Storm Water Management Model Research Articles

Development of an Integrated Urban Flood Model and Its Application in a Concave-Down Overpass Area

Urban floods caused by extreme rainstorm events have increased in recent decades, particularly in concave-down bridge zones. To simulate urban flooding processes accurately, an integrated urban flood model (IUFM) was constructed by coupling a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM), a widely used pipe convergence module in the storm water management model (SWMM), with an inundation module that describes the overflow expansion process associated with terrain and land-cover. The IUFM was used in a case study of the Anhua Bridge (a typical concave-down overpass) study area in Beijing, China. The spatial-temporal variations in flood depth modeled by the IUFM were verified to be reliable by comparison with actual measurements and other simulations. The validated IUFM was used to obtain temporal variations in flood range, depth, and volume under four rainstorm scenarios (return periods of 3-year, 10-year, 50-year, and 100-year). The results showed that the surface runoff process, overflow from drainage networks, and overflow expansion process could affect the flooding status by changing the composition and spatial configuration of pervious or impervious patches, drainage capacity, and underlying surface characteristics (such as terrain and land-cover). Overall, although the simulation results from the IUFM contain uncertainties from the model structures and inputs, the IUFM is an effective tool that can provide accurate and timely information to prevent and control urban flood disasters and provide decision-making support for long-term storm water management and sponge city construction.

Evaluation of augmented infiltration based LIDs for low lying urbanizing coastal catchments: a case study of Chennai city, India

ABSTRACT The study assessed the effectiveness of infiltration-based Low Impact Development (LID) techniques and augmented infiltration LIDs (such as recharge shaft) in a coastal urban catchment in India using a semi-coupled approach between numerical models VS2DI and Storm Water Management Model (SWMM). Site specific VS2DI modelling indicated that the infiltration LIDs resulted in more saturation excess runoff due to the soil’s insufficient hydraulic conductivity and increased lateral flow. Catchment-scale modeling indicated that LIDs significantly improved water retention (p ≪ 0.05), with a 35% reduction in total runoff volume. The recharge shafts were shown to be more efficient in reducing runoff volume and peak runoff, particularly for high runoff rates (more than 22 mm/hr). The study suggests that direct recharge to the aquifer through recharge shafts could be a suitable solution to manage runoff and meet the demand for domestic water supply during times of water scarcity in coastal urban catchments.

Catchment-Scale Hydrologic Effectiveness of Residential Rain Gardens: A Case Study in Columbia, Maryland, USA

To mitigate the adverse impacts of urban stormwater on streams, watershed managers are increasingly using low-impact development and green infrastructure (LID-GI) stormwater control measures, such as rain gardens—vegetated depressional areas that collect and infiltrate runoff from rooftops and driveways. Their catchment-scale performance, however, can vary widely, and few studies have investigated the cumulative performance of residential rain gardens for event runoff control in intermediate-sized (i.e., 1–10 km2) suburban catchments. We modeled three years of continuous rainfall-runoff from a 3.1 km2 catchment in Columbia, MD, USA, using the Storm Water Management Model (SWMM). Various extents of rain garden implementation at residential houses were simulated (i.e., 25%, 50%, 75%, and 100% coverage) to determine the effects on peak flow, runoff volume, and lag time. On average, treating 100% of residential rooftops in the catchment reduced peak flows by 14.3%, reduced runoff volumes by 11.4%, and increased lag times by 3.2% for the 223 rainfall events during the simulation period. Peak flow reductions were greater for smaller storm events (p < 0.01). Our results show that residential rain gardens can significantly improve the runoff response of suburban catchments, and that they represent an effective and relatively low-cost option for urban watershed management and restoration.

Urban inundation mapping by coupling 1D − 2D models and model comparison

Urban inundation mapping is important for early warning, management, and drainage network planning. Urban flood simulations typically utilize a 1D model focused on pipe nodes, whereas 2D simulations are required over a land area. In this paper, our focus is on their coupling, so that a dynamic 1D-2D model is obtained. We couple the Storm Water Management Model (SWMM), a widely utilized urban drainage model, with 2D models to simulate urban inundation. The 1D-2D coupled inundation model uses the 1D model output, which represents the overflow volume of sparsely distributed pipe nodes. After coupling, surface inundation distribution maps are obtained. We developed a physically-based 2D overflow diffusion model (2D-DM) and compared it with two geostatistical models: Ordinary co-kriging (OCK) and Regression Kriging (RK). The study area is the central area of Haining City in China, where a severe storm occurred on August 3, 2018. The 2D-DM performed best (RMSE = 0.232), followed by RK (RMSE = 0.286), and OCK (RMSE = 0.361), but did not provide uncertainty measures, in contrast to the geostatistical models. We conclude that 1D-2D coupling was done successfully, with the different 2D models showing different qualities. To enhance urban inundation mapping, it is suggested to couple the 1D model with both physical and statistically based 2D models for a more comprehensive assessment of potential inundation areas and depths.

