BUILDUP,WASHOFF, AND EVENT MEAN CONCENTRATIONS1

ABSTRACT: Most watershed water quality simulation models require the user to specify pollutant buildup and washoff rate parameters for pollutants, by land use. Buildup and washoff rates are difficult to measure directly, and only limited guidance and few observed data are available from the literature. Many studies, however, report storm event mean concentrations (EMCs). These EMCs must arise as a result of the buildup and washoff processes, but typically represent the net contribution from a variety of pervious and impervious surfaces. This paper explores the relationship between EMCs and buildup/washoff parameters. An assumption of the mathematical form of the buildup/washoff relationship gives an algebraic expression for the EMC consistent with model assumptions. This yields techniques to separate observed EMCs into contributions from different land uses and from pervious and impervious surfaces. Given this relationship, numerical optimization may be used to estimate site specific values of buildup and washoff parameters from observed storm EMCs for use in modeling. Use of this approach helps ensure that model parameters are consistent with observed data, providing a rational starting point for final model calibration. Several site examples demonstrate use of the method.     

NATURAL EROSION RATES AND THEIR PREDICTION IN THE IDAHO BATHOLITH1

ABSTRACT: Natural rates of surface erosion on forested granitic soils in central Idaho were measured in 40 m² bordered erosion plots over a period of four years. In addition, we measured a variety of site variables, soil properties, and summer rainstorm intensities in order to relate erosion rates to site attributes. Median winter erosion rates are approximately twice summer period rates, however mean summer rates are nearly twice winter rates because of infrequent high erosion caused by summer rainstorms. Regression equation models and regression tree models were constructed to explore relationships between erosion and factors that control erosion rates. Ground cover is the single factor that has the greatest influence on erosion rates during both summer and winter periods. Rainstorm intensity (erosivity index) strongly influences summer erosion rates, even on soils with high ground cover percentages. Few summer storms were of sufficient duration and intensity to cause rilling on the plots, and the data set was too small to elucidate differences in rill vs. interrill erosion. The regression tree models are relatively less biased than the regression equations developed, and explained 70 and 84 percent of the variability in summer and winter erosion rates, respectively.     

EFFECTS OF WATERSHED REPRESENTATION ON RUNOFF AND SEDIMENT YIELD MODELING1

ABSTRACT: This paper evaluates the effects of watershed geometric representation (i.e., plane and channel representation) on runoff and sediment yield simulations in a semiarid rangeland watershed. A process based, spatially distributed runoff erosion model (KINEROS2) was used to explore four spatial representations of a 4.4 ha experimental watershed. The most complex representation included all 96 channel elements identifiable in the field. The least complex representation contained only five channel elements. It was concluded that oversimplified watershed representations greatly influence runoff and sediment yield simulations by inducing excessive infiltration on hillslopes and distorting runoff patterns and sediment fluxes. Runoff and sediment yield decrease systematically with decreasing complexity in watershed representation. However, less complex representations had less impact on runoff and sediment‐yield simulations for small rainfall events. This study concludes that the selection of the appropriate level of watershed representation can have important theoretical and practical implications on runoff and sediment yield modeling in semiarid environments.     

Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).     

Analysis of Roadside Inhalable Particulate Matter (PM10) in Major Korean Cities

A data analysis of three major Korean cities was conducted to assess roadside inhalable particulate matter 10 μm or smaller in aerodynamic diameter (PM₁₀), including temporal and meteorological variations, over a recent period of 4 to 6 years. The yearly roadside PM₁₀ concentrations presented a well-defined increasing trend or no trend depending on the roadside monitoring station. Most mean values exceeded or approximated the Korean standard of 70 μg/m³ per year for PM₁₀. A representative roadside diurnal trend was characterized by a distinct morning maximum. In most cases, the Sunday roadside concentrations were similar to or somewhat lower than the weekday concentrations, and the PM₁₀ concentrations presented a well-defined seasonal variation, with the maximum concentration in March. The monthly maximum concentrations observed in March were most likely attributable to Asian dust storms. In two metropolitan cities (Seoul and Busan), the frequency of days with roadside PM₁₀ concentrations exceeding the standard of 150μg/m³ per 24 h was much lower for the roadside monitoring stations than for the residential monitoring station, whereas in the third city (Daegu), this result was reversed. Interestingly, the average maximum concentrations observed for the roadside sites in Seoul and Busan during March were higher than those for the residential sites, suggesting that the roadside concentrations responded more to the dust storms than the residential areas. The relationship between the pollutant concentrations and five important meteorological parameters (solar radiation, wind speed, air temperature, relative humidity, and precipitation) showed that the number and type of meteorological variables included in the equations varied according to the monitoring station or season. Finally, the current results confirmed that attention should be given to the PM₁₀ exposure of residents living near roadways.     

