Green Roof Performance for Stormwater Management in Equatorial Urban Areas Using Storm Water Management Model (SWMM)

Many Low Impact Developments (LIDs) have recently been developed as a sustainable integrated strategy for managing the quantity and quality of stormwater and surrounding amenities. Previous research showed that green roof is one of the most promising LIDs for slowing down rainwater, controlling rainwater volume, and enhancing rainwater quality by filtering and leaching contaminants from the substrate. However, there is no guideline for green roof design in Malaysia. Hence, Investigating the viability of using green roofs to manage stormwater and address flash flood hazards is urgently necessary. This study used the Storm Water Management Model (SWMM) to evaluate the effectiveness of green roof in managing stormwater and improving rainwater quality. The selected study area is the multistory car park (MSCP) rooftop at Swinburne University of Technology Sarawak Campus. Nine green roof models with different configurations were created. Results revealed that the optimum design of a green roof is 100 mm of berm height, 150 mm of soil thickness, and 50 mm of drainage mat thickness. With the ability to reduce runoff generation by 26.73%, reduce TSS by 89.75%, TP by 93.07%, TN by 93.16%, and improved BOD by 81.33%. However, pH values dropped as low as 5.933 and became more acidic due to the substrates in green roof. These findings demonstrated that green roofs improve water quality, able to temporarily store excess rainfall and it is very promising and sustainable tool in managing stormwater.

Linking a Storm Water Management Model to a Novel Two-Dimensional Model for Urban Pluvial Flood Modeling

This article describes a new method of urban pluvial flood modeling by coupling the 1D storm water management model(SWMM)and the 2D flood inundation model(ECNU Flood-Urban).The SWMM modeling results(the overflow of the manholes)are used as the input boundary condition of the ECNU Flood-Urban model to simulate the rainfall–runoff processes in an urban environment.The analysis is applied to the central business district of East Nanjing Road in downtown Shanghai,considering 5-,10-,20-,50-,and 100-year return period rainfall scenarios.The results show that node overflow,water depth,and inundation area increase proportionately with the growing return periods.Water depths are mostly predicted to be shallow and surface flows generally occur in the urban road network due to its low-lying nature.The simulation result of the coupled model proves to be reliable and suggests that urban surface water flooding could be accurately simulated by using this methodology.Adaptation measures(upgrading of the urban drainage system)can then be targeted at specific locations with significant overflow and flooding.

Evaluation of accuracy of linear regression models in predicting urban stormwater discharge characteristics

Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days （ADD）, have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency＇s Storm Water Management Model （SWMM）. The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid （TSS） discharge loads and event mean concentrations （EMC） were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.

基于弱耦合求解方法的排水管网底泥输运模拟

通过将SWMM(storm water management model)模型与底泥输运模型耦合计算实现对于排水管网底泥输运工况的模拟。利用该耦合求解方法,底泥输运过程对于管渠过流断面以及水流中污染物浓度的影响均可进行定量计算。耦合计算过程中全局时间步长由SWMM的时间步长确定,通过对底泥输运模型进行适当的调整使其适应SWMM时间步长,从而实现模拟的数值稳定性,避免了底泥输运模型出现过度沉积或过度冲刷引起数值不稳定的情况。该模拟方法通过2个案例进行了验证。通过案例的模拟结果可以看出该耦合过程可以给出稳定且合理的模拟结果,可以模拟管渠底泥的沉积及冲刷的过程以及其对于管渠过流断面及污染物浓度变化的影响。相较于单纯的SWMM模拟结果,耦合模型可以给出更加准确的模拟结果。

基于SWMM的鱼清河流域内涝模型研究

鱼清河流域作为山东省南四湖(微山湖、昭阳湖、独山湖、南阳湖)西侧的典型易涝区,常年遭受涝灾。通过SWMM(Storm Water Management Model)软件用于城市内涝过程模拟时采用的子汇水区加排水沟(管)道的模式,构建了基于SWMM的鱼清河平原洼地流域内涝模型,并且对产流计算结果及内涝淹没结果的合理性进行了分析,结果表明,模型计算结果合理、可靠,可为平原洼地的治理工作提供支撑。该研究成果可以为同类型地区的内涝研究工作提供参考。

Probability mass first flush evaluation for combined sewer discharges

The Korea government has put in a lot of effort to construct sanitation facilities for controlling non-point source pollution. The first flush phenomenon is a prime example of such pollution. However, to date, several serious problems have arisen in the operation and treatment effectiveness of these facilities due to unsuitable design flow volumes and pollution loads. It is difficult to assess the optimal flow volume and pollution mass when considering both monetary and temporal limitations. The objective of this article was to characterize the discharge of storm runoff pollution from urban catchments in Korea and to estimate the probability of mass first flush （MFFn） using the storm water management model and probability density functions. As a result of the review of gauged storms for the representative using probability density function with rainfall volumes during the last two years, all the gauged storms were found to be valid representative precipitation. Both the observed MFFn and probability MFFn in BE-1 denoted similarly large magnitudes of first flush with roughly 40% of the total pollution mass contained in the first 20% of the runoff. In the case of BE-2, however, there were significant difference between the observed MFFn and probability MFFn.