Regression Modeling of Particle Size Distributions in Urban Storm Water: Advancements through Improved Sample Collection Methods
Publication: Journal of Environmental Engineering
Volume 138, Issue 12
Abstract
A new sample collection system was developed to improve the representation of sediment entrained in urban storm water by integrating water quality samples from the entire water column. The depth-integrated sampler arm (DISA) was able to mitigate sediment stratification bias in storm water, thereby improving the characterization of suspended-sediment concentration and particle size distribution at three independent study locations. Use of the DISA decreased variability, which improved statistical regression to predict particle size distribution using surrogate environmental parameters, such as precipitation depth and intensity. The performance of this statistical modeling technique was compared to results using traditional fixed-point sampling methods and was found to perform better. When environmental parameters can be used to predict particle size distributions, environmental managers have more options when characterizing concentrations, loads, and particle size distributions in urban runoff.
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Information & Authors
Information
Published In
Journal of Environmental Engineering
Volume 138 • Issue 12 • December 2012
Pages: 1186 - 1193
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Jun 2, 2011
Accepted: Jun 26, 2012
Published online: Aug 3, 2012
Published in print: Dec 1, 2012
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