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.

Scale Effects in Hydraulic Model Tests of Rock Protected Structures, HR-119, 1970

A laboratory investigation was undertaken to determine the limiting model Reynolds number above which the scour behavior of rock protected structures can be reproduced in hydraulic models scaled according to the Froude criterion. A submerged jet was passed over an initially full scour pocket containing uniform glass spheres and the rate of scour was measured as a function of time. The dimensions of the scour pocket and jet and the particle diameters were varied as needed to maintain strict geometric similarity. For each of two different Froude numbers the Reynolds number was varied over a wide range. The normalized scour rate was found to be practically independent of the Reynolds number, R, (based on the jet velocity and particle diameter) at values of R above about 2.5 x 10^3, and to decrease with Rat smaller values. A grid placed in the jet was found to have a very strong effect on the scour rate. In an attempt to explain the effect of R on the scour behavior, turbulent pressure and velocity fluctuations were measured in air flows and water flows, respectively, over rigid scour pockets having the same geometry as those formed in the scour experiments. The normalized spectra of the fluctuations were found to be nearly independent of R, but the flow pattern was found to be very sensitive to the inlet condition, the jet deflecting upward or downward in a not wholly explainable manner. This indicates that scour behavior can be modeled only if the approach flow is also accurately modeled.

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.