Optimal low-impact development Facility Design in Urban Environments: A multidimensional optimization approach employing slime mould and nondominated sorting genetic algorithms

This study presents the application of the slime mould algorithm (SMA) and the nondominated sorting genetic algorithm II (NSGA-II) to optimize low-impact development (LID) strategies in urban areas. The focus is on minimizing costs and improving water quality, using three LID practices (vegetated swales, bioretention systems, and porous pavements) in combination with a drainage system. The effectiveness of this stormwater management model (SWMM)-SMA-NSGA-II model is demonstrated in Tehran, Iran, where bioretention is found to be the most successful approach for improving water quality. The results also show that the SMA outperforms the NSGA-II in optimizing cost-effective LID solutions and is more computationally efficient, potentially due to its crossover operator. This research highlights the importance of considering qualitative aspects of urban runoff management. The study demonstrates that the combination of multiple LID strategies and the use of SMA and NSGA-II have the potential to achieve optimal solutions for managing stormwater in urban areas.

Urban storm water prediction by applying machine learning techniques and geomorphological characteristics

ABSTRACT The Storm Water Management Model (SWMM) is a reliable software program for simulating stormwater runoff in combined drainage facilities. However, it faces challenges in efficiency, especially when executing real-time forecasting. This research explores an alternative machine learning (ML) approach to predict water levels in sewer and street drainage systems utilizing SWMM data for model training. The goal is to construct a hybrid ML model for urban flooding prediction, considering hydrological conditions, geomorphologic properties, and drainage facility features. A robust training method is introduced to deliberate complex flow conditions. The suggested approach achieves favourable performance in predictive accuracy and computational efficiency. Findings include: (1) similarity between ML and SWMM flooding depth on street nodes increases from 62.3% to 96.2% with the proposed training; (2) the proposed model is about 50 times faster than SWMM in urban flood simulations; (3) reliable predictions from the ML model are demonstrated through four accuracy metrics.

Modeling the effect of land use change to design a suitable low impact development (LID) system to control surface water pollutants

Growth in urbanization has led to increased impervious surfaces, exacerbating flood risks and water quality degradation. This study investigated the impact of land use change and Low-Impact Development (LID) systems on urban runoff quality and quantity in the second region of Tehran. Pioneering an innovative approach, the integration of the Land Change Modeler (LCM) with the Stormwater Management Model (SWMM) signifies a paradigm shift in urban water management. Combined with other hydrological models, this new approach provides a comprehensive method for assessing the future effectiveness of LID practices. The Event Mean Concentration Method (EMC) was used in this study to measure Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Total Phosphorus (TP), and Zinc (Zn) in urban runoff from five land uses. Results pinpointed transportation land uses as the primary source of pollutants. Using LCM, the study forecasted a surge in urban runoff pollutants by 2030, particularly in the Northwest area of the region due to anticipated land use shifts towards commercial and residential land uses. Model results showed an 11 % increase in TSS over a decade, highlighting the importance of land use change in runoff quality. The study used three types of LIDs to reduce contaminants in dense urban areas. Assessing the impact of LID scenarios on runoff pollutants using SWMM revealed that the bio-retention cell had the best performance, reducing TSS by 20.92 %, and the vegetative swale had the worst performance, reducing TSS by 8.43 %. The study also concluded that combining LIDs would be more effective than using them separately. The results of this study suggest that LID systems can be an effective way to reduce urban runoff pollutants and improve water quality in the second region of Tehran. However, more research is needed to optimize the design and placement of LID systems in different urban areas.