DRY AND WET WEATHER FLOW NUTRIENT LOADS FROM A LOS ANGELES WATERSHED1

Effective watershed management requires an accurate assessment of the pollutant loads from the associated point and nonpoint sources. The importance of wet weather flow (WWF) pollutant loads is well known, but in semi‐arid regions where urbanization is significant the pollutant load in dry weather flow (DWF) may also be important. This research compares the relative contributions of potential contaminants discharged in DWF and WWF from the Ballona Creek Watershed in Los Angeles, California. Models to predict DWF and WWF loads of total suspended solids, biochemical oxygen demand, nitrate‐nitrogen, nitrite‐nitrogen, ammonia‐nitrogen, total Kjeldahl nitrogen, and total phosphorus from the Ballona Creek Watershed for six water years dating from 1991 to 1996 were developed. The contaminants studied were selected based on data availability and their potential importance in the degradation of Ballona Creek and Santa Monica Bay beneficial uses. Wet weather flow was found to contribute approximately 75 percent to 90 percent of the total annual flow volume discharged by the Ballona Creek Watershed. Pollutant loads are also predominantly due to WWF, but during the dry season, DWF is a more significant contributor. Wet weather flow accounts for 67 to 98 percent of the annual load of the constituents studied. During the dry season, however, the portion attributable to DWF increases to greater than 40 percent for all constituents except biochemical oxygen demand and total suspended solids. When individual catchments within the watershed are considered, the DWF pollutant load from the largest catchment is similar to the WWF pollutant load in two other major catchments. This research indicates WWF is the most significant source of nonpoint source pollution load on an annual basis, but management of the effects of the nonpoint source pollutant load should consider the seasonal importance of DWF.     

太阳风暴对短波电子装备性能的影响及应对措施

目的掌握太阳风暴对短波电子装备性能的影响及应对措施,为系统设计提供参考。方法分析太阳风暴的表现形式,并从作用距离、目标检测、定位精度等方面给出太阳风暴对短波超视距雷达、短波通信等装备的影响。结果电离层SID、电离层暴可造成短波通信中断,短波通信可用频段变窄。电离层强吸收可降低天波超视距雷达作用距离和目标定位精度,电子浓度、电离层虚高快速变化影响超视距雷达检测性能和定位精度,负相电离层暴使天波超视距雷达可用频段严重变窄。地球磁暴期间,电磁场突变产生的强电压和电流有可能烧毁用于天、地波超视距雷达的电子设备。电离层非规则现象对超视距雷达有严重影响。结论太阳风暴对电子装备性能有利有弊,要分别对待。系统设计时应充分考虑太阳风暴的影响,在出现太阳风暴时,采取针对性措施降低其影响。     

基于多线程技术的中国海风暴潮数值预报可视化程序开发

首先简要介绍了中国海的风暴潮及灾害情况,对杭州湾一带的风暴潮进行了重点阐述。在风暴潮二维数值模型FBM的基础上开发了具有可视化界面的数值计算程序,能直观的显示风暴潮发展时历,包括风暴潮最大增水、台风风向和移速。采用了多线程技术,可节省时间,程序具有Windows风格的人机交互界面,操作方便。通过几个算例测试,本程序计算结果符合工程预报需要,可为同类研究做一些参考,具有推广意义。     

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.     

2012年春季京津冀地区一次沙尘暴天气过程中颗粒物的污染特征分析

本研究表征了2012年春季一次沙尘暴天气过程中京津冀地区大气可吸入颗粒物(PM10)的污染特征.借助PM10的水溶性元素、有机碳和元素碳的浓度,分析推断沙尘暴天气过程中矿物气溶胶对城市气溶胶污染的交汇叠加作用.使用中流量大气颗粒物采样器,于2012年4月1日～5月24日,在北京市西三环、天津空港经济区和张家口火车南站附近同时采集可吸入颗粒物(PM10),采用离子色谱和元素碳/有机碳分析仪分析获取其水溶性离子、元素碳和有机碳浓度.结果表明,采样期间北京、天津和张家口这3个采样点PM10质量浓度的日均值分别为233.82、279.64和238.13μg·m-3.4月27～29日,3个地区发生了沙尘暴天气,PM10质量浓度的最大日均值分别达755.54、831.32、582.82μg·m-3.沙尘暴期PM10的有机碳(OC)浓度、二次有机碳(SOC)/OC的比值、硝酸根(NO-3)和硫酸根(SO2-4)浓度均高于非沙尘暴期间.采用电荷平衡计算证明沙尘暴期间大气颗粒物表明呈碱性,说明外来沙尘暴与本地污染相互叠加,矿物元素改变了颗粒物表面的酸碱性,沙尘暴和有机物发生耦合,促进了二次有机物的转化.