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Denver, CO, United States

Dry K.,CH2M HILL | Hopkins D.,One Denver Federal Center | Gasser M.,Denver Federal Center
Pipelines 2010: Climbing New Peaks to Infrastructure Reliability - Renew, Rehab, and Reinvest - Proc. of the Pipelines 2010 Conference | Year: 2010

Utilities construction in areas where known groundwater and soil contamination is present requires up front planning and attention to constraints imposed by the owner, as well as local, state and federal regulatory agencies to mitigate cost and time risks. This paper presents the concept of a Materials Handling Plan (MHP) to mitigate these risks and was developed concurrent with design to incorporate areas known contamination and design data into the quantification and materials handling protocols for differing excavated materials that the Constructor might encounter during construction. After identifying the likely contamination and material handling protocols, the A/E, using GIS tools, historical maps, and known areas of soil and groundwater contamination to quantify each type of contaminated material the Constructor was likely to encounter. This approach was used at a former WWII munitions plant with antiquated infrastructure that is now occupied with government agencies. This facility requires replacement and rehabilitation of all or portions of water, sanitary sewer, storm water and electrical systems and has known volatile organic compounds (VOCs), metals, polyaromatic hydrocarbons (PAHs) and asbestos contamination in the soil and VOCs contamination in the groundwater. © 2010 ASCE. Source


Friedel M.J.,Denver Federal Center
Environmental Modelling and Software | Year: 2011

This study demonstrates the novel application of genetic programming to evolve nonlinear post-fire debris-flow volume equations from variables associated with a data-driven conceptual model of the western United States. The search space is constrained using a multi-component objective function that simultaneously minimizes root-mean squared and unit errors for the evolution of fittest equations. An optimization technique is then used to estimate the limits of nonlinear prediction uncertainty associated with the debris-flow equations. In contrast to a published multiple linear regression three-variable equation, linking basin area with slopes greater or equal to 30 percent, burn severity characterized as area burned moderate plus high, and total storm rainfall, the data-driven approach discovers many nonlinear and several dimensionally consistent equations that are unbiased and have less prediction uncertainty. Of the nonlinear equations, the best performance (lowest prediction uncertainty) is achieved when using three variables: average basin slope, total burned area, and total storm rainfall. Further reduction in uncertainty is possible for the nonlinear equations when dimensional consistency is not a priority and by subsequently applying a gradient solver to the fittest solutions. The data-driven modeling approach can be applied to nonlinear multivariate problems in all fields of study. © 2011. Source


Fassnacht S.R.,Colorado State University | Fassnacht S.R.,Cooperative Institute for Research in the Atmosphere | Hultstrand M.,Colorado State University | Hultstrand M.,Denver Federal Center
IAHS-AISH Proceedings and Reports | Year: 2015

The individual measurements from snowcourse stations were digitized for six stations across northern Colorado that had up to 79 years of record (1936 to 2014). These manual measurements are collected at the first of the month from February through May, with additional measurements in January and June. This dataset was used to evaluate the variability in snow depth and snow water equivalent (SWE) across a snowcourse, as well as trends in snowpack patterns across the entire period of record and over two halves of the record (up to 1975 and from 1976). Snowpack variability is correlated to depth and SWE. The snow depth variability is shown to be highly correlated with average April snow depth and day of year. Depth and SWE were found to be significantly decreasing over the entire period of record at two stations, while at another station the significant trends were an increase over the first half of the record and a decrease over the second half. Variability tended to decrease with time, when significant. © Author(s) 2015. Source


Olea R.A.,U.S. Geological Survey | Cook T.A.,Denver Federal Center | Coleman J.L.,U.S. Geological Survey
Natural Resources Research | Year: 2010

The Greater Natural Buttes tight natural gas field is an unconventional (continuous) accumulation in the Uinta Basin, Utah, that began production in the early 1950s from the Upper Cretaceous Mesaverde Group. Three years later, production was extended to the Eocene Wasatch Formation. With the exclusion of 1100 non-productive ("dry") wells, we estimate that the final recovery from the 2500 producing wells existing in 2007 will be about 1.7 trillion standard cubic feet (TSCF) (48.2 billion cubic meters (BCM)). The use of estimated ultimate recovery (EUR) per well is common in assessments of unconventional resources, and it is one of the main sources of information to forecast undiscovered resources. Each calculated recovery value has an associated drainage area that generally varies from well to well and that can be mathematically subdivided into elemental subareas of constant size and shape called cells. Recovery per 5-acre cells at Greater Natural Buttes shows spatial correlation; hence, statistical approaches that ignore this correlation when inferring EUR values for untested cells do not take full advantage of all the information contained in the data. More critically, resulting models do not match the style of spatial EUR fluctuations observed in nature. This study takes a new approach by applying spatial statistics to model geographical variation of cell EUR taking into account spatial correlation and the influence of fractures. We applied sequential indicator simulation to model non-productive cells, while spatial mapping of cell EUR was obtained by applying sequential Gaussian simulation to provide multiple versions of reality (realizations) having equal chances of being the correct model. For each realization, summation of EUR in cells not drained by the existing wells allowed preparation of a stochastic prediction of undiscovered resources, which range between 2.6 and 3.4 TSCF (73.6 and 96.3 BCM) with a mean of 2.9 TSCF (82.1 BCM) for Greater Natural Buttes. A second approach illustrates the application of multiple-point simulation to assess a hypothetical frontier area for which there is no production information but which is regarded as being similar to Greater Natural Buttes. © 2010 International Association for Mathematical Geology (outside the USA). Source


Helmkamp J.C.,Denver Federal Center | Aitken M.E.,University of Arkansas for Medical Sciences
Journal of Agricultural Safety and Health | Year: 2011

The objective of this study was to summarize basic information on the characteristics of work-related ATV deaths among civilian persons 18 years of age or older in the U.S. from 1992 through 2007. Work-related ATV death data were obtained through the Bureau of Labor Statistics' annual Census of Fatal Occupational Injuries. From 1992 to 2007, 297 work-related ATV deaths occurred among persons over 17 in the U.S. Ninety-two percent were male, 93% were white, 23% were ages 18 to 34, 51% were ages 35 to 64, and 26% were ages >65. Half of the fatal incidents involved overturns resulting in head and chest injuries. Sixty percent of crashes occurred on farms and 20% occurred on highways. The fatality rate among agricultural production workers was significantly higher than the rates in all other industries. While more in-depth analysis of incident and exposure data for this growing problem will more clearly define personal risk and causal factors in the long term, in the short term, stronger emphasis must be placed on the development of prevention strategies, particularly focused on older workers in the agriculture production industry. © 2011 ASABE. Source

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