illegal drugs like cocaine, data from the National Survey on Drug Use and Health (NSDUH) show that nearly one-third of people aged 12 and over who used drugs for the first time in 2009 began by using a prescription drug non-medically.1 The same survey found that over 70 percent of people who abused prescription pain relievers got them from friends or relatives, while approximately 5 percent got them from a drug dealer or from the Internet.2 Additionally, the latest Monitoring the Future study—the Nation’s largest survey of drug use among young people—showed that prescription drugs are the second most-abused category of drugs after marijuana.3 In our military, illicit drug use increased from 5 percent to 12 percent among active duty service members over a three-year period from 2005 to 2008, primarily attributed to prescription drug abuse.

Iowa Plan for Brain Injury, 2007-2010

Traumatic Brain Injury (TBI) impacts the lives of thousands of Iowans every year. TBI has been described as the “Silent Epidemic” because so often the scars are not visible to others. The affects of brain injury are cognitive, emotional, social, and can result in physical disability. In addition to the overwhelming challenges individuals with brain injury experience, families also face many difficulties in dealing with their loved one’s injury, and in navigating a service delivery system that can be confusing and frustrating. In 1998, the Iowa Department of Public Health (IDPH) conducted a comprehensive statewide needs assessment of brain injury in Iowa. This assessment led to the development of the first Iowa Plan for Brain Injury, “Coming Into Focus.” An updated state plan, the Iowa Plan for Brain Injuries 2002 – 2005, was developed, which reported on progress of the previous state plan, and outlined gaps in service delivery in Iowa. Four areas of focus were identified by the State Plan for Brain Injuries Task Force that included: 1) Expanding the Iowa Brain Injury Resource Network (IBIRN); 2) Promoting a Legislative and Policy Agenda, While Increasing Legislative Strength; 3) Enhancing Data Collection; and, 4) Increasing Funding. The IDPH utilized “Coming Into Focus” as the framework for an application to the federal TBI State Grant Program, which has resulted in more than $900,000 for plan implementation. Iowa continues to receive grant dollars through the TBI State Grant Program, which focuses on increasing capacity to serve Iowans with brain injury and their families. Highlighting the success of this grant project, in 2007 the IDPH received the federal TBI Program’s “Impacting Systems Change” Award. The Iowa Brain Injury Resource Network (IBIRN) is the product of nine years of TBI State Grant Program funding. The IBIRN was developed to ensure that Iowans got the information and support they needed after a loved one sustained a TBI. It consists of a hospital and service provider pre-discharge information and service linkage process, a resource facilitation program, a peer-to-peer volunteer support network, and a service provider training and technical assistance program. Currently over 90 public and private partners work with the IDPH and the Brain Injury Association of Iowa (BIA-IA) to administer the IBIRN system and ensure that families have a relevant and reliable location to turn for information and support. Further success was accomplished in 2006 when the Iowa legislature created the Brain Injury Services Program within the IDPH. This program consists of four components focusing on increasing access to services and improving the effectiveness of services available to individuals with TBI and their families, including: 1) HCBS Brain Injury Waiver-Eligible Component; 2) Cost Share Component; 3) Neuro-Resource Facilitation; and, 4) Enhanced Training. The Iowa legislature appropriated $2.4 million to the Brain Injury Services Program in state fiscal year (SFY) 2007, and increased that amount to $3.9 million in SFY 2008. The Cost Share Component models the HCBS Brain Injury Waiver menu of services but is available for Iowans who do not qualify functionally or financially for the Waiver. In addition, the Neuro-Resource Facilitation program links individuals with brain injury and their families to needed supports and services. The Iowa Plan for Brain Injury highlights the continued need for serving individuals with brain injury and their families. Additionally, the Plan outlines the paths of prevention and services, which will expand the current system and direct efforts into the future.

Iowa Calibration of MEPDG Performance Prediction Models, 2013

This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.

Iowa Calibration of MEPDG Performance Prediction Models: Tech Transfer Summary

This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 representative pavement sites across Iowa were selected. The selected pavement sites represent flexible, rigid, and composite pavement systems throughout Iowa. The required MEPDG inputs and the historical performance data for the selected sites were extracted from a variety of sources. The accuracy of the nationally-calibrated MEPDG prediction models for Iowa conditions was evaluated. The local calibration factors of MEPDG performance prediction models were identified to improve the accuracy of model predictions. The identified local calibration coefficients are presented with other significant findings and recommendations for use in MEPDG/DARWin-ME for Iowa pavement systems.

Models and approaches for environmental education in Iowa, 1999

This guide provides a variety of tools that can help an educator, building staff or school district decide how to include environmental education in their curriculum.

Implementation Manual — 3D Engineered Models for Highway Construction: The Iowa Experience; RB33-014, 2015

3D engineered modeling is a relatively new and developing technology that can provide numerous benefits to owners, engineers, contractors, and the general public. This manual is for highway agencies that are considering or are in the process of switching from 2D plan sets to 3D engineered models in their highway construction projects. It will discuss some of the benefits, applications, limitations, and implementation considerations for 3D engineered models used for survey, design, and construction. Note that is not intended to cover all eventualities in all states regarding the deployment of 3D engineered models for highway construction. Rather, it describes how one state—Iowa—uses 3D engineered models for construction of highway projects, from planning and surveying through design and construction.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.

Investigation of AASHTOWare Pavement ME Design/DARWin-ME Performance Prediction Models for Iowa Pavement Analysis and Design, 2015

The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models.