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.     

山地城市典型硬化下垫面暴雨径流初期冲刷研究

为了解山地城市典型硬化下垫面暴雨径流初期冲刷效应,对山城重庆的8场暴雨进行了径流全过程监测,并与平原城市作了对比分析.结果表明:TSS(总悬浮物)、COD和TP来自城市交通干道的贡献较混凝土屋面大,而TN、NH3-N两者相当;对于重金属,除Cd外,城市交通干道重金属的EMC(Event Mean Concentration)值均高于混凝土屋面.城市交通干道,初期40%的暴雨径流携带了53%±16%TSS,66%±10%COD,59%±2%TN,58%±2%NH3-N,51%±5%TP;而混凝土屋面,初期40%的暴雨径流携带了64%±20%TSS,66%±17%COD,55%±14%TN,52%±14%NH3-N,56%±3%TP,建议两类硬化下垫面至少以初期40%的暴雨径流作为控制量.与平原城市相比,山地城市交通干道初期40%的暴雨径流携带污染负荷TSS与COD的比例比平原城市分别高出16%和22%,初期冲刷效应更加明显.     

降雨和土地利用对地表径流的影响-以北京北护城河周边区域为例

以北京北护城河周边区域为例,探讨了降雨和土地利用对地表径流的影响。选取了2011-2012 年4-11 月的15 场降雨,分别代表小雨、中雨、大雨、暴雨、大暴雨和特大暴雨这6 个雨量级。利用校准的雨洪管理模型（Storm Water Management Model, SWMM）分别模拟每次降雨事件下研究区7 个控制断面的地表径流深度。结果表明,地表径流深度随降雨量的增加显著线性增加。当降雨量在不同量级之间变化时,地表径流深度的变化幅度不尽相同。在不同的降雨事件中,降雨量和地表径流深度随时间的动态变化趋势可能有很大的差异,但地表径流深度在某一时刻的值的高低均决定于之前1~2 h 的降雨量,而地表径流深度的总体上升或下降趋势均决定于前期累积的降雨量。地表径流深度随渗透面积比例的增加显著下降,且变化曲线存在临界阈值（为15%~20%）。在暴雨、大暴雨和特大暴雨时,渗透面积比例对地表径流的影响更大。研究结果可为控制汛期城市地表径流量和洪峰流量、减少城市内涝提供土地利用和管理方面的理论依据和决策建议。     

3种生物滞留设计对城市地表径流溶解性氮的去除作用

城市地表径流溶解性氮(N)的有效控制具有挑战性.2015构建了3种不同设计的生物滞留设施:壤砂种植紫穗狼尾草(CB)、壤砂种植紫穗狼尾草设置饱和带(MB1)、壤砂种植紫穗狼尾草设置饱和带并添加10%木块(MB2).在模拟城市地表径流水文、水质变化条件下,研究3种生物滞留种植植物、设置饱和带以及添加碳源对城市地表径流溶解性N(NH_4~+-N、NO_3~--N)的去除作用.通过为期1年试验监测表明,在进水NH_4~+-N浓度平均值为(5.45±2.21)mg·L-1情况下,3种生物滞留对NH_4~+-N均具有显著的去除作用(去除率95%).基质吸附、硝化与植物吸收是生物滞留有效去除城市地表径流NH_4~+-N的主要途径.在进水NO_3~--N平均值为(5.88±2.32)mg·L-1情况下,CB、MB1和MB2出水NO_3~--N浓度的平均值分别为(4.04±2.64)、(0.84±1.18)和(0.26±0.48)mg·L-1,相应去除率分别为31.3%、85.7%和95.6%.生物滞留种植紫穗狼尾草、设置饱和带以及添加碳源均可显著降低出水NO_3~--N浓度,减少NO_3~--N淋溶输出,提高NO_3~--N去除率.植物吸收和微生物反硝化是生物滞留去除NO_3~--N的主要途径.进水NO_3~--N浓度、水量、间隔天数是影响生物滞留出水NO_3~--N浓度的主要因素.生物滞留种植紫穗狼尾草、设置饱和带并添加碳源,在水文、水质变化情况下,仍可有效去除城市地表径流溶解性N.     

太湖上游城市宜兴城区主干道路径流污染特征解析

通过监测2015年8月—2016年9月7场典型降雨事件,系统分析太湖上游城市宜兴城区3个不同功能区(环科园、新城区和老城区)主干道路径流污染特征.研究表明:宜兴市城区主干道路径流浊度、COD、TN、NH_3-N、TP浓度分别为(77.2±66.9)NTU、(97.2±79.7)、(3.0±1.9)、(0.93±0.59)和(0.35±0.36)mg·L~(-1).COD和TN超出地表水环境Ⅴ类标准,是该地区径流特征污染物.降雨过程中污染物浓度整体呈下降趋势,伴随有不同程度的波动,主要受地表残留污染物及降雨强度的影响.3个区域TN浓度差异不大,且主要以溶解态存在(60%);环科园、新城区TP浓度差异不大,且主要以颗粒态存在(70%);然而,受居民生活活动的影响,老城区TP主要以溶解态存在(60%).此外,受交通及道路坡度影响,新城区道路径流浊度和COD污染最为严重.不同降雨事件径流污染物浓度变化较大,主要受干期长度和降雨强度的影响.干期长度越长、降雨强度越小,污染物累积量及可冲刷量越大.因此,加强控制宜兴市道路初期径流、路面颗粒物、径流颗粒物和TN以及老城区TP,对保护径流主要受纳水体南溪水系及太湖水体具有重要意义.     

