A novel water quality module of the SWMM model for assessing low impact development (LID) in urban watersheds

• Published in: Journal of hydrology (Amsterdam) 2020-07, Vol.586, p.124886, Article 124886
• Main Authors: Baek, Sang-Soo, Ligaray, Mayzonee, Pyo, Jongcheol, Park, Jong-Pyo, Kang, Joo-Hyon, Pachepsky, Yakov, Chun, Jong Ahn, Cho, Kyung Hwa
• Format: Article
• Language: English
• Subjects: Climate change; Low impact development; Storm water management model; Water quality
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2020.124886

•The modified LID module in SWMM improved water quality predictions.•The modified model provided more accurate predictions of LID than the original model.•The simulated water quality was sensitive to the temporal distribution of rainfall.•The thickness of soil mixing zone (Dmix) and attachment rates at soil (ka) were found to be the most sensitive parameters. The rapid increase of impervious area and climate change greatly affect the hydrological, environmental, and ecological system at the local, regional, and global scales. These phenomena can increase the peak flow and surface runoff carrying anthropogenic pollutants, thereby severely deteriorating the water quality of the surface waters. Low-impact development (LID) practices have been proposed as a promising urban management methodology to mitigate these environmental issues. Numerical models have been increasingly utilized as an analyzing tool for evaluating the LID performance. However, LID-associated numerical models are oversimplified in terms of water quality simulation by only considering the dilution effect by rainfall in LIDs. This study resolved this challenge by modifying the water quality module of LID in the stormwater management model (SWMM). We evaluated the module performance for simulating total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) of the LID facilities. Using the developed model, we conducted the LID scenario analysis under the climate change scenarios. The scenario analysis was applied in the urban area which focused on flow rate and TSS. The modified module provided accurate results for pollutant simulations, yielding an average value of Root mean square error-observation Standard deviation Ratio (RSR) of 0.52, while the original module showed an unacceptable performance, with an RSR value of 1.11. Scenario analysis showed that the hydrological outputs were sensitive to the volume of rainfall while the water quality results were sensitive to the temporal distribution of rainfall. Based on these statements, the modified water quality module in LID developed in this study will be useful in designing LID facilities and in formulating guidelines for LID installation.