Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters haveoccurred almost annu...Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters haveoccurred almost annuallyinthe urban area of Beijing, the capital of China. Based on a selforganizing map(SOM) artificial neural network(ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product(GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANNis suitable for automatically and quantitatively assessing risks associated with waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors,producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. The points that were assigned risk grades of IV or Vwere located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.展开更多
The pollutants in urban storm runoff, which lead to an non-point source contamination of water environment around cities, are of great concems. The distributions of typical contaminants and the variations of their spe...The pollutants in urban storm runoff, which lead to an non-point source contamination of water environment around cities, are of great concems. The distributions of typical contaminants and the variations of their species in short term storm runoff from different land surfaces in Xiamen City were investigated. The concentrations of various contaminants, including organic matter, nutrients （i.e., N and P） and heavy metals, were significantly higher in parking lot and road runoff than those in roof and lawn runoff. The early runoff samples from traffic road and parking lot contained much high total nitrogen （TN 6-19 mg/L） and total phosphorus （TP 1-3 mg/L）. A large proportion （around 60%） of TN existed as total dissolved nitrogen （TDN） species in most runoff. The percentage of TDN and the percentage of total dissolved phosphorus remained relatively stable during the rain events and did not decrease as dramatically as TN and TP. In addition, only parking lot and road runoff were contaminated by heavy metals, and both Pb （25-120 μg/L） and Zn （0.1-1.2 mg/L） were major heavy metals contaminating both runoff. Soluble Pb and Zn were predominantly existed as labile complex species （50%-99%）, which may be adsorbed onto the surfaces of suspended particles and could be easily released out when pH decreased. This would have the great impact to the environment.展开更多
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 mode...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.展开更多
The rapid urbanization and industrialization involve an unsustainable use of natural systems,leading to various problems in cities.The urban hydrological system experiences fluctuating amount of surface runoff water w...The rapid urbanization and industrialization involve an unsustainable use of natural systems,leading to various problems in cities.The urban hydrological system experiences fluctuating amount of surface runoff water when it rains heavily.It has been suggested that green roofs significantly mitigate storm water runoff generation even in tropical climate.Green roofs have become popular due to its proven benefits by mitigating urban heat island effects and protecting biodiversity.The annual rainfall and runoff relationship for green roofs is determined by the depth of the substrate.Water retention capacity mostly depends on substrate's physical conditions such as dry or wetness.Generally 6 mm to 12 mm rainfall is required for dry substrate to initiate runoff whereas response of wet conditions is mostly straight.Besides,there are some other factors affecting runoff dynamics such as type of a green roof and its slope,age of green roof,type of vegetation,soil moisture characteristics,weather.The review indicates that there is not much research in green roofs performance over storm water runoff;hence there is a need for further research.This paper reviews and addresses the role of green roofs in urban storm water management.展开更多
受全球气候变暖、城市化进程加快的共同影响,近年来城市极端降雨事件频发导致内涝灾害发生。基于水文、水动力模型得到的城市雨洪数值模拟结果难以展示降雨、内涝渐变过程等问题。提出雨洪内涝过程三维实景动态模拟表达方法,首先采用GAS...受全球气候变暖、城市化进程加快的共同影响,近年来城市极端降雨事件频发导致内涝灾害发生。基于水文、水动力模型得到的城市雨洪数值模拟结果难以展示降雨、内涝渐变过程等问题。提出雨洪内涝过程三维实景动态模拟表达方法,首先采用GAST(GPU Accelerated Surface Water Flow and Transport Model)水动力模型对雨洪内涝过程数值模拟,通过Godunov类型有限体积法进行数值离散,采用GPU并行技术加速计算获取不同输出时间下的数值模拟结果,创新设计了GAST模型数值模拟结果与数字高程模型数据耦合方法,构建了数字淹没网格模型(Digital Inundation Grid Model,DIGM),基于WebGL和三维地理信息系统(3D Geographic Information System,3D GIS)技术开发三维实景动态可视化引擎,构建雨洪内涝过程三维实景动态渲染机制,对雨洪内涝过程三维实景动态模拟进行表达。最后,采用本方法实现了西安2020年7月10日2次强降雨致涝过程三维实景动态模拟表达,结果生动直观准确,与实测结果吻合度高,表明该方法可有效弥补现有城市雨洪内涝数值模拟表达方法的不足,具有良好的应用价值。展开更多
基金supported by the National Key R&D Program of China (GrantN o.2016YFC0401407)National Natural Science Foundation of China (Grant Nos. 51479003 and 51279006)
文摘Due to rapid urbanization, waterlogging induced by torrential rainfall has become a global concern and a potential risk affecting urban habitant's safety. Widespread waterlogging disasters haveoccurred almost annuallyinthe urban area of Beijing, the capital of China. Based on a selforganizing map(SOM) artificial neural network(ANN), a graded waterlogging risk assessment was conducted on 56 low-lying points in Beijing, China. Social risk factors, such as Gross domestic product(GDP), population density, and traffic congestion, were utilized as input datasets in this study. The results indicate that SOM-ANNis suitable for automatically and quantitatively assessing risks associated with waterlogging. The greatest advantage of SOM-ANN in the assessment of waterlogging risk is that a priori knowledge about classification categories and assessment indicator weights is not needed. As a result, SOM-ANN can effectively overcome interference from subjective factors,producing classification results that are more objective and accurate. In this paper, the risk level of waterlogging in Beijing was divided into five grades. The points that were assigned risk grades of IV or Vwere located mainly in the districts of Chaoyang, Haidian, Xicheng, and Dongcheng.