Optimizing urban green infrastructure using a highly detailed surface modeling approach

Urban trees and forests show a better ecosystem with many benefits, including pure air quality. The development of urban green infrastructure (UGI) creates a better management system that greatly impacts social values in an urban system. The UGI and construction activities are receiving much attention for their effectiveness in addressing various urban ecological, social and economic issues. Using green infrastructure in stormwater management can reduce the influence on urban sewerage systems and, eventually, on building water resources. The main goal of the research is to optimize the green infrastructure to provide a less-pollution, well-organized, and pleasurable environment for the inhabitants. Various models are used to study the present rainfall-runoff scenario, but the stormwater management model (SWMM) is the most preferable and suggested model. Once the parameters are accessed, optimizing the green infrastructure (GI) will be easy. A complete SWMM model is evaluated over the complete surface, and a hydrological measurement is presented. The evaluation study presents various component percentages: asphalt (37%), green (27%), ceiling (21%), grit (12%), and cemented area (2%), which provides rainproof coverage of approximately 60%. A design is developed about the diverse events of GI in urban exploiting the SWMM and demonstrates its stimulus on the rainfall-runoff behaviour. In recent years, very little attention has been given to green spaces in urban areas, which not only increases pollution but also decreases the urbanization. Therefore, urban green spaces are more important to improve air quality and resident living standards. Over the given scenario and the rainfall event, a decline of the quantitative discharge parameters is evident, such as discharge volume (i.e., from 3.6 to 61.8) and the peak discharge rate (i.e., from 5.4 to 62.7%). The simulation results show that green areas give high satisfaction with low construction costs, which shows the superlative performance ratio of the examined measures. From the investigation, it is also recommended to have green areas and public spaces in impervious urban areas, which greatly reduced the runoff in the project area.

Assessing the Lifecycle Environmental Resilience of Urban Green Infrastructures Coping with Acute Disturbances and Chronic Stresses

Urban green infrastructure (UGI), a key component of nature-based solutions (NbSs), plays a vital role in enhancing urban resilience. Nonetheless, the absence of a thorough resilience evaluation for UGI has hindered the efficacy of its design and implementation. This article proposes an innovative urban environmental resilience index (ERI) framework designed to evaluate the lifecycle performance of UGI. First, a coupled environmental resilience evaluation system is proposed that encompasses indicators for the adaptation to acute disturbances and the mitigation of chronic pressures. Second, the inventive formulas for calculating the environmental resilience index are presented, which establish the weighting of indicators through Delphi-analytic hierarchy process (AHP) analysis, and the Storm Water Management Model (SWMM), GaBi, and i-Tree models are employed for the quantitative assessment. Third, four representative UGI scenarios in urban built-up areas have been selected for comparative analysis and in-depth discussion by calculating the resilience index. This research presents UGI solutions as adaptive measures for “Black Swan” events and “Gray Rhino” phenomena, offering significant case studies and methodological frameworks which will inform future endeavours in green and sustainable urban development.

Evaluation of hydraulic adequacy of runoff disposal in urban watersheds of rapidly expanding towns

ABSTRACT The growth of cities significantly alters natural catchments by increasing impervious surfaces and necessitating the installation of an appropriate drainage system. Arba Minch is rapidly expanding and facing street flooding. The objective of this study is to assess the hydraulic adequacy of runoff disposal in urban watersheds located in rapidly expanding towns. Stormwater Management Model (SWMM) was used to perform rainfall-runoff simulation. Personal Computer SWMM (PCSWMM) was used to carry out calibration and validation in the watershed. The primary and secondary data were used. Five Land Use/Land Cover (LULC) categories identified were asphalt, cobble, vegetation, bare soil, and roof. The result shows 33.49% area is covered with highly impervious land cover. The overall calibration and validation are a very good fit with the observed flow. The total runoff volume of 9494.15 km3 was generated from the town area which is 13.7 km2. The peak runoff determined from 373 sub-catchments varied from 0.01 to 4.48 m3s−1. According to the simulated result, 7.46% of existing drainage channels were flooded. Anticipating future runoff generation, this study evaluates the inadequacy of existing drainage channels in urban areas. Hydraulic analysis is recommended before constructing drainage structures to protect from flooding.

Assessing the impacts of urbanization and climate change on urban drainage system

AbstractUrban flooding is one of the significant issues that many cities are dealing with to ensure sustainable development. Upgrading the drainage systems is a standard measure that engineers have often used to reduce the risk of flooding. Because of climate change and urbanization, stormwater management systems may be inadequate to convey generated overflow in their catchment, which results in severe flooding in many cities worldwide. This research investigates climate change and urbanization's influence on urban flooding by simulating the EPA Stormwater Management Model for drainage systems in an urban catchment in An Ha, Tam Ky, Quang Nam. The results showed that urbanization shortens the initial abstraction ability while climate change increases extreme rainfall and water levels of receiving sources. Additionally, the impacts are even more substantial when the high urbanization rate increases by more than 70%, together with climate change.