极端冰雪条件下的顺层岩质边坡滑移稳定性分析

推导了典型岩石边坡在极端冰雪条件下的滑移稳定系数的表达式;通过计算分析,揭示了岩石边坡滑移稳定系数随裂隙内水深、坡高、坡角、滑面倾角等因素变化的规律及与冻深的关系,并绘制岩石边坡滑移稳定系数与边坡几何要素之间的关系图.研究表明,当考虑极端冰雪灾害影响时,岩石边坡滑移稳定系数发生较为明显的变化:随裂隙饱水程度、坡面角、主...     

Effect of selected organic and inorganic snow and cloud components on the photochemical generation of nitrite by nitrate irradiation

The effect of selected organic and inorganic compounds, present in snow and cloudwater was studied. Photolysis of solutions of nitrate to nitrite was carried out in the laboratory using a UVB light source. The photolysis and other reactions were then modelled. It is shown that formate, formaldehyde, methanesulphonate, and chloride to a lesser extent, can increase the initial formation rate of nitrite. The effect, particularly significant for formate and formaldehyde, is unlikely to be caused by scavenging of hydroxyl radicals. The experimental data obtained in this work suggest that possible causes are the reduction of nitrogen dioxide and nitrate by radical species formed on photooxidation of the organic compounds. Hydroxyl scavenging by organic and inorganic compounds would not affect the initial formation rate of nitrite, but would protect it from oxidation, therefore, increasing the concentration values reached at long irradiation times. The described processes can be relevant to cloudwater and the quasi-liquid layer on the surface of ice and snow, considering that in the polar regions irradiated snow layers are important sources of nitrous acid to the atmosphere. Formate and (at a lesser extent) formaldehyde are the compounds that play the major role in the described processes of nitrite/nitrous acid photoformation by initial rate enhancement and hydroxyl scavenging.     

Spectroscopic Distribution of Dissolved Organic Matter in a Dam Reservoir Impacted by Turbid Storm Runoff

Spectroscopic characteristics of dissolved organic matter (DOM) in a large dam reservoir were determined using ultraviolet absorbance and fluorescence spectroscopy to investigate spatial distribution of DOM composition after turbid storm runoff. Water samples were collected along a longitudinal axis of the reservoir at three to four depths after a severe storm runoff. Vertical profiles of turbidity data showed that a turbid water layer was located at a middle depth of the entire reservoir. The spectroscopic characteristics of DOM samples in the turbid water layer were similar to those of terrestrial DOM, as demonstrated by the higher specific UV absorbance (SUVA) and the lower fluorescence emission intensity ratio (F ₄₅₀/F ₅₀₀) compared to other surrounding DOM samples in the reservoir. Synchronous fluorescence spectroscopy revealed that higher content of humic-like DOM composition was contained in the turbid water. Fluorescence excitation–emission matrix (EEM) showed that lower content of protein-like aromatic amino acids was present in the turbid water DOM. The highest protein-like fluorescence was typically observed at a bottom layer of each sampling location. The bottom water DOM exhibited extremely high protein-like florescence near the dam site. The particular observation was attributed to the low water temperature and the isolation of the local bottom water due to the upper location of the withdrawal outlet near the dam. Our results suggest that the distribution of DOM composition in a dam reservoir is strongly influenced by the outflow operation, such as selective withdrawal, as well as terrestrial-origin DOM inputs from storm runoff.     

An Analysis of Patterns and Trends in United States Stormwater Utility Systems

Several factors, such as municipality location and population, are thought to influence trends among stormwater utilities (SWUs); however, no analysis of the relationship between these factors and SWU characteristics has been performed. This article corroborates hypothesized relationships and identifies trends and patterns in the establishment, funding mechanism, and magnitude of SWUs by analyzing location, population density, home value, and year of establishment for a comprehensive national SWU database with data for 1,490 SWUs. The equivalent residential unit (ERU), a SWU that charges based on impervious area, was the most prevalent funding mechanism in all National Oceanic and Atmospheric Administration Climate Regions of the United States except the West and West‐North‐Central. The ERU was also found in larger cities with high population densities, whereas the Flat Fee, a SWU that charges a single rate for all properties, was found in smaller towns. Higher home values were correlated with higher monthly fees for 28% of the municipalities analyzed. The residential equivalence factor, a SWU that charges based on runoff produced, was popular in municipalities with higher home values, whereas the Flat Fee was popular in municipalities with lower home values. The number of SWUs established increased with Phase I municipal separate stormwater and sewer system (MS4) permit and Phase II small MS4 permit deadlines. Summary tables provide guidance to aid municipalities considering a SWU.     

Testing and Improving Temperature Thresholds for Snow and Rain Prediction in the Western United States

The phase of precipitation at the land surface is critical to determine the timing and amount of water available for hydrological and ecological systems. However, there are few techniques to directly observe the precipitation phase and many prediction tools apply a single temperature threshold (e.g., 0°C) to determine phase. In this paper, we asked two questions: (1) what is the accuracy of default and station optimized daily temperature thresholds for predicting precipitation phase and (2) what are the regions and conditions in which typical temperature‐based precipitation phase predictions are most suited. We developed a ground truth dataset of rain vs. snow using an expert decision‐making system based on precipitation, snow depth, and snow water equivalent observations. This dataset was used to evaluate the accuracy of three temperature‐threshold‐based techniques of phase classification. Optimizing the temperature threshold improved the prediction of precipitation phase by 34% compared to using 0°C threshold. Developing a temperature threshold based on station elevation improved the error by 12% compared with using the 0°C temperature threshold. We also found the probability of snow as a function of temperature differed among ecoregions, which suggests a varied response to future climate change. These results highlight a current weakness in our ability to predict the effects of regional warming that could have uneven impacts on water and ecological resources.