基金supported by the Knowledge Innovation Program of Chinese Academy of Sciences for Young Scientists in Frontier Research (No.07l4161b10)the National Natural Science Foundation of China (No.20807033)
文摘The pollutants in urban storm runoff, which lead to an non-point source contamination of water environment around cities, are of great concems. The distributions of typical contaminants and the variations of their species in short term storm runoff from different land surfaces in Xiamen City were investigated. The concentrations of various contaminants, including organic matter, nutrients （i.e., N and P） and heavy metals, were significantly higher in parking lot and road runoff than those in roof and lawn runoff. The early runoff samples from traffic road and parking lot contained much high total nitrogen （TN 6-19 mg/L） and total phosphorus （TP 1-3 mg/L）. A large proportion （around 60%） of TN existed as total dissolved nitrogen （TDN） species in most runoff. The percentage of TDN and the percentage of total dissolved phosphorus remained relatively stable during the rain events and did not decrease as dramatically as TN and TP. In addition, only parking lot and road runoff were contaminated by heavy metals, and both Pb （25-120 μg/L） and Zn （0.1-1.2 mg/L） were major heavy metals contaminating both runoff. Soluble Pb and Zn were predominantly existed as labile complex species （50%-99%）, which may be adsorbed onto the surfaces of suspended particles and could be easily released out when pH decreased. This would have the great impact to the environment.
基金supported by the Korea Ministry of Environment, as "The Eco-innovation Project" (No. 413111-003)
文摘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.
文摘The rapid urbanization and industrialization involve an unsustainable use of natural systems,leading to various problems in cities.The urban hydrological system experiences fluctuating amount of surface runoff water when it rains heavily.It has been suggested that green roofs significantly mitigate storm water runoff generation even in tropical climate.Green roofs have become popular due to its proven benefits by mitigating urban heat island effects and protecting biodiversity.The annual rainfall and runoff relationship for green roofs is determined by the depth of the substrate.Water retention capacity mostly depends on substrate's physical conditions such as dry or wetness.Generally 6 mm to 12 mm rainfall is required for dry substrate to initiate runoff whereas response of wet conditions is mostly straight.Besides,there are some other factors affecting runoff dynamics such as type of a green roof and its slope,age of green roof,type of vegetation,soil moisture characteristics,weather.The review indicates that there is not much research in green roofs performance over storm water runoff;hence there is a need for further research.This paper reviews and addresses the role of green roofs in urban storm water management.
文摘受全球气候变暖、城市化进程加快的共同影响,近年来城市极端降雨事件频发导致内涝灾害发生。基于水文、水动力模型得到的城市雨洪数值模拟结果难以展示降雨、内涝渐变过程等问题。提出雨洪内涝过程三维实景动态模拟表达方法,首先采用GAST(GPU Accelerated Surface Water Flow and Transport Model)水动力模型对雨洪内涝过程数值模拟,通过Godunov类型有限体积法进行数值离散,采用GPU并行技术加速计算获取不同输出时间下的数值模拟结果,创新设计了GAST模型数值模拟结果与数字高程模型数据耦合方法,构建了数字淹没网格模型(Digital Inundation Grid Model,DIGM),基于WebGL和三维地理信息系统(3D Geographic Information System,3D GIS)技术开发三维实景动态可视化引擎,构建雨洪内涝过程三维实景动态渲染机制,对雨洪内涝过程三维实景动态模拟进行表达。最后,采用本方法实现了西安2020年7月10日2次强降雨致涝过程三维实景动态模拟表达,结果生动直观准确,与实测结果吻合度高,表明该方法可有效弥补现有城市雨洪内涝数值模拟表达方法的不足,具有良好的应用价值。