Environmental Regulation and Stormwater Management Strategies for an Urban River in Northwest China: A Sustainable Approach

Low-impact developments (LIDs) have emerged as effective strategies for mitigating the adverse impacts of urbanization on river environments. This study aims to enhance river environment quality by examining the effects of LIDs and land use/cover change (LUCC) in the context of river environment and hydrological conditions. Using the Stormwater Management Model (SWMM) in an urban river setting, the study investigates the impact of LIDs on urban river water volume. An analysis of river runoff quality and quantity is conducted, followed by the development of an optimal river water regulation scheme through a multi-objective ecological scheduling model. The results reveal that the incorporation of LIDs can substantially decrease river runoff yield for varying recurrence periods of design rainstorms. Consequently, the flood peak reduction rate ranged from 10% to 18%, and the flood volume experienced a reduction of 10–29% in the study area. The combination of river water regulation, LIDs and LUCC leads to a decrease in river water volume within the lower river channel by up to 47% especially in a typical dry year and dry season, accompanied by a decline in river flow velocity and water self-purification capacity. A risk-based multi-objective stochastic optimization model is employed to ensure sustainable management of urban river runoff in terms of both quantity and quality. This research contributes to the advancement of knowledge in sustainable basin management practices and offers practical insights for policymakers involved in the management of water resources and environmental conservation in semi-arid basins.

Design Issue Analysis and Operation Effect Evaluation of Large-Scale Storage Tank

In order to address the issue of combined sewer overflows (CSOs), W city has constructed a large-scale storage tank with a volume of 220,000 m3. The storage tank is planned for CSO control in the near term and stormwater runoff pollution control in the long term. However, the actual operation of the storage tank is unsatisfactory. This paper elucidates the design scheme and operation mode of the tank and analyzes the challenges encountered during its design and operation. A storm water management model (SWMM) model was constructed to simulate the effect of the storage tank working in a combined sewer system (CSS), a separate sewer system (SSS) and a decentralized storage situation. This study determined that during the 2022 rainy season, the actual reduction in pollutants by the storage tank was only about 60% of the designed value. As a result, the inadequate treatment capacity of the downstream wastewater treatment plant (WWTP) resulted in the water being retained in the tank for a long time, leading to unsatisfactory operation outcomes. If the storage tank works in SSS and the problem of water retention can be solved, it could reduce the total runoff volume by 30% and the total amount of pollutants by 40% during the same rainy season. At the same time, under the premise of constant total storage volume, if decentralized storage tanks were used to control runoff pollution, the reduction effect can be increased by up to 11.6% compared with that of the centralized storage.

Optimizing the deployment of LID facilities on a campus-scale and assessing the benefits of comprehensive control in Sponge City

Rapid and intense urbanization has brought a wide range of serious issues like flooding and water pollution, which have become a great concern in a lot of cities. In response to these problems, Sponge City (SPC) has emerged as a potential solution. This study utilized the Stormwater Management Model (SWMM) to simulate urban runoff and determine an optimal combination of Low Impact Development (LID) strategies for reconstructing the study area. Upon analyzing the existing rainwater drainage system and revealed that it could only meet the design return period of 2-years, and identified the vulnerable flood-prone area and the maximum overflow node. After comprehensive consideration of various factors, the sponge reconstruction scenario selected four LID facilities combination: Porous pavement, Rain garden, Sunken green belt, and Green roof. Results indicated that when P = 1-yr, 5-yr, 10-yr and 20-yr, the total runoff in the LID scenario decreased by 43.91 %, 43.93 %, 45.95 % and 47.11 %, respectively. LID facilities substantially mitigate stormwater runoff and peak flows during moderate to light rainfall events. These LID facilities prove effective in reducing pollutant concentrations (reduction rate is all over 42 %), with notable reductions in Chemical Oxygen Demand (COD) and Suspended Solids (SS). This paper offers valuable insights that can serve as a reference for the construction or renovation of SPC, shedding light on effective strategies and considerations for managing stormwater and mitigating the impact of urbanization.

