Removal of Low Density Sediments by Vegetative Filters

نویسندگان

  • Brent M. Hall
  • Dean E. Eisenhauer
چکیده

The use of vegetative filter strips (VFS) is a longstanding best management practice for the removal of sediment and other pollutants from overland flow. Many attempts have been made to model the effectiveness of a VFS based upon soil, vegetation, and sediment properties, and also upon flow conditions, but little work has been done to investigate the reliability of the existing models when considering sediments, such as microbial pathogens, that have a lower density than the mineral sediments used for development of the models. The objectives of this study were to: 1) quantify the ability of a VFS to remove low density sediments from overland flow, and 2) assess the impact of infiltration on the effectiveness of a VFS. A 0.3 meter wide by 5 meter long artificial VFS with a controllable rate infiltration system was constructed in a variable slope flume. Tests were conducted to investigate VFS effectiveness for 3 inflow rates and 3 infiltration rates, and each condition was also modeled with the computer program VFSMOD (Muñoz-Carpena et al., 1999) for comparison between experimental and modeled results. Flume results ranged from 75% to 93% of sediment trapped by the artificial VFS, based upon flow conditions, while modeled results were significantly higher, ranging from 98.6% to 100% of sediment trapped by the VFS. However, an unknown proportion of the observed difference between the observed and modeled results is likely due to the observations that the experimental setup violated the assumption that no bed load transport takes place within the VFS. The water inflow rate had a significant effect upon VFS effectiveness, but infiltration rate was an insignificant factor in VFS effectiveness, most likely because of the relatively low percentage of inflow water that infiltrated within the artificial VFS. To my loving wife, Kyla, without whose support this project would not have been possible.

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تاریخ انتشار 2016