A. James Clark School of Engineering

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The collections in this community comprise faculty research works, as well as graduate theses and dissertations.

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    Examination of a GIS-Based Water Quality Model using USGS Gaged Watersheds in Maryland
    (2007-06-13) Shivers, Dorianne E.; Moglen, Glenn E; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Water quality models are important tools used by the Maryland Department of the Environment (MDE) in developing Total Maximum Daily Loads (TMDLs), which serve as water quality standards. The MDE tool, which spatially interpolates output from the Chesapeake Bay Program Watershed Model (WSM), is often used because it requires little time, data, or training. In contrast, the WSM requires extensive time, data, and training to run. This study examines if the MDE tool provides accurate estimates of pollutant loads and whether the mid-level complexity model AVGWLF provides comparatively more accurate estimates. The accuracy of the models was assessed based on qualitative comparisons, t-tests, and Nash-Sutcliffe coefficients. The MDE tool was found to more accurately predict total nitrogen and total sediment loads and the AVGWLF model was found to more accurately predict total phosphorus loads. The study also found that a consistent method for calculating observed loads needs to be developed.
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    Characterization and Mobilization of Arsenic in Various Contaminated Materials
    (2005-08-03) Peterson, Michael Clayton; Torrents, Alba; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Arsenic is a potentially toxic contaminant of concern even at relatively low concentrations in the environment. The complex chemistry of arsenic in the environment is influenced by a variety of chemical and physical factors. The presence of iron minerals is believed to be particularly important to arsenic mobility. Extraction methods were used to evaluate arsenic and iron in a variety of contaminated materials including mine tailings and soils. The contaminated materials were also evaluated for arsenic mobilization in batch experiments while pH and redox potential were monitored. A relationship between arsenic and iron was observed to occur in most, but not all, of the arsenic-contaminated samples. The most mobile fractions of arsenic were shown to be highly correlated with a simulated human oral bioavailable extraction method in the samples evaluated. The mobilization of arsenic by the simulated bioavailable extraction method was associated with a negligible mobilization of iron.