Assessing urban drainage pressure and impacts of future climate change based on shared socioeconomic pathways

The increasing frequency of urban flood disasters presents a significant obstacle to urban sustainability. Urban flood management aims to reduce the flood occurrences, currently addressed through urban drainage systems. Previous studies have demonstrated future precipitation extremes will pose larger pressure on urban drainage network, but when and where the pressure will reach a dangerous level have never been assessed in any city of China. This study establishes the initial framework for identifying critical decades and hot spots of urban drainage pressure changes due to future climate change, through a case study conducted in southern China (Haining city). Urban drainage pressure was assessed by a combination of the urban drainage model known as the Storm Water Management Model (SWMM) and pipe statistics. Using climate projections from the latest phase of Coupled Model Intercomparison Project (CMIP6) under four typical SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios, we project the changes in urban drainage pressure by 21st century, and identify the key decades and high risk areas with the occurrence of dangerous pressure levels. The results indicate an overall upward trend in urban drainage pressure for Haining city, with over 97% of the flooding nodes projected to firstly reach the dangerous level by the 2030 s. Comparisons of the patterns under different SSP-RCP scenarios, suggest that a higher forcing pathway would expedite the deterioration of urban drainage pressure, particularly in urban areas with lower DEM and high building intensity. This has broad implications for better informing disaster management and policy-making in similar cities, especially those with inadequate drainage capacities.

Evacuation information methodology that combined a flooded environment and pedestrian behavioral model

Disaster information influences decision-making. Wireless internet and location-based services, aided by recent technological advances, have laid the foundation for providing personalized disaster information. Despite the provision of simple disaster forecasts and warnings, provision of specific evacuation actions (“where” and “how,” i.e., location and reachability of safe areas) and location-based personalized information that consider real-time disaster situations are a pressing priority. Thus, this study proposed and developed a three-step methodology for providing disaster information during floods that combined a flooded environment and pedestrian behavioral model, namely, 1) prediction of the flooded environment, 2) analysis of evacuation routes based on the movement time of evacuees according to the flood depth, and 3) provision of evacuation information by selecting the optimal evacuation route. This model was demonstrated in the Gangnam Station area in Seoul, Korea. Flooded environment prediction modeling of the target area was performed by applying the 100-year rainfall design to the Storm Water Management Model. The optimal evacuation route, according to the flood depth, was selected by applying the behavioral model (movement time calculation formula) for each evacuee derived through an evacuation behavior experiment. The pre- and post-flooding age- and gender-wise total evacuation distance and time were compared and analyzed. Post-flooding, the evacuation distance and time increased by 168.3% (381.34 m) and 172.3% (3.16 min) on average, respectively, indicating that evacuees must travel farther and longer. The analysis of post-flooding evacuation route change types revealed changes in evacuation distance and time in cases where shelters and evacuation routes and time were significantly different depending on evacuee characteristics (age and gender). This indicated that specific and visual disaster information can be provided according to evacuees’ age and gender using the proposed methodology. This study can serve as the basis for designing an advanced and personalized disaster information system that can provide specific evacuation actions to aid fast evacuation decision-making during floods.

Simulations of low impact development designs using the storm water management model

This study assessed the U.S. Environmental Protection Agency's Storm Water Management Model (SWMM) for urban water management challenges. This study conducted a sensitivity analysis to identify the most influential factors in the SWMM. Moreover, the performance of SWMM was evaluated with the HYDRUS-1D module in simulating infiltration rates. The sensitivity results showed field capacity as the most significant factor, highlighting the need for advanced modeling techniques to consider factors like field capacity. The SWMM was evaluated by the HYDRUS-1D that SWMM consistently underestimated peak infiltration rates and commenced infiltration calculations only when soil moisture exceeded field capacity. It reveals its limitations in handling unsaturated soil conditions and highlights the consideration of the matric head of the soil during the infiltration calculation in soil media. Moreover, the evaluation of bioretention areas showed larger areas resulting in more substantial flow reductions but with significant variability under different rainfall conditions. Accordingly, this result emphasizes the importance of careful consideration for environmental factors in bioretention design. This study contributes by enhancing understanding of SWMM's limitations in simulating urban water management challenges. Thus, this research will offer technical assistance to stakeholders focused on challenges such as runoff, hydrologic cycle, and urban flooding in urban areas.

