Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Environme...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Environmental Management
Article . 2019 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
versions View all 2 versions
addClaim

Considering the effect of groundwater on bioretention using the Storm Water Management Model

Authors: Hwansuk, Kim; Kristine Joy B, Mallari; Jongrak, Baek; Gijung, Pak; Hyun Il, Choi; Jaeyoung, Yoon;

Considering the effect of groundwater on bioretention using the Storm Water Management Model

Abstract

The Storm Water Management Model (SWMM), with its recently released low impact development (LID) module, is among several models used for the performance evaluation of LID facilities in reducing runoff and pollutants. Modeling is often difficult because of the variety of factors affecting the LID system. Among these factors, the effect of groundwater can be important in the LID modeling results due to the possibility of its interaction with LID. In this study, the performance of the SWMM-LID controls in predicting runoff from bioretention cells was evaluated for a site under groundwater influence. In addition, for considering the groundwater effect in the model, this study explores the utility of the SWMM groundwater model in predicting runoff under groundwater influence. Runoff from the considered watershed draining into the bioretention cells was well-simulated with very favorable performance statistic values (r2 = 0.96, NSE = 0.94, % difference = 2.76). However, comparison of simulated with observed runoff from bioretention cells produced weaker statistical values (r2 = 0.69, NSE = 0.65, % difference = 18.22), which is thought to be due to the presence of events affected by groundwater interference. Removal of these events and recalibration were able to improve the overall results, suggesting that the influence of groundwater should be taken into account for better LID modeling of the study site. In order to consider the groundwater influence, the SWMM groundwater model was used in tandem with LID controls to provide an additional influent source to bioretention cells. This resulted in a good fit for two events which were thought to be impacted by groundwater (events in which outflow exceeded inflow) and overall better performance (r2 = 0.95, NSE = 0.95, % difference = 3.49) compared to the results obtained by using only LID controls. In conclusion, the SWMM groundwater model can help deal with groundwater-impacted events. However, for better representation of the phenomenon, the LID module itself needs to be improved to account for direct interaction with groundwater.

Related Organizations
Keywords

Rain, Water Movements, Water, Groundwater

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    20
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
20
Top 10%
Average
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!