Bioretention-Based Stormwater Management Using EPA SWMM: Bibliometric and Systematic Literature Review with Implications for Tropical Regions

Giovanni Ivander

doi:10.33603/jgst.v10i2.12504

Authors

Giovanni Ivander Civil Engineering Department, Faculty of Engineering, Al-Azhar University, Medan, Indonesia

DOI:

https://doi.org/10.33603/jgst.v10i2.12504

Keywords:

bibliometric analysis, bioretention, saturated hydraulic conductivity, SWMM, systematic literature review,, tropical stormwater management

Abstract

Rapid urbanization has increased impervious surfaces, reducing infiltration capacity and intensifying stormwater runoff and flood risks. Bioretention, as a Low Impact Development (LID) approach, has been widely applied for sustainable urban stormwater management. However, the development and applicability of the EPA Storm Water Management Model (SWMM)-based bioretention modeling under tropical climate conditions remain insufficiently synthesized. This study evaluates global research trends, knowledge structures, critical design parameters, and the applicability of SWMM-based bioretention systems in tropical regions through bibliometric analysis and a Systematic Literature Review (SLR) following the PRISMA framework. A Scopus-based search covering 2021–2026 identified 1,067 articles for bibliometric analysis and 22 articles for SLR synthesis. Bibliometric analysis revealed four major research clusters: urban climate adaptation, bioretention performance and stormwater quality, SWMM-based hydrological modeling, and urban drainage integration. Research contributions remain dominated by China, the United States, and Europe, while tropical regions represent only 4.7% of the dataset. The SLR shows that bioretention performance depends strongly on hydrological conditions and design characteristics, with peak flow reductions ranging from 14.3% to 94%. Saturated hydraulic conductivity (Ks) was identified as the key calibration parameter. The study highlights the need for tropical parameter databases, locally validated SWMM models, and integrated hydrological–water quality simulations.

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