Operation Risk Simulation and Interaction Impact of Stormwater and Sewage Systems Based on Storm Water Management Model

With the increasing urbanization rate, higher demand is placed on drainage systems, necessitating analysis of their risk profiles. While many studies focus on the individual hydraulic modeling of stormwater and wastewater systems when considering operational risks, they often overlook the exacerbating effects of combined stormwater and wastewater flows on each other’s risks. In this study, we constructed a model of the combined stormwater and wastewater drainage system in Lijiao, Guangdong Province. We analyzed the operational risks of both stormwater and sewage networks in different scenarios, focusing on full-load pipes, overload pipes, node overflows, and minimum flow velocities. Furthermore, we compared the exacerbating effects of sewage and stormwater on each other’s network operational risks. Simulation results indicated that, for sewage networks with combined sewer sections, the lengths of full-load pipes and overload pipes increased by an average of 27.4% and 16.3%, respectively, during rainy weather scenarios compared to dry weather. After considering the inflow of sewage into combined sewer sections, the average length of full-load pipes increased by 3.8 km, overload pipe length increased by 1.1 km, and overflow volume increased by 2.26 × 104 m3. As the return period of rainfall events increases, these inter-system impacts gradually diminish. Therefore, when modeling drainage systems and assessing operational risks, particularly during low return period rainfall events, the inclusion of both stormwater and sewage in combined sewer networks should be comprehensively considered.

Efficiency evaluation of low impact development practices on urban flood risk

Urban flood risk assessment delivers invaluable information regarding flood management as well as preventing the associated risks in urban areas. The present study prepares a flood risk map and evaluate the practices of low-impact development (LID) intended to decrease the flood risk in Shiraz Municipal District 4, Fars province, Iran. So, this study investigate flood vulnerability using MCDM models and some indices, including population density, building age, socio-economic conditions, floor area ratio, literacy, the elderly population, and the number of building floors to. Then, the map of thematic layers affecting the urban flood hazard, including annual mean rainfall, land use, elevation, slope percentage, curve number, distance from channel, depth of groundwater, and channel density, was prepared in GIS. After conducting a multicollinearity test, data mining models were used to create the urban flood hazard map, and the urban flood risk map was produced using ArcGIS 10.8. The evaluation of vulnerability models was shown through the use of Boolean logic that TOPSIS and VIKOR models were effective in identifying urban flooding vulnerable areas. Data mining models were also evaluated using ROC and precision-recall curves, indicating the accuracy of the RF model. The importance of input variables was measured using Shapley value, which showed that curve number, land use, and elevation were more important in flood hazard modeling. According to the results, 37.8 percent of the area falls into high and very high categories in terms of flooding risk. The study used a stormwater management model (SWMM) to simulate node flooding and provide management scenarios for rainfall events with a return period ranging from 2 to 50 years and five rainstorm events. The use of LID practices in flood management was found to be effective for rainfall events with a return period of less than 10 years, particularly for two-year events. However, the effectiveness of LID practices decreases with an increase in the return period. By applying a combined approach to a region covering approximately 10 percent of the total area of Shiraz Municipal District 4, a reduction of 2–22.8 percent in node flooding was achieved. The analysis of data mining and MCDM models with a physical model revealed that more than 60% of flooded nodes were classified as "high" and "very high" risk categories in the RF-VIKOR and RF-TOPSIS risk models.

Effectiveness of bioretention system and vegetated swale for reducing urban flood risk in equatorial region: a case study in Kuching, Malaysia

One of the main causes of urban inundation is the rise of impermeable surfaces brought on by increasing urbanization. Low impact development (LID) practices have been employed in previous studies to mitigate urban flooding. However, the effectiveness of LID practices in reducing runoff peaks and improving water quality is unknown, especially in the equatorial region. This study explored nine alternative scenarios to evaluate the effectiveness of the bioretention system and vegetated swale using the Storm Water Management Model (SWMM). Using precipitation data of December 2021, the Swinburne University of Technology Sarawak Campus has been chosen as the case study. The findings demonstrated that these two LID practices could significantly lessen urban flooding. Under scenario 7, the combination of 28.4% bioretention system and 11.3% vegetated swale reduced the maximum runoff peaks by 22.98% at Peak A, 24.71% at Peak B, and 24.09% at Peak C. In the meantime, under scenario 7, the implemented LID practice has removed 20.09% of TSS, 19.75% of TP, and 12.26% of TN. It was discovered that runoff peak reduction increases as the area covered by vegetated swale and bioretention system increases. The outcomes showed that bioretention system performed better than the vegetated swale in reducing peak runoff and enhancing water quality. Local authorities can use the findings of this study to offer recommendations for reducing disaster risk, controlling urban flooding, and revitalizing urban areas.