Predictive power of clean bed filtration theory for fecal indicator bacteria removal in stormwater biofilters

Citation:
Parker, EA, Rippy MA, Mehring AS, Winfrey BK, Ambrose RF, Levin LA, Grant SB.  2017.  Predictive power of clean bed filtration theory for fecal indicator bacteria removal in stormwater biofilters. Environmental Science & Technology. 51:5703-5712.

Date Published:

2017/05

Keywords:

biofiltration systems, coastal waters, development, escherichia-coli removal, laboratory-scale, low-impact, monte-carlo-simulation, porous-media, southern california, urban stream syndrome, waste-water

Abstract:

Green infrastructure (also referred to as low impact development, or LID) has the potential to transform urban stormwater runoff from an environmental threat to a valuable water resource. In this paper we focus on the removal of fecal indicator bacteria (FIB, a pollutant responsible for runoff associated inland and coastal beach closures) in stormwater biofilters (a common type of green infrastructure). Drawing on a combination of previously published and new laboratory studies of FIB removal in biofilters, we find that 66% of the variance in FIB removal rates can be explained by clean bed filtration theory (CBFT, 31%), antecedent dry period (14%), study effect (8%), biofilter age (7%), and the presence or absence of shrubs (6%). Our analysis suggests that, with the exception of shrubs, plants affect FIB removal indirectly by changing the infiltration rate, not directly by changing the FIB removal mechanisms or altering filtration rates in ways not already accounted for by CBFT. The analysis presented here represents a significant step forward in our understanding of how physicochemical theories (such as CBFT) can be melded with hydrology, engineering design, and ecology to improve the water quality benefits of green infrastructure.

Notes:

n/a

Website

DOI:

10.1021/acs.est.7b00752