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Investigating the Effects of Data Resolution on QUAL2K predictions
Spring Runoff Conference (2011)
  • Andrew Joseph Hobson, Utah State University
  • Bethany T Neilson, Utah State University

Stream water quality is increasingly managed with the aid of mathematical or numerical models that incorporate the influences of biological, chemical, and physical processes. Such models require forcing, population, and calibration/validation data to effectively predict the influences of management strategies. Changes to the resolution of these data are anticipated to affect model predictions and, therefore, may bias interpretation of water quality control strategies. By analyzing model sensitivity to these data, information indicating appropriate levels of data resolution can be extracted. In 2010, instream water quality studies were conducted for nine central and northern Utah streams that receive wastewater effluent. Data and preliminary modeling results from a subset of the sites will be presented as well as the key issues identified with the supporting data collection. Information regarding future data collection and modeling efforts necessary to develop appropriate data collection resolution will be discussed. Overall, this effort will aid in guidance to minimize the number of data types and resolution required while maintaining acceptable model uncertainty.

  • data resolution,
  • QUAL2K,
  • water quality modeling
Publication Date
Spring March 29, 2011
Citation Information
Andrew Joseph Hobson and Bethany T Neilson. "Investigating the Effects of Data Resolution on QUAL2K predictions" Spring Runoff Conference (2